WHITE PAPER

Game-Changing AnalyticsHow IT Executives Can Use Analytics to Create Innovation and Business Success

SAS White Paper

Table of Contents

The CIO Role: From Tactical Technology Service Provider

to Strategic Business Leader . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Speed of Knowledge: The Differentiator of the Decade . . . . . . . . . . . . 1

Analytics: The Technical Enabler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

What Is Analytics? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Stepping Up to Big Data Analytics for Speed of Knowledge . . . . . . . . . 5

The Strategic Role of the CIO in Driving Analytics . . . . . . . . . . . . . . . . 6

Delivering a Robust Analytics Platform . . . . . . . . . . . . . . . . . . . . . . . . . 6

Learn More . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Contributor: Eric Williams, retired Executive Vice President and Chief Information Officer at Catalina Marketing

Corp., spent nearly 20 years directing strategic technology, research and development, and new

application development; he also held the position of Chief Privacy Officer. During his tenure,

Williams led the development of Catalina’s multipetabyte data warehouse (still one of the largest

transaction-level databases in the world) and was also instrumental in developing the first Internet-

delivered loyalty marketing solution for basket-level data management. Under his direction, Catalina

was the development partner and one of the first companies to implement in-database predictive

analytics that allowed data mining technologies to operate in the database.

Previously, Williams was Vice President of Research and Development for Catalina Marketing and

Vice President of Retail for Catalina’s SuperMarkets Online division. Williams is an inventor with

both US and international patents to his name. With more than 30 years of experience and a broad

industry perspective, his background includes management, sales, marketing, systems design

and development, and operations positions with retailers, software development and information

technology companies.

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Game-Changing Analytics

The CIO Role: From Tactical Technology Service Provider to Strategic Business LeaderIf your IT organization still operates with a tactical, service-driven mentality where the focus is “keeping the lights on,” you’re probably finding it a challenge to secure and fully leverage a seat at the executive table . But it’s never been more critical for you to break out of this way of thinking – and lead your organization to use information and knowledge in breakthrough ways .

Companies fight every day to defend their markets, find and keep their customers, and grow in the face of intensifying competition . Executive teams and boards understand this, and it’s driving them to expect their CIOs to do more – a lot more – to help their businesses thrive and excel . It’s no secret that information technology can help organizations transform and differentiate, accelerate the pace of business, analyze markets and customers, and create new revenue opportunities . Executives have also witnessed first-hand how breakthrough technologies such as “big data,” high-performance analytics, cloud technologies and in-memory data management can enable innovations that drive revenue, competitive differentiation and business transformation .

So the spotlight is on IT executives to step up to the plate and lead the way forward . The question is, where should CIOs’ focus be as they lead their organizations forward? What technologies are the low-hanging fruit with the greatest potential to help executives achieve their goals?

Speed of Knowledge: The Differentiator of the Decade

According to Eric Williams, Retired Chief Information Officer at Catalina Marketing Corp ., there is a dominant trend that points the way forward: the need for speed of knowledge . “Speed of knowledge is the differentiator of the decade,” he explains . “For years, people have been turning data into information that helps them make sense of the data . But information only provides insight into what is happening – not what to do about it . For example, knowing that sales are lagging in a certain area is important, but integrating this information into a knowledge process so that a business can act upon these insights is critical . What they really need is knowledge about their business, markets and customers so they can truly change the business .”

And today, companies need knowledge more quickly than ever – sometimes in real time . For example, companies that can access knowledge about their products and their customers’ wants and needs faster than the competition have a distinct advantage over everyone else . “We live in the ‘me generation’ where everything is about ‘me,’” says Williams . “People gravitate to companies that are of interest to them and connect with them in a personal way . So there’s huge revenue potential for companies that turn their customer data into knowledge that helps them tailor messages, offers, products and services to the individual .”

