Smart teaching. Why data analytics ranks with reading, writing and arithmetic. The new way to be smart. Contents: IBM Software Business Analytics

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1 Smart teaching Why data analytics ranks with reading, writing and arithmetic Contents: 1 The new way to be smart 2 Not your father s data mining 2 Case in point: Putting data analytics on the MBA program 3 The Rise of data analytics 4 Part of the toolkit 4 Students speak out 6 Conclusion 7 About IBM The new way to be smart What do identifying consumer buying habits, preventing future crime, administering pre-emptive health care and detecting fraud have in common? All can be achieved today through the use of predictive analytics. It s no wonder then that data mining should be part of the required curriculum at every college, university and MBA program, just as surely as English or math. With English, you don t need to be Shakespeare, but if you can t communicate clearly you ll be ill-prepared for a successful career. With math, you don t need to be Einstein, but if you can t work with numbers you are going to have a hard time succeeding in business. The same is true for data analytics. You don t need to be a statistician, but you do need to understand how to leverage data to manage your business and make smarter decisions. It s the new way to be smart. That s what Ian Ayres argues in his book, Super Crunchers: Why Thinking By-the-Numbers Is the New Way to Be Smart. We are in a historic moment of horse-versus-locomotive competition, where intuitive and experiential expertise is losing out time and time again to number crunching, writes Ayres. Now something is changing. Business and government professionals are relying more and more on databases to guide their decisions. It s happening everywhere, Ayres suggests in a series of anecdotes; data-driven decision-making is revolutionizing every business model from baseball to wine-making. The reason is simple: knowledge is power. Using data instead of gut instinct to drive decisions is the difference between knowing and guessing. What products should you bring to market? How should they be packaged or priced? How will customers respond? What special offers should you extend? Which customers will remain loyal? Underlying all these questions is one fundamental issue: what works? Of course, there s the equally fundamental corollary of the things you should avoid, or what doesn t work? Analyzing relevant data to answer these questions and basing your business decisions and actions on facts is a better way to achieve success than by acting on intuition alone.

2 SPSS in For more than 40 years, IBM SPSS technology supported the administrative and instructional needs of educational institutions worldwide: 80 percent of all US colleges and universities All Ivy League schools All 25 of Forbes 2009 America s Top Best Colleges 97 percent of Forbes 2009 America s 100 Best Public Colleges 95 percent of Forbes 2009 America s 100 Best Private Colleges 9 of the Top 10 Online Colleges Not your father s data mining Data mining from a few years ago is not the same as today s data analytics. Data has evolved and analytics has advanced. The Internet has made everyone smarter with access to vastly more information on products, prices, companies, competitors and the opinions of their peers. In turn, businesses have access to much more data today than just five years ago. This data can be found in the usual places in business organizations, including sales (e.g. CRM), marketing (e.g., a company s website) and finance (e.g. ERP). A vast amount of unstructured data available from information sources such as call center logs, customer satisfaction surveys, , wikis, blogs, tweets and evolving forms of social media. But the power of this information can t be leveraged until it can be unlocked, deciphered and applied in its appropriate context. Just as data has evolved so, too, have the collect and analyze it. Using advanced text mining algorithms and improvements in natural language processing, businesses can extract valuable concepts and sentiments from customer surveys and other sources of unstructured data, and with this information develop much deeper insight into their customers. Based on previous responses of customers and patterns of behavior, vendors can predict actions how customers will likely respond to a product, an offer, a communication with a high degree of accuracy. Moreover, solutions for predictive analytics and decision management enable businesses to take the next step and connect the dots between analysis and action. With these technology solutions, businesses can transform structured and unstructured data from a wide range of sources into actionable intelligence, delivering this intelligence to employees in real time, enabling them to make informed decisions influencing their actions across the enterprise. Data analytics is not only the new way to be smart; in business, it s the new way to act smart. Case in point: Putting data analytics on the MBA program Dr. Girish Punj, professor of marketing in the School of Business at the University of Connecticut, has been teaching data analytics to graduate students since Many of the students who have taken the course over the years were well along in their professional careers, with most working full time. They have come from diverse educational backgrounds, ranging from liberal arts and business to engineering and science. All of the students have taken a graduate-level statistics course as part of the University of Connecticut s core MBA requirement. For many of these students, taking the journey with Dr. Punj to understand the power of data analytics has advanced their thinking, actions and career possibilities as they returned to their respective employers. 2

