What Challenges Continue To Face Business Owners?

That question may not be entirely fair, as different challenges are faced by different types of businesses. Many types of businesses share delivery deadlines.  Customers of all types tend to want their product or service when they want it and lead time is irrelevant to them.

We can say that most people understand that building a structure from scratch will take some time. The builder’s supply problems are not something the buyer considers.  Deadline expectations are something that must be built into the customer’s education process.

In the manufacturing process we have to look at whether there is tooling, molds or die involved. A supply of raw materials must be secured. Then a facility must be found or created to make the product. Beyond that there is the distribution for both pre and post production.

How long will a product be needed? That is a common business challenge. I sure hope I don’t need to go all the way back to the buggy whip to make my point. Few people foresaw how quickly the public phone and all related parts became nearly completely irrelevant.

Today the fast paced evolution of tech products lead to a business cycle where at six months a product can be considered yesterday’s wonder gadget.  In fact, upon introduction companies have found their product line was side stepped by a competitor and left in the dust. The phrase… “All dressed up and nowhere to go.” Quickly jumps to mind.

Customers and their wants and needs have been many times called, “fickle.” Out guessing or predicting the next fast moving product or idea can lead to many sleepless nights for all sizes of businesses. 

Learning to use data to forecast you customer’s needs (and wants) is a good first step to understanding and quickly responding to the business challenges your company faces and perhaps more importantly will face in the coming months and years.

Warning Reading This Could Lead to More Sleepless Nights: Forecast accuracy in the supply chain is typically measured using the Mean Absolute Percent Error or MAPE. Statistically MAPE is defined as the average of percentage errors. Most practitioners, however, define and use the MAPE as the Mean Absolute Deviation divided by Average Sales. This is in effect a volume weighted MAPE. This is also referred to as the MAD/Mean ratio. 

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