Gaining Competitive advantage through Knowledge process outsourcing

Gaining competitive advantage through analytics outsourcing

Table of contentsExecutive Summary 2Introduction 5A Knowledge Competitor: The Capital One story 61. Winning Companies Compete with Knowledge 72. Actionable Insights in Every Corporate Function 113. The Current State of Knowledge Processes 234. Achieving Knowledge Centricity 255. Changing the Game 34How analytics outsourcing can help the retail financial services industry 416. Becoming a Knowledge Competitor 447. Summary 47 wns.com

Executive SummaryContinuous and sustained growth is the goal of and causal relationships between economicevery organization. However, as an organization outcomes and the drivers of these outcomes.expands, it has to confront challenges which canbe considered as by-products of growth. How the Let’s take a simple example. Every day, companiesorganization tackles these challenges (some make hundreds of decisions that impact theircompanies may view them as goals) determines its competitive position. Those decisions that are seensuccess. Some of them are: as ‘core’ to the business — performance during the sales lifecycle — are generally based onUnderstandingn customer behavior in different strong, continual analytic support. But more often regions than not, analytic support for fuelling decisionMonitoringn and optimizing marketing spend science comes in bursts, perhaps when there is a radical unforeseen change in the business or whenDrivingn sales force productivity to the next level the management changes. And those decisionsEstablishingn and optimizing logistics to gain that are not seen as ‘core’ are starved of supply chain efficiency knowledge support.Reducingn risk What it means to compete withEnteringn new markets with a targeted strategy knowledgeIn addition, growing organizations will also have to In contrast, those few organizations that win byget their arms around concepts like Big Data, competing with knowledge (perhaps less than 10Cloud, Mobile Platforms and Social Media. percent of all companies) generate insights inside rigorous ‘knowledge processes’ where standardIf accomplished, these goals can quickly operating procedures for performing these effortsdifferentiate a company from its competitors. are hard-coded into the organization. The culture of knowledge-driven decision science permeatesBut how does a company achieve these goals or every function and every level of the business.surmount these challenges? Competing with knowledge involves determiningBy competing with knowledge and driving their which of a company’s many daily decisions allowdecision science by actionable insight! In this the organization to out-maneuver its competition.context, what is knowledge? Knowledge is a The knowledge competitor analyzes those chosencomprehensive and linked set of insights obtained decisions deeply and continuously, examining allwith discipline and speed, based on fact and relevant facts that create a context for decision-transparent in methodology, generated by making. Managers at all levels of a knowledgerigorously and consistently assessing all drivers of competitive organization buy in to decision-makingperformance, both inside and outside the frameworks that incorporate intuition as well asbusiness. the insights generated from research and analytics. And importantly, these frameworks are flexible,Insights are generated through research and and easily reinvented to adapt to changinganalytics – the quantitative methods, investigative conditions.and predictive, used to explain and identify trends2

As an example, Capital One, a leading global For organizations that really want to succeed asfinancial services firm, grew from a relatively small knowledge competitors, Analytics Outsourcingdivision of US-based Signet Bank to a Fortune presents an opportunity to rapidly transform their200 organization that rivals even the largest global business from one driven by intuition and ad-hoccredit card companies by competing with knowledge gathering and analysis practices to oneknowledge. The company runs about 300 that is driven by insight. Some companies have‘experiments’ every day to understand the likely successfully outsourced their analyticseffectiveness of new products or programs before it requirements with remarkable impact.launches any full-scale initiative. Through theseknowledge-enabled experiments, Capital One has A leading home entertainment chain maximized itsdramatically increased customer retention and revenues in a short shelf life product cycle bylowered the cost of acquiring a new account. accurately forecasting its daily SKU inventory. A leading beverage manufacturer created scalableThe sophistication and consistency with which cross-country tiers to optimize product conceptcompanies leverage knowledge processes and tests it needed to launch a new product. In theseindustrial strength analytics separate top-tier cases, the analytics service provider’s teamscompetitors like Capital One, P&G, Amazon and worked as extensions of the companies’ staff, andTesco from the rest of the pack. leveraged access to data, as well as the centralized nature of an analytics delivery center to increaseThe edge lies in Analytics Outsourcing sophistication levels and render industrial strength analytics that top tier companies look for.Most companies know very little about where andhow they can deploy knowledge processes to drive Analytics Outsourcing resolves the challengesdecisions within their organizations. Their associated with becoming a knowledge competitordecisions are often reactive rather than proactive by:and based on intuition rather than knowledge.Even when an organization recognizes the need for Establishing a federated engagement model andknowledge discovery, their understanding as to systematically standardizing fragmented analyticshow knowledge processes should be structured for services (within the organization as well as acrossmaximum benefit is often poor. third party service providers) creating efficiencies in horizontal leverage across the company. ThisDespite its criticality to business performance, a enables enterprises to examine businesssubstantial percentage of companies do not opportunities and challenges in a consistent andleverage knowledge in their decision science. Why? systematic manner. Rather than creating anBecause truly competing with knowledge is internal model to define how knowledge is createddifficult. and distributed, which is time-consuming and difficult, the company can turn to a provider toNegligible automation, limited documentation and deliver, and standardize the knowledge repositoryrestricted knowledge transfer limit data re- spanning all business areas and geographies. Allusability. This leads to repeated need for data you then need is openness to joint investmentsengineering, impacting productivity. The lack of a and a strong governance model across thecommon framework of engagement leads to company’s business units and third party analyticsseepage of knowledge and limited governance on service providers.intellectual property (IP). The inability to quicklyscale up leads to inefficient utilization of highly Augmenting suboptimal corporate skill sets byskilled analytical resources. expanding the capabilities of a single departmental analyst with a full range ofCompanies seeking to change the way they develop knowledge specialists and data scientists. Theand act on insights can look to a trend that has effects of disaggregating the single analyst’s skillsbeen developing since the 1970s: outsourcing. into a trinity of specialized skill sets — industry or domain knowledge, quantitative skills such as wns.com | 3

statistics and data management skills — introduce The benefits from setting up an outsourcedthe benefit of speed (ability to scale up or down, Knowledge Center of Competency can beand deliver services fast), reducing cost and remarkable:increasing productivity. Standardized n sales force effectiveness models ensure that each market approach is uniform;Making knowledge processes easily scalable by adjusted to local market contexteffortlessly expanding to create knowledge across acompany’s geographies, every day, 24/7. Because Standardized n sales and marketing reportsanalytics service providers are dedicated to the provide the management a consistent andbusiness of knowledge discovery, they have the accurate view of market conditionsbenefit of scale — size, scope and location — that Insights n can be extracted from market andmost companies simply cannot replicate when they business researchperform their processes internally. This helpsdevelop industrial strength analytical capabilities Analytics n optimize closed loop marketing effortscompany-wide, establish a strong backbone of n product New launches are fully supported acrossenterprise analytics in the company and achieving the globe with pricing, forecasting, product andEvery Day Low Cost (EDLC) in the delivery of competitive research, consumer analytics andanalytics services. economic and financial modellingBreaking down corporate silos and establishing Compliance n processes can be governed betterbest practices by becoming the company’s clearing and standardizedhouse for knowledge requests; establishing broader Graphics n development is industrializedand deeper resource pools; and deliveringexpertise in areas outside the company’s primary n reduction Cost in research and analyticsdomain. operating expenditure Improvement n in turnaround timesBreaking the cultural barriers that inhibitcompeting with knowledge. Sophisticated analytics Development n of more productive models,service providers implement collaboration tools as backed by facts.a delivery method to speed up the consumption ofknowledge. So even far-flung stakeholders in the Because many companies do not compete withcompany can see what types of business problems knowledge, those who do are today’s out-in-frontare being solved by their colleagues in different competitors, using research and analytics toparts of the organization. That itself can spark a generate actionable insights across theircultural shift to knowledge-driven decision making. businesses. Some leverage analytics outsourcing toThis also promotes increased creation of IPs and more quickly, more effectively and more cheaplyartifacts, and improved documentation and get — and stay — ahead of the competition. Andknowledge transfer. as the global business environment continues to change — as competitive forces become dramatically sharper — competing with knowledgeThe Knowledge Center of is now more important than ever before.Competency (CoC)The solution may lie in transitioning to ananalytics delivery center — a Knowledge Center ofCompetency (CoC) — which ensures thatknowledge discovery is standardized to avoidmultiple versions of the truth. The CoC can alsohelp companies leverage this knowledge acrossgeographies to account for unique marketdifferences, and is institutionalized and governedby a set of best practices that can be disseminatedacross the organization.4

IntroductionThis WNS industry thought leadership series paper Most business decisions are made in anexamines the important role that knowledge environment where a variety of forces are in play atprocesses play in all aspects of corporate decision the same time: competition, consumer behavior,making, and how companies can ‘move up the economics and demographics are just a few of theknowledge curve’, in order to compete more vectors that impact the shape of the decision.effectively. And processes to develop knowledge are more highly developed around the core disciplines of aIn a world where economic realities seem to change company; for example, credit risk rating in a creditevery day, and the behavior of competitors and card company or analytical processes for catchingcustomers is no longer easily predictable, companies fraudulent claims in a health insurer, given thatthat are readily equipped to identify their these processes are critical to the core business.opportunities, define their needs, standardize their These processes typically reside within functionalmethodologies or change their organizations and tools silos; hence these knowledge processes do notin order to quickly navigate today’s turbulent waters draw upon the greatest depth of institutionalare the likely winners – and they win by competing knowledge. Often the resources that deliver thearmed with knowledge. For the purposes of this paper, processes have a range of skills that focus only onknowledge is defined as a comprehensive set of the core discipline. As a result, the approach lacksinsights obtained with discipline and speed, based on a full 360° view, a full set of insights.fact, transparent in methodology, and generated byrigorously and consistently assessing all drivers of To illustrate the importance of a comprehensiveperformance both inside and outside the business – approach, which brings a variety of disciplineswith a 360° view. together to generate holistic insights, take the example of pricing for a product or service.Where do insights come from? They are generatedthrough the rigorous use of research and analytics Making price point decisions based on(R&A). Research refers to the process of gathering and benchmarks a company must achieve, or onsynthesizing information from primary sources competitor behavior alone, gives only one view.(directly from customers or opinion leaders) and / or Adding an analysis of demand, including a newsecondary sources (from published content). Analytics analysis of consumer elasticity curves,refers to the quantitative methods, both investigative cannibalization analysis or positioning on a brandand predictive, that explains and identifies trends and equity map adds new dimensions. And even morecausal relationships between economic outcomes and insight could be generated by determining thetheir drivers. R&A processes can be conducted on an impact of trade promotions, displays andad-hoc basis, such as one-off piece of research or packaging changes on demand. Assembling thespreadsheet exercise, or inside more rigorous entire picture requires skills and models that‘knowledge processes’ where standard operating analyze all these factors in totality, and theprocedures for process delivery are hard coded into capacity and discipline to respond in real time.the organization. wns.com | 5

Take another example: In many companies, R&D This paper serves as a guide for thoseefforts for new product or SKU variants are driven organizations that, like Capital One, desire toby logic that ranges from ‘my competitor is going compete with knowledge – ready to elevate theto do it so I have to do it’ to a strategy of ‘letting a quality and the rigor of their insights, potentiallythousand flowers bloom.’ As a result, the financial changing the way the entire enterprise works. It isand market benefits of the deployment of financial designed to provoke each company’s answers toand human resources behind those efforts are not key questionsfully evaluated. Early-stage forecasts are often n do How knowledge processes support decisionoverly optimistic or may not evaluate the making?implications upon the entire product portfolio What n are the challenges most organizations faceadequately. And consumer propensity-to-purchase when moving to a knowledge-centric company?models are typically generalized rather than being n do How organizations effectively compete withevaluated for their uniqueness to a company’s knowledge?positioning on a brand equity map.Why? The analytic rigor with which decisions are What n models are leading companies increasingly adopting in order to become full-fledgedmade is sub-optimal. Understanding the knowledge competitors?implications of every driver — quickly and with theright tools and rigor in order to institutionalizeinsights — is key to becoming a knowledgecompetitor.Case Study A Knowledge Competitor: The Capital One storyIn the 1980s, Signet Bank — at the time, hardly a target its individual customers. The experimentsleading competitor in the American credit card are a cost-effective strategy to estimate thebusiness — hired two financial services effectiveness of products and programs before theconsultants to leverage knowledge to generate company launches any full-scale initiative.better customer insights. The pair found, based ona series of analyses, that those customers who For example, in its savings business, Capital Onesincurred large amounts of debt in short periods experiments with CD interest rates, rolloverand then slowly paid off the balances were far incentives and minimum balances have allowedmore profitable than customers who made small the company to predict — with relative precisionpurchases and paid their balances in full each — how different offers will change retention ratesmonth. and revenue generation. Using research and analytics, the Capital One savings businessThis realization led Signet to introduce the dramatically increased retention and lowered theindustrys first balance transfer card. It later spun cost of acquiring a new account. Competing withoff its increasingly successful credit card division knowledge, Capital One has grown from a relativelyas Capital One, by then a leading competitor. small division of Signet Bank to a Fortune 200Capital One has stayed true to its knowledge-based organization that rivals even the largest globalroots, running an average of 300 research and credit card companies.1analytics (R&A) ‘experiments’ each day to better1 Thomas H. Davenport and Jeanne G. Harris, Competing on Analytics (Boston: Harvard Business School Press, 2007), 42.6