3 The rise of data analytics Dr. Punj makes a point at the start of each course to establish for his students the rising importance of data analytics in the world of business. I start the course, says Dr. Punj, by discussing the significance of data mining in the business world, referring to surveys that have been done on the importance of the methodology. Most of the surveys identify data mining as a top 10 technology or trend. I talk about how data mining skills are valued in the marketplace, how individuals with the skill will command a premium, and why they are an integral part of the toolkit for MBA students. There is much evidence for Dr. Punj to draw from. Enterprises are seeking practical methods of doing more with less and doing it better. Data analytics is a rare tool that fills the bill, and so the spotlight has turned its way. Thus, there s a growing body of evidence on the rising importance and impact of data analytics. Data analytics is everywhere In 2009, Rexer Analytics 1 surveyed 710 data miners from 58 countries and found that data analytics is used across many business functions (most frequently CRM/marketing, sales and research and development) and across many industries (typically academic, financial services, retail, telecommunications, manufacturing, medical and insurance). Data analytics is in demand According to a recent Accenture survey, nearly three-fourths of executives at large companies in the U.S. and U.K. said they are working to increase their company s use of analytics. 2 To perform analytics, you need individuals with analytical prowess. Of course, this demand is reflected in current hiring trends as well as salaries. As companies ramp up hiring, they are in hot pursuit of a particular kind of employee: those with experience in statistics and other data-manipulation techniques, reported The Wall Street Journal. Those with strong statistics backgrounds will earn up to 20 percent more than generalist engineers, who typically start with salaries in the low six figures. 3 Data analytics is changing how business is done. The Rexer Analytics survey of data miners also found that: 60 percent of respondents say the results of their data modeling exercises are deployed always or most of the time More than half say their results are helping to drive strategic decisions Nearly half say their results are driving operational processes Nearly a third say their results are driving product or service creation, development and improvement 1 Karl Rexer, PhD, 3rd Annual Data Miner Survey 2009 Survey Summary Report. 2 Competing Through to Achieve High Performance, Accenture Information Management Services, December New Hiring Formula Values Math Pros, The Wall Street Journal, April 8,

4 In today s world we have an enormous amount of data residing in organizations and flowing through the Internet. The data does not provide knowledge, it s just static data. To extract meaningful and actionable information, we need to understand and analyze it. Tools like IBM SPSS Modeler Premium provide insight to information hidden in the data, from which organizations can make better decisions, directly helping the bottom line. Student View: Kapil on the importance of understanding data Employment of individuals with data analytic skills is projected to grow 18 percent from 2008 to The use of statistics is widespread and growing, reports the U.S. Bureau of Labor Statistics. Statistical models aid in decision making in both private industry and government. There will always be a demand for the skills statisticians provide As data processing continues to become more efficient and less expensive, an increasing number of employers will want to employ statisticians to take advantage of the new information available. Part of the toolkit I mention, says Dr. Punj, how data mining skills are helpful for career advancement during good economic times, and a form of job insurance during bad economic times. He points students to which bills itself as the data mining community s top resource. It has listings for data mining jobs, says Dr. Punj, some with six-figure starting salaries, and that always gets students attention. A glance at kdnuggets jobs list on a random day found 54 jobs listed with such titles as Analytics Specialist; Credit Policy Risk Analyst; Director of Analytics; Director of Research, Algorithms and Data Mining; Forecast Analyst; Forensic Analytics Manager; Junior Analytics Manager; Manager of Database Marketing; Senior Games Analytics Engineer; Senior Analyst; and Senior Statistician, to name a few. These jobs are open at companies ranging from leading web e-tailers to restaurant chains, from insurance companies to dating services, from FORTUNE 500 companies to start-ups, from LA to New York to Geneva to Bangalore to Beijing. The fact that some of these positions have been open for more than three months in an economy with high unemployment suggests that demand for data analyst skills has outstripped supply. You don t have to make a career of data analytics or have a primary focus on data analytics in your role to benefit from a data analytics class. Just having the skill as a part of the toolkit can prove beneficial to your career. Data analysis, as Dr. Punj defines it, is the discovery of interesting, meaningful and actionable patterns hidden in large amounts of data. The ability to take static data, as one past student states, and extract meaningful and actionable information gives any organization the knowledge to make better decisions that directly help the bottom line. Students speak out Kapil was a project manager with GE and at the mid-point of his career he took Dr. Punj s Data Analytics Course. Today, Kapil is Relationship Manager Finance & Risk Business Solutions at one of the world s largest banks. 4

