What Artificial Intelligence Research and Toyota’s JIT Revolution Can Teach Us About Analytics

Michael Watson Ph.D Partner
Read Time: 3 minutes apprx.
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Last week, the Wall Street Journal’s Review section ran a long article from Walter Isaacson on artificial intelligence.   The overall article was very interesting, but two key points are worth mentioning.  One, the arrival of true artificial intelligence (a machine’s ability to think like a person and innovate– or even become super smart and be able to improve itself indefinitely) always seems about 20 years off.  This suggest that obtaining artificial intelligence may not ever arrive.  But, this leads to the second key point:  that the goal of machines becoming as smart (or smarter) than people may not be the right objective.  Instead, the most fruitful use of artificial intelligence may be to combine the best of what computers can do with the creativity and the best of what people can do.

Also, last week, the subject of my Operations Excellence class at Northwestern in the MEM department was on Toyota’ Just-in-Time (JIT) revolution.  By the 1980’s, the US automakers knew that Toyota was manufacturing cars much more efficiently than they were.  But, they didn’t exactly know why.  One common theory was that the Toyota plants were using many more robots and automation.  This led some US automakers to create the “light’s out” factory– a factory requiring no human intervention.

This “light’s out” factory was a big disaster and not achievable– much like the goals of artificial intelligence.

After more careful study, Toyota was not relying on technology alone, but on the concept of autonomation– or “automation with a human touch”.  Or, in other words, allowing robots and machines do what they do best and letting people do what they do best may lead to the biggest productivity gains on the factory floor.

Both of these points are a good example on how your organization should think about analytics.  Analytics will open up many new insights for you, allow you to do things you haven’t been able to do before, and create new value for you.  But, to get the most out of analytics, you cannot rely just on new algorithms and new data sets to make decisions.  You need to have people with the right analytics mind-set to best use and guide the analysis.

We are seeing that the companies getting the most out of analytics are doing just this:  they are embracing the latest analytics technology, using data in creative ways, and creating an organization trained in analytics to guide the effort.