Stuff Happens in the Real World

I traveled with a colleague earlier this week.  We flew to Charlotte from two different locations.  Our flights were scheduled to land around the same time.  Fortunately, our flights landed when they were supposed to, despite bad weather in the north.  We decided to rent one car.  Unfortunately, we had a Seinfeld moment at the rental car counter.  (https://www.youtube.com/watch?v=4T2GmGSNvaM Worth 2 minutes, even if you’ve seen it hundreds of times.)  We had to wait about a half-hour for a car to arrive.

As we waited, I thought about how challenging it is to have products in the right place at the right time.  The rental car company had a reasonable estimate of its demand; most people make reservations.  But storms throughout the country altered their supply.  For example, I’m sure customers kept cars longer after flights were canceled.  They probably returned cars to different locations as well.  No amount of big data analysis could have predicted the rental car company’s supply challenges.  Even if the company knew it was going to be out of cars, weather would have prevented it from moving cars to the locations where they were needed.

We all want to optimize our supply chains and carry as little inventory as possible.  Excess inventory costs money.  We all know that.  But what are the costs of not having a product?  Does your line shut down?  I’m sure that costs a lot more than a little inventory.

We expect technology to solve all of our problems.  Real-time data certainly helps us run our businesses better.  But “stuff” happens in the real world.  Shipments are delayed.  Machines break.  Power outages occur.  Spreadsheet analysis gives us a false sense of security.  Our “just-in-time” world often relies on every facet of our supply chain/operations running smoothly.  Take a look at that analysis.  Perhaps a better question to ask is not how to optimize every process but what are the risks if something goes wrong.

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