1. Winning CompaniesCompete with KnowledgeThe success of Capital One, along with other Competing with knowledge as aenviable corporate brands, certainly establishes competitive differentiatorthat knowledge processes separate the Despite the clear importance of knowledge-drivenoutperformers from the pack. Yet becoming one of decision making, a substantial percentage ofthose outperformers by competing with knowledge companies do not leverage (or do not fullyis likely easier said than done. And acknowledging leverage) knowledge in their decision science.a high-level need to institutionalize knowledge is As recently as May 2002, a survey by executiveonly the first step. This section examines the other search firm Christian and Timbers found thatfactors that are important in order to compete 45 percent of corporate executives relied more onwith knowledge. instinct than on facts and figures in runningAs is the case with corporate changes, it is easy to their business.understand the need, but implementation is the Even more recently, Harvard Universitychallenge. By their very nature, knowledge management professor Tom Davenport andprocesses permeate every corporate function – consultant Jeanne Harris found similar results in awhether it is sales and marketing, human survey of 371 medium- to large-sized firms. Theresources or risk management. And each industry survey was designed to decode the amount ofhas specific knowledge needs; for example, the analytical capability embedded in thespecific analytic processes embedded in media organizations. Only 10 percent of respondents putindustry research and development do not themselves in the highest category, which wascompare to those in a financial services described by the statement “Analytical capabilityorganization for the launch of a consumerfinance product. is a key element of strategy.”2 Davenport and Harris further suggested that of those 10 percent, probably half are “full-bore analytical competitors.” While Davenport and Harris did not disclose the specific companies in that 10 percent, it is not difficult to identify these pioneers. Tesco sending you the coupon for a product that you intended to buy on your next shopping trip; Capital One’s offer of a card with an interest rate, spending limit and loyalty bonus features that perfectly match your lifestyle; it is analogous to creating a shampoo that somehow seems to address your unique hair care needs.2 Thomas H. Davenport and Jeanne G. Harris, Competing on Analytics (Boston: Harvard Business School Press, 2007), 24. wns.com | 7

So it appears that those companies, which arefull-fledged knowledge competitors, have gained La Russa appreciated the informationconsiderable competitive advantage, and first- generated by computers. He studiedmover status, over peer companies. However, the rows and columns. But he alsothis advantage — leaving the firms whose decisionmaking is still driven primarily by suboptimal knew that they could take you only sointuitive processes — cannot last forever. Just as far in baseball, maybe even confusebest practices are institutionalized, competing you with a fog of over analysis. As farwith knowledge processes such as research andanalytics will eventually become commonplace, as he knew, there was no way tobecoming a business imperative rather than simply quantify desire. And those numbersa competitive one. All the more reason then that told him exactly what he needed tothe time to compete with knowledge — to move know when added to twenty-four yearsahead of the pack — is now. of managing experience.3Intuition is not knowledgeCompeting with knowledge is not about denying Intuition alone is an inferior driver of businessthe benefits of strong intuition. Companies are decisions, even though making decisions based onwell-served by leaders at all levels who act on intuition alone is incredibly alluring. Businessfinely honed intuition. Making knowledge-driven strategist Eric Bonabeau, while writing for thedecisions is about pursuing intuition in a more Harvard Business Review, described that allure:measured way – checking out and verifying the “We want to believe in the transformative power ofsoundness of intuition through research and intuition. For one thing, it’s romantic. It raisesanalytics, then acting on it. business above the drab world of spreadsheets and income statements and turns it into something ofAt times the possession of knowledge can actually an art form. The executive office becomes a placespark intuition. Indeed, insight and intuition of inspiration and vision rather than planning andtogether make an extremely powerful decision- number crunching.”4making team. While one can argue that thecompanies that make knowledge-driven decisions While intuition-based decision making is seen aswill out-compete firms that make intuition-driven swift and attractive, knowledge-based decisiondecisions, the most successful organizations are making is anything but slow and dull. Competinggenerally those that combine the two. with generated insights is not merely working with spreadsheets and income statements, planningSt. Louis Cardinals coach Tony La Russa does just and number crunching; it is about using whatthat, and has two World Series titles to show for it. corporations know (based on research andIn the book ‘Three Nights in August’, which analysis) to drive business decisions, which isprofiled La Russa throughout a three-game series sparked and illuminated by intuition.between Cardinals and Cubs in late 2003,Pulitzer-winning journalist Buzz Bissinger writes Bonabeau sums up the benefits of knowledge combined with intuition succinctly. “Our desire to believe in the wisdom of intuition blinds us to the less romantic realities of business decision making. We remember the examples of hunches that pay off but conveniently forget all the ones that turn out badly.”53 Buzz Bissinger, Three Nights in August (Boston: Houghton Mifflin, 2005), 201.4 Eric Bonabeau, “Dont Trust Your Gut,” Harvard Business Review, May 2003, 3.5 Eric Bonabeau, “Dont Trust Your Gut,” Harvard Business Review, May 2003, 3.8

1. Winning Companies Compete with KnowledgeActing on knowledge writes, “We found no evidence that the good-to-Companies competing effectively with knowledge great companies had more or better informationknow that simply unearthing reams of information than the comparison companies. None. Both setsis not enough. Rather, it is important to make the of companies had virtually identical access to goodright information available in a manner that allows information. The key, then, lies not in betteran organization to act on that knowledge. In one of information, but in turning information intothe leading guides to becoming a great information that cannot be ignored.”6organization, management consultant Jim Collins Exhibit 1: The path to competitive advantage Business imperative achieved Proactive or reactive focus Focused analytic efforts that – e.g. gain market share by on a business imperative, (for e.g.) deepen understanding better customer targeting or e.g. drive to gain or defend of customer segments or achieving superior financial market share optimize pricing strategies results by optimized pricing strategies Ability to consistently deploy Availability of talent analytics across the Domain experts, statisticians organization with the help of pool with analytical and analysts with specialized specialized analytic skills sets positioned to capabilities organized in capabilities and knowledge deliver insight structured processes processes that are scaleable, and available anywhere / anytime Widespread availability of Organizational culture knowledge processes enables Knowledge is institutionalized where decisions are senior management and a pre-requisite in supported by analytical expectation of well-supported decision making insight decision making How knowledge Knowledge drivers The end result processes helpSource: WNS6 Jim Collins, Good to Great (New York: HarperCollins, 2001). wns.com | 9

Without a doubt, better knowledge leads tosuperior business outcomes for companies. We found no evidence that the good-to-Perhaps the company is losing market share or has great companies had more or betteran outdated product mix. Knowledge processes —whether they deliver sophisticated customer information than the comparisonsegmentation study, analyze distribution channels companies. None. Both sets ofor support a new product launch — help the companies had virtually identical accesscompany to solve the business problem or realize to good information. The key, then, liesthe opportunity. The result? Increased marketshare, fewer stock-outs, faster product launches not in better information, but in turningand an improved pricing strategy, resulting in a information into information that cannotposition where a company can potentially be ignored.out-compete peer companies. - Jim Collins, Management ConsultantImplementing knowledge processes could betermed analogous to diligently turning over rocksin order to see what is lurking in the dirt. In ‘Good The rocks are akin to customers, suppliers,to Great’, Collins quotes Pitney Bowes executive competitors and the inner workings of theFred Purdue: “When you turn over rocks and look company. Companies that compete with knowledgeat all the squiggly things underneath, you can ring-fence all the facts and issues, seek toeither put the rock down, or you can say, ‘My job understand them, and make decisions accordinglyis to turn over rocks and look at the squiggly – rather than making blind decisions, unaware ofthings,’ even if what you see can scare the hell the potential impact of facts and traps that lurkout of you.”7 beneath, waiting to damage the company. Ignorance, in business, is not bliss.7 Jim Collins, Good to Great (New York: Harper Collins, 2001), 72.10

2. Actionable Insightsin Every Corporate FunctionClearly, winning companies drive their decisions How actionable insights are generated:using actionable insight generated from research research and analyticsand analytics. This section underscores the need No matter what the function or industry, insightsfor insight in every corporate function. Certainly are gained through the application of research andthe need for analytics is critical in industries that analytics – methodologies and protocols whichgenerate reams of data from transactions – retail, allow the business to gather, synthesize andtelecom, financial services and gaming, forexample. But there is no function, regardless of extract insights from data. Exhibit 2 highlightsindustry, that cannot benefit from the insights that some of the most common types of research andresearch and analytics (R&A) yields. analytics processes. Exhibit 2: The components of research and analytics Business and financial research Domain-specific analytic services n Company / industry research n Consumer analytics n Business intelligence n Operational analytics n Corporate finance n Risk analytics n Equity research n M&A research n Library / documentation services Data services Market research n Data management n Research design n Report delivery and development n Survey management n Customer communication management n Data collection n Ad hoc analysis and insights n Data processing n Sourcing and spend analytics n Analysis and presentationSource: WNS wns.com | 11

Business and financial researchBusiness and financial research, at a high level,is the process of accumulating and synthesizingsecondary information on markets, geographies,competitors, products and other less structureddata available in syndicated reports, informationportals, company literature, industry-specific andfinancial databases and the Internet. Theobjectives are linked to the business context forwhich the research is being performed.The research provides a profile of marketplaceactivities: what is occurring, who the players are,how they are doing it, and other key facts aboutthe situation. It is either used as-is by decisionmakers tasked with making subjective decisionsbased on intuition, or paired with morequantitative results coming from correlativeanalytic models to deliver a deeper understanding Financial research has embedded within itof the quantitative implications of industry trends fundamentally the same process of aggregatingand competitor behavior in the context of a market and synthesizing data as in business research, butsituation. For example, business research (BR) the nature of the data, the uses of the product andcould involve gathering competitive data about the skills required to perform it are quite different.new product launches for a consumer packaged As indicated by its name, financial researchgoods (CPG) firm, identifying competitor store focuses on creating insight from financiallocations supporting a new store opening strategy information, primarily information extracted fromfor a retailer, delineating competitor product financial statements.features for a consumer financial services (CFS)company, gathering product and commercial Companies use financial research to developinformation on steel suppliers for the procurement benchmarks and relative performance metrics forarm of a major automobile manufacturer. themselves. In such applications, analysts use higher-end financial techniques to breakWhen consumed as a discrete product, business consolidated statements into geographic,research typically informs qualitative decisions and business unit, or product level financials.acts as a foundational step for strategic decisions In the world of professional and financial advisoryon markets and products. Discrete could mean services, this capability is used to identify M&Athat the requirement is one-time, but many targets, screen securities for investment purposescompanies actively maintain and refresh market, and populate equity research reports withproduct and competitive information, especially if quantitative financial facts.this information is a vital input to a structuredknowledge process within the decision making Financial research can also be extremely powerfulapparatus of the company. When married to an when married to certain types of analyticanalytic process where business research becomes modeling. As an example, when companies area supplier of ‘meta-data’ to an analytic or data- evaluating the sequencing strategy for a product ordriven decision process, business research plays a service in the global marketplace, understandingpowerful role in bringing external context to the revenue and financial performance of playersinternal data. with geographic skews is one of the defining12

2. Actionable Insights in Every Corporate Functionvariables, along with broader demographic and tactical analytic decisions is not always affordable.attitudinal data. Whereas in business research, Market research agendas are typically set annuallyextracting insights from data has a qualitative by the strategic team within the marketingaspect, the skills required in financial research department. When a tactical decision on price orrequire analysts with strong financial and micro-messaging comes up six months lateraccounting backgrounds. (potentially in a geography that was not studied at the outset), this body of research is difficult toMarket research fund or obtain quickly. What does exist is often not fit for purpose and the resources to analyze theMarket research (MR) is a discipline that information for a new campaign may not befundamentally gathers a wide range of information available. Therefore, the only way in which marketrelative to the market for goods and services by research can prove to be valuable at a tacticalprofiling the behaviors of current, former and level is if it can be performed in a scalable,prospective customers. Historically, companies tap frequent, low-cost manner.into market research agencies to decide whichquestions should be asked, how should they be Even in companies that are structured to get theasked, and to whom they should be asked in order best value out of their market research, a certainto better understand or predict the behavior of percentage of their spend is dedicated to simplytheir customers. A significant amount of spend in refreshing the body of research accumulating overmarket research is driven by the need to make an the years – a relatively repetitive process. In thisinformed decision when spending billions of instance, the need to re-build and test the basicdollars reaching existing and prospective survey design and strategy model is minimal. Oncecustomers through advertising. the higher-value, front-end component of market research is stripped away, the process of collectingCommonly, companies that wish to reach specific and processing the data is actually fairlysegments of the mass population or exploit the commoditized. Collecting data from consumers orinspirational qualities of a brand to drive businesses is becoming significantly lessconsumption are the heaviest users of this service. expensive with the availability of tools such asMarket research also comes into play when Computer Aided Telephonic Interviews (CATI) orcompanies are launching new products or services with the use of technologies such as Computerand/or features where communication with existing Aided Web-based Interviews (CAWI). Processingand prospective customers is important. data in tools like SAS or SPSS requiresDespite the need to understand and track the programming skills that are now found in relativebehavior of today’s customer ever more closely,the amount of market research performed isactually limited. The reason? Most marketingmanagers believe that there is always some degreeof uncertainty with the reliability of results.The studies themselves are labor intensive andexpensive to conduct. But most importantly,despite tons of data gathered from consumers,companies find that their ability to extractinsight from this data is limited and constrainedby economics and the objectives of theresearch itself.Given that the primary function of MR is to informadvertising spend decisions, the depth andbreadth necessary to support many and frequent wns.com | 13

