What Is Managerial Analytics?
- Confusion About the Meaning of Analytics
- What Is Analytics?
- So, What's New?
- What Is the Best Type of Analytics?
- What Is Managerial Analytics?
This chapter is from the book
This chapter is from the book
This chapter is from the book
Confusion About the Meaning of Analytics
The field of analytics (and its frequently used synonym Big Data) has captured the imagination of managers everywhere.
Companies often publicly claim that they are committed to analytics. General Electric recently announced a big push into “analytics” to take advantage of the data generated by its own industrial machines.1 IBM and Ohio State University announced the creation of an analytics center that is projected to employ up to 500 people doing analytics work. Google touts its own internal analytics for its superior searching capabilities and offers its services to others to track their own websites. This list of companies and their newly publicized analytics capability could go on and on.
Not wanting to miss the excitement, consulting and software companies are also touting their analytics services and products. The more skeptical may think that some of these firms didn’t change anything except their marketing messages to include the word “analytics.” But even the skeptical view does not refute the fact that there is clearly a lot of demand for analytics—otherwise these firms would not be trying to jump on the bandwagon in the first place.
The term analytics has even made it into the popular press. It is common to see it used in the business section and even on the front page of the newspaper. The movie Moneyball (based on the book of the same name)—showcasing how the clever use of statistics helped the Oakland A’s create a low-cost winning team—might be most responsible for the term analytics catching the general public’s eye. Those following politics closely have also likely read about President Obama’s re-election campaign’s heavy use of analytics to target the voters most likely to vote for him. These forays into mainstream culture (sports and politics) furthered the public’s interest in analytics.
Responding to the demands of employers and students’ desires to be employable, universities have started to offer degrees in analytics. It is very likely that you have come across articles in major publications that talk about the demand for people with analytics skills.2
But just what is analytics? Companies and journalists are better at using the word analytics than at telling you what it is. Without a definition, how do you know if what you are doing is analytics? How do you apply analytics to your situation? How do you know if your vendors are really even selling you an analytics solution?
Whenever a word has such good connotations yet is poorly defined, it is at risk of becoming just another buzzword that will be forgotten when the next one comes around. The CEO wants more analytics projects, so managers put the word analytics into all their project titles, without substantively changing anything they are doing. Vendors realize that they can rename what they’ve always done as analytics, and it will sell better. And if a certain group of products become associated with the word analytics, then the companies selling those products have no incentive to clarify; why clarify the term if it is working to your advantage? Part of the appeal may very well lie in the mystery of analytics to some people: It sounds complex and promises great returns, so we better do it!
If you are serious about applying analytics correctly, how do you know where to start? How do you know when and where you are going to get value from analytics? Will any analytics projects do, or are some better than others?
Adding to the confusion, the term Big Data is starting to be used alongside analytics. The term Big Data is also not well defined. For example, how is Big Data different from a large data set? And does analytics only apply to Big Data? Do analytics and Big Data mean the same thing?
This book cuts through the confusion and gives you clear definitions of analytics and Big Data. You’ll get a look at this newly defined field so you will have a deep understanding of the term.
We take the position that analytics is more than just a buzzword or a fashionable trend. Analytics, performed well by capable people, can bring tremendous value to your company or organization. And it applies to companies and organizations of all shapes and sizes. It applies almost everywhere—to large and small companies, non-profits, and educational institutions. It applies to healthcare and medicine, government agencies, science, law enforcement, and the military. Analytics projects can be started by the head of an organization, a manager of a department, or even a single individual. But analytics can bring value only if you and the people in your organization know what it is, can communicate it clearly, and apply it correctly.