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For example, many traditional retail businesses used to follow the old mantra of “buy low, sell high,” where they would buy merchandise at the best price and then try to sell that same product to all of their customers . Today’s most successful retailers are taking another approach: working with their suppliers to match consumers’ desires with the products they buy . This is not to say that price is not important, but for the leaders in this area, price is no longer the only factor to consider . Central to success, however, is having accurate, complete and timely insights into what customers want .

Speed of knowledge is also helping successful companies fail faster – and cheaper – when launching new products and services . According to Williams, this is a key competitive advantage; companies in the US alone launch as many as 20,000 new products each year – and, on average, 98 percent of them will fail in the first few years . “There is a significant cost to product development and customer acquisition,” explains Williams . “Companies can’t afford to blanket consumers with free samples and ads today because it simply costs too much, and the risk of product failure is too high . Winners have early knowledge about who has a high likelihood of interest in their product so they can target them, cost-efficiently market to them ahead of the competition and win them over . Research shows that when people try and like a new product, they tend to remain loyal to it for an average of 18 months – a long time to recoup costs and make a profit .”

Equally important, speed of knowledge gives winners early knowledge – within hours, days and weeks of a launch in a test market – about which products aren’t working so they can either quickly fix what’s wrong or scrap the product early and stop the bleeding from a financial perspective . “Failing early frees up corporate resources to invest in new product development and marketing initiatives that could pay off,” adds Williams . “Many companies don’t even know that their products are going to fail until they’ve already spent massive amounts of money producing and marketing them . They don’t have the speed of knowledge to know what’s happening in their markets and with their customers .”

These are just some examples of why speed of knowledge is so critical to business success – and why CIOs that lead their organizations to invest in it become trusted strategic advisers .

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Game-Changing Analytics

Analytics: The Technical EnablerAnalytics enables speed of knowledge and the associated business agility, rapid decision making and innovations that enhance competitiveness . IDC concurs about the strategic importance of analytics to companies today, stating that, “Business Analytics is the #1 technology area to gain competitive advantage in the years ahead .”1 Let’s take a closer look at what we mean by analytics relative to business intelligence (BI) and reporting .

What Is Analytics?

Many CIOs think that they are already “doing analytics” because they have implemented business intelligence and reporting tools . But analytics is distinct from BI and reporting, offering a whole new world of value to the business .

Business intelligence and reporting tools are essential components to enabling analytics within an organization . These tools organize large amounts of data and present it as information that helps people see what’s happened in the past . For example, you can:

• Monitorthesaleschangesinaregion,storeorsection.

• Understandtherecency,frequencyandsalesactivityoftheirconsumers.

• Examinethefrequencyoftop-sellingitemsinshoppingbaskets.

But historical perspectives alone don’t necessarily help decision makers address the realities of today’s businesses . For example, you also need a way to:

• Predictwhowillbeinterestedinanewproductorservice.

• Forecastsalesvolumeforanewproductintroduction.

• Makesenseofthepricepointsofkeymerchandiseanddeterminepromotionalpricing.

• Predicttheeffectofputtingakeyproductonsale–forexample,whatthiswilldotooverall basket sales, loyalty and the frequency of trips by the “best” customers .

As discussed previously, to address these types of needs, you need usable knowledge . And that’s what analytics solutions are uniquely capable of providing . Analytics platforms (such as the SAS® Analytics Platform) give companies sophisticated, integrated functionality that helps them understand their business, markets and customers in deeper ways, thus enabling a competitive advantage . Analytics functions can include:

• Predictive analytics and data mining – Build descriptive and predictive models and then deploy results throughout the enterprise so you can determine which products and categories provide the highest returns in consumer satisfaction and loyalty .

• Visual analytics – Enhance analytic effectiveness with dynamic data visualization so you can immediately understand the effects of your promotion activity across the business enterprise .

1 “Big Data Analytics: Future Architectures, Skills and Roadmaps for the CIO.” IDC. Philip Carter. September 2011.

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• Forecasting – Analyze and predict future outcomes based on historical patterns so you can select the right products, establish the optimum price and/or promotion, and minimize markdowns .

