Someone pointed me to this Harvard Business Review article by Donald Marchand and Joe Peppard, “Why IT Fumbles Analytics,” which begins as follows:
In their quest to extract insights from the massive amounts of data now available from internal and external sources, many companies are spending heavily on IT tools and hiring data scientists. Yet most are struggling to achieve a worthwhile return. That’s because they treat their big data and analytics projects the same way they treat all IT projects, not realizing that the two are completely different animals.
Interesting! I was expecting something pretty generic, but this seems to be leading in an unusual direction. Marchand and Peppard continue:
The conventional approach to an IT project, such as the installation of an ERP or a CRM system, focuses on building and deploying the technology on time, to plan, and within budget. . . . Despite the horror stories we’ve all heard, this approach works fine if the goal is to improve business processes and if companies manage the resulting organizational change effectively.
But we have seen time and again that even when such projects improve efficiency, lower costs, and increase productivity, executives are still dissatisfied. The reason: Once the system goes live, no one pays any attention to figuring out how to use the information it generates to make better decisions or gain deeper—and perhaps unanticipated—insights into key aspects of the business. . . .
Our research, which has involved studying more than 50 international organizations in a variety of industries, has identified an alternative approach to big data and analytics projects . . . rather than viewing information as a resource that resides in databases—which works well for designing and implementing conventional IT systems—it sees information as something that people themselves make valuable.
OK, I don’t know anything about their research, but I like some of their themes:
It’s crucial to understand how people create and use information. This means that project teams need members well versed in the cognitive and behavioral sciences, not just in engineering, computer science, and math.
I’m a bit miffed that they didn’t mention statistics at all here (“math”? Really??), but I’m with them in their larger point that communication is central to any serious data project. We have to move away from the idea that we do the hard stuff and then communication is just public relations. No! Communication should be “baked in” to the project, as Bob C. would say.
One more thing
One thing that Marchand and Peppard didn’t mention, but is closely related to their themes, is that people make big claims about the effect of analytics, but ironically these claims are just made up, they’re not themselves data-based. We saw this a couple years ago with a claim that “one or two patients died per week in a certain smallish town because of the lack of information flow between the hospital’s emergency room and the nearby mental health clinic.” Upon a careful look, these numbers (saving 75 people a year in a “smallish town”!) fell apart, and the person who promoted this claim has never shown up to defend it.
Hype can occur in any field, but I get particularly annoyed when someone hypes the benefits of data technology without reference to any data (or even, in this case, the name of the “smallish town”). Business books (you know, the ones you see at the airport) seem to be just full of this sort of story.