abundance in the marketplace. The extraction of Take MIS, for example: The service is reflective ofbasic information from MR is also something that data management and representation rather thanrequires a fairly low level of incremental skill – assembly. When it comes to processes where dataa combination of the ability to create a headline sets must be created to support analytics, morefrom a table of data, and visual aid complex skills may be required. Such as(for example, MS PowerPoint) skills. understanding what kind of data must be assembled requires a deeper understanding of theWith the trend towards commoditization of a analytics that will be ultimately performed usingsubstantial portion of the MR process, it is the data. As a result, in most cases, data servicesincreasingly possible to drive the use of market and analytics are deployed in conjunction withresearch down into the tactical bowels of an each other.organization. The cost advantage emanating fromthe disaggregation and portability of skills enablescompanies to perform a lot more market research,deploying it more broadly within the organizationto better support tactical decision making.For example, a leading consumer packaged goodscompany studies the propensity to purchase itsproducts. It uses structured equation modeling toidentify the discrete product features that areimportant to its customers, then launches a shortmarket survey to make sure that the results of thatanalytic exercise are valid when actual customersare, through market research, asked about theperceived value of a specific feature / pricecombination. A leading consumer financialservices company designs a credit product withcertain specific features based on an analysis of Some of the specific processes within datathe behavior of their existing customer base. services include:It then validates that hypothesis with marketresearch to ensure that the right segment of n management, Data which helps companiesconsumers in fact find value in that feature. manage their complex data processes. In addition to managing data integration fromData services disparate systems, data management teams ensure that clean data is available in usable,Data services refers to a set of capabilities by complete and uniform formats for analysis viawhich a company manages, extracts and stable data processes.manipulates the vast data sets that mostorganizations obtain from their enterprise systems. Report n delivery and development, which focusesTypical data sets contain information on on transforming raw data elements into usablecustomers, sales, products, financials, supply business-centric reports for decision supportchain information and transaction-level across a range of functions. The output rangeinformation. The objectives of data services range varies from MS Office outputs to graphical userfrom obtaining information on what has happened interface-driven drill-down reports prepared viain the business (MIS) to establishing the right data requests which can be either customized orsets to perform higher-level analytics. standardized.While there are a variety of processes and Customer n communication management assiststechnical skills required to perform these stakeholders with management of the end-to-processes, data aggregation processes are not in end customer communication process acrossand of themselves ‘knowledge processes’. Rather, multiple channels such as direct or e-mail.they are key enablers of knowledge processes. Services may include campaign targeting /14

2. Actionable Insights in Every Corporate Function response modeling or campaign execution and function. Broadly speaking, consumer-related evaluation measured by ROI, which in turn is analytics typically find their application in sales fed back to complete a closed-loop marketing and marketing departments; operationally-oriented process. Skills required for customer analytical problems are found in manufacturing or communication management include proficiency supply chain environments; and financial or risk- in both proprietary software and standard related analytics are the focus of finance campaign tools as UNICA / SAS. organizations.Ad-hocn insights and analysis (I&A) delivers a Given that analytics deals with data, which specific understanding of transactional data in analytics are performed is both driven and limited order to connect disparate trends to better by what kind of data an organization collects or understand the market / operational landscape. has access to. For consumer analytics, the most It uses both statistical techniques and typical data sets involve market research data and algorithms to corroborate, evaluate and uncover / or transactional data. Transactional data can be business issues which would otherwise be internally generated by companies that deal ignored or unexamined. directly with their consumers (such as retailers orSourcingn and spend data services assist telecom firms) or can be purchased from third stakeholders with vendor selection as well as the party vendors (such as retailers that sell shopper management of the sourcing process. This data). Broadly, these types of analytics are focused service helps companies source correctly, around revenue and marketing-oriented issues manage and forecast spend, and identify savings such as: Who is buying? Why are they buying? opportunities. When are they buying? Are they buying more or less than in the past? Organizations striving to develop a deeper insight into customer behaviorBusiness domain-specific analytics will typically augment their information onWhile business research, financial research and consumers with internal data from other parts ofmarket research are typically focused on collecting their organization (such as the data that can beand synthesizing facts, data mining assists derived from their call centers) or meta-dataorganizations in managing, integrating and (environmental data such as demographics andmanipulating data and analytics focuses on taking wealth information). Ideally, they will gatherthose facts and extracting insight out of them. It is information from market research or shopper datathe last step in creating actionable insights from on their competitors as well so that their modelsknowledge to drive business decisions. are more fully informed.How are business decisions driven by actionableinsights? At the highest level, multi-facetedbusiness issues, questions or challenges arebroken into analytic problem statements andsolved by specialists. The first step in this processrequires developing an understanding of theproblem itself – an intimate understanding of whatbusiness issue must be solved or what hypothesisproved or disproved. However, proficiency withrespect to the statistical techniques that should bedeployed for the analysis, or surety as to what kindof data is actually available within theorganization, is generally missing.The type of business issue being tackled, the kindof data available for analytics, and the skills ortechniques required to unearth the solution vary by wns.com | 15

In the case of operational analytics, the focus analytics can reduce the chances that theturns to how efficiently an organization is doing its organization will be on the receiving side of ajob of fulfilling consumer demand. From a fraudulent transaction.manufacturing perspective, firms are looking atgenerating production efficiencies at a production- But for detecting frauds, and understanding of theline level all the way up to a network of business domain is imperative. Hence, at themanufacturing plants. They are measuring and outset of any analytical investigation, a domainanalyzing through-puts, reject-rates and factor expert (typically an MBA with prior experience incosts such as the labor and raw materials required the industry and in the function) engages with theto create a unit of output. Service elements of stakeholder and explores the boundaries of theorganizations that process transactions or handle issue itself. The ‘what’ and ‘why’ of the situation iscalls approach analytics with a similar perspective; discussed in some detail so that the domainin this instance the ‘product’ may be handling analyst understands the objectives of the analyticcalls from customers. effort. Recommendations are made on altering the scope of the study based on the analyst’s previousAnalytic techniques also support supply chain experience solving similar problems for otherdecision making where companies strive to stakeholders. If the problem posed is beingoptimize their supply chain and distribution investigated for the first time, then there should benetwork, looking to minimize the costs incurred in a fairly detailed conversation about the availabilitythis part of the value chain and achieve Every Day of data sets within the organization, theLow Cost. Data generated by company ERP architecture within which the data resides andsystems is the basis on which analytics are limitations inherent within the data. It may alsoperformed; therefore ERP systems have require discussion about what other kinds ofsophisticated analytic tools built on top of their internal data or even third-party data need to becore systems. Evolved organizations also consider integrated with the traditionally deployedthe demand element when optimizing what is data sets.shipped where so as to minimize inventory, stock-outs and returns. With the advent of just-in-time In the perfect scenario, a statistician and the leadsupply chains, manufacturers deploy predictive data engineer are teamed with a domain expert.models that use historical demand, stock positions The statistician is typically proficient in certainand environmental factors to modulate the speed types of data sets (market research or pricing orwith which replenishment is taking place. transactional datasets) but has also spent timeOptimizing networks and a focus on the financial working on solutions for the particular industry.costs of making and moving products are the key His (or her) responsibility is to ensure that theanalytic imperatives in operational analytics. appropriate statistical techniques are used based on the objective of the data problem and the typeFinancial analytics is typically centered on the of data to be analyzed. The data engineer isneed for finance organizations to control and drive typically proficient in certain programmingpredictability into a company’s financialperformance. Analytics can be used to predictfinancial performance — revenues or costs —based on historical performance, environmentaldrivers, booking history, or other leadingindicators. Costs can be predicted based on adetailed understanding of cost drivers. Riskanalytics are typically most developed in thefinancial services industry from a credit riskmanagement perspective but can also be used inless credit-intense environments to assist incollections. Fraud is another area where predictive16

2. Actionable Insights in Every Corporate Functionlanguages and certain types of relational where there is a need to score existing customersdatabases. His job is to either deploy his on their likelihood of attrition, for example,knowledge of the stakeholder’s data architecture or the end product might be a database with attritionunderstand (in the case of a new relationship) scores against customer identification tags.where the data resides, how it can be extractedand what kind of manipulation it will require in a Often a point or ‘development’ solution rolls overtool such as SAS – based on the solution defined into a ‘production’ solution. There may be a needby the statistician and the issue as understood by to automate the algorithms developed into a tool orthe domain analyst. model that is run and maintained by the analysts on a periodic basis. A good example of this is aThe final result or end product of the analytical situation where one of the world’s leading ITinvestigation can vary dramatically depending on services companies periodically runs models tothe type of problem posed to the team. In a identify existing customers for new productsituation where a stakeholder requests an analysis promotional information distributed throughof why a particular product lost market share in a e-mail campaigns.particular geography, the end product may be aPowerPoint presentation with a storyline that lays Exhibit 3 highlights the ways in which analyticsout the logic flow and analysis. In a situation support business decisions in every functional area, ranging from sales and marketing to research and development functions and manufacturing and supply chain to risk management functions. Exhibit 3: How analytics supports decision making across the business - an illustration Segmentation and targeting n Understand your Brand effectiveness n customer / leverage your Acquisition analytics n loyal customers Retention analysis n Marketing Get the most out of your Cross sell - up sell analytics n and sales Portfolio optimization Media, entertainment and publishing marketing spend n Consumer packaged goods (CPG) Market mix modeling n Drive sales force Sales forecasting n productivity Sales force effectiveness Professional services n Financial services Design new products Competitive landscaping n Retail R&D, new Volume forecasting and enter new markets n products Launch visibility studies with well thought-out n and markets strategies Pricing sensitivity analysis n Risk-based pricing n Reduce product cost Strategic sourcing n Manufacturing Demand forecasting Optimize logistics and n and supply Inventory planning reduce demand-supply n chain Logistics planning mismatches n Spend analytics n Credit risk analytics n Compliance Quantity the probability Fraud analytics n of adverse outcomes to Collections and recovery and risk n reduce risk Analytics n Loan forecasting nSource: WNS wns.com | 17

How actionable insights are leveraged business-to-business context, consistently applyingAn organization that is not leveraging knowledge in sales analytics helps companies understand whichall functional areas — from sales and marketing, phase of the sales cycle customers are in, andproduction and R&D to supply chain and corporate what actions might move them from one part ofstrategy — will not gain the full range of benefits the sales lifecycle to another. In short, the rightthat come with being a knowledge competitor. sales analytics determines which decisions willIndeed, within today’s increasingly complex, global lead to maximum success in sales programs.companies, the outputs of every corporate function Tesco, the UK’s leading retailer, is a good examplein some way impact the market position of a of an organization which gained competitivecompany’s products or services. For example, advantage over its peers by using research andadvanced supply chains must obtain the right analytics in sales to drive customer retentionproduct at a lower price point and deliver it faster decisions. One of the world’s largest food retailers,to the right point of sale. Finance departments operating in 13 countries and through every typemust find innovative ways in which to structure of retail format, the company began itstheir own credit or products so that they become transformation through analytics in 1995 when itcheaper to consumers. Marketing functions in any introduced its loyalty card, the Clubcard. With theindustry are challenged to identify a precise slice customer insights it derives from Clubcardof consumers whose aspirational or other needs purchase data, Tesco creates promotions tailoredremain un-served. R&D functions must speed specifically to its customers’ priorities andproduct launches by streamlining and focusing the interests, issuing seven million targeted variationsdiscovery process. Research and analytics allows of product coupons each year. As a result, Tescothe corporate functions to generate those outputs has outstripped its competitors in terms of couponmore efficiently, more quickly, and more redemption rates, customer loyalty and financialeffectively. performance.8Leveraging actionable insights Retail banks such as Wells Fargo routinely ‘score’in sales their customers to predict the likelihood that an existing customer would be interested inWhen implemented correctly, research and purchasing another product from its diversifiedanalytics supports informed decision making at product slate. As a result, while most customers ofevery phase of the sales lifecycle, from acquisition retail financial services organizations buy betweento cross-selling / up-selling to managing attrition to two and three discrete products from their serviceenticing customers who have left to return. In the provider, Wells Fargo boasts of a cross-sell rate of over five products per retail customer. Their scoring models are not the only reason why they are able to achieve such path-breaking experience. Wells Fargo has researched and analyzed the very process by which consumers can be induced into consuming more products and has aligned the organization to support this process. A leading U.S. auto insurer long struggled with finding the right compensation model for its agent broker community. Research and analytics helped the company cluster its agencies based on the profile of the products they have sold, along with variety of other practice specific markers. It was8 Clive Humby and Terry Hunt, Scoring Points: How Tesco is Winning Customer Loyalty (Philadelphia: Kogan Page, Ltd., 2003).18

