Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series)


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This book is designed not only to provide a broad understanding of retail but show how to use the data that these companies have. Each chapter covers a different focus of the retail environment from retail basics and organization structures to common retail database designs.

Numerous cases studies and examples are given throughout. As analysts, we try to see problems in black and white, with as little gray area as possible. What may be seen as obvious in one country, however, is a new concept in another. Managing many different analytics teams and projects across these countries became somewhat of a learning and teaching exercise.

I was and happily still am constantly learning about the different cultural nuances of each country. One such difference comes from the use of prebuilt software. One of my teams was up on all the latest software and felt that this gave them a competitive advantage in developing quick and effective analytic solutions. While these differences can be overcome, the majority of my time dealing with global teams was spent explaining what type of analysis I need to get completed.

This may sound simple, but when the basic retail terminology was missing, the management task became enormous. With so many young and intelligent MBAs with little firsthand experience in retailing, how do you explain stock-keeping units or package quantities, much less market basket analysis with trade area overlays? With every country in a different time zone, it was difficult to have everyone on a call at the same time to explain some of the basic retail analytics fundamentals.

At the time, I was just hoping to get my teams on an even level with one another with basic terms and concepts, which was totally self-serving, as I wanted to cut back on my 2 A. What I finally ended up with is a book filled with examples of projects and solutions, along with a complete list of terminology that I have used across my broad retail background. I had no idea that this would end up in a book, much less be sought after by acquaintances across the world.

I am humbled by this, because this book was a labor of love. I have included a glossary of terms that are commonly used by retailers as well as a list of retail-oriented projects.

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No project can be a failure if you learn from the outcome. Try to be creative in your pursuits to solve business hurdles. Your creativity can be your best asset. Analytics is an art as much as a science and you need to keep balance. I have a deep retail and financial services background, and blend both perspectives in my writing.

I also at times strive to keep the creditcard marketing point of view in scope. Keep this in mind as you read through each section. Ideally, we would like to influence all of these factors. For the best results, refer to the glossary of terms at the end of the book. Understanding these terms will help your ability to use each concept. Acknowledgments While this book was a labor of love on my part, it took many people over the years to help me gather the inquisitive analytics spirit to try so many differing retail avenues.

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I must thank Kmart Corporation as a whole for placing me on the leadership fast track, which meant moving me to a new division every two to three years. I never had a chance to get bored. Over a year career that encompasses many different areas, I began my career pushing buggies and ended up 23 years later managing the complete database marketing for the company. This hands-on experience has been invaluable throughout my career. I need to single out Tom Lemke, whom I met when he was the vice president of marketing for Kmart. I have had the opportunity to continue working with Tom over the years.


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Tom has a great mind for seeing the future, and has always pushed me to either prove or disprove his concepts with hard-core analytics. This constant challenge has pushed me to continually try new methods and concepts to validate strategic and business processes. I wish to thank David Fogarty, the vice president of Global Decision Sciences for GE Money, for his belief that global retail analytics has a place in a large organization.

His constant support was very much appreciated. His constant and unwavering belief that I could make a difference in my overseas assignment gave me the confidence I needed. I still follow his advice. Tom Davenport, although a great author himself, always takes the time to speak with aspiring authors and offer advice. I followed his advice, which is one reason this book was finally completed. Tom, thank you for being a great inspiration. I have to thank my wife, who has had the patience to put up with my frequent trips out of the country and late nights working with my global teams.

She has always been a great partner in these efforts. She is my best friend and has been for 30 years. Over my career I have met so many individuals that have helped frame my diverse perspective on business and analytics that I cannot possibly name them all. All I can say is thank you, and hope that I continue to meet more of you. CHAPTER 1 Retailing Analytics: An Introduction T he purpose of this chapter is to help develop a basic understanding of retail terminology and concepts across a wide variety of backgrounds and experience levels.

The one constant factor is that we are all using analytics in some form in the support of our organizations. A significant portion of my work over the past seven years has involved using data from consumer credit card programs to improve retail in many areas. Credit card data can be found in various levels of detail, from bin range at the transaction to aggregated card type Visa, MasterCard, etc. I include the use of credit data within the various sections and show how it was used to improve many types of analytics. I also include perspectives from the credit card companies, as many of these companies do not have any practical retailer experience.

They constantly struggle trying to find a bridge between credit and retail. I have found analytics to be a great bridge between retail and credit companies, as the data provided by both, when combined, can be an extremely important source of insights. Helping these credit companies understand retail organizations will, in the end, help retailers.

Fuzzy metrics are very hard to measure mathematically and, as such, are difficult to grade for performance. Customer relationship management CRM is all about the customer, which, in this case, is your client, the retailer. But instead of just getting the end customer to use more of our card services, we also wanted to have a positive influence so that the clients retailers, in most cases would request more products from GE, seek more consultation from analytics, and allow us more involvement within their inner circle. All of these outcomes are very positive, but again, difficult to equate back to any financial gain.

Do not lose sight of the importance of these soft benefits; they can be long-term relationship builders. One aspect that can be measured is contract continuation versus renegotiations. Another strong indicator of how the client is feeling toward you is its willingness to recommend either you or your organization to its peers, often referred to as a net promoter score.

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This can be absolutely invaluable in the business community, and is now a key performance indicator KPI in evaluating many businesses. They pay the bills and bring in the profit. If you can show that increased credit card usage or fact-based analytics will sell more products, they will listen. Remember, the retailer business is selling merchandise, not credit. If you can show that data usage will give the buyer brand manager a competitive advantage, she will pay attention.

Almost without fail, retailers are set up in a hierarchical arrangement.

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There will be different groups within the merchant buying area, usually apparel, hard lines, commodities, sporting goods, and so on. While managing the credit card analytics area, I have found it easiest to align with the head of one merchandise area that best suits credit card marketing, maybe an early adopter someone who easily accepts new concepts.

When you align with this person, try to make it a win for the retailer with some tangible benefits for the card.

Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series) Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series)
Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series) Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series)
Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series) Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series)
Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series) Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series)
Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series) Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series)
Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series) Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series)
Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series) Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series)
Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series) Delivering Business Analytics: Practical Guidelines for Best Practice (Wiley and SAS Business Series)

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