Analytics

Which to trust: the algorithm or intuition?

The McAfee piece to which he is referring is a Harvard Business Review piece entitled: Big Data’s Biggest Challenge? Convincing People NOT to Trust Their Judgment.

Patel’s post and the ensuing debate has brought my background in accounting into fresh focus while allowing me the opportunity to dig into some fascinating academic research.

I’ve been data driven without appreciating it in a fully conscious fashion pretty much all my professional life. Training as an accountant does that to you. I learned early on that numbers hold magic but few people get that. Math geeks do, some stat geeks do. Most others find the topic too hard. Instead and to this day, most view the accountant in a pejorative sense as ‘the bean counter.’

Maybe that’s true from a pure, regulatory standpoint but then most of the people I know who form the new generation of accountants (and those who are re-inventing themselves) see those required tasks as merely a stepping stone to a future that engages clients/co-workers/partners/colleagues…pretty much everyone who asks a question in a way that positively shapes decision making. So what’s the fuss here and why should you care?

The McAfee problem
I generally find McAfee’s thinking to be problematic. He was the academic who provided legitimacy to much of what we termed Enterprise 2.0 and which for years I disavowed on the basis that ‘content without context in process is meaningless.’

It was a tough position to take as most others who liked the E2.0 idea thought I was being snarky for the sake of it. I kept coming back time and again to the same question: Show me the evidence for your assertions? And while some could show random success I could see no discernible patterns to suggest that E2.0 was anything other than a marketers wet dream.

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