2. Actionable Insights in Every Corporate Functionthen able to use this information, combined withpanel research, to attribute motivational drivers toeach cluster and design specific compensationprograms to meet the needs of the clusters. As aresult (after some trial and error), the insurer wasable to grow revenues and enjoy greater profitability,despite paying out more in terms of absolutecommission to fewer loyal, high-performing agents.Leveraging actionable insights inmarketingWhile research and analytics are important in everyarea of the business, it is in the marketing arenathat organizations invest more on knowledge thanany other functional area – in part because of thebreadth of data required for analysis. Whatever theindustry, marketing organizations are charged with On messaging alone, customers are exposed to athe challenging task of trying to meet the infinitely large number of marketing messages every day, invaried needs of consumers. This effort one form or another. Implemented in the right way,encompasses almost every feature of a product or analytics identifies which messages to send, when,service – price, packaging, point of sale and to whom, cutting through the glut ofpromotions and marketing messaging. competing messages so that one resonates and compels action. Marketers must be able to answerBecause of their extreme reliance on data, a number of questions:marketers are faced with a dual challenge – bothextracting insight from mounds of quantitative What n is the universe of potential buyers for mydata increasingly available through ERP systems or product and how are they segmented? Whichby distribution channels in the form of customer segments prefer me to my competitors and why?data, and predicting unarticulated needs and Are those segments growing or shrinking?behaviors from qualitative data gathered through n does How my consumer see me or why does hemarket research. These challenges must be met at buy me? Is that image changing? Do I have thetwo levels: a strategic level where the broad right positioning or does my competitor have apositioning of the product or service is cast in more sustainable brand position? Should Iconcrete and adhered to rigorously, and at a reinforce or alter the image?tactical level where decisions on factors like priceare made both periodically and frequently, n can How I reach my existing customers and newdepending upon market conditions. Compounding potential customers? For example, what mediathis challenge is that each tactical decision itself will they be watching? Where will they besets in motion an effort to analyze the success or watching? What will they be watching it on?ROI of marketers’ efforts. This attempt to analyze, Is the time that I reach them a time which willlearn and act from a constant cause and effect spark consumption?cycle is further regularly affected by the decisions Managing competitive price strategies,that competitors and the trade channels are SKU proliferation and multiplying trade channelsmaking, not to mention broader societal macro- requires the marketing department to use researchtrends such as economic conditions, demographics and analytics to develop an understanding of suchand buying power that over time shift fundamental fundamental questions as:consumption behavior. wns.com | 19

Whatn truly does the pricing power of my product a vital forensic and forecasting tool, helping in the marketplace mean? When will a price organizations assess the implications of past reduction in a premium product undercut the performance and model future implications. position of other products in my portfolio? All too often, financial planning and analysisWhenn a competitor drops his price, should I departments spend the bulk of their analytic react? If yes, by how much? What is the optimal resources looking at results out of context and time price-volume tradeoff? evaluating such reports as variance of actual spend versus budgeted spend. Analyses such as these areWhatn are the tradeoffs that consumers make in fundamentally flawed if the base budgeting deciding package size and price per ounce? process, which is inextricably linked to the How is that tradeoff impacted by where the business, is broken. Rather, finance departments product or service is consumed?Whatn should be my promotions or discounting strategy? What kind of a lift will it give my sales? Will it damage my brand position?While many of these questions focus on theexternalities that marketers have to deal with,analytics must make marketing more of a sciencethan an art. Given the vast budgets spent onmarketing (both advertising and promotions),marketers remarkably spend little time measuringthemselves. As advertising pioneer JohnWanamaker said, “Half my marketing dollars arewasted; I just don’t know which half.” should be able to predict what the spend shouldPost messaging, the application of R&A gauges have been, given the appropriate cost drivers of asuccess. The output evaluates the effectiveness of particular category. For example, Activity Basedmarketing campaigns, whether the initiative is Costing (ABC) is a classic analytic tool by whichimpacting consumer decisions as expected. costs are organized not by spend category (labor, depreciation) but by an underlying activity whichIndeed, analytics that measure the effectiveness of drives the cost (warehousing, selling, distributing).marketing activities are very powerful. As an Once one understands the relationship betweenexample, one leading CPG firm has a $2.5 billion the cost driver and the cost itself, rather than theannual marketing budget. The company uses very cost by period, it is possible to predict with somesophisticated methods to analyze the effectiveness accuracy a pro-forma cost based on what actuallyof its marketing spend – it actually knows, for happened in that financial period. Variances canexample, whether 100 or 75 TV commercials are then be analyzed against predicted values whichmore effective. That kind of measurement is not sharpens the forensic analysis context.typical in marketing functions, but is reflective ofthe level of sophistication companies can achieve Spend analytics for products and servicesthrough knowledge processes. purchased from third parties is another area where finance or procurement functions can effectivelyLeveraging actionable insights in leverage research and analytics to reduce directfinance and risk management and indirect costs. Hunting for alternate suppliers, identifying the right commercial agreement andIn the finance function, actionable analytics are benchmarking against other companies all play a role in reducing cost in all categories. Analytics also plays a large role in the fraud arena, a function where finance functions must pay increasing attention. Taking consumer fraud as an example, analytics helps companies create the20

2. Actionable Insights in Every Corporate Function and credit limit should be extended. This type of analytics is performed using past credit history (as provided by FICO scores or similar scoring), income and asset / liability information, employment profile and a variety of other factors. Leveraging actionable insights in research and development Within the research and development function, analytics plays a key role in helping companies ration increasingly limited research dollars by focusing them on R&D effort where the probability of commercial success is the greatest. Analytics adds vital marketing insights to the research process. Companies traditionally exhaustmarkers which identify a potentially fraudulent major funding on market research before theytransaction even before it is consummated. undertake product development in an R&DThis example is particularly relevant in online environment. However, this tells them little aboutbusinesses; for instance, one of the leading online how to sequence their launch in a globaltravel agencies combats fraud with a unique marketplace. To provide insight, one of the Unitedcombination of analytic tools. It has identified a States’ largest consumer packaged goodsvariety of transaction-specific and consumer- companies uses research and analytics to definegeneric factors that predict the likelihood that a the sequencing of product launch and supportparticular transaction is fraudulent. When across more than 60 countries globally. Thisanalyzing past fraudulent transactions, it found company knows that, when compared to themarkers such as the city pair of the airline ticket developed West, most global markets are stillbeing purchased combined with the time of evolving from a consumer-behavior and readiness-purchase, the location of the transaction, the past to-consume perspective. The consumption ofpurchase pattern of that client, the time of year, products such as hair conditioner and disposablethe dollar value of the transaction and time diapers, for example, is highly correlated to abetween the date of the transaction and date of variety of income and socio-cultural factors; thetravel, then built a series of complex business penetration of products can predict an emergingrules into a fraud tool that flagged transactions for sophistication in consumption behavior or suggestfurther human evaluation. the need for local remedies with similar applications. A combination of research andParticularly in the current economic environment analytics gave the CPG major the insights to assesswhere it is essential to quantify the probability of where the 60+ markets lined up on a consumptionadverse outcomes to reduce corporate risk, it is curve, thus highlighting the markets for first waveimperative to focus research and analytics on launch and investment. To provide the rightmanaging risk and compliance. All industries, decision support, the company created predictiveparticularly financial services, have been hit hard models correlating demographic data such asbecause of inadequate risk practices. For example, wealth, urbanization, and age cohorts with historiccredit risk analytics predict the likelihood that a consumption rates of products launched inprospective customer will be delinquent or default recently developed markets, supported by researchon his / her obligation to pay. It is also used to to identify comparable products and attitudinaldecide what the appropriate interest rate is that qualities of the consuming population.the customer should be charged and which terms wns.com | 21

Leveraging actionable insights in Understanding what sparks performance in sales people and then designing variable compensationhuman resources policies in response can drive higher salesThere are a variety of ways in which research and productivity and retention of the best andanalytics adds actionable insights to the critical brightest. For example, in a transaction processingtask of maintaining employee satisfaction as well environment, a major outsourcing companyas high performance. Companies often refer to converted a fixed with variable compensationtheir employees as their most important assets but model into a primarily variable compensationit is unclear how many of them understand the model. Supporting analytics suggested that thefactors that drive employee satisfaction. Obtaining variance in productivity in a highly repetitive andanswers to questions such as: ‘Which employees standardized task was too great to be explained byare likely to leave the organization?’ ‘Why?’ ‘What innate capability but was better explained bycharacteristics of their employee experience are motivational issues. Thus, bringing average andpotentially causal factors?’ is critical. below-average performers up the curve created a 30 percent rise in productivity. The work wasThe first step in the analytic process is polling the performed with fewer people; as a result, thoseemployees with the appropriate set of questions that were retained earned more – a true win-winthat identifies their attitudes towards their work situation.and professional desires. Analyzing their responsesalong with performance data, demographics, Training is another area where analytics can play atenure, compensation practices and other policies role –improving training techniques and helpingcan reveal and predict which employees are most the retention of course collateral. Using analytics,likely to leave and which are most likely to stay. the aforementioned outsourcer was able to performIn environments such as call centers or transaction test trials on different classroom formats in orderprocessing centers where retaining staff can play a to evaluate content retention and productivity onkey role in keeping external customers satisfied, the production floor.these types of analytics play a key role.As an example, a leading online travel agencyfaced with attrition issues analyzed the factorsdriving employee retention and found that workcontent, front-line agent empowerment and shiftstaffing patterns were the most significant factorsdriving employee retention. With research andanalytics, the company had the tools to effectivelymanage its workforce satisfaction.Employee compensation models — particularly insales forces and in work environments wherepeople are paid on a work output basis — can alsobe transformed through the help of analytics.Understanding what sparksperformance in sales people and thendesigning variable compensationpolicies in response can drive highersales productivity and retention of thebest and brightest.22

3. The Current State ofKnowledge ProcessesNo two companies execute knowledge processes move into a line or supervisory position. Whilequite the same way. They are executed variously numerically adept, he’s unlikely to be a specialistacross the corporate landscape, based upon the in any particular knowledge skill set such aspositioning of three primary environments – statistics. Such a specialization could, in fact, getinternal roles, technology and the use of in the way of being promoted to a line job –third parties. pigeon-holing the MBA as an analytic specialist.This section examines how companies leverage Within a few years, the analytic work completed forthose environments differently. Some companies a few specific business situations positions thestandardize the use of analytical technology while analyst for the next line job while his analyticothers perform knowledge processes on tools models are inherited by the next recently hiredranging from MS Excel spreadsheets to MBA. In high-growth environments, the pace ofsophisticated technologies deployed throughout rotation through analyst positions is raised to athe organization. Some companies augment speed which makes the institutionalization ofdelivery with contracts with third party analysts, knowledge practically impossible. In tough times,while others outsource a substantial portion of the first positions companies cut are thesetheir knowledge functions. generalist analyst positions. As a result, it is difficult to embed a structure and skill set to turnInternal roles a company’s knowledge into insight.Many roles in the corporate roster contain at least The ‘Analytic Superman’some responsibility for analytics. A good way tounderstand the spectrum of talent that is deployed The Analytic Superman is a math genius oris to look at the two primary positions that typically statistics whiz who generally is long tenured withinshoulder the bulk of the company’s ‘analytic load’ the specific organization. He (or she) knows the– the departmental analyst and the ‘Analytic business inside and out, knows the source and theSuperman’. They are worlds apart in terms of dependability of the data, and understands theindividual capability and how they deliver behavior of the competition. And he isanalytics. exceptionally fluent in the bedrock of analytics – statistics and math.The departmental analyst For all this knowledge, he is highly compensated.Departmental analysts are typically hired from And, as one of a very few such professionals, he isMBA programs. They possess good general a black box. Requests for insight go in, and‘business sense’ along with some level of domain-relevant insights come out eventually, atproficiency with spreadsheet programs and above- the pace at which he can turn around a project. Inaverage math skills. Most MBAs look at the analyst effect, the Analytic Superman is the only guy inrole as a stepping stone to greater responsibility. the company who can do what he can do. He has aThe departmental analyst is trying to learn enough line stretching out his door and down the hall toabout the company and its products to quickly the elevator, people waiting for this superman to wns.com | 23

give insight into their problem or question. more ‘fuzzy logic’ environments of a business, the prevailing analytic tool is the commonCompanies deploy the Analytic Superman to solve spreadsheet. However, tools — whethertheir important analytic problems. But they cannot spreadsheets or otherwise — are not analytics inafford to hire sufficient supermen (even if they and of themselves; rather, they consume analytics.could find them) on a global scale. This is clearly If anything, deploying tools only increases thenot a scalable model for a company aspiring to need for a company to create analytics in the formcompete with knowledge. Supermen are not only of algorithms or quantitative business rules thatrare, but expensive and reputation savvy, so only first feed and refresh these tools. So while tools are antier companies can retain them. And when they important means by which a company can become aleave, there is limited talent to fill their shoes. knowledge-based competitor, they in no way solve the basic need for companies to analyze their data.The upshot? The Analytics Superman is abottleneck in democratizing the consumption ofactionable analytics across the organization. Use of third partiesOnly the largest geographies get attention. Another approach to delivering knowledgeAnd the methodologies are not standardized processes is to outsource a task or a series of tasksnor communicated. of which research and analytics is simply a component. For example, companies often outsource the analytics and execution supportingTechnology direct mail campaigns. A number of serviceThe technology tools which companies deploy vary providers will, based on the client’s input, segmentin their level of sophistication. Wherever an a universe of prospects, design and distribute aanalytic problem has a material impact on a direct mail campaign around a product or service.company’s cost of doing business or its ability to Another example is in the field of collectioncompete, the technology is generally robust and analytics where companies commonly hand oversophisticated. These tools typically provide pools of consumer receivables for cents on thedirectional ‘markers’ or clues in industry-specific dollar to third parties who then use analytics tosituations such as identification of fraudulent figure out what they will be able to recover frominsurance claims. Other tools deal with functional the pool through call center agents.challenges such as intelligent call routing in callcenter settings. In either case, this technology can Clearly there are third-party companies that arerarely be deployed straight out of the package. experts in the fields of direct mail or collections,The business challenges they address are typically and it often makes sense for the organization towell-bound within a specific function or task. tap into best practices through those third-partyWhile they codify the more mechanical aspects of players, rather than to try and become an expert inanalytics by providing filters and ‘what-if’ direct mail and collections itself. It follows the oldscenarios, insight remains the domain of the adage of doing what one’s good at and leaving theanalyst. They also require a high degree of rest to someone else.customization to incorporate business-specificsituations, processes, policies and rules. In somecases, their biggest value-add is the ability tocreate work-flows around knowledge processes,enabling diverse stakeholders to provide input andbe alerted to tactical decisions being made.Yet the need for analytics extends well beyondthese ‘closed-loop’ environments where repetitive,mechanistic decisions need to be made. In the24

