Business Analytics Insights


Published on

Get inspired with several articles from leading experts about how Business Analytics can help businesses grow faster with the right fact based decisions.

Published in: Business, Technology
  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Business Analytics Insights

  1. 1. businessanalyticsinsights Brain trust Enabling the confident enterprise with business analytics Informed decision making • Business analytics for industries and SMBs • Analytics applied to processes • Essentials to get started
  2. 2. Editor-in-Chief Anna Brown Copy Editors Amy Dyson Trey Whittenton Chris Hoerter Editorial Contributors Kelly LeVoyer Greg Wood Anne Milley Michael Dowding Design Patrice Cherry Circulation Copyright © 2010 SAS Institute Inc., Cary, NC, USA. All rights reserved. Limited copies may be made for internal staff use only. Credit must be given to the publisher. Otherwise, no part of this publication may be reproduced without prior written permission of the publisher and copyright owner. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and Ellen Brandt other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. 104447_S50296.0310 Production Melody Fountain
  3. 3. Contents|P1 contents 2 The impact of business analytics on performance and profitability Jim Goodnight 4 Business analytics: helping you put an informed foot forward Jim Davis 8 How organizations make better decisions Thomas H. Davenport 12 Business analytics in action Gail Bamford, David Wallace, Mike Newkirk and Becca Goren 16 The art, act and science of knowing Thornton May 20 What business analytics means for small and medium businesses Matthew Mikell 23 Embedding analytics into processes Thomas Davenport, Jeanne Harris and Robert Morison ACCESS THIS REPORT ONLINE: 27 8 essentials of business analytics Jim Davis 30 The art of the possible: business analytics to measure corporate sustainability Alyssa Farrell
  4. 4. P2|Performance and Profitability The impact of business analytics on performance and profitability By Jim Goodnight, CEO, SAS With the rising complexity of global busi- For example, with the right analytics, re- ness, gut decisions and hunches no tailers can predict how many red sweat- longer suffice. Successful responses to ers they need in stock and how many threats and opportunities now depend on smalls or larges they need based on local rapid and smart execution. Let me state demographics. They can also determine it plainly: Business analytics is the key to optimal prices for hundreds of thousands achieving these challenging objectives. of products at multiple locations. Pricing Our world generated more data in 2009 used to be an art. Now, giant retailers can than in the previous recorded history of zero in on the optimal price for all their mankind. A good deal of this data can SKUs and stores. Banks can determine be converted into useful information and the optimal amount of cash to keep in competitive advantage – by applying the ATMs. Automakers can predict how right analytics. many spare parts they’ll need on hand – and when. The answers are out there – in the data we capture and store. Harrah’s, a global casino operator, uses analytics to optimize its marketing and Right now, that capture and storage customer loyalty programs. Thanks is costing huge amounts of money. largely to its use of analytics, Harrah’s Analytics converts those tremendous ranks No. 1 in profits as a percentage costs into invaluable assets. of revenues and has increased its share of wallet from 36 percent in 1998 to 45 Far more than mere reporting or dash- percent today. boards or scorecards, business analytics is a discipline that digs deeper into these vastly larger sets of data to uncover the most important insights. It can mean “so- cial network analysis” to study behaviors and relationships on multiple levels to uncover fraud. It can involve in-database analytics to optimize retail assortments or pricing. It can mean analyzing portfo- lios to manage risk positions.
  5. 5. Performance and Profitability|P3 In the Philippines, the Bureau of Internal Here’s my advice: Take the time to learn Revenue used analytics to recoup $114 about analytics. Take the time to discover million in unpaid value-added taxes, a how analytics can provide an objective 400 percent ROI in the first year. In Swe- view of your world, not only as it appears den, they are using analytics to reduce today but also how it’s likely to appear the number of patients who die from clini- tomorrow. I’m not talking about gazing cal errors. In addition to reducing unnec- into a crystal ball. I’m talking about the essary deaths, they expect to save $10 capability of competitive organizations to billion in health care costs at the national develop and implement strategies today level through their analytic efforts. that are based on a careful analysis of their likely outcomes in the future. 1-800-FLOWERS.COM changes prices and offerings on its Web site, sometimes And here’s my crystal-ball view: The abil- hourly, because it uses analytics. It also ity to predict future business trends with uses analytic software to target print and reasonable accuracy will be one of the online promotions with greater accuracy. crucial competitive advantages of this And it uses analytics to optimize its mar- new decade. And you won’t be able to keting, shipping, distribution and manu- do that without analytics. facturing operations. The result: a $50 million reduction in costs last year. ONLINE Business Analytics Knowledge Exchange Jim Goodnight has been at SAS’ helm since the company’s incorporation in 1976, overseeing an unbroken chain of revenue growth – a feat almost unheard of in the software industry.
