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This chapter is from the book

This chapter is from the book

Managerial Analytics: An Applied Guide to Principles, Methods, Tools, and Best PracticesManagerial Analytics: An Applied Guide to Principles, Methods, Tools, and Best Practices

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This chapter is from the book

This chapter is from the book

Managerial Analytics: An Applied Guide to Principles, Methods, Tools, and Best PracticesManagerial Analytics: An Applied Guide to Principles, Methods, Tools, and Best Practices

Learn More Buy

What Is Managerial Analytics?

We use the term managerial analytics as the title of this book, so we should define what it means. We define managerial analytics as what a manager needs to know about the field of analytics to make better decisions. So we are using the term to refer to understanding the field of analytics from a manager’s perspective. Or, in other words, managerial analytics helps prevent you from being fooled or confused by the many different analytic terms and solutions offered, helps you see what is possible, and helps you do more on your own.

Managerial analytics is about understanding the difference between descriptive, predictive, and prescriptive analytics. It is about understanding the different tools and where they fit in. It is about cutting through the buzzwords to help you better understand solutions.

Hopefully you are now sensing how large the field of analytics really is. You can get an advanced degree in very specific niches within the analytics field. As a manager, you cannot understand every nuance. You should, though, understand what problems the different disciplines of analytics can solve. And you should know what types of decisions a particular project will help you with.

Another way to think about this is that you will often be presented a single tool as a way to do analytics. We want this book to help you, as a manager, cut through the confusion and determine which type of analytics you need and for which types of projects a tool may provide value. No one solution will cover the full range of the field of analytics. This knowledge should help you select analytics projects that meet your objectives and then guide successful implementations.

Managerial analytics is not devoid of technical material. As the importance of data and analytics increases, you will have to be more comfortable with the technical aspects if you want to succeed as a manager. While you won’t be expected to understand all the nuances of different disciplines, you should understand the limitations of a given analytics solution—and what that solution won’t do. Many times, an analytics solution will be presented by someone pushing an idea, and it will be impossible to tell what the solution won’t do. Vendors commonly write descriptions of their analytics solutions that make it seem like a single solution will solve all your problems. If only it were this easy.

This book covers enough of the key technologies behind descriptive, predictive, and prescriptive analytics so that you will know if a project is on track, you will know what experts you may need, and you can better understand the details of the solutions being presented to you and have a healthy understanding of their limitations. In other words, with this understanding, you are less likely to be fooled or confused by vendors and co-workers using the term analytics in a vague way.

But managerial analytics is about more than not getting fooled. It is also about the art of the possible. The analytics movement is real because it produces real value. To capture this value, however, you need to know what is possible. So managerial analytics is about understanding how analytics can apply to your business. One of our goals with this book is to get you thinking about your company or organization in a new way. That is, by seeing different examples and understanding the different areas of analytics, you may uncover opportunities for adding value in ways you hadn’t thought of before—and these new ideas may turn out to be much more important than current projects you are working on. If you want your entire company or just your small department to make better use of analytics, the more you and your colleagues understand what is possible, the more value you will find.

Finally, not everyone has access to a large IT department and teams of analytics experts. In fact, most people don’t. So don’t think of managerial analytics as just something that big firms do. Instead, managerial analytics is for organizations of all sizes. Managerial analytics is about giving you enough information that you can get started with what you have. From what we have seen, most managers have plenty of room to use the data and tools they have in order to make better decisions. Don’t wait for big projects; you can start now.

The rest of this book is devoted to helping you understand managerial analytics—analytics from a manager’s perspective. This will help you whether you are doing a single project within an organization or rolling out analytics solutions to your entire organization.

It will help you understand the definition, help show you how the types of analytics work together, and present you with practical applications that are applicable to a wide range of organizations. It provides cases and examples to solidify the ideas throughout. And, since analytics is a technical field, this book also discusses the technical aspects of analytics. You can skip these sections without losing the flow of the book. But, as a manager, the more you understand the technical aspects, the better you will be able to apply analytics.

Is Competing on Analytics a Strategy?

Davenport’s article, “Competing on Analytics,” was not written to define analytics. It was written to show that firms that are dedicated to using analytics to tackle the biggest issues and using analytics throughout the firm could do significantly better than other firms in their industry. In the article, he also discusses ways a firm can structure itself to be an analytics competitor. It becomes clear from the article that analytics could be a highly strategic tool for any firm.14

An article in Analytics Magazine stated, “In many ways, business analytics is the next competitive breakthrough following business automation but with the goal of making better business decisions, rather than simply automating standardized processes.”15

And you can find many other similar claims.

Based on all this, it might be easy to declare that competing on analytics can be classified as a strategy. A CEO may try to claim “We will compete by being the best at analytics.”

Ben Reizenstein, from Northwestern University’s Kellogg Business School, actually posed this exact question: Is analytics a strategy? Or, is it just a tool to help you do what you do, but better? He was leaning toward the latter. That is, with all the hype around analytics (much of it deserved), we might have lost track of the idea that analytics can help support your strategy. So, maybe it is not a strategy but a great tool to help you execute your strategy.

For example, “Competing on Analytics” uses Marriott as an example. For a hotel chain, the strategy might be to provide the best business hotels or the best resort hotels, or to be in every market or to be only in large urban business districts. The use of analytics is a way to help the hotel chain really execute its strategy, but its commitment to analytics is not necessarily the strategy itself.

If analytics is a strategy, then you have to wonder if every analytics project has value. If analytics supports your strategy, you can then judge analytics projects as they relate to executing your strategy.

In Davenport and Harris’s book, Competing on Analytics (the follow-up to the article), they mention that analytics is not a strategy but that it supports developing certain business capabilities.16

On the other hand, consider again the hotel example. You could imagine a scenario where a hotel decides to be the best business hotel and will use analytics to do just that. This could be contrasted with a strategy of being the best business hotel by focusing solely on hiring service-oriented people or having a unique sales force to win corporate clients, or to focus on buying distressed hotels in good markets to keep real estate costs low. The list could go on. There is nothing that dictates that a firm needs to use analytics to be better. In this sense, analytics is an integral part of the strategy. It dictates the type of people the firm hires and the investments the form makes in IT, for example.

Davenport and Harris mention that the companies that are best at analytics mention it in their annual reports and press releases, and it is highly visible to the top of the organization. They even mention that the firm’s strategies are built around analytics—suggesting something possibly a bit closer to a strategy than just a supporting role.17

Another way to look at this issue is to divide strategy into the business strategy (what the business is trying to be) versus operational strategy (how to achieve the business strategy). With this view, clearly analytics is an operational strategy that supports the business strategy.

We want to present you with a balanced view that neither over- nor undersells analytics. Our aim with this discussion on strategy is not to provide an answer but hopefully to stir a lively debate in your organization about the role that analytics will play.

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