4. Achieving Knowledge CentricityOrganizations that compete with knowledge — that developing the right methodologies and controls touse knowledge to drive business decisions at all leverage the talents of select third party resourceslevels of the organization — become knowledge- to augment internal processes, or by developing acentric. The concept that knowledge is king strategy to outsource processes end-to-end to thirdpermeates all functions and all levels. It becomes party analytics service providers. No matter whatingrained in the culture, in the CEO’s vision, in the approach, the goal is the same: to best peerevery aspect in which the company does business. companies by becoming a knowledge competitor.Yet many organizations struggle to achieve Using Davenport and Harris’ research as a point ofknowledge centricity. This section examines departure, the first step in becoming a knowledgecommon challenges companies face in becoming competitor is assessing the current state ofknowledge-centric and what can be done to knowledge processes within the organization.overcome these obstacles. Their research indicates that companies typically follow a continuum of development as illustratedMoving through the five levels of in Exhibit 4.knowledge competitionOrganizations can become knowledge-centric inthree ways – by re-engineering their internalknowledge processes and organization, by Level 5 Level 4 Level 3 Level 2 Level 1 Industry Knowledge- knowledge Aspire to driven leader Knowledge Inability leverage business silos to generate knowledge within the actionable organization knowledge wns.com | 25

Exhibit 4: The five levels of knowledge competition Current state of Organizational knowledge Value derived Research and analytical readiness capabilities analytics footprint Level 1 n Required skills not extant Understanding on an Little analytical Inability to generate internally ad-hoc, post-mortem infrastructure actionable basis as to why it n Lack of organizational will knowledge happened n Focus only on basic transactional functionality Level 2 n Business unit / function- Understanding of Analytical resources Knowledge silos centric knowledge creation business and issues embedded in local within the which must be functional teams n Lack of vision to action / organization addressed to improve compete on knowledge individual business n Little or no information units / functions sharing across business units / functions Level 3 n Desire to leverage knowledge Ability to capture Local analytical Aspire to leverage driven from the top current conditions delivery model in knowledge attempt to place n Efforts underway to integrate understand future / better understand internal trends knowledge capabilities Level 4 n Centralized efforts to Ability to anticipate / Central, Knowledge-driven understand business trends adapt to changes in enterprise-wide business holistically external / internal analytical environments to structure n Knowledge creation, capture obtain / retain and management key driver competitive for people performance advantage Level 5 n Knowledge driven innovation Generating consistent CXO-driven, Industry knowledge driving business growth business value well-established leader through insights to analytical n Employees passionate and obtain competitive processes committed to analytics advantage over embedded in competition organizationSource: Adapted from Thomas H. Davenport and Jeanne G. Harris, Competing on Analytics(Boston: Harvard Business School Press, 2007), 36.26

4. Achieving Knowledge CentricityThe continuum suggests that the journey towards It also assumes that the senior managementbecoming a knowledge competitor involves the objective to become more analytically driven haslevels in which a company evolves on a variety of now percolated further down into the organization.fronts. Initially, in level 1, the challenge is a The culture of using quantitative support to guidefundamental one – while there may be a desire to decisions is now something to which mostbecome more analytical, the company finds that it managers within the organization ascribe. As ahas neither the resources nor the skills to embark result, meetings and business discussions areon the journey. To compare, level 2 companies find peppered with facts and analytic investigations.that over time they have developed someknowledge capabilities in pockets within their So far, the stage-by-stage evolution describedorganization, typically in areas where not having emphasizes how knowledge discovery and itsquantitative skills is simply not an option. importance is viewed and deployed by an organization. But equally as important is the ‘how’Achieving level 3 is an important watershed for an and the ‘what’ – ‘how’ the knowledge is createdorganization; it reflects a situation where and ‘what’ kind of knowledge is created. Onlyexecutives (typically senior management) have companies that truly believe in the benefits ofrealized that, in order for their company to keep up creating a knowledge repository and insightwith the competition, they must become more creation go the extra mile, taking the time to thinkquantitative in their decision making. through changes in organizational design as aThis realization is typically arrived at when a catalyst to the process of knowledge discovery, andcompany’s competitors consistently generate making investments to ensure that the knowledgehigher returns, launch better products and gain created is complete and rich in insight.market share. Level 4 can be considered anincremental step from level 3 but mostimportantly, it demonstrates to the organizationthat the aspirations of level 3 can be convertedinto tangible results on the ground.Level 5 knowledge centricity: Achieving a360° view of the businessAmongst the most knowledge-savvy level 5 leaders,knowledge-driven decision science is part of thecompany culture. The process of knowledgediscovery and consumption is collaborative,encompassing the organization in everydepartment, at every level. To become a level 5leading-edge, out-in-front knowledge competitor,companies must adopt a 360° approach – it is thebrass ring of competing with knowledge. Because knowledge processes within organizations typically sit within white-collar environments,Achieving level 5 implies an evolution on a variety managers mistakenly assume that these processesof fronts. At a minimum, it requires that the ability cannot benefit from standardization, that they areto leverage knowledge on specific issues and not scalable, and that there are no efficiencies tosituations that was achieved in level 4 is now a be gleaned from centralizing them andfeature of just about every material decision the disaggregating them by skill set. It is this lack ofcompany makes. This ability spans the full standardization and scalability that actually standsspectrum of business decision making – from in the way of a company becoming a truestrategic decisions to tactical decision making. knowledge competitor. wns.com | 27

Finally, while all managers would readily agree that The five level of knowledge competition quiz:their business issues are multi-dimensional in Where do you stand?nature (it would help them to understand not only Where does your organization fall on the path tothe quantitative relationships that their data becoming a knowledge competitor? Is yours aprovides them with but also contextual data – for knowledge-centric organization where knowledge isexample, information about competitive moves, easily accessible to drive all business decisions,what consumers are saying on blogs or trade large and small? Or is your organization stillchannel developments as it relates to the business impaired? Where knowledge is used to driveissue at hand), managers in level 5 companies are business decisions, is it ad-hoc?willing to invest in knowledge creation that fills inthe blanks on contextual information – we call thisa 360° approach to knowledge creation.Answer these questions to see where your organization falls on the knowledgecompetition continuum1. What are your company’s knowledge 1 point: We know what has happened capabilities? historically in our business; for example, we can accurately explain where we have 1 point: Our knowledge capabilities are gained or lost share and why. negligible; in decision making, we’re largely ‘flying blind’. 2 points: We can extrapolate existing trends, for example on price or on consumer 2 points: Knowledge creation is local and preferences. opportunistic and does not support our company’s full range of capabilities. 3 points: We know which levers we can deploy and by how much we need to activate them to 3 points: Our organization has started to improve a specific metric against a implement integrated knowledge processes. competitor. For example, we can predict with reasonable certainty our share position 4 points: We are able to leverage knowledge- against a competitor based on a specific driven decision making to create a point-in- change in our price. time advantage for a specific business issue against our competition. 4 points: We know how to use knowledge to innovate and differentiate our products and 5 points: We are equipped to leverage services. For example, we can use our knowledge-driven decision science to create knowledge of the consumer and how his / her sustainable, enterprise-wide advantage over preferences have evolved over time to predict our competition. demand for our product based on features we plan to introduce into our product or service2. What questions might knowledge answer over the next year or two. in your business? 5 points: We ask, and answer, questions such 0 points: Dont know / We rely on individuals as: Whats next? Whats possible? How do we rather than any systematic method for making stay ahead? We know enough about the business decisions. market, consumer behavior, where our28

4. Achieving Knowledge Centricity competitors are headed, and what new 2 points: The value of knowledge processes products and services will emerge in the can be measured in the ROI of specific future to predict the next sea-change in our decisions where we have applied knowledge. product or service markets. 3 points: Knowledge processes may eventually drive future enterprise performance3. What are your knowledge objectives? and market value. 0 points: Not clear about our knowledge 4 points: At some point in time, knowledge objectives. processes will be the important drivers of 1 point: To obtain more accurate data on enterprise performance and market value. where we are today. 5 points: Knowledge processes are the 2 points: To use knowledge so that decisions primary driver of performance and market are supported by facts, not just made by value of our enterprise. intuition. 5. What would best describe your 3 points: To institutionalize processes so that organization’s current research and we consistently use knowledge in our decision making. analytics footprint? 4 points: To extract unique insights from 0 points: Our research and analytics footprint knowledge processes in order to gain is non-existent. competitive advantage from specific decisions 1 point: Few analytic processes or dedicated in specific situations. resources are embedded in the organization. 5 points: To use knowledge constantly so 2 points: Analytic resources are embedded in as to consistently make decisions that range local functional teams. from the strategic to the tactical with the objective of changing our competitive position 3 points: Analytic delivery models are in a fundamental and permanent way. embedded in specific processes. 4 points: There is an enterprise-wide analytic4. How do your knowledge processes structure in place but CXO backing is not currently drive value? apparent. 0 points: We dont have any knowledge 5 points: Analytic processes are processes in place. well-established across the enterprise with visible leadership from the CXO. 1 point: They do not drive discernable value. wns.com | 29

Where do you fit on the knowledge competition scale? Level 5 Level 4 Level 3 If you scored If you scored between 21 and Level 2 between 16 and 25 points, you Level 1 If you scored are at between 11 and 20 points, your If you scored organization is at Level 5: If you scored between 6 and 15 points, your Level 4: Competing with between 1 and 5 10 points, your organization is at Leveraging knowledge points, your organization is at Level 3: Aspiring knowledge, To maintain and organization is at Level 2: to compete with but not enhance your Level 1: Lacking Generating knowledge comprehensively advantage as the ability to knowledge in To move to To move to your competition generate local teams or level 4, your level 5, your moves actionable insights units primary goal primary goal aggressively To move to To move to should be to should be to toward level 2, your level 3, your clear the major develop cross- knowledge primary goal primary goal capability functional, competition, your should be to put should be to hurdles on your coordinated, primary goal basic, integrated develop a clear path to programmatic should be to transaction vision among knowledge approaches to expand your functionality and stakeholders that competition. knowledge 360° view of high-quality data driving decisions creation and knowledge-driven in place, then to with knowledge knowledge-driven decision making, harvest the will add value to decision making. using knowledge proverbial ‘low- your business. to solve business hanging problems and knowledge fruit’ – take full to begin making advantage of knowledge-driven business decisions with opportunities.9 discrete, easy-win knowledge processes.9 Note: This quiz was developed by WNS based on Davenport and Harris “Competing on analytics stages model.”See Thomas H. Davenport and Jeanne G. Harris, Competing on Analytics (Boston: Harvard Business School Press, 2007), 36.30

4. Achieving Knowledge CentricityWhat stands in your way to becoming a to scaling knowledge resources and processes across the organization. Exhibit 5 highlights someknowledge competitor? of the most common challenges associated withFor most organizations, embedding knowledge in companies prevailing methods of internallybusiness processes is easier said than done. creating and consuming knowledge.Challenges range from the inadequacy of skills Exhibit 5: Challenges to becoming a knowledge competitor Skill set n Need for specialized skill sets challenges n Cost of in-house capabilities Scale n Difficult to scale across divisions / product categories / challenges services / global locations Organizational n Corporate silos challenges n Knowledge processes not organizational core competency Standardization nDisparate company-wide process challenges nLack of a well defined knowledge delivery model n Threatens executive power Cultural challenges n Buy-in from all stakeholders difficultSource: WNSSkill set challenges are making decisions based on inadequate orThe delivery of knowledge processes requires incorrect knowledge.specialized skill sets in order to generate If a company does decide to make the investmentactionable insights. Yet, in organizations that have in specialized skills, these resources are hard tonot achieved a measure of knowledge centricity, find. The number of graduates with math, science,knowledge process professionals’ skill sets are statistics and other quantitative degrees continuesgenerally suboptimal. to decline in the United States. Even if theseWhere well-educated, domain-rich knowledge resources can be sourced, they are very expensive.process employees do exist, they often are — by For example, a U.S.-based statistician with five toeducation or experience — not capable of nine years of experience earns, on average, overdelivering the full range of analytical processes. $77,000 per year, while an analyst with lessUnfortunately, analytic processes require highly experience earns over $56,000 per year. Givenspecialized capabilities. The result? Companies are their short supply, these resources are only willingrelying on small teams of individuals without the to work for top-tier companies, companies thatcollective skills necessary to respond to any and all already embedded an analytic culture in their styleknowledge requests, suggesting that organizations of working. wns.com | 31

