Minotaur works with a variety of process manufacturers, and part of that work involves managing the information around production. In our experience, manufacturers need information on production to be as accurate as possible in order to fine tune the production process.
Analyzing this information using certain metrics can be a great way to understand what’s happening in production. Two great metrics for keeping track of the efficiency of production is to use cost and yield variance. These two metrics can be calculated as part of a process to analyze the efficiency of production.
Planned Cost vs. Actual Cost
The first variance metric that can be used to analyze production is to determine the variance in the cost of the good that you made. Typically when you go to plan for a production run, you’ll have an idea of the cost of the goods that are going to be used during the production. This would be the cost of the raw materials being used in the production run, also known as your planned cost. In addition to these costs, you would want to allocate a certain amount of labour to the run for anticipated labour costs.
After the production run has finished, you would then be able to determine the cost of the raw materials used, which would be considered your actual cost. In addition, you would know how much labour was required and be able to use that for your calculation. The calculation for planned vs. actual cost is:
(Planned Cost of Materials + Planned Cost of Labour) / (Actual Cost of Materials + Actual Cost of Labour)
Ideally, the answer would be one and you would output exactly what you expected. In the real world, chances are something will happen in production that will affect this calculation. It could be a production worker spilled some materials while pouring it in and that you actually had to use more, or perhaps the line went down and additional labour resources went to bringing it back online. If the number is below one then that’s a good result because you ended up using fewer resources than expected, and assuming output was the same, you were able to run more efficiently than normal. If the answer is above one then it’s bad for the opposite reason.
Planned Yield vs. Actual Yield
The second production variance metric we’ll discuss is calculating the planned yield vs. the actual yield. This point ties partially back into the costing metric, as we had to assume in the last example that output planned and actual output were the same. In reality, just like with costs, there will be variance and you will end up with good runs and bad runs and your yield will be affected accordingly. This is a good metric to use for comparing shifts because it focuses on output. Perhaps your night shift is actually less productive; that might make a significant difference depending on the size of your company.
The planned yield is essentially how much of a good you expect to make when production is finished. To make it easy, let’s assume that your customer ordered one hundred finished goods units. You schedule a production run to make those finished products and you expect one hundred finished goods from production.
The actual yield is calculated after by determining whether or not you actually made what you planned. Experienced production managers would know right from the example that if the customer orders one hundred units; you would likely need to plan to produce one hundred and five units, just to be safe. Some boxes might get crushed, someone might drop something, or perhaps your raw materials couldn’t stretch as far as planned because you couldn’t get the material fully out of the container. The formula for comparing the two is:
(Planned Finished Good Units Made) / (Actual Finished Good Units Made)
Ideally, just like the first one, we would want our answer to be one or more, which would indicate we got a positive result from production. If the production manager wanted to make one hundred but ended up with an extra five, that’s a bonus and this number will be higher than one. If something went wrong however, which will happen sooner or later, the number would be below one, indicating a poor yield.
The concept of perfect production can sometimes be one that production people will idolize, a world where there are no inefficiencies. In reality, everyone accepts that there’s always a certain element of human error and randomness that plays into life, production included. The issue is that many production software packages are assuming that you are planning for a perfect production run. If you planned to make one hundred, wouldn’t it be bad if you only made ninety five?
Not necessarily. It’s important for these metrics to work, that you are using the real world planned values, rather than perfect world values, because making ninety five units may in reality be the best, most efficient production run you’ve ever done, and that should be reflected in your metrics. Different people solve the perfection problem in different ways.
Minotaur uses a method where at the time you enter a Bill of Materials, you can specify the perfect world yield (ie. I’m going to make one hundred units) and the real world quantity (ie. with those materials, I’ll be happy to get ninety five units). We recommend production is planned using the real world quantity and that it’s also used to calculate these metrics. That way, every time your metric is more than one, you know that you really did have a better than normal production. Inversely, every time your metric is less than one, you know that it’s indicative of a real issue that needs to be addressed.
In basic terms, Minotaur recommends using production cost and yield variances to analyze how effective a production run was. By comparing how much you thought production would realistically cost with how much it actually cost, you can determine whether you’re being efficient in your resource allocation and use. By comparing how much you thought you’d realistically get out of production with how much you actually got out, you can determine whether you’re production process is working. These two metrics can really help you find out whether the problems are with production, what shifts are making it happen and what shifts aren’t, and find opportunities to improve your production process