• Model management and monitoring – Streamline the process of creating, managing and deploying analytical models so you can monetize the value created by analytics more rapidly than the competition .

• Operations research – Leverage optimization, project scheduling and simulation techniques to identify the actions that will produce the best results so you can respond quickly to those solutions that demonstrate the most value to your organization .

• Quality improvement – Identify, monitor and measure quality processes over time so you can quantify the value generated on these successes and curtail those that are not providing the desired results .

• Statistics – Use statistical data analysis to make fact-based decisions so you can build upon the successes provided by your predictive solutions .

• Text analytics – Maximize the value buried in unstructured data assets so you can understand the comments and sentiments of your consumers and address negative issues before they become a PR nightmare .

It’s important to note that each of these analytical functions provides unique value when used alone – but they only give you a singular perspective on your data . When used together, they can provide a complete, multidimensional view into your business, markets and customers – in other words, more complete knowledge .

For example, if you are a retailer, you probably run standard reports that rank the top-selling items in your stores and use this information to determine what items deserve coveted shelf space – and what items don’t . But making decisions without a correlation of these items to your top-revenue consumers can lead to significant lost revenues . For instance, at a grocery store, your best consumers may not be buying soda – a common, top-selling item – but they may be purchasing natural laundry detergent, a lower-volume but higher-margin product that you might deem “unimportant” to your bottom line . If you drop this detergent from your shelves, you run the risk of losing high-revenue customers . Integrating BI and higher analytics functions can give you an understanding of these linkages between items and consumers .

You also need to understand and predict the success of product promotions with regard to sales of a category . Trying to do this using traditional BI leaves you in the dark because you can’t analyze the linkage of a given product or category sale against the loyalty or overall basket sales of your targeted consumer . To return to our prior example, a traditional BI report will show category sales of carbonated beverages, but it won’t analyze this data against your best shoppers, which in this case, purchase all-natural detergent, not soda . If you had this analytics-enabled insight, you could, for instance, send your best customers promotional offers for “green” household cleaners and even organic food – items that are more likely to interest them .

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Game-Changing Analytics

Stepping Up to Big Data Analytics for Speed of Knowledge

If the volume, velocity and variety of data that you have exceed your storage or compute capacity for accurate and timely decision making, you have a “big data” problem . This can make even traditional BI and reporting processes time-consuming and inefficient – and use of advanced analytics almost impossible . For example, it may take days to prepare and explore data, develop data models and deploy them . You may need to integrate multiple data sources into a “single view of the truth” – a complex endeavor . Or you may have data sources that were not created equal . In these cases, how do you address the different speeds of information from disparate data sources, or normalize and manage this information onslaught? You may also have difficulty managing multilevel access to the same information source .

Given the massive amounts of data companies are collecting and creating – and their customers are generating through Facebook, blogs, Twitter and other social media – big data problems are increasingly common . These types of unstructured data can be staggering in size and complexity, so your big data problems will only grow as you integrate this unstructured data with your traditional, structured data .

Yet getting a handle on big data challenges is fundamental to success today . Numerous analysts have written recently that the way companies respond to the big data trend will become the foundation of competition, innovation and growth . Put simply, companies that can transform their big data problem into real knowledge faster will have a significant edge over the competition .

That’s why leading organizations in diverse industries are tackling their data management issues head-on . For example, one strategy is to bring analytics tools to data rather than bringing massive volumes of data to analytics tools, which is critical if you need to provide millions of rows of information to a data modeler for predictive analytics . Companies such as Teradata, Greenplum and Netezza are making this easier to do by offering new database appliances made from commercially available CPUs, memory and disks . These appliances are essentially high-powered PCs with special software that helps IT departments manage and maintain large databases scattered across many machines, equipping companies using predictive analytics to go from creating a few models monthly to generating multiple models hourly .

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Companies that have invested in big data analytics are seeing improvements in every business discipline, including:

• Corporate strategy – For instance, SAS customers are able to simulate different strategic, complex scenarios using what-if analysis .