Scale challenges consumers, the position of the brand in the mindWhen companies create and consume knowledge of the consumer, the pricing strategy, thein an ad-hoc or department-by-department competitive set the product faces and the salesfashion, effectively scaling knowledge work can be strategy. The input into this process therefore mustextremely difficult. come from conceivably every single function within the organization. And once a forecast has beenAnalytic capabilities tend to be well-developed in created, the results of the effort should bepockets and closely allied to certain geographies, communicated back into each of the functionaldepartments or perhaps even specific analytic areas so that the results govern the manufacturing,tasks. The loyalties of the resources tend to be distribution, sales and marketing plans of thealigned to their managers and often their organization – a truly collaborative process.capabilities are a well-kept secret from the rest ofthe organization. In such circumstances, it is verydifficult for an organization to fully leverage thesecapabilities across geographies or in newfunctional areas.Companies that rely on individual contributors,rather than organized teams, to generateknowledge often find it challenging to quickly andeffectively ramp up knowledge creation to service abusiness challenge or opportunity. In organizedteams, analytic processes can be disaggregated byskill requirements, ensuring that resourcesspecializing in hard-to-find skills are used in themost efficient manner across a larger analyticworkload.Organizational challengesMany knowledge processes require collaboration It is fair to say that the delivery and managementacross corporate departments in order to achieve of knowledge processes are typically not within anoptimal results. However, these departments are organization’s core competency. This lack ofusually at uneven stages of development when it attention to the process itself by which insight iscomes to research and analytic capabilities. created means that when other seemingly moreThe ‘silo’ effect is also in play; leadership has pressing business issues surface, any progress orvarious, and often conflicting political objectives investment in further knowledge centricity goes byand aspirations. These factors render a the wayside. To compete effectively, knowledgecollaborative knowledge effort extremely processes designed to inform business decisionschallenging. Therefore, the results of analytic tasks should be as integral a part of business operationsare driven by the lowest common factor rather than as budgeting, marketing to new customers orthe highest common multiple. Forecasting is a developing a new product line.classic example of this challenge – while planningmay be the function that owns the process, the Standardization challengesprocess requires data from just about every other Given that knowledge processes are generallyfunction. How much a company will sell of a developed and used in pockets by transientproduct (particularly a new product) depends on a resources without deep specialties, one can expectvariety of factors, including the dynamics of these processes themselves to lack standardizationmarket supply and demand, past performance of across product divisions, geographies or businessthe companys products in launch situations, the units. As a result, analytic processes with the samedegree to which a product meets the needs of objective are run with inconsistent data32

4. Achieving Knowledge Centricity Implementing knowledge processes correctly is not easy and moving to knowledge-driven decision making can be a hard pill for some executives to swallow. Stanford professors Jeffrey Pfeffer and Robert I. Sutton write in the Harvard Business Review that “evidence-based practice (such as knowledge-based decision making) changes power dynamics, replacing formal authority, reputation, and intuition with data.”11 Knowledge-based decision making is also a great leveler. Rather than being solely accessible to executives with many decades of experience to inform intuition, knowledge can be — and should be — accessible to anyone and everyone inside the organization. Pfeffer and Sutton quote former Netscape CEO James Barksdale: “If the decision isdefinitions; analytics that manipulate price going to be made by the facts, then everyone’sinformation from a company’s transaction systems, facts, as long as they are relevant, are equal. If thefor example, can create vastly different outputs decision is going to be made on peoples opinions,depending on the definition of price. Spreadsheets then mine count for a lot more.”12built by individuals across business units or The trade-off that an executive is asked to make ingeographies may use different modeling leading his organization to become a knowledgetechniques, statistical techniques, or assumptions competitor is worthwhile. He may give up some ofon consumer metrics like elasticity or macro- the seeming prestige that comes with being theeconomic variables such as growth and inflation. one with the talent and experience necessary toAs long as these processes are delivered in silos, make intuition-based decisions in exchange forthere is little prospect of standardizing the rules, being the leader of an organization thatassumptions and techniques for analytics. consistently outperforms its competitors. Clearly, asking executives to make that trade-off — andCultural challenges then getting the buy-in of stakeholders at all levelsCompeting with knowledge, unlike other corporate — will be difficult.transformation initiatives, is not a ‘panacea thatthe CEO can simply delegate’.10 Whenimplemented correctly, knowledge processes arefully integrated top-to-bottom in every function,every process, and in every decision throughoutthe business. They are deemed strategic andingrained into the company’s culture.10 Michael Hammer and James Champy, Reengineering the Corporation (New York: HarperCollins, 2003).11 Jeffrey Pfeffer and Robert I. Sutton, “Evidence-Based Management,” Harvard Business Review, January 2006, 11.12 ibid. wns.com | 33

5. Changing the GameOrganization, culture, skills, talent, tools, phase of the trend to outsource. During the latestandardization – together all these challenge the 1980s and early 1990s, organizations came to thecompany to become a true knowledge competitor. realization that they could not only leverageBut companies that seek to make rapid, outsourcing to save cost, but also mitigate risk,substantive change can look to a trend in business avoid capital outlays and expand skill sets.models that has been taking hold since the 1970s,and has proven to be an effective and flexible Organizations also realized that there werestrategy to scale, tap into talent, and most opportunities to leverage those benefits in otherimportantly, change the way the company develops areas in addition to IT. The industry moved fromand acts on insight. This trend is outsourcing. outsourcing IT processes to the outsourcing ofAs leading companies become increasingly adept business processes — commonly referred to asat tapping into sources of talent offshore, they business process outsourcing or BPO — initiallyhave outsourced higher value, complex, transactional or rules-based processes such asspecialized skill and knowledge-based work such accounts payable or customer care, moving up theas research and analytics, commonly referred to as complexity ladder to judgment-based processesanalytics outsourcing. such as treasury or industry-specific processes such as underwriting support for life insurance companies. Moving these processes to third partyThe evolution of analytics outsourcing providers is proving a good strategy to deliver notWhen companies first outsourced, the focus was on only cost and quality, but flexibility as companies’obtaining support for the implementation of needs change.technology within their company. Processes such asthe development of applications were migrated Today, outsourcing in its various forms has beenoffshore in order to tap into the emerging workforces adopted as part of the business model of thein countries such as India. Over time, other world’s largest companies. And cost, quality andprocesses grouped together as information process flexibility are no longer the sole drivers; companiesoutsourcing or ITO — help desk, IT support — found seeking competitive advantage are examining thetheir way offshore as technology made it possible to potential to outsource processes that were formerlywork 24/7 in geographies around the world. considered ‘core’ or ‘mission critical’. Not only have these companies found that suppliers areThis movement of work brought an added fully equipped to provide industry-specific andadvantage – cost savings. The availability of lower complex problem solving skill sets such as thosecost labor in emerging economies, more accessible required by research and analytics, but thattechnology and the ability to rapidly shift non-core, suppliers have implemented privacy, security andrepetitive and discrete tasks drove the first IP standards to mitigate any risk in transferring critical data.34

Today, there is a ripe environment for the kind of But as the leading analytics service providers’high-end, strategic, partnership-based outsourcing offerings have evolved, so have their clientthat is analytics outsourcing. Indeed, estimates organizations. For example, rather than deliveringsuggest that the size of the analytics outsourcing discrete market research services to professionalindustry will range from $10 to 17 billion by services or corporate firms, analytics outsourcing2010.13 While ITO and BPO have grown at offers comprehensive, domain-targeted knowledgecompounded annual rates of 34 percent over the services such as business and financial researchlast five years, and are projected to grow at 24 and analytics to clients in a wide range ofpercent a year over the next five, the analytics industries, ranging from consumer packaged goodsoutsourcing market is projected to grow by 50-70 to consumer financial services, retail andpercent annually.14 entertainment, often to a level of sophistication that cannot be rapidly or easily replicated inAnalytics service providers are fully able to help house.their clients become 360° knowledge competitors.Initially, providers offered ‘horizontal’ services — As it continues to evolve and grow, the analyticsmarket research, business and financial research, outsourcing market is moving toward a sharedor analytics — largely for professional services services center of excellence model, here calledfirms. Client organizations typically purchased the ‘Knowledge Center of Competency’ model – andiscrete services – research or analytics, for approach that goes hand-in-hand with developingexample, from the analytics service provider. 360° knowledge capabilities. Exhibit 6: KPO evolves towards the knowledge center of excellence model Analytics outsourcing started small but is evolving towards a shared services environment Knowledge shared 1st Generation 2nd Generation 3rd Generation services center n Engage a provider n Contract for a series n Add new Relationship known for specific of repeatable tasks capabilities expertise n Analytical / research n Series of projects in n Multiple parallel projects project work a stream of expertise n Integrated approach to solving Type of work n Simple MIS n Predictive modeling business problems using multiple capability sets - e.g. n Graphics n Business research contextual information through n Market research primary of secondary research to support analytic findings n Test to see if simple n Seek improved n Take advantage of knowledge Client knowledge work can service levels and management, scalability, best objective be offshored process practices management, e.g. faster turnaround times, reduced errorsSource: WNS13 “WNS plans to up the ante in KPO business,” The Economic Times, 27 Mar 2008,http://economictimes.indiatimes.com/Infotech/WNS_plans_to_up_the_ante_in_KPO_business/articleshow/2902891.cms14 TPI, “Knowledge Process Offshoring: A Balanced View of an Emerging Market,” July 2007,http://www.tpi.net/pdf/researchreports/KPO_ResearchReport_july07.pdf wns.com | 35

Exhibit 6 demonstrates the development of they did not comprehensively deal with theanalytics outsourcing services from discrete decision support needs of the entire organizationknowledge process work to integrated, vertically- across departments and geographies. The outputspecialized services – not unlike the shared from this effort also needs to be disseminatedservices model that has been widely adopted for across this broad spectrum to ensure the differentfinance processes. As providers have assumed pieces of an organization that the particularend-to-end knowledge processes, the metrics on decision touches are well-coordinated. However,which they are judged have changed from simple the basic building blocks that create thisservice levels such as turnaround time or accuracy knowledge are essentially the same – finitelyto whether or not the client achieves the business arrayed skill sets (statistical, data manipulation,outcome it targeted by way of the knowledge domain) and types of research and analyticsprocess (For example, collection analytics). (business and financial research, market research, predictive analytics, etc.). Companies that want anIn its first phase, clients try out the concept of all-pervasive knowledge environment andanalytics outsourcing, testing providers’ understand the power of concentrating in onecapabilities by outsourcing lower-end, discrete location resources with similar skill sets haveknowledge processes. Satisfied with performance, created analytic hubs, or ‘Knowledge Centers ofcompanies often move to the second phase, Competency’ – again, essentially shared servicestesting the delivery of higher-end but still discrete environments for knowledge processes.processes, now delivered in a series or as a part ofa program rather than as one-off projects. Within these centers, based on the relevant skill set they possess, resources are brought to bear in a project environment against types of business challenges (pricing, forecasting, etc.) and types of analytic / technical techniques (data sets used, statistical techniques, etc.). This specialization helps institutionalize the approach to similar kinds of problems. Further, analytic or research tasks for business challenges are broken down to match the resource specialization available – so a forecasting effort would be broken into research tasks, quantitative / modeling tasks, etc. Senior analysts then pull together the work output from the team and synthesize it, extracting insights alongWith the acknowledged success of the second the way.phase, companies are now comfortable leveraginga wider range of analytics service provider Appropriate individuals within the organization cancapabilities. They are adopting an integrated interact (for example, request research) with thisapproach to knowledge work, asking providers to centralized resource through web-based knowledgedeliver higher-end services such as developing portals no matter where they may becustomer lifetime value models or fraud geographically. These web portals also serve as amanagement models. This holistic approach gets repository for business challenges addressed in theclose to the end-game, the ‘Knowledge Center of past, helping analysts in different parts of theCompetency’ where knowledge created by a organization learn from the efforts of their peersvertically-specialized provider is consumed thousands of miles away.throughout the organization.As we have discussed, level 5 efforts to createleverageable knowledge would be inadequate if36

