Senior Fellow and Director of Decision Engineering at Intel Corporation
Karl G. Kempf is a Senior Fellow and Director of Decision Engineering at Intel Corporation. Since joining Intel in 1987 he has lead a team of decision scientists charged with building decision-support processes and tools focused on faster better decision making across the corporation. Kempf has co-edited three books and published more than 175 contributions in decision science. He has been a research adjunct at Missouri State, Arizona State, North Carolina State and Stanford Universities. He is a member of the National Academy of Engineering (NAE), a Fellow of the IEEE, and an INFORMS Fellow. His team at Intel has won the INFORMS Prize, the Wagner Prize, and twice been Edelman finalists. Prior to joining Intel he was involved in motor racing, movie special effects, and aerospace factory automation.
Track: Emerging Analytics
Tuesday, April 16, 10:30–11:20am
Intuition is Unreliable, Analytics is Incomplete
In today’s environment, there are many cases where the difference between a good decision and a poor one can be hundreds of millions if not billions of dollars. Decision makers strive to apply their intuition, but intuition is unreliable. Sometimes it is useful, other times misleading. Analytics practitioners want to apply their computational tools, but given the complexity of these cases their models are inescapably incomplete.
Nobel Laurates have explored one side of this situation from the perspective of human psychology. Simon pointed out the bounded rationality available to decision makers while Kahneman described the plethora of biases afflicting that same population. But they failed to supply answers to two important questions crucial to analytics professions. 1) How bad are the decision makers left to rely only on their intuition? Stated a different way, when we start to apply analytics, how much benefit can we reliably expect? 2) Can we benefit from utilizing the intuition? Can analytics inform intuition AND intuition inform analytics to supply a solution superior to either technique applied alone?
We briefly supply an answer to the first question based on projects at Intel Corporation over the past 30+ years. Our answer to the second question occupies the bulk of our presentation. This includes evaluation of ideas from the literature including “pre-mortems” and “nudges”, but will focus on two related approaches we have found to be especially powerful. At one extreme, we will describe support systems for decision makers in operations with examples drawn from manufacturing and supply chain. At the other extreme we address systems that support senior management in deciding product development funding to maximizing profits.