  6. 6. P4|Face Forward with Business Analytics Business analytics: helping you put an informed foot forward By Jim Davis Most companies today have plenty of Why BI is not enough data. Creating intelligence and glean- Business intelligence provides histori- ing real insight from this data is what cal, metric-driven decision making – continues to elude organizations. De- and answers questions like, how many spite years of talk about scorecards and units did we sell, what did customers metrics, gut feelings and experience are buy and for how much? BI is charac- often still the guides for making impor- terized by the creation of simple rules tant, sometimes critical decisions, even and alerts and the distribution of known though current research reveals a clear facts to systems and people. These link between business performance and decisions have a low transformational the use of business analytics. impact on the business. So what exactly is business analytics BI is still a highly valuable part of your and how can it help? Business analytics overall business analytics environment, is, simply put, the application of ana- however, offering an excellent general lytical techniques to resolve business purpose backbone for ad hoc analysis issues. It provides organizations with a and basic operational reporting. framework for decision making, helping organizations solve complex business For example, BI can alert management problems, improve performance, drive on how many credit card transactions sustainable growth through innovation, were completed on a given day. It can anticipate and plan for change while also develop a simple rule for automatic managing and balancing risk. reporting, like reporting on transactions greater than $10,000 to the regulators. It sounds like a lot, but if you break it down it’s all about enabling effective From a more strategic decision perspec- decision making. Organizations make tive, business analytics can help answer decisions every day, and these sit on a questions such as what new products continuum from frequent, up to millions should we offer and in what markets? per day to transformative, which occur Or relative to the example, which credit less frequently but greatly impact orga- card transactions are likely to be fraudu- nizational strategy. The need for agile lent? Business analytics can predict this decision making has never been greater with certainty and automatically deny but unfortunately, IT infrastructure, peo- transactions – while reporting activities ple and processes are lagging behind. in real time.
  7. 7. Face Forward with Business Analytics|P5 A business analytics framework is not a monolithic and costly approach but rather provides for incremental growth to achieve strategic goals at any given stage of an organization’s value chain. Business analytics allows organizations In this way, business analytics drives In the following report, you’ll hear from to “face forward,” bringing insight to innovation and improves an organiza- several experts about how business transformative decisions. It benefits all tion’s speed of response to market and analytics can be applied to business aspects of an organization’s value chain, environmental changes. In the credit card problems across all types of organizations, including: scenario, business analytics can not industries and value chains. Perhaps • Inbound logistics: receiving, storing, only discover the causal factors of fraud, then it will become part of your plan to inventory control and transportation but also forecast accurately when it will outthink and out-smart the competition. scheduling. occur again. The company can then change business processes accordingly. • Operations: including factors such as packaging, equipment maintenance, A step toward business analytics testing and all activities that add value Effective decision making requires from the raw material to final product. a business analytics framework that • Outbound logistics: the activities re- incorporates the people, processes, quired to get the finished products to technology and culture of an organiza- market, including warehousing and tion. This common framework provides distribution management. flexibility across the entire range of analytical decision-making types from • Marketing and sales: activities that highly managed operational analytics lead a buyer to purchase the product, (such as a setting a simple credit limit) including channel selection, advertis- to discovery-based analytics (such as ing, promotion, selling, pricing, retail credit fraud scenarios or setting dynamic management and shelf space optimi- credit limits). zation. A business analytics framework is not • Service: activities that maintain a a monolithic and costly approach, product’s value, including customer but rather provides for incremental support, repairs, installation, training, growth to achieve strategic goals at any spare parts management and more. 1 given stage of an organization’s value chain. It offers business-ready analytical ONLINE applications with underlying technolo- Business Analytics Knowledge Exchange gies for key services like data man- 1 Porter, Michael E., Competitive Advantage : Creating agement and quality, reporting and Credit card fraud management and Sustaining Superior Performance. 1985. advanced analytics.
  8. 8. P6|Face Forward with Business Analytics Six questions about your company’s information The modern organization is awash in information – yet, too often, it falls short of the tools, methods and expertise it needs to derive the greatest value from this untapped asset. Information about the most important facets of the business – customers, processes, employees, competitors and more – is gathered but not analyzed, reported but not understood, guessed about rather than acted upon. But not with business analytics. Ask these questions of your company and join aggressive competitors by being a smart organization. 1. Where should we leverage business analytics? Focus business analytics where you already compete. The payoff is greatest where you are playing to your strength, not where you are playing catch-up. 2. Why now? Because the technology is ready. Because competitors are likely exploring the possibilities of analytical competition, too. And because it’s always risky to delay capitalizing on a new business capability. 3. What’s the payoff? Business analytics is all about anticipating the payoff in order to maximize it. The analytics initiative succeeds when the business capitalizes on an opportunity that analytics reveals. 4. What information and technology do we need? Most companies don’t lack for sufficient data, but instead suffer from a lack of integration and a lack of quality. Without good data, you simply can’t do good analytics. 5. What kind of people do we need? You need a variety of talented people: analytical professionals who design and refine analytical algorithms, and perform data mining; analytical semiprofessionals who do substantial amounts of modeling and analysis but are unlikely to develop sophisticated new algorithms or models; analytical amateurs who need to understand something of the analytical basis for operations and decisions; and the analytical manager who focuses the work of analytical professionals. 6. What roles must senior executives play? Committed senior executives provide the passion and the resources to drive their organizations in an analytical direction. In virtually every successful firm, senior management sets an analytical strategy and continually pushes it forward. ONLINE
  9. 9. Face Forward with Business Analytics|P7 HSBC: fraud detection that exceeds aggressive goals With fraud levels surging around the world, banks are facing greater regula- tory scrutiny, as well as risks associated with damaging publicity from fraud. The ability to correctly make split-second decisions on accepting credit card transactions – before fraud occurs – is more important than ever. Using SAS Fraud Management, part of ® the SAS Business Analytics Framework, HSBC prevents, detects and manages financial crimes by scoring and accept- ing or rejecting millions of transactions a day in real time – at the point of sale. As a result, the global financial services leader has achieved significantly lower incidence of fraud across tens of mil- lions of debit and credit card accounts. “The proof is in our fraud numbers – our detection rates and our false positives – which continue to meet our aggres- sive goals,” said Derek Wylde, Head of Group Fraud Risk, Global Security and Fraud Risk for HSBC. ONLINE Jim Davis is Senior Vice President and Chief Marketing Officer for SAS.