5. Changing the GameHow analytics outsourcing resolves drive business decisions. While outsourcing knowledge processes does relieve the firm fromchallenges to becoming a knowledge obtaining, manipulating and correlating knowledgecompetitor in-house, it does not abdicate the firm from itsSmart companies are never afraid to change the responsibility for ingraining knowledge-drivenbusiness model when it moves performance onto a decision science into the company culture. Thenew trajectory. In the case of knowledge processes, external provider can conduct the knowledgecompanies can tap into external resources when discovery, perform the research, run the analytics,those resources can perform knowledge services but the company must force a change in how thewith higher quality, greater efficiency and knowledge is used, allowing it to come from everyeffectiveness, at a lower cost, in less time. corner of the organization. This is all the more applicable for companies with federatedThat does not mean, however, that businesses are engagement models.off the hook when it comes to using knowledge to Exhibit 7 highlights how analytics outsourcing resolves the challenges faced on the path to knowledge centricity. Exhibit 7: How analytics outsourcing resolves the challenges to becoming a knowledge competitor Advantages of the Knowledge Center of Compentency Leverage specialized skill sets n Access affordable resources n Skill sets Better utilization of resources n ts lien or c Scalability nAchieve scale across geographies and business units ks f ec len nOvercome corporate silos ott Organization nEstablish and industrialize best practices lb na t er In nStandardize disparate analytical processes Standardization nEstablish a well-defined delivery model n Standardize disparate analytical processes Cultural challenges n Establish a well-defined delivery modelSource: WNSResolving skill set challenges single analyst to create knowledge, the analyticsAnalytics outsourcing enables the organization to service provider can offer more – the domainaugment suboptimal corporate skill sets by analyst who works side-by-side on site with theexpanding the capabilities of a single brand manager supported by a statistician and adepartmental analyst with as many as three data scientist. That three-person approach ensuresknowledge specialists. Whereas client that every necessary skill set is available in theorganizations might rely solely on the expertise of a knowledge discovery. wns.com | 37

The effects of that disaggregation of the single Resolving scale challengesscientist’s skills into a trinity of specialized skill Partnering with an analytics services providersets are substantial means knowledge services are easily scalable –Eliminatesn the bottleneck that results when all easily expanded up to create a knowledge knowledge requests flow through a limited repository across a company’s geographies, every number of analysts, introducing the benefit of day, 24/7. By definition, the process of working speed. with an outsourcing service provider requires an organization to extract its knowledge processesReducesn cost. If it is even possible to find a from the many internal nooks and crannies they statistician with deep domain knowledge, that reside in and optimize them for scale, skills talent is expensive. By disaggregating the (both quality and quantity), process steps, scientist’s functions, it is possible to quality control and a variety of other process dramatically reduce the costs associated with hygiene factors. knowledge creation.Increasesn productivity by deploying a specific skill against that component of an analytic task that the skill is best suited to address, it is possible to increase productivity.By delivering knowledge processes from lower-costgeographies, organizations benefit from access tohigh levels of training and expertise availablewithin a substantial pool of PhDs and MBAs,coupled with the benefits of lower costs.For example, in India, from which many providersoperate, the educational curriculum is rich from aquantitative skills perspective. Such skills are alsoprized from a socio-cultural perspective andfamilies encourage their wards to get ‘hard’degrees. At the same time, labor costs aresubstantially lower in India than in the U.S. This examination itself is the first step in makingor Europe. knowledge processes scalable so that an optimized process can be provided to stakeholders across anDelivering analytics outsourcing also requires organization on an ‘any-place, any-time basis’.talent with domain experience. Fortunately, avariety of industrial sectors — such as consumer Once an organization makes knowledge servicespackaged goods, retail, financial services and available to the rank and file of an organization, onetelecommunications — have exploded from a would expect (over time) a substantial increase indomestic market perspective in countries such as the consumption of these resources. Scaling sub-India as the IT / BPO services industry has optimal processes (for example, processes whereexpanded. These companies increasingly provide a due to lack of standardization, core assumptionsbase of domain-savvy talent to help drive forward change from one instance to another, or processesclient engagements in analytics outsourcing Not that lack automation or streamlining and aresurprisingly, India’s growth story continues to drive therefore time consuming, expensive and prone tothe reverse ‘brain drain’ effect with more and more errors) would be an effort doomed to failure.Indian professionals coming back to India, aftereducation abroad, for professional pursuits. Because analytics service providers are dedicatedBusiness domain-specific roles in analytics to the business of knowledge creation, they haveoutsourcing provide a vehicle for analytical Indians the benefit of scale — size, scope and location —working in Fortune 500 companies to come back that most companies simply cannot replicate whento India and perform their roles remotely.38

5. Changing the Gamethey manage their processes internally. practice delivery model. Rather than creating anOutsourcing helps develop industrial strength internal model to define how knowledge is createdanalytical capabilities company-wide, establish a and distributed to ensure collaboration among allstrong backbone of enterprise analytics in the business areas, the client can turn to analyticscompany and achieving Every Day Low Cost service providers to deliver and standardize,(EDLC) in that delivery of analytics services. knowledge in all areas of its business. EstablishingService providers can streamline process steps, a federated engagement model and systematicallyinject technology to make the processes more standardizing fragmented analytics services (withinefficient, source talent from anywhere in the world, the organization as well as across third-partyall at the right cost, and then deliver the process service providers) also creates efficiencies into the right stakeholders within an organization, no horizontal leverage across the company. Goodmatter where they reside. governance is, of course, a pre-requisite for the federated engagement model to succeed.Resolving organizational challengesAnalytics service providers can resolve a company’sorganizational challenges, breaking down corporatesilos and establishing best practices, byBecomingn the client’s main clearinghouse for knowledge requests. One leading CPG company was able to overcome one of the fundamental challenges associated with becoming a knowledge competitor — the pervasive corporate silo structure — by creating a centralized knowledge team offshore to provide support to Standardization means that for a certain types of brand managers distributed around the world. analytic problems, a company uses a consistent Within a centralized team that the company analytic solution – a holistic approach that defines could not have created on its own, analysts what issues need to be looked at for a given could share information across what would be — problem, statistical techniques that embody the in the client organization — corporate silos, latest and greatest thinking on how a particular promoting collaboration to standardize problem is solved, data that is consistently sourced knowledge creation and leverage best practices. from the right data storehouses within an organization, and resource skill sets that are evenlyOfferingn broad and deep resource pools, deployed, no matter when or where the solution is leveraged from engagements with many clients required. A consistent approach to segmentation across a range of industries. Providers staff efforts may mean agreement within an highly-specialized analysts who can tackle organization on how consumer segments are business requests in a wide variety of functional defined from market research data. For example, areas. a company can decide that a certain statisticalOfferingn knowledge expertise in areas outside modeling technique is the gold standard for the company’s primary domain. While analysts analytic tasks around pricing. For other analytic on the client’s centralized team may not be tasks that involve the analysis of sales data, familiar with trends or functions outside the analysts can agree on which specific corporate company’s primary focus, an analytics service data repository is to be used and with what provider can leverage its experience across a adjustments. variety of industries to offer wide-ranging knowledge expertise. Similar to the rigor brought by BPO service providers for transactional processes, knowledgeResolving standardization challenges processes also benefit from standard operatingBy partnering with the right analytics service procedures that ensure that the solutionsprovider, a company can quickly implement a best themselves are trustworthy and devoid of errors wns.com | 39

that can creep in when a company relies more These portals enable senior management toon art than science when resolving its analytic evaluate where analytics is being used inside anproblems. organization and provide a ‘paper trail’ on what decisions were made and why. They also provide aResolving cultural challenges means to take the cost of analytics and allocate itEven with the most comprehensive change to users within an organization, a key means ofmanagement programs in place, achieving cultural controlling the costs and RoI of such programs.change is not guaranteed. An alternative to dealing This represents a radical shift in the rules ofwith the complexities of tackling the cultural engagement and indicates a maturing of thechallenge is to implement a ‘build it and they will analytics outsourcing service delivery model.buy in’ approach. Leaders with the conviction that Once the naysayers see the success of analyticsbecoming knowledge-centric is an imperative for outsourcing for themselves, they may well jump onsuccess can mandate the consolidation of research board. Perhaps they were unwilling to riskand analytical capabilities — ideally in an investment in knowledge capabilities sight unseen,analytics outsourcing relationship in which all but once they see the results of knowledge-drivenbusiness areas can tap into the knowledge center decision making in their business, they are farof competency — to generate the knowledge to more likely to buy in.drive their business decisions.Sophisticated analytics service providers Additional analytics outsourcing benefitsimplement collaboration tools as a delivery For companies that really want to succeed asmechanism to speed up research and analytic knowledge competitors, analytics outsourcingconsumption. A common approach is to put a represents an opportunity to transform theknowledge center of competency at the other end business from one driven by intuition and ad-hocof an ‘analytic portal’, a portal that acts as a knowledge gathering and analysis practices to onelibrary of analytic solutions and as a means to that is driven by insight – to resolve the challengesrequest and receive analytic solutions from the associated with becoming knowledge competitors.shared service environment created within the But analytics outsourcing also offers otheranalytics service provider. Now far-flung business benefits. Like ITO and BPO before it,stakeholders have a window into what types of analytics outsourcing certainly delivers costbusiness problems are being solved by their savings through economies of scale and laborcolleagues in different parts of the organization. arbitrage. But analytics outsourcing goes farThis itself can spark the use of analytics where beyond savings, generating gains throughpreviously the reliance was on intuition. This efficiencies, productivity increasespractice promotes increased creation of IPs and and new capabilities.artifacts and improved documentation andknowledge transfer. Another advantage to be gained from analytics outsourcing comes from leveraging the client- specific domain expertise and organizational knowledge built up within a knowledge center of competency set up by an analytics service provider. While the best service providers bring business domain knowledge to such programs, sophisticated organizations are most interested in embedding their own way of looking at business issues. Creating a center of knowledge competency allows those organizations to externalize their knowledge and then make it available more broadly across their footprint.40

5. Changing the GameImplementing actionable insights in the retail financial services industryToday, an industry under siege, such as retail For example:financial services, has more need for actionable 0 By running specific campaigns, banks caninsights than ever before. By obtaining powerful more effectively acquire new customers.insights across the entire retail banking value 0 Cross-sell strategies can be developed bychain, in order to maximize profitability, minimizerisk and reduce cost, consumer banks can survive mapping the customer’s unmet needs to aand thrive. product portfolio. Additional services and products can then be sold by offeringCertainly knowledge processes can support better products in the same range, or up-sellingdecision making when it comes to cost control in offering a product by answering to acustomer operations. But savvy organizations customers higher need.infuse disciplined research and analytics processes 0 Using research and analytics, retentionin sales and marketing, risk and distribution strategies can be designed to targetprocesses. customers who are most likely to attrite. Marketing and promotional strategies canMarketing and sales analysis then be devised to target and reduce attrition.In this fierce competitive landscape, for the retailbanking industry to remain profitable, its business Increase n sales force effectiveness: Sales forcemodel must increase its customer centricity across effectiveness (SFE) analytics analyzing andthe customer’s entire lifecycle. By implementing optimizing the interaction between the salesan end-to-end research and analytics program, force and their clients in various SFE spheresbanks are able to: such as segmentation and targeting, client profiling, call planning, sales force sizing andImproven customer satisfaction: Customer structure and territory design and alignment. satisfaction can be measured by fielding a disciplined customer survey program, taking Risk management customer feedback on aspects ranging from With dramatic spikes in delinquencies and charge- time taken to stand in a line in the bank to the offs, the retail banking industry has developed salience of the available product suite. increasingly stringent lending standards for By analyzing feedback, the bank makes the potential and existing customers alike. adjustments necessary to increase market share By implementing insight-based lending strategies through the right products, and enhance the which allow a bank to take calculated risks, the customer experience. bank can position for portfolio growth.Developn insights from data: Targeted analyses on Credit n risk: Research and analytics can calibrate transaction datasets segments customers based the optimum balance between losses and revenue on their transaction behavior. The segments can growth, set the optimum cut off score for be then be further analyzed using data mining application approval, build predictive risk models and advanced statistical techniques in order to for defaults, and support decision making on understand which segments are the most credit limit increases and decreases for a portfolio profitable or which deliver the highest return on based on customer behavior, transaction history, marketing investment. change in credit score and other external factorsBuildn and strengthen profitable relationships: Collection n strategy: By implementing knowledge The stage at which customer is on the customer processes, banks are able to build delinquency lifecycle is critical to the development of models utilizing customer data including past marketing strategy. transaction, payment and delinquency data wns.com | 41

Exhibit 8: Knowledge processes in retail financial services Sales and marketing Risk Operations Campaign Credit risk Branches n MIS nIn-house credit scoring n Network expansions / n Prescreen evaluation nValue@risk consolidations n Model diagnostics nCredit portfolio monitoring n Format analysis n ROI analysis nRisk based pricing n Performance and profitability analysis Acquisition Collections ATM n Prospect analysis nCollection scoring n Network expansions / n Segmentation and targeting nCall scheduler analysis consolidations n Promotion optimization nDelinquency modeling n Cash loading and route planning n Performance and profitability analysis CRM Fraud n Cross-sell and up-sell models nScoring n Activation; balance build nRouting n Lifetime value / profitability nModeling Marketing channel spend n Market mix modeling n Channel spend optimization Retention n Churn prediction / retention n Loyalty / switching patterns Enabling / Data mining and management supporting Reporting, dashboards and visualization processes Model and tool development and recalibration along with other external data to segment each kind of fraud, it is then possible to develop customers who self cure or who need collection predictive algorithms, building them into a treatment. These analyses in turn contribute to process as a prevention mechanism. call intensity analysis – determining the Pricing n optimization: The struggle to price optimum time and frequency with which to products competitively is a never-ending set of contact a delinquent customer. challenges, loaded with tough questions such as:Fraudn strategy: Research and analytics allows a 0 What should our overall rate level be, and how bank to build effective identity, transaction and should it be spread to classification? payment fraud defenses against growing losses. 0 By tapping into the experience of subject matter Whats the competition doing? experts in a particular area and coming up with 0 What are the prevailing market conditions? business rules to identify the trigger points for42

