What led you to write this book? Davenport: We had collaborated earlier on a project looking at how companies develop analytical capabilities. We both found it rewarding. Jeanne has been at this whole decision support thing for some time. I had a hypothesis that was verified in our initial research that human factors might differentiate companies more than just data. I wanted to explore that more. And I was approached by SAS (Institute) and Intel and they asked if I would look at who some of the leading analytical users were.
Harris: What's new and exciting is that instead of using BI as this point of light, companies are emerging to use it as a source of competitive differentiation.
How are some leading organizations using analytics to gain a competitive edge? Davenport: One of the things that we say is that companies should be using analytics to support their distinctive capabilities. For Netflix, that distinctive capability is increasingly being able to predict what DVDs their customers will like. They have developed an audience preference algorithm (called Cinematch) in which they try to predict whether a customer will enjoy a movie based on how much they liked or disliked other movies. They're willing to pay $1 million to anyone who can improve the algorithm by 10% under a contest they're having.
Harris: UPS just announced that they're totally redoing their (ground delivery) routes to reduce their number of left turns their trucks make to improve productivity and reduce gas consumption.
You also mention The Boston Red Sox in the book. How are they using analytics to try gain an edge over the Yankees? Davenport: In professional sports in general, the key analytical capability is figuring out which players to acquire in the first place. The Red Sox aren't quite as rich as the Yankees but they are richer than the Oakland A's, who have to be really good at evaluating undervalued players. The Red Sox have figured out how the Oakland A's can do the initial work and then hire the players if the A's can't pay them enough.
The Red Sox also apply analytics to decide what to do on the field. In 2003, the Red Sox hired this guy Bill James who is the god of baseball statisticians. The new owners were more analytically focused than previous ownership. Bill James developed this idea of on-base percentage and slugging percentage as a method of success instead of batting average -- and the Red Sox have applied this aggressively. The A's were the pioneers. Not all (baseball) teams are that analytical. The (Chicago) White Sox aren't that analytical. The (St. Louis) Cardinals are somewhere in the middle. The (Atlanta) Braves are historically quite intuitive.
Harris: We're seeing this across professional sports. AC Milan (a professional soccer team) has a little bit different focus, getting players who are not injury prone. There are 200 data points they look at. There's been a transformation occurring throughout professional sports. The New England Patriots have also applied analytics successfully.
So are the Yankees using analytics? Davenport: There's not much evidence that they have. They haven't hired any big statisticians. The players that they have do have good numbers in the traditional sense. A guy like [Alex Rodriguez] does, but that hasn't helped his team produce. They would be incredibly powerful if they had that, too.
Let's switch gears. Can a public sector agency use analytics to 'compete' either against public or private sector 'rivals'? Davenport: New York City was one of the earlier adopters with the CompStat (Comparative Statistics) program, one of the reasons why Rudy Giuliani can say they reduced crime so much when he was mayor.
Harris: Very early in my career, I worked in the public sector and we used analytics at the IRS for fraud detection. Some government agencies have some very sophisticated capabilities.
We often hear about the need for IT organizations to scrub their dirty data. How much of a problem is data integrity? Harris: Data integrity is absolutely a huge issue if you don't have it. The integrity of data in the average corporation is getting better overall. The reason some of these executive dashboards failed is that they tried to put a pretty face on some pretty bad data. But it's a continuing challenge for organizations. Data cleansing isn't very fun. But (leading) companies pay a lot of attention to ensuring they have the cleanest, most accurate data they can have.
Speaking of dashboards, some CIOs complain that CEOs and other executives have demanded these tools to view and act upon daily or weekly operations data -- but then either ignore the dashboards or use them lightly. What's the disconnect here? Davenport: We make the distinction between reporting activities and analytical activities. Dashboards are purely reporting oriented. There's no model that describes which non-financial factors drive financial performance and so forth.
One of the things we advocate to people who drive reporting are what are the underlying analytical models that make those dashboards more meaningful. Hilton Hotels determined that for every 5% increase in customer loyalty this year they generated a 1% increase in revenues the following year. Making the information meaningful can help generate more interest in these dashboards.
You devote a chapter of the book to analytical people. What are some of the successful characteristics of CEOs who get this? Davenport: In the really analytical companies, CEOs are really driving things. They need to be really passionate about this topic and do more testing and make decisions based on analytics and facts as opposed to intuition. If you're the head of marketing or HR or supply chain, it's a question of asking, 'Should my function be using analytics in a more aggressive way? What's the way that we could build some distinctive capabilities and gain competitive advantage using analytics?'
What are some improvements that CEOs can make to better leverage analytics? Harris: One of the things we found very consistently (among leader companies) is instilling a fact-based culture in your organization. You don't want people to be making decisions by the seat of their pants, you want them to be based on facts. That's one thing an executive can do: foster a climate of fact-based decision-making.
What does the future of analytical competition hold? Davenport: We tried to break that issue up into several different categories. There are the strategic drivers, human drivers and technological drivers. From the strategic side, more and more companies will start to view this as a critical capability that they'll need to have and what does the long term competition look like with respect to analytics.
The airline industry was pioneers with analytics with things like yield management and crew scheduling, but they coasted on their reputations a bit and suffered. Capital One is competing in a credit card market where lots of banks have adopted their approaches. So they have to constantly be thinking about how they can introduce analytics to (other) areas of banking or other innovative approaches they can take.
The real issue is that there's going to be an analytical talent race. There already is to some extent. One software company told us it can take up to a year to find someone who understands the nature of their business and has strong analytical capabilities. It will be interesting to see if more of this work goes offshore. There are lots of smart people in India and China, for example. But there are trust issues with having someone handling your data who's located thousands of miles away.
Harris: Analytics will also be used to differentiate products and offerings, such as Progressive Insurance offering customers the opportunity to evaluate competitors' quotes. There are golf clubs under development that can analyze your swing and provide you biometric feedback.
What might IT managers learn from the book? Davenport: I think they might have a much greater sense of what the business value of BI might be. The discussion has often been around things like 'Should you have a data warehouse or a series of data marts?' IT had a tough time getting senior executives motivated to pay for and move forward on this, so this should be a nice way for IT people to engage senior management on the business value of analytics.
Harris: It's actually changing business models. It's a whole way of changing the dialogue with your senior management team.