5 Data analytics is valuable because it provides a framework to obtain a better understanding of the data itself and where it comes from. This in and of itself is valuable to anyone who is involved with managing information in their career, because it enables that individual to have a deeper understanding of how the end product was derived. Student View: Jennifer on the value of data analytics No IT or finance job is without data analysis, says Kapil. What I learned from Dr Punj s class helped me look at any data very differently, whether it s grouping or classifying data based on some emerging trends and then analyzing features/properties of each data group to make key decisions on next steps. I would say that learning the data analytics skills gives us tools, skill and knowledge to do the data analysis in a much more efficient way, which saves times and helps make better decisions. I am much better in understanding data, analyzing it, articulating it and making decisions based on it. In summary, says Kapil, I always encourage people to take a course in data mining and analytics. It s one of the most practical courses that one can learn from and apply in his/her job the next day. People can see the benefits and results immediately. Jennifer was employed at a large national insurance company where she was engaged in analyzing the performance of our agency plant when she took Dr. Punj s course in Now she s Director of home marketing at a regional property casualty insurance company. We perform data analytics to assess and measure agency performance. From a marketing perspective, we want to better classify our agents in order to maximize our potential with them. The goal is to create a profile of our most successful agents and try to use that profile as a model when looking at the rest of our agency plant and even use it as a measure against prospects to see if they would be a good fit. Data analytics is not Jennifer s main job description as a marketing director, but it has directly impacted her career. It has made me more comfortable in managing data and has enabled me to see data from multiple perspectives. Prior to data analytics and finance, I would say my understanding of data analytics was rudimentary. It has also helped me become more effective at screening out the noise that exists in data sets. In view of her own experience, Jennifer says: I would strongly recommend taking data analytics even if the students use those skills indirectly as part of their job. Data analytics can be applied numerous ways in the work environment and it does not always require the use of a formal data analytics system. It provides students with a better understanding of how data can be leveraged and maximized, especially when businesses today can struggle with data overload and insufficient analytical tools. Rambabu, another former student in Dr. Punj, today is Director of ERP systems for Priceline.com, where he is responsible for managing all the accounting, financial, and reporting applications. 5

6 There are tremendous number of companies out there that collect lots of data but very few actually do much with it, beyond storing it in a database and simple reporting. Storing data is not good enough. For competitive advantage one must be able to analyze the data to understand the future. Storage is getting cheaper, computing power is increasing and getting cheaper, consequently analysis can be done at a relatively low cost, and people who have the understanding and ability to do this will be in demand. Also tools like IBM SPSS Modeler Premium actually make the analysis easier with graphical tools to build the models. Student View: Rambabu on using data vs. storing it Prior to this course I really did not have much experience with data analytics tools other than basic statistical analysis of data, says Rambabu. Due to this class I have become aware of the possibilities and, as a part of my final project, used IBM SPSS software extensively to help our marketing team understand our customer demographics. This course gave me the knowledge to ask the right questions, says Rambabu, especially when large and complex datasets need to be analyzed. Because of the course, he adds, I have an extremely strong analytical background and have to deal with lots of analytics to help our business users understand data, trends, and work with them to make strategic decisions. Rambabu uses his knowledge of data analytics on a regular basis in his current job. Priceline has a 365-day moving forecast of our key business metrics with yesterday s forecast being replaced with actual metrics of data collected. These forecasts are used to steer Priceline s business and plan for future initiatives. Payables and receivables analysis is key to our revenue and cash flow analysis. Data analysis, while not his core role, has opened up new opportunities. I am not yet responsible for the data warehouse (DW) and business intelligence (BI) team, but there is a possibility if my role was to expand in the future. Conclusion At the start of this paper we asked Why does data analytics rank with reading, writing and arithmetic? We ve seen that figuring out what works is increasingly important to enterprises of all types across all industries. As a result, individuals with strong analytical skills are in high demand. And, because demand has outstripped supply, they re commanding high salaries. Analyzing data, says Rambabu, could be a very lucrative and an exciting career. For professors who are considering teaching a data analytics course, or advocating a data mining degree, there s a wealth of material available to make it relatively easy to get started. At the IBM SPSS online Educator Resource Center, you ll find syllabi, tutorials, datasets, presentations and exercises from Dr. Punj and other educators, as well as special offers on data mining and predictive analytics software for academic use. The simple reason to teach data analytics is that the private sector is demanding it. Students benefit from the knowledge, as do the companies that stand ready to hire them to improve their decisionmaking based on facts and data. Check out the IBM SPSS Educator Resource Center at to get started. 6

7 About IBM IBM software delivers complete, consistent and accurate information that decision-makers trust to improve business performance. A comprehensive portfolio of business intelligence, predictive analytics, financial performance and strategy management, and analytic applications provides clear, immediate and actionable insights into current performance and the ability to predict future outcomes. Combined with rich industry solutions, proven practices and professional services, organizations of every size can drive the highest productivity, confidently automate decisions and deliver better results. As part of this portfolio, IBM SPSS Predictive Analytics software helps organizations predict future events and proactively act upon that insight to drive better business outcomes. Commercial, government and academic customers worldwide rely on IBM SPSS technology as a competitive advantage in attracting, retaining and growing customers, while reducing fraud and mitigating risk. By incorporating IBM SPSS software into their daily operations, organizations become predictive enterprises able to direct and automate decisions to meet business goals and achieve measurable competitive advantage. For further information or to reach a representative visit 7

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