I have been to a lot of companies and worked with a lot of people over the years, and I've come to the realization that we all use the tools we know to deal with issues we face. If you ask an assassin to fix a problem, someone is going to die. If you ask a programmer to fix a problem, a new program will be created.
If you use work orders to produce goods and aren’t getting manufacturing analytics out of your ERP system, you have an important resource that’s untapped. The good news is this can be fixed. The other good news is fixing it will lead to a smoother operating production floor with a more predictable output. There is no “easy” button, but there is a proven method you can follow to mine manufacturing analytics. Companies that use this method find managing production is easier, because they have data. They know what to fix, and just as importantly, what to leave alone. Data leads to focus, which leads to better results. It’s not magic, but it does work.
It seems that “manufacturing data analytics” is the popular buzz term in every facility these days. Management concludes they must collect and analyze as much data as possible to identify trends and opportunities within the manufacturing process. Every sample of data should somehow equate to an ability to gain a competitive advantage. And yet the most common result is analysis paralysis.
It seems like managers involved in the manufacturing production process never have enough reports or data. It’s not uncommon for our consultants at Visual South to get requests that begin with, “It would be great if I could get a report that…” Truth be told, the requests usually make a lot of sense. So, we develop the report and our customers start using it.
When I talk to Visual South customers about using their ERP system to guide them to manufacturing process improvements that could be made, I always ask who is responsible for the variance in estimated vs. actual costs in a completed work order. In some cases, I get a quick answer with a name. That speaks volumes to me because it means they are proactive in looking at cost data. Companies who do this become comfortable with the accuracy of the data. This doesn’t mean they like all the data; but that’s the point. If there is an unacceptable variance, they find out what caused it. Perhaps the standard was wrong (in either direction). Perhaps the execution was flawed or exceeded expectations. The important thing is they know about it, and can do something about it.
