Gaining Competitive advantage through Knowledge process outsourcing

4,161 views
4,050 views

Published on

Understanding every aspect of customer behavior. Getting the most out of marketing spend. Driving sales force productivity to the next level. Optimizing logistics to gain supply chain efficiency. Reducing risk. Entering new markets with a targeted strategy. If accomplished, these goals quickly differentiate a company from its competitors. Read more such articles at http://www.wns.com/Insights/Articles/tabid/81/Default.aspx

Published in: Business, Education
0 Comments
5 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
4,161
On SlideShare
0
From Embeds
0
Number of Embeds
9
Actions
Shares
0
Downloads
218
Comments
0
Likes
5
Embeds 0
No embeds

No notes for slide

Gaining Competitive advantage through Knowledge process outsourcing

  1. 1. Gaining competitive advantage through analytics outsourcing
  2. 2. 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
  3. 3. 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
  4. 4. 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
  5. 5. 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
  6. 6. 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
  7. 7. 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
  8. 8. 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
  9. 9. 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
  10. 10. 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
  11. 11. 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
  12. 12. 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
  13. 13. 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
  14. 14. 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
  15. 15. 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
  16. 16. 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
  17. 17. 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
  18. 18. 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
  19. 19. 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
  20. 20. 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
  21. 21. 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
  22. 22. 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

×