  10. 10. P8|Better Decisions How organizations make better decisions The following article is an edited excerpt of an article distributed by the International Institute for Analytics. By Thomas H. Davenport Relatively few businesses and organiza- tions have given full and proper attention to one of their most important activities: making decisions regarding key questions such as what strategies and business models to pursue, which products and services to offer, which customers to target, what prices to charge and what Author and researcher Tom Davenport is the employees to hire. Organizations with President’s Distinguished Professor at Babson College. poor decision processes and tools eventually encounter poor outcomes, His newest book is Analytics at Work: Smarter Decisions, and performance suffers. Better Results (with Jeanne Harris and Robert Morison, However, new analytics, decision auto- from Harvard Business Press). mation tools and business intelligence systems make it possible to make better use of information in decisions. “Wisdom of crowds” approaches and technologies allow larger groups of people to partici- pate meaningfully in decision processes. Organizations cannot afford to ignore these new options if they wish to make the best possible decisions. Given both negative and positive incen- tives to get better, one might expect that organizations would attempt to improve their decisions — that they would prioritize them, examine their current level of effectiveness, investigate new options for making them better and implement some of those options. In my survey and analysis of dozens of corporations, I found that while they are, indeed, doing some of these things,
  11. 11. Better Decisions|P9 In a survey and analysis of dozens of corporations, Davenport found that very few organizations have undertaken systematic efforts to improve a variety of decisions. very few organizations have undertaken decision-oriented context from the start. systematic efforts to improve a variety of If a test between two alternative Web decisions. In this excerpt I describe some page designs is performed, it is gen- of the more frequent approaches used to erally assumed that a decision to adopt intervene in decision processes. the winning page will be made. Other analytical approaches may not have as Analytics, testing and data clear a path to a decision. Infrastructures predicated on analytics and data were among the most A prerequisite of virtually any form of common decision-making frameworks analytics is high-quality data, so it is not among the surveyed firms. Eighty-four surprising that data-oriented responses percent of respondents mentioned an were also common. Sixty-six percent analytical component in their decision of respondents mentioned some issue improvement efforts and 66 percent involving data. The most common were: mentioned efforts to improve data. The range of analytical techniques • Having difficulty in accessing data. employed was quite broad. Scoring • Creating a common data architecture. approaches based on statistical analyses (usually some form of regression analy- • Eliminating duplicate data. sis) were common. Other approaches included optimization, behavior-based • Integrating “master data customer targeting, statistical forecasting, management.” prediction of various phenomena and the • Achieving “one version of the truth” use of text analytics. in functional or process areas. Not surprisingly, many Systematic testing was one form of • Dealing with too much data. organizations reported analysis that was being used somewhat that they needed to change frequently by companies; 18 percent • Gathering data from channel partners. mentioned it specifically in interviews. business processes to One key virtue is that it creates a • Creating new metrics. make better decisions.
  12. 12. P10|Better Decisions Technology support – and overrides Changes in business processes • An insurance company adopted – for decisions Not surprisingly, many organizations enterprise risk management. Several firms surveyed mentioned spe- reported that they needed to change cific analytical software, testing software, business processes to make better • The Six Sigma approach to process data warehouses and Web analytics/ decisions. Forty-three percent men- quality and decision outcomes was reporting software. Two other tech- tioned process changes of some type. implemented at a financial payments nologies were mentioned frequently: For instance, some described process firm and a staffing firm. specialized information display technolo- changes around supply chain manage- • A financial services firm uses the gies and business rule engines. ment in an IT firm, lease processing in “net promoter score” for customer an auto financing firm, financial process- Thirty-eight percent of companies in the satisfaction decisions. es in health insurance or new product study mentioned some use of specialized development processes. Several organi- • An economic decision analysis information displays such as scorecards zations mentioned changes for decision- approach, popularized and taught and dashboards. These tools, typically oriented processes made in the context by Stanford’s Engineering School found in the business intelligence of Six Sigma programs. and the Strategic Decisions Group, category, allow decision makers to see is used by an oil company. only the information that they need to However, some decision-focused ana- make a decision. Several firms mentioned lysts noted that their original goal wasn’t In addition, three responding organiza- using specific display approaches not necessarily to identify and implement tions developed analytically focused generally supported by conventional BI process changes, and that they had to decision processes that have been widely tools, including the “A3” format for work with other groups to accomplish used in IT systems development, but are displaying key issues in a particular them. As one head of an analyst group not widely known in the decision-making business domain. Some companies are at an IT firm commented, “We didn’t or analytics literature. Sometimes called using neuroscience principles to guide initially have the franchise to do process “agile methods” or “rapid prototyping,” how information is presented and improvement — our thing was analytics. they involve the creation of a series of digested. This may be a bellwether of But it kept coming up on our projects. So short-term deliverables, and frequent future attempts to link information and we eventually just made it a part of our review of them by the client and stake- decision making. standard approach.” holders for the decision. The organi- zations that use this approach found Another popular decision technology Decision-oriented methods and tools that it led to results that better fit the involves using business rules to enable Several organizations reported that decision-makers’ requirements, and at automated or semiautomated decision one aspect of their decision processes a faster pace. processes — sometimes in conjunction was an overarching, strategic manage- with analytics (e.g., scoring-oriented ment approach to guide all aspects of applications). Many organizations em- their efforts. Most of these initiatives are ploy business rules but allow humans well-known approaches to business to override the recommended decisions and management. when appropriate.