5. Changing The Game 5. Changing the 0 How will customers respond to a price n locations: New Which markets or areas have the change? greatest potential for new ATM or branch traffic? 0 What is the potential impact on earnings? Performance n and profitability analysis: Which locations will deliver the highestTraditionally, companies have relied on cost-based performance based upon capacity usage,pricing strategies to set prices. And while cost profitability, risk factors and customerremains a critical consideration, it does not factor demographics?in the implications of the competitive context orcustomer behavior. n cash ATM loading optimization: What is the optimal cash replenishment schedule in whatDistribution denominations and in which locations?To better serve existing and potential customers,banks must expand their network of branches andATMs. Understanding market potential, customerhabits, preferences, transactions anddemographics is the key to effective decisionmaking. Analytics can help the bank determine wns.com | 43

6. Becoming a Knowledge CompetitorThe advantages of implementing analytics If the organization is at level 1 (Lacking the abilityoutsourcing vary according to the aspiration of the to generate actionable knowledge) or level 2organization. If a company already drives its (Generating knowledge in local pockets), fordecisions with knowledge, analytics outsourcing example, the starting point on the path tocan help retain competitive advantage more knowledge competition will be different than if theefficiently and cost-effectively. If the organization company has already reached level 4 (Leveragingaspires to move up the scale of knowledge knowledge, but not fully).competition, analytics outsourcing can helpachieve the end state more rapidly. Analytics Exhibit 9 highlights the four starting points fromoutsourcing has a role to play in every company – which companies can embark on the road toknowledge-novice or knowledge-savvy, regardless knowledge competition, depending on their level ofof the industry. But how a company engages sophistication and the type of market challengesanalytics outsourcing depends on where the they face. Outsourcing discrete analytic tasks is acompany falls in the five levels of knowledge good way to test whether the organization is readycompetition. to tackle a more analytic approach to decision making. It also tests an analytics service provider’s capabilities. Exhibit 9: Paths to knowledge competition Solve peripheral or readily Resource constrained n Discrete extractable knowledge tasks with Need for specialized resources n knowledge modest domain knowledge Variable cost model n tasks requirements Start with tasks that act as building Easy to implement and scale n Low-to-high blocks for more complex analytics – e.g., Low failure rate n complexity start with MIS, reporting and data analytics Develop client-specific domain knowledge n projects before forecasting and segmentation in service provider Benefits of a coordinated, program-based n Partner across functions on related approach Process thread - knowledge tasks that support a discrete process thread within an organization – Concentration and standardization of n based projects analytic activities e.g., a new product launch Cross-training, knowledge sharing n Identify knowledge process that Business are critical to driving enterprise- imperative n Razor-sharp focus on imperative level business imperatives – - based projects e.g., stopping share loss to a n 360o solution competitorSource: WNS44

Levels 1 and 2: Lacking the ability to knowledge creation such as MIS, reporting andgenerate actionable knowledge and data analytics. Processes that form the basic ‘knowledge building blocks’ inside yourgenerating knowledge in local pockets organization will help the sourcing partner build– start with discrete tasks domain expertise unique to you. If you have pain-If the organization sits relatively low on the points and bottlenecks in these processes, youranalytical savviness scale, beginning analytics sourcing partner’s process skills can remove them.outsourcing implementation with discrete analytic It also frees up your analytical talent from theirtasks is generally the safest route. The goal for the more mundane tasks and gets them focused onorganization is to pick the ‘low-hanging fruit of the more strategic issues. Naturally, with rightknowledge tree’, commencing with a low-risk, sourcing, you will get productivity and costreadily extractable analytic task. Because the efficiencies. As decision science is increasinglyorganization is just embarking on the road to driven by actionable insights, moving up thecompeting with knowledge, starting with a task complexity chain to processes such forecastingthat is not overly complex and does not require and segmentation becomes the logical andmuch domain knowledge will increase the chances anticipated next step.of a successful outcome.At this level, the organization should focus oninsights that can be developed without theallocation of many resources, generally withouthighly specialized resources, and developed undera variable cost model. Of course, just like exercise,even modest focus will pay rich dividends. Betterresponse from marketing programs, reduced fraud,better forecasting all have hard dollars as benefitsto offer. More importantly perhaps, this is anopportunity to invest in a proof of concept to proveto the companys stakeholders (internal andexternal) that knowledge-driven decision makingcan take competitive position to the next level. Initial projects should be easy to implement andLevel 3: Aspiring to compete with scale and designed with low potential for failure.knowledge – move from low-to Further, ramping up the complexity fosters a strong relationship with the analytics service provider,high-complexity projects giving them the opportunity to develop theIf the company has achieved level 3 of competing company-specific domain knowledge that iswith knowledge, it already conducts more complex, critical to success as the projects becomeintegrated analytics processes. Outsourcing as a more complex.proof of concept is still important and stakeholderswill be closely monitoring the speed of completion Levels 1, 2 and 3 engagements gain most tractionand the quality of deliverables. This suggests the when the initial engagements are focused on aright place to begin outsourcing analytics business challenge. If the problem to be solved isprocesses is to start with less complex tasks that the loss of market share or the improvement ofsupport the broader analytical capabilities of the overall customer experience by some factor, theclient. For example, it may be appropriate to analytic solution will resonate more stronglycommence sourcing more investigative forms of with stakeholders. wns.com | 45

Level 4: Leveraging knowledge, but not How should level 4 and 5 companies get started on a analytics outsourcing program? Suchfully and Level 5: Competing with companies have well developed knowledgeknowledge – start with process thread- processes, particularly in pockets supporting high-based projects / business imperative- impact decisions. Good examples are pricing analytics, supply chain analytics, forecasting orbased projects fraud. Another way is to organize the programEven companies that compete effectively with around top of mind business objectives driving theknowledge benefit from implementing analytics senior management team. Processes and tasksoutsourcing. Analytically savvy companies use supporting a drive to cut distribution costs —analytics outsourcing to augment their own supply/demand optimization, fleet utilization,resources and leverage the global delivery footprint forecasting, store lifecycle management, etc. —of their outsourcing partners. As before, the are well linked and can be supported with a highlyorganization gets all the benefits of outsourcing – specialized skill-pool.refocus of internal talent, efficiencies, etc. Theadditional benefit that analytics outsourcing Whatever the scope of the analytics outsourcingdelivers uniquely to such companies is the ability engagement, it should set the organization on theto standardize knowledge processes and make path to competing with knowledge, or moving upthem scalable. In these cases, remaining cutting the knowledge savviness scale. Analyticsedge in core areas of expertise is the driver to outsourcing is simply an extension of theleverage the analytics outsourcing delivery model. company’s enterprise, allowing a large complexQuality with speed, flexibility and lower cost are organization to consistently make smarter,key benefits. better decisions.46

7. SummaryIn today’s environment with the largest drop in decision making capabilities in-house is not alwaysconsumer spending since 1947; widely fluctuating the best way to compete with knowledge. Rather,oil prices; dramatically rising corporate borrowing many companies – more every day – are turning tocosts; increasing competition from companies in third-party analytics service providers to createemerging economies; and a global economic crisis knowledge centers of competency within whichthat has already brought down scores of venerable companies can become leading-edge, out-in-frontinstitutions, organizations that have both deep and knowledge competitors.broad knowledge of its business, its customers andits competitors will have an important competitive This paper was developed as a guide to competeadvantage. The companies that compete with with knowledge elevating the quality and rigor ofknowledge will be much better equipped to both the organization’s insight and ability to act onsurvive the economic downturn and flourish in the those insights. It was designed to provoke answersupturn than its competitors. to key questions that include: n do How organizations effectively compete withYet using knowledge to succeed in a tough knowledge?economy is not the most compelling reason forbecoming a knowledge competitor. Driving n do How knowledge processes support decisiondecisions with knowledge, in fact, is as important making?in a strong economy as in a weak one. In good What n are the challenges most organizations faceeconomic times, it allows companies to move when moving to a knowledge-centric company?leagues ahead of their peers by leveragingknowledge processes to improve customer What n models are leading companies increasinglyretention, more accurately forecast revenues, adopting in order to become full-fledgedbetter manage risk or prevent fraud and optimize knowledge competitors?R&D investment. How do organizations effectivelyConsider some of the greatest business successstories. Many of the corporate leaders we most compete with knowledge?admire gained a competitive edge by competing Examples and case studies make it clear thatwith knowledge – driving all aspects of the those organizations that leverage knowledgebusiness with actionable insights. These winning processes such as research and analytics tocompanies use knowledge processes such as generate a 360° view of their business — and thenresearch and analytics as strategic weapons. act on the insights generated — are able toAnd they know that developing knowledge-driven outcompete their peers. wns.com | 47

How do knowledge processes support Analytics outsourcing and the knowledge center of competency model, a model which aggregates anddecision making? leverages knowledge processes across theHundreds of decisions are made every day across corporation, provide companies a number ofevery business in every function. There is no advantages, in addition to those benefitsfunction, no business, no industry that cannot traditionally attributed to outsourcing (costbenefit from insights that harnessing knowledge savings, quality improvements, better efficiencyyields. In all areas of the business — from sales to and productivity gains). Those advantages include:marketing, finance and risk management to R&Dand human resources — organizations can win by Ability n to tap into specialized skill sets andgenerating actionable insights. Research and affordable resourcesanalytics (R&A) processes — business and Better n resource utilizationfinancial research, data services, domain-specific Scale n across geographies and business unitsanalytic services and market research — are some Standardization n of enterprise-wide bestof the tools knowledge competitors use to gather, practices for knowledge discovery andsynthesize and extract insights from their data. consumption, resulting in elimination of corporate silosWhat are the challenges most Ability n to quickly establish a well-definedorganizations face when moving to a delivery modelknowledge-centric company? A ‘build n it and they will buy in’ solution toLeveraging research and analytics processes to cultural resistance.make knowledge-driven business decisions is noteasy. In fact, only a small percentage of The importance of knowledge is not particularlyorganizations manage to drive decisions with novel; the legendary figure and author of Art ofknowledge, hence the power of becoming one of War, Sun Tzu, wrote about it as early as the 5ththose few knowledge competitors. The common century B.C. “If you know the enemy and knowchallenges that make competing with knowledge yourself, you need not fear the result of a hundredmore difficult include inadequate or ill-matched battles. If you know yourself but not the enemy, forskill sets, an inability to scale, the challenges of every victory gained you will also suffer a defeat.breaking down, the lack of a well-defined If you know neither the enemy nor yourself, youknowledge process operating model, and a cultural will succumb in every battle.”resistance to fact-based decision making.What models are leading companies Today, companies can achieve thatincreasingly adopting in order to confidence — and that edge —become full-fledged knowledge by knowing their competitors,competitors? themselves, and their customers, andBecause of the difficulties associated with then acting on those insights. Andbecoming a knowledge competitor, many these insights are easier than ever toorganizations look to third-party experts for help. generate, assimilate and act onThe rise of increasingly mature and savvy third-party outsourcing providers is allowing companies through analytics outsourcing.to leverage analytics outsourcing and a ‘knowledgecenter of competency’ model to quickly andefficiently reap the benefits of competing withknowledge.48

Notes wns.com | 49

The intent and purpose of this report is purely for information dissemination. WNS and theauthors have made no attempt to verify the reliability of sourced information and cannot beheld responsible for any areas of concern with the informations usage. This report shouldnot be construed or taken as professional advice or statements of direction.Any result taken by the reader, its organization, or related parties either directly or indirectlyare at the sole discretion and responsibility of the user / reader. The information containedin this document is not a substitute for proper analysis, research, legal advice, accounting,tax or professional services and use of the data, its conclusions, and projections are at yourown risk. WNS, the authors and their organizations, and contributors cannot be held liablefor negligence, errors, omissions, improper conclusions, regulation violation, assessments,projected directions and / or any recommendations within or beyond their control orknowledge without limitation.Without limitation, WNS and the report authors and contributors will not be liable for anydirect, indirect, consequential, punitive or other damages. This includes but is not limited toreal or perceived obligation or breach of services surrounding intent, action, regulation,statute, or tort. The content of this report should be taken “as-is” and no additionalexpressed or implied representation or warranty will apply. Use of this document is at thereaders, and if applicable, their organizations own risk.Subject to copyright limitations, (c) 2012, All Rights Reserved

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About WNSWNS is a leading global business processoutsourcing company. WNS offers business value to200+ global clients by combining operationalexcellence with deep domain expertise in keyindustry verticals, including Travel, Insurance,Banking and Financial Services, Manufacturing,Retail and Consumer Packaged Goods, Shipping andLogistics, Healthcare and Utilities. WNS delivers anentire spectrum of business process outsourcingservices such as finance and accounting, customercare, technology solutions, research and analyticsand industry-specific back-office and front-officeprocesses. WNS has over 25,000 professionalsacross 30 delivery centers worldwide, includingCosta Rica, India, the Philippines, Poland, Romania,South Africa, Sri Lanka, UK and US.To learn more, please write to us atmarketing@wns.com or visit wns.com

Gaining Competitive advantage through Knowledge process outsourcing

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