• Customer value – SAS customers have realized improvements – of 15 percent and greater – in marketing campaigns through faster, more targeted offerings that produce in tens of millions of dollars in additional revenue .

• Risk management – SAS customers in the financial and utility industries are making value-at-risk calculations faster and maximizing performance at customer engagements .

• Operational efficiency – SAS customers in the manufacturing industry enhance profits through real-time predictive asset maintenance .

The Strategic Role of the CIO in Driving AnalyticsAs an IT executive, you are uniquely positioned to play an integral role in implementing analytics across your enterprise . As a CIO or CTO, for example, you have operational insight into every aspect of your organization and a unique blend of business and technical expertise, allowing you to answer not only “What can we do?” but also “What can it mean to our business?” In other words, you understand what can be accomplished technically, as well as what can be accepted and supported by departments, users and managers . And when you deliver and support a robust analytics platform that enables sophisticated analytics to the enterprise, you can provide compelling value to all of your internal “customers” and help the business outperform its peers .

Delivering a Robust Analytics Platform

The first step is to evaluate your business needs and determine who on your management team understands the value of your organizational data . Almost every company has at least one person who routinely asks: “I wonder why this happened? How we can stop it from happening again?” These are the people who can help you lead the charge in your quest to use information and analytics to propel your organization’s success . For example, they can:

• Obtainanorganizationalcommitmenttouseanalyticstomakedecisions.

• Educatepeoplesotheyunderstandthatanalyticscancreatecompetitivedifferentiation and have a direct impact on the bottom line .

• HelpITprofessionalsrealizethattheycanprovidestrategicvaluetotheorganizationby using and promoting analytics .

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Game-Changing Analytics

The second step is to take a strategic approach to the analytics life cycle and embrace the integration of analytics into the technology infrastructure of your business . If your BI or analytics group becomes a silo within a mass of business structures, it will fail . Information management, information reporting and predictive analytics must be integrated within your overall business so that’s viewed as the source of “knowledge that runs the business,” not simply “data from the analytics team .” The foundation for this step is establishing consistent, effective data management . As noted by Gartner, “The IT organization needs to dramatically modernize its IT systems, transforming outdated data management infrastructure and replacing it with a more up-to-date and superior information environment .”2

The third step is to incrementally invest in a state-of-the-art, high-performance analytics architecture for the enterprise . The best way to do this is to partner with a company that can help you design and implement this platform . This initiative can be led from the top down or incrementally (department by department), assuming everyone uses the same vendor technology so that everything integrates – for a comprehensive platform over time .

Williams provides the following additional advice to IT executives seeking to embark on an analytics initiative across the enterprise:

• Think predictive. According to Williams, his very smart colleague and CEO frequently shared this wisdom: “You cannot manage the past – only the future .” So predict what will come – don’t report on what happened . If you only look at what was, you will never manage or change what will be .

• Work in conjunction with the business to deliver what’s needed. Work cross-departmentally and collaborate with line-of-business executives to help them break out of silos and share data proactively by using analytics to make decisions and plans .

• Let your technology choices be guided by your organization’s knowledge requirements. Implement what’s quickest to give you speed of knowledge .

• Perform an information and analytical assessment before you begin your initiative. Make sure you can answer these questions: What information would change the decisions we make as a company? Do we have access to this information, and can I provide it the right people in the right timeframe for it to be useful? Can our business processes truly be changed to use this information? Are there individuals within our organization who are willing to integrate it into their business processes?

2 Gartner Hype Circle for Enterprise Information Management, July 2011.

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Learn MoreAre you ready to lead your organization to use analytics for speed of knowledge? Success is all about transforming data into information and, ultimately, into knowledge . Data gets you into the information game – so find out what data you already have and what you still need – and then integrate and standardize it . Using BI and reporting tools, you can turn data into trusted information . Then take the leap to advanced analytics, which turns that data and information into knowledge . And knowledge is what separates winners from losers in today’s competitive markets . Knowledge changes everything; it enables you to take the strategic, customer-centric actions that are essential to capturing and retaining customers .

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