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.
If you want manufacturing analytics, the first step is to tell your ERP system how you make what you make. This is crucial. If your routings are missing steps or your bill of materials is wrong or incomplete, your ERP doesn’t know any better, so it’s going to create an inaccurate baseline you will measure against. The goal is to have a clean, accurate work order. This includes making sure the hourly costs and burden for each routing step is correct. This is usually done once for each resource in the resource maintenance record. Also, the standard cost for each material needs to be correct. Again, this is usually done once in the part maintenance record.
I know telling you to make sure your work orders are structured and costed properly is easy to write and harder to do, but it’s the foundation of all your manufacturing analytics. Knowing what you did is useless if you don’t have an idea of what you were planning to do. The bigger the delta between the two—in either direction—the more room for improvement there is.
How is that delta determined? Money is a great measuring stick; it’s an unbiased language everyone understands. When you have clean, accurate work orders, each work order will have an estimated cost. Each resource has a value based on its hourly cost and the time needed. Each raw material has a cost based on the standard cost of the material and the amount needed. Add all that up, and you have the estimated cost of that work order. This is your baseline.
To generate actual costs and compare them against the estimates, you need to issue raw materials and report labor for each step to the work order. These transactions build up your actual costs of the work order.
The concept is pretty straight forward, but I realize the execution is harder. Remember that it gets easier after you get over the learning curve.
If you go through all that work, it’s important to keep the data clean. How? The answer is so simple you’ll think I’m kidding: Use the data.
Yep, this is what a lot of companies forget about. If you go through the trouble of creating accurate work orders that define accurate costs, and put in the discipline to accurately collect actual costs, don’t just use that information to recost a part from time to time. You’re not using the data enough! It will degrade and eventually be deemed unreliable. What a shame.
Related: How to Make Manufacturing Data Matter
Related: Improve the Bottom Line
Learn how to use the data every single day with these four quick steps:
The outliers are the jobs you want to focus on; it shouldn’t be more than a few jobs. Anything more is too overwhelming. Dive deep to figure out what the problems are and then address the problems.
After a few days working with the data, figure out acceptable boundaries for an upper and lower percentage. From that point, only look at jobs that fall outside those boundaries. (Remember, this should only be a few jobs.) As issues are addressed, the boundaries will stop producing jobs to look at. Pull in the boundaries. When the new boundaries stop producing jobs to look at, pull them in again. At some point you’ll find the natural boundaries for your company.
By analyzing what you thought would happen compared to what actually happened, you focus on fixing things that produce bad data or bad outcomes. This is how the data stays clean – by using it.
If you don’t have an ERP system that supports all of this, we can help. Follow the links below to learn how.