Life must be lived forwards but can only be understood backwards.
You’ll get no argument from me about the power of analytics. I’ve seen it firsthand, and I wouldn’t have written this book if I didn’t grasp its potential to make better decisions. As is often the case today, though, there’s no shortage of hype around it. As I wrote in Message Not Received, far too many software vendors, consulting firms, industry experts, and talking heads often exacerbate matters with buzzwords, forced “backronyms,” and opaque models that confuse far more than they convey.
This brief chapter shines a spotlight on the different types of analytics.
At a high level, I like to think of analytics as the process of using raw data to derive valuable insights and increase understanding of a topic. By analyzing historical and current events, you can identify potential trends. Analytics allows individuals, groups, and even entire organizations to make optimal—or at least better-informed—decisions.
More than ever, these decisions run the gamut. Today, they involve making money, identifying errors, and mitigating risk, as well as reducing costs, customer churn, or employee turnover. Analytics are useful irrespective of company size and in just about every industry. Many nonprofits use analytics, as does just about every major sports franchise these days.
Analytics go beyond simple statistics. Let’s say ...