Yesterday, I started sharing a list of five strategies for successful data management from the Harvard Business Journal’s article “Why IT Fumbles Analytics.”
Their main point is IT staff will use conventional methods for managing and deploying big data projects to their peril. Instead, “they need a fundamentally different approach and mind-set.” I have covered the first two strategies, focusing on how people use information and emphasizing information as the method for unlocking value from IT. Here are the other three:
3. Equip IT project teams with cognitive and behavioral scientists
IT professionals tend to “focus less on the ‘I’ and more on the ‘T” in IT.” While this might work well enough for creating solutions to support retail transactions, it doesn’t work as well when the “goal is to support the discovery of knowledge.”
Many companies attempt to address this problem by “expose IT professionals to complex business issues” and hire more data scientists. But this is not enough. Only by adding experts “versed in the cognitive and behavioral sciences, who understand how people perceive problems, use information, and analyze data in developing solutions, ideas, and knowledge” will you be armed for success.
Your big data project will just go to waste if you ignore these behavioral challenges, as people tend to “search for or interpret information in a way that confirms preconceptions.”
4. Focus on learning
Big data and analytics projects should have a focus on learning. Oftentimes, an employee will have a hunch about something and your company should promote a culture encouraging them to follow up their instinct. The author has four pointers for moving in the right direction:
- Promote and facilitate a culture of information sharing
Learning in organizations often takes place in teams. So it is crucial to ” foster a colloborative culture in which transparency, trust, and sharing” motivates employees to share their best ideas and knowledge. - Expose your assumptions, biases and blind spots
“Be willing to re-frame the what, why and how of your accepted business practices.” Test assumptions and push limits as a matter of course. - Strive to demonstrate cause and effect
If a particular business problem occurs on a regular business problem, use data to explore why that might be and what could be changed going forward. - Identify the appropriate techniques and tools
It is easy to use technology and associated tools as a crutch. But it is people, not tools who “do the actual thinking and learning.” So managers should expect to “get their hands dirty during the iterative process of generating business insight.”
5. Worry more about solving business problems than deploying technology
IT project management is focused on “neutralizing threats to the successful delivery of a new system.” Projects focused on creating value from information should not rush to deploy technology. When they do, they threaten the ability to actually solve business problems because in their haste, IT staff makes the wrong assumptions and selects technology that doesn’t necessarily meet the need.
The author describes how one company had to delay deployment of tablets for use by sales people on the floor in their stores because assessing how different information layouts and presentation styles improved communication with customers took longer than expected. While delayed the tablets was a concern, “the goal of improving how sales managers and staff use information ” was the primary goal and success factor.
All of these strategies together will culminate in an environment where “people can use the company’s data and their own knowledge to improve the firm’s operational and strategic performance.” What company wouldn’t like to say that about their own behaviors?