Thomas Davenport, distinguished professor of Information Technology and Management at Babson College in Wellesley, Mass., has co-authored another business analytics title that includes a new model to help organizations improve their analytics capabilities.
Published early this year, Analytics at Work: Smarter Decisions, Better Results (which Davenport co-authored with Jeanne Harris and Robert Morison) follows up on Competing on Analytics: The New Science of Winning, which Davenport also co-authored with Harris in 2007.
The first book looked at how organizations can start to make more analytical decisions; the second helps those that want to become even more analytical than they already are, said Davenport to executives at a recent dinner series event hosted by SAS Institute Inc. in Toronto.
The DELTA model
DELTA is the Greek letter for change, and in terms of the model, an acronym for five success factors: D (accessible, high-quality data), E (enterprise orientation), L (analytical leadership), T (strategic targets), A (analysts).
“You can’t be analytical without data and the companies that are highly analytical tend to have good data … but more than that, I think the companies that are analytical leaders also have distinctive data,” he said.
Organizations need to take an enterprise-wide, as opposed to localized, approach in terms of data, people and technology capabilities, said Davenport.
“It’s not everybody making these decisions on their own. It’s as an enterprise saying, ‘What do we really want to do? What is our strategy? How does analytics fit into it? How do the different groups who have analytical capabilities relate to each other?” he said.
Analytical senior executives make it easier to develop a highly analytical organization, he said. Davenport highlighted Gary Loveman, CEO and president of Harrah’s Entertainment Inc., as an example.
Organizations must also establish a target for their analytical work. “You have to have some focus for your analytical activity, because at least initially, you can’t be analytical about everything,” he said.
And good analysts are key to success. “If you want to be good at analytics, you better have some very smart people,” said Davenport.
There are different classes of analysts: the high-level analytics professionals create new algorithms and communicate them effectively, the analytical semi-professionals can do “some” digital analytics and spreadsheet work, and the front-line analytical amateurs (like bank tellers) need to explain offers to clients in a way that is persuasive, he said.