  13. 13. Better Decisions|P11 Conclusion From my research, it’s clear that organizations recognize the importance Analytics improves of improving decisions. Although the decisions survey was not a random sample, Davenport’s research found the most individuals in 90 percent of organiza- common types of decisions improved by tions surveyed identified some analytics include: attempt to improve decisions through • Pricing decisions (consumer goods, better processes. Second, organiza- industrial goods, government contracts, tions employ a variety of intervention maintenance contracts, etc.). types to improve decisions across • Decisions to target consumer segments analytics, culture and leadership, and (by retailers, insurers, credit card firms). data. The most successful organiza- tions adopted multiple interventions • Merchandising decisions (brands to buy, quantities and allocations). at once to improve a decision. • Location decisions (for bank As a result, analysts — previously branches or where to service industrial responsible for data gathering and equipment). ONLINE analysis — are morphing into consultants • Treatment protocols for health care. Order it now – Analytics at Work: Smarter who may be responsible for framing deci- Decisions, Better Results • Product development for sions, process redesign, communication pharmaceutical firms. and education programs, and change Read the full International Institute for management — all in addition to the • Student performance in educational Analytics research organizations. traditional analysis functions. • Evaluating marketing approaches Engage with analytic leaders Organizations seeking to implement (in both consumer and and researchers decision improvements should become B2B environments). familiar with these common intervention • Hiring decisions. types and create ongoing capabilities to • Vehicle routing decisions. deliver them. Analysts — previously responsible for data gathering and analysis — are morphing into consultants who may be responsible for framing decisions, process redesign, communication and education programs, and change management — all in addition to the traditional analysis functions.
  14. 14. P12|Business Analytics in Action Business analytics in action How are key industries deriving value from their business analytics implementations? By Gail Bamford, David Wallace, Mike Newkirk and Becca Goren HEALTH CARE • Increased compliance on medication According to the World Health Organi- reconciliation by more than 50 percent zation, global health spending totalled in a nine-month period. more than US$4.1 trillion in 2007, with $639 as the total health expenditure • Dramatically reduced the rate of hos- per person. That number will only grow pital-acquired infections by measuring in ways that affect businesses and where infections originated and what citizens. admission conditions closely corre- lated with acquired infections. Despite these huge investments, health care quality is uneven and resistant to • Improved government/industry ac- changes and improvements. How can creditation/compliance by incorpo- rating national guidelines into key we enhance health care delivery while metrics. controlling those costs? It starts by carefully measuring and monitoring the • Developed new methods for caring for quality of that care – a complex task stroke patients while controlling costs. perfectly suited for business analyt- By taking better care of these patients, ics. Here’s how some forward-thinking the hospital expects fewer complica- health care institutions are delivering tions, which will reduce costs. better quality of care more efficiently. Karolinska Institute Maine Medical Center The Karolinska Institute in Sweden Named to US News and World Report’s needed a way to examine the effects “America’s Best Hospitals” list for of drugs, other treatments and lifestyle orthopedics, heart care and gynecologic factors on patients with rheumatoid ar- care, Maine Medical Center uses SAS thritis. Using SAS Business Analytics, Business Analytics to understand key the Institute has deployed a Web-based patient care metrics – and sustain a patient self-help application and predic- quality-driven culture. The data-driven tive modeling to determine which treat- approach has produced excellent results: ments will be most effective for certain segments of RA patients.
  15. 15. Business Analytics in Action|P13 BANKING • Cleanse and integrate. Cleanse and In a challenging economic and regula- standardize third-party credit and tory climate, bankers must be especially customer data, enrich it (e.g., add vigilant. Two key indicators of a bank’s geocoding tags) and integrate it into health are net charge-offs (NCOs) – the a single data store. value of loans written off as uncollect- able – and nonperforming loans (NPLs) • Analyze and score. Develop scoring that are in default or delinquent more models to analyze debtor-customer than 90 days. segment data against objectives, in- cluding “maximize profits” or “minimize In the past two years in the US, bank writeoffs” or against constraints, such Optimizing collections NCOs have soared by an average of as loan types, outstanding balances or A leading Australian financial institution more than 350 percent across all insti- days delinquent. previously relied on instinct when contact- tutions, with institutions holding assets ing delinquent customers. Since introduc- of $5 billion or less showing growth of • Optimize and execute treatment ing SAS for collections optimization, it has almost 500 percent. NPLs as a percent- strategies. Analytical models help achieved a 300 percent ROI in less than six age of average loan balances have risen collections teams understand who is months. A debt purchasing firm based in more than 278 percent at US banks with most likely to respond, which commu- the UK uses SAS to predict debt portfolio $1 billion or more in assets. How can fi- 1 nication channels work best and how performance. This enables the firm to nancial institutions improve their collec- much payment to expect. make quicker decisions on acquiring new tions and protect their bottom line? debt portfolios at the right prices, collect Collections optimization driven by more from each portfolio and grow rev- Business analytics can provide the in- business analytics delivers the results enues by 50 percent annually. sights that institutions need to reduce that institutions need to improve their both loan writeoffs and the cost of col- profitability. lections activities. First, models created within a business analytics framework can identify likely candidates for work- 1 Source: SNL Financial outs and loan modifications. Second, business analytics can optimize collec- tions activities to improve the probability of success and maximize self-treatment among debtor segments. It starts with three basic steps.
