“Of course I’m data driven. I take the data and I use that as an input to my final decision-making process.” A very common statement to many managers and so called knowledge workers. Is combining data and intuition a good idea in decision making? What would be the impact of taking operational decision and/or business rules management to the next stage with "thinking machine"?
The McKinsey Quarterly article, "Artificial intelligence meets the C-suite" explores the impact that “thinking” machines may have on top-management roles with experts including the authors of "The Second Machine Age", Erik Brynjolfsson and Andrew McAfee. Enjoy the read.
With predictive analytic and the massive data, a true data-driven decision making would improve the decision making outcome. And business rules management and operational decision management are the low hanging fruits taking advantage of the advancement in AI fields.
On the other hand, having a badly developed business rules and decision models could escalate the problem in multi folds. The automated scheduling case of Starbucks mentioned in Wharton Management article - Can a Robot Be Your Boss? - is a good example or poor decision model. The (data-driven) algorithm probably only considered the demand side and not taking into account of the supply side rules. In fact it is also a case that shows the importance of operational decision management and athe potential consequence for lack of it.
Well, our knowledge workers could finally working on the creative and innovative side of works and also focusing on the human side providing motivation to staff members, rather than trying to combine intuition with data driven in decision making. "It still matters a great deal to have a good boss, and it is still one of the worst things in the workplace to have a bad one.”
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