Linking business analytics to economic value is a hard problem. Despite all the smarts that get poured into models, it's hard to tie them to financial measures such as profitability. And, because of that, it's hard to justify investment in analytics. Need headcount? Sorry, try again. Need tools? Sorry, can't afford it. Need training? You can send one person, not everyone who needs it.
Personally, I disagree. And, I'm good company. Business analytics drives major returns for many organizations, many of which are more than happy to link their performance to their use of business analytics. The real secret is that for every company standing up proudly announce their use of business analytics, there's another three in the wings keeping quiet because they know it's a major competitive advantage, and they don't want to share their competitive secrets. One of the highlights of SAS Global Forum this year was hearing Gary Loveman speak about the phenomenal success Caesars Entertainment has had through embracing business analytics. Bear in mind, this is real return. By tracking how analytics has changed their business, Caesars can point to specific examples. They can predict which customers will be profitable even if offered a free chartered flight. They know what the most efficient routing is for their fleet of chartered planes, delivering thousands of flights per year. They even know that by applying business analytics, they've been able to more than double their return on investment from capital when compared to a direct geographic competitor.
For a company like that, it's not a question of whether or not to invest in business analytics. It's simply a question of what's next.
The thing is, getting to this point needn’t be hard. It just requires recognizing that business analytics is about more than algorithms. What else is it about?
- Defining the value that will be created, communicating that value, delivering it, and -- equally as important -- measuring it.
- Understanding that while focusing on the outcomes is essential, successfully delivering business analytics also requires a strong understanding of the softer side of organizational psychology.
- possibly most importantly: knowing that transitioning from applying business analytics as a point solution into a functional line of business and, eventually, as a major source of enterprise-level competitive advantage, things need to be approached differently.