  16. 16. P14|Business Analytics in Action MANUFACTURING such as point-of-sale (POS) data and From diapers to jet engines and almost historical shipment data. Once that data everything in between, manufacturing is aggregated, business analytics models expertise is a competitive differentiator for and tools can accurately forecast the companies that follow optimal practices demand for products by family, individual and methodologies to attack inefficiencies SKU, geography, customer type, etc. and eliminate waste. Business analytics With a clear and accurate demand is essential in these settings to improve picture, manufacturers can properly production and sales planning, enhance allocate raw materials across plants and the supply chain, reduce inventory, regions – all optimized by distribution streamline logistics and much more. channel – to create complete roll-ups in Meaningful ROI with master planning schedules. Business Analytics For example, with demand forecasting, One SAS customer increased company business analytics can be a key TELECOMMUNICATIONS profitability by accurately predicting prod- contributor to a manufacturer’s success. You’ve likely experienced it before – your uct demand and customer behavior – more Better forecasts deliver ROI by: cell phone loses service one too many than doubling its forecasting accuracy. It times, so you switch providers. Low found that for every 1 percent reduction in • Reducing inventories. barriers to churning mean providers must forecast variance, it saved $200,000. vigilantly and carefully invest to maintain • Improving order fulfillment rates. and increase their service quality and Another manufacturer improved two seemingly competing objectives. It simul- customer satisfaction rankings. After • Shortening cash-to-cash cycles. taneously reduced inventory by 20 percent, all, your satisfaction keeps them in eliminating millions of dollars of holding Many manufacturers struggle with business. costs, yet improved service levels, which optimally managing and forecasting directly and positively affected customer Network managers typically receive error their raw materials requirements, work- satisfaction. reports and alarms after a network device in-process (WIP) inventory and finished fails. The team addresses the stream of goods inventories. Without the right mix of trouble tickets, but never gets insight into raw materials, production plans fall apart underlying causes or trends for outages. and customer orders are delayed (or, The result: long call-resolution times. worse, canceled). Missing WIP forecasts similarly leads to inefficient schedules With business analytics and approaches and a crippling misallocation of finished such as predictive fault analysis, network stocks – not having the right quantities of managers can analyze performance the right goods at the right time and in to pre-empt failures. They can analyze the right places. While the data is often trouble tickets and optimize corrective available to prevent, identify and correct services, shortening times you are these imbalances and inefficiencies, it without coverage. is usually not integrated, analyzed and shared across the organization. Strong data management, including data quality and reporting capabilities – Data management technologies can all key underpinnings for business bring together islands of information analytics – can help quickly identify
  17. 17. Business Analytics in Action|P15 One large telco service provider used SAS to identify emerging issues (an average of two weeks prior to failure) and double the percentage of tickets resolved within 48 hours. service and network issues. Business analytics helps to: • Identify and remove duplicate trouble tickets. • Understand faults and performance on a macro level. • Determine which services have the highest fault rates. In addition to analyzing network performance, predictive analytics technologies can help evaluate demand, faults and systems to improve resource utilization and quality of service (QoS). A telco provider can then identify Gail Bamford is a SAS Global Industry Marketing Manager for Public Sector. when and where network resources are deployed and quality/performance variations over time. David Wallace is a SAS Global Industry Marketing Manager for Financial Services. Business analytics allows network and service managers to better understand Mike Newkirk is a SAS Global Industry Marketing Manager for Manufacturing. causes and impacts of failures. They can prioritize and pre-empt outages, optimize repairs and mitigate risk with answers to Becca Goren is a SAS Global Industry Marketing Manager for Communications, key questions: Media and Entertainment. • How significant is each factor influencing network faults degradation? ONLINE Health care providers keep pace with change • Which network faults are tied to a given trouble ticket? The standard for clinical data analysis and reporting • Which faults are related and what are their impacts? Solutions for better risk management ONLINE Armed with predictive fault analytics, Get the full stories on: a telco provider can limit the times you Maine Medical Center Compete in manufacturing lose a signal and continually improve overall service, allowing it to keep your Karolinska Institute Invest wisely, communications service providers business.
  18. 18. P16|The New Know The art, act and science of knowing An excerpt from The New Know 1 By Thornton May The Internet makes self teaching — and lifelong learning — the rule rather than the exception. Historians ultimately will come to consensus on what to call the time period between the frenzy that was the dot-com bubble and the period be- fore society finally enters the data cloud. For want of a better phrase, I call the 20- year interregnum we currently inhabit (1995 – 2015) the Age of Little Informa- tion. I come to this label not because the age exhibits a lack of information. Quite the contrary, it is during this epoch that information — previously locked away in analog form — is becoming widely digitized. The New Know has changed our reality along 10 fundamental dimen- sions. Futurist Thornton May positions analysts as heroes New Know Reality #1: of the age we are about to enter in his new book, You will be expected to do The New Know: Innovation Powered by Analytics. something with information. All this newly digitized information has had, relatively speaking, little impact on behavior and little impact on organiza- tional outcomes. We are now exiting a historical moment of undermanaged and only occasionally acted-upon informa- tion to an environment requiring much more active, much more intense, much more aggressive information manage- ment. You as an executive will be held much more accountable for your data management behaviors. You will be expected to transform “data lead” into 1 Copyright 2009 by John Wiley & Sons, Inc. All rights reserved. Reprinted with permission. “knowledge gold” via the expeditious
  19. 19. The New Know|P17 sensemaking leading to efficacious ac- New Know Reality #3: tion. In the Age of Little Information, we You will have to know more were data vegetarians. In the New Know about knowing. we will have to become information and knowledge carnivores. One of the major changes defining the new competitive environment is the New Know Reality #2: requirement to know more about know- There really is more to know. ing, what experts sometimes refer to as metacognition. Society is about to The New Know will be awash with undergo a tectonic shift in how it thinks data. Processing power doubles every about thinking. Driving this cognitive 18 months. Storage capacity doubles plate shifting are the RSS feeds, pod- every 12 months. Bandwidth through- casts, blogs, old-media headlines and put doubles every nine months. There evening news programs, which are is more to know. Organizations are increasingly filled with images and having trouble keeping up — and, sadly, instances of current-generation leaders the fact that there are more facts arriving being asked by dissatisfied next- at a faster rate of speed is not even the generation voters, customers and tip of the cognitive iceberg. Like the “fog shareholders: “What were you of war,” info warriors speak of the “fog thinking?” Looking beneath the surface, of facts” (e.g., confusion about what they are really asking: “How were you information is to be believed, what infor- thinking? Via what processes, using mation sources are credible and what what data and assisted by what tools did version of reality is to be acted on). In a you arrive at your course of action?” world of multiple sources of information and 24-hour decision making, the very New Know Reality #4: character of information is changing. Brain science and decision A “fact” is no longer a “fact.” science are converging. Scientists do not know how the brain works — yet. But they are sneaking up on it. Readers may be surprised to learn that neuroscience has been around for over 100 years. Neuroscience has progressed to the point that we at least know what we do not know.
