IT Management

It’s time to think big—about Big Data, that is. Big Data is the idea of using statistical analysis of enormous quantities of data to draw conclusions that lead to positive actions. Given the publicity Big Data receives these days, you need to address how and whether to deal with it. Here we discuss the information you need to consider regarding the risks, your situation and possible courses of action.

To consider the risks, imagine, for example, that George, your VP of marketing, is considering the advantages of Big Data. If you do nothing, he may end up running the project himself, taking the credit for any successes, reducing IT’s influence. On the other hand, if you commit significant resources to Big Data on your own, and don’t show positive results, you will take the blame. If you and George together make Big Data happen, and he criticizes your contribution, this also reduces IT’s influence.

To consider your situation, think about what data you have and who you have to analyze it. You can’t do Big Data unless you have large volumes of data and highly trained staff to interpret it. This may require finding someone with a degree in statistics or a similar level of knowledge. 

If You Don’t Know Where You’re Going, Then Every Road Will Take You There

You can’t succeed with Big Data if you don’t have measureable objectives. Finding patterns in the data isn’t a useful objective since it has no relation to profits or company goals.

Likely, only George and the marketing department have the knowledge to specify the objectives. They might hope to “increase sales by 10 percent” or “identify customers who aren’t worth maintaining” or “identify new product and service opportunities,” since all of these can relate to profits.
     
You may have a good relationship, a bad relationship or no relationship with George. George may or may not have a clear understanding of what he would hope to accomplish with Big Data. You and your staff may have to help George be specific about what he hopes to accomplish with Big Data.

Courses of Action

Possible actions include doing nothing, trying to do Big Data on your own, trying to do Big Data with George, agreeing with George to investigate further by taking some baby steps together and meeting with George to learn more about his expectations and what he has to offer. 

Meeting with George will help you get the information you need to decide what action is best for you. Prepare for the meeting by listing what large sets of data and trained staff you have.

You can prepare further by listing what you know of George’s goals and problems. Use these to develop statements of what Big Data might do for George. If you don’t know which is more important to him—increasing sales/margins, expanding into new geographic or Internet areas, reducing returns on sales, identifying key customers or leveraging current customers to gain more customers—then find out. 

Turn these into benefit statements and then into gentle inquiries such as: “I’m no expert on statistics, but would it be useful to you if we could analyze this data to identify the customers who bring us the most profit, identify some common factor in the most productive salespeople or some other finding that’s not immediately obvious? What would you like to get out of this?” His response will tell you whether or not to pursue Big Data. If he responds with interest, you might mention that Big Data needs someone who knows statistics and inquire if anyone on his staff is qualified to help.

You can measure your success in this effort by the degree to which you and George jointly decide whether and how to address Big Data.

Note that there may be more than one George, and not always in the marketing department. You know that IT can’t succeed in Big Data without real collaboration from George. You’re probably the best person to start that collaboration and then decide how to proceed.

The next column will address how to determine whether any of your areas of responsibility are causing you problems, and what to do about it if they are.