  20. 20. P18|The New Know Carly Fiorina, former CEO at Hewlett-Packard, believes that distilling truth from overwhelming amounts of information is To some extent, it is a simple truism New Know Reality #6: the essence of leadership. that the brain is involved with all things Information management Is the that comprise our human existence. essence of leadership. It follows, loosely, therefore, that understanding the brain will help us Low-cost communications give rise to understand the human condition more almost toxic levels of spin, hype and fully. The big news is that the brain pos- empty rhetoric. Leaders are able to sesses innate qualities that influence cut through all the noise. Does your individual experience and opinions. organization filter its data? Carly Fiorina, There are things that can be known— former CEO at Hewlett-Packard, that need to be known by executives believes that distilling truth from over- seeking to maximize value from the whelming amounts of information is the knowledge assets available to the essence of leadership. She believes that enterprise. all of us are overwhelmed with informa- tion, and what sets great leaders apart New Know Reality #5: is their ability to cut through the clutter The environment is changing and distinguish the truly important from our brain. the merely interesting. The information flood should be viewed New Know Reality #7: as a permanent macroenvironmental A more connected world. change. Thinking in Darwinian terms, what adaptive pressures does this One of the transformational elements environmental change place on us? moving society to the New Know is “Daily exposure to high technology — something analysts at Forrester Re- computers, smart phones, video games, search call the “groundswell.” Josh search engines — stimulates brain cell Bernoff, Vice President at Forrester, alteration and neurotransmitter release, contends: “There’s so much information gradually strengthening new neural flowing out of the groundswell, it’s like pathways in our brains while weaken- watching a thousand television chan- ing old ones. Because of the current nels at once. To make sense of it, you technological revolution, our brains are need to apply some technology, boil- evolving right now — at a speed like ing down the chatter to a manageable never before.” stream of insights.” The new scarce re- source in the next economy will be the human attention needed to make sense of information. The question is: How will we be able to keep up?
  21. 21. The New Know|P19 New Know Reality #8: useful to know where it will step. Every Math matters. key process in your enterprise is locked in a room with an elephant — a critical Mathematics is now so widely accept- process, serving a critical customer. ed as the arbiter of truth in the modern Business analytics tells you where that world that it has become the backbone elephant will step. of disciplines ranging from physics (of course) to economics and sociology. New Know Reality #10: If you are locked in a Backing up a statement with mathemat- Knowing can change the world. ics gives it an aura of validity, even if the room with an elephant, it topic has to do with something as math- If knowledge is power, then “knowl- is useful to know where edge about power should be especially ematically messy as human behavior. empowering,” says John Murrell, the it will step. Every key However, many otherwise “normal” ex- very-much-in-the-know editor of Good process in your enterprise ecutives have a pathological aversion Morning Silicon Valley. For instance, is locked in a room with to math. This is not just unfortunate, it using 15,000 meters, a subset of Na- an elephant — a critical is dysfunctional. Some intuition about tional Grid Customers will be able to numbers, counting and mathematical access their energy — use information process, serving a critical ability is basic to almost all animals. via the Internet, by a thermostat read- customer. Business People use math to make decisions out, or through text messaging, and use analytics tells you where every day. “In an age where you need the data to change their consumption to be numerate to do almost anything patterns. Program participants are ex- that elephant will step. (from building bridges to conquering pected to save 5 percent, or about $70 disease), governments anxiously com- a year, on their energy bills. Change ad- pare their performance in mathematics vocates from all fields of endeavor are with that of competitor nations.” excited about the possibility of putting new information in front of people in the New Know Reality #9: hopes of changing behavior. There are significant downsides to not knowing. Success requires materially expanding what you know and adding precision and efficiency to the processes (analyt- ics) whereby you come to know. Here is a metaphor to keep in mind as you think about the New Know. If you are locked in a room with an elephant, it is
  22. 22. P20|Business Analytics for SMBs What business analytics means for small and medium businesses An interview with Matthew Mikell, SMB Global Product Marketing Manager When it comes to business analytics, general constraints when listening to it sometimes seems like only major en- organizations that are SMBs: terprises garner the spotlight. That’s somewhat understandable given the 1) Decision-making style complexity and scope of their analytical Transitioning from gut instinct to fact- The Wine House discovers challenges and the nature of their high- based framework can be difficult in part $400,000 in ‘lost’ inventory profile brands. But the fact is, far more because the former approach has likely small to medium businesses (SMBs) are served the successful SMB very well. Economic times may be tough, but Bill poised to implement business analytics Most SMBs have Excel experts who Knight, owner and President of The Wine House, is toasting a 100 percent return on solutions. can generate some great static charts his investment in SAS. The first day its SAS and graphs — and I wouldn’t ever want In the US, these companies have to denigrate the value those reports application was live, the brick-and-mortar revenues of less than $500 million. In provide. But there’s so much more val- and Internet retailer discovered 1,000 items of wine that hadn’t moved in more Europe, the SMB category comprises ue that can be derived from in-depth than a year. companies with a maximum of EUR 450 analyses. Once SMB executives get million (about US$611 million). While in a real glimpse of the insights that are “We had a huge sale to blow it out, gener- the Asia Pacific region, SMB often refers lurking beneath the surface of their ating $400,000 in capital in one weekend,” to both employee numbers and revenue, transaction data, their willingness Knight said, “and just in time, because in and range between 200 and 250 to adopt business analytics increases today’s economy, we’d be choking on that employees and $200 million and $500 inventory.” pretty quickly. million in revenue. In many ways, these Using SAS, The Wine House has reduced businesses are striving for the same 2) Cash flow its aged inventory by 40 percent. “Now I goals to grow their business through In addition to a shift in decision-mak- can get the answers I need and base de- innovation, and need the same sophisti- ing style, cash constraints can pose cisions on facts rather than gut intuition,” cated functionality scaled appropriately very real obstacles for an SMB that says Knight. “I’ve got less money tied up to their processes. In this Q&A, wants to mature in this area. Consid- in inventory, I know who our best custom- Matthew Mikell, SAS Global Product ering the business analytics frame- ers are, how to market to them and can Marketing Manager, shares his perspec- work helps improve margins, retain key monitor the effectiveness of our marketing. tives on what business analytics means Our ROI with SAS has been well over 100 customers and grow share of wallet in their to SMBs. percent in less than a year, so my return on markets. However, the long-lasting investment has been fantastic.” Q. What are some of the unique return on investment far outweighs the challenges that SMBs face with capital required to undergo the transition. ONLINE respect to business analytics? A: SMBs primarily face the issue of scale. At SAS we have heard four
  23. 23. Business Analytics for SMBs|P21 SMB executives – often owners or people with lengthy tenures – worry about letting go of the information flow and empowering people to make decisions that were previously reserved for executives. 3) IT resources and infrastructure at a disadvantage. Internally, employees More than 80 percent of SMBs with need these tools to be productive. Oth- about 100 employees have only four erwise, it’s gut-based decisions, or cut- dedicated IT staffers. They’re stretched ting and pasting from multiple tools. thin, and that can make it very difficult The truth is what brought you to where to expand the IT mandate beyond criti- you are typically won’t take you to the cal business operations into managing next level. But it’s very difficult, cultur- business analytics environments. ally, to walk away from what’s made 4) Business analytics maturity you successful. SMB executives – often owners or people with lengthy tenures – SMBs must have an appreciation for worry about letting go of the information the level of skills required to meet over- flow and empowering people to make all strategic goals through business decisions that were previously reserved analytics. Research from Aberdeen for executives. Group suggests that SMBs without the relevant skill sets are poorly positioned Q What’s the best way for SMBs to drive value from an analytical solu- to tackle the adoption of business tion. It reports that SMBs using some analytics? sort of analytical applications perform at a higher level than their competitors A: Of course, every company differs – that do not.1 particularly at the SMB size. But we’ve found that there is a general approach to The main SMB challenge for moving to the adoption of business analytics. The business analytics is the understanding first step is to ensure you have sponsor- of its impact on these four critical areas, ship from company executives. Clearly and building a capability that is cost- lay out the business analytics benefits effective and remains flexible and easy and return to the management team. to use. This transparency is key at the SMB level as SMB executives are tradition- Q. Why should SMBs adopt ally heavily involved in analyses, report- business analytics? ing and the decision-making process. Make it clear how business analytics will A: It essentially boils down to competi- resolve a compelling issue or attract and tive pressures. SMBs need to continu- retain customers, for example. ally innovate. If you’re an SMB that isn’t constantly seeking to optimize every possible aspect of the operation, you’re 1 Aberdeen Group, 2009, Beyond Spreadsheets: The Value of BI and Analytics.
  24. 24. P22|Business Analytics for SMBs The second strategy is to focus on a Q. What’s the difference between Q. Can you share some examples particular business process or issue. business analytics for large enter- of how SMBs have been able to Don’t introduce business analytics as prises vs. SMBs? capitalize on business analytics? a broad, unfocused utility for general usage. This will occur naturally as you A: In a nutshell, it’s about scale. Deploy- A: Sure. We’ve worked with an energy- solve more focused issues, building up ment and support strategies will have a trading company that enables staff to confidence in fact-based decision mak- different nature. What’s more interesting predict what today’s electricity and ing as a core competency. Some of the to me, however, is the important com- gas purchases will sell for months later typical issues that we see being solved monality: functionality. Business analyt- when consumers buy. Business analytics with business analytics include improv- ics in SMBs is not about presenting a supplies that intelligence to traders in a ing customer data quality for improved subset of functionality but rather surfac- cleaner, faster and more accurate way. marketing, invoicing or customer ser- ing the right functionality for the problem at hand, and opening up to more as the A collection agency uses SAS Business vice, or improved product pricing and business requires it. Despite their size, Analytics to analyze bad-debt portfolios packaging analysis to drive a higher SMBs face similar challenges to make before acquiring those assets. This is a market share. better and more informed decisions to quantum leap forward from its previous Finally, don’t rest on your laurels. Capi- continue innovating in their markets. It is model, which was simply buying any talize on your initial success to broaden therefore essential to provide a rich set debt assets for as little as possible and deployment to other areas of the orga- of features and a very high level of tech- hoping to collect successfully. nization. Those adoptions move faster nology usability. once you can point to a successful track A player in the secondary-ticket market record in another area. uses SAS to develop a deeper under- standing of the needs of its thousands of customers. By segmenting them and catering to psychographics, the company can optimize how frequently it contacts the customers and improves loyalty. ONLINE Software for SMBs Some of the typical issues that we see being solved with business analytics include improving customer data quality for improved marketing, invoicing or customer service, or improved Matthew Mikell leads Global Product Market- product pricing and pack- ing for SMB markets and software-as-a-service (SaaS) offerings at SAS, supporting strategic aging analysis to drive a planning, messaging and product offerings higher market share. through direct and indirect channels.
  25. 25. Analytics at Work|P23 Embedding analytics into processes In their latest book, Analytics at Work: Smarter Decisions, Better Results, Thomas Davenport, Jeanne Harris and Robert Morison show how companies apply analytics in their daily operations. This excerpt, ‘Embedded Analytics in Action,’ explores what to consider when infusing analytics into business processes. We see examples of analytics at work The solutions naturally demand very within core processes in a variety of sophisticated and industrialized ana- business areas. Statistical analysis has lytics: for capacity planning of aircraft been a feature of supply chain and lo- and truck fleets, for routing packages gistics management for decades, start- through its distribution network, and for ing with the techniques of statistical scheduling and routing delivery trucks. process control (SPC) and total quality For a company this steeped in analyti- management (TQM). cal applications, the frontier is moving closer to real-time, dynamic adjustments. Real-time analytics are helping guide For example, UPS is experimenting with call center workers in their interactions algorithms to adjust the order of deliv- with customers. And analytics are well eries as conditions (e.g., road closures, established in the engineering and sim- extraordinary customer need) change. ulation sides of product design. Making processes analytical Among business support functions, The effects of analytics on the opera- analytics are essential to many facets tions of a process can be profound, of finance, common in the management and over time you may want to reengi- of technology operations, and rela- neer the overall business process and tively new to human resources (though revamp its information systems to of enormous potential there). In cor- capitalize on the potential for analyt- porate development, key decisions — ics-based improvement. But you can for example, regarding mergers and start embedding analytics without a acquisitions—may benefit greatly from major overhaul. For processes that rely analytics, but few companies take a extensively on enterprise systems, it process approach to such activities. may be possible to simply start taking advantage of the analytical capabilities Consider the example of UPS to whet that are already included in the soft- your appetite for embedding analytics ware. However, many process analytics in your core business processes. As a initiatives will require tools, techniques, logistics company, UPS lives and and working relationships that are likely breathes the “traveling salesman to be new and unfamiliar at first. We problem”—how to reach a variable have found that implementing analytics- Reprinted by permission of Harvard Business Press. Excerpted series of destinations most efficiently from Analytics at Work: Smarter Decisions, Better Results by enabled processes requires applying with the right delivery capacity, and often Thomas Davenport, Jeanne Harris and Robert Morison. four major perspectives. All rights reserved. in designated time windows, every day.
  26. 26. P24|Analytics at Work The effects of analytics The first is process implementation. Third is systems implementation. The on the operations of a Occasionally a business may create analytical system must be incorporated process can be profound, a new analytically enabled process into the set of systems and technolo- and over time you may or rebuild a process from scratch, but gies supporting the business process. most often you are adding capability to In building these interfaces, it helps to want to reengineer the and altering an existing process. Espe- employ process-oriented technologies, overall business process cially given the iterative nature of many including capabilities of ERP systems, ... but you can start analytical applications, it’s essential to workflow and document management measure baseline process performance systems. And integrating and testing embedding analytics first and to run the enhanced process the new systems and interfaces is criti- without a major overhaul. in parallel to the original (perhaps as a cal given analytics’ reliance on a broad pilot or test) in order to refine the new range of quality data and the fact that process and measure its performance analytics-based decisions may dramat- and value. In some cases, process ically change process flow. simulation can yield insights about how the process might perform even before Human implementation is the fourth implementation. perspective. Often the greatest imple- mentation challenge, especially when Next, organizations should consider analytics is new to the process and the model implementation. Much of the people performing it, is on the human distinctive work of process analytics side. Only people can tell if an embed- centers on designing, developing and ded application is resulting in good iteratively refining statistical algorithms decisions, so be sure to involve them in and descriptive or predictive models developing, managing and monitor- or rule-based systems. If you are go- ing the assumptions and results of any ing to industrialize important decision embedded model. Another important processes, it is important that the rules, factor is developing the right mix of assumptions and algorithms in your automated and human decision making model are correct. Analytical projects and enabling process performers to generally require different tools and trust and use their new analytical infor- development methodologies from mation and sometimes tools. those employed in more traditional sys- tems development. And, of course, this work is performed by business analysts and programmers with special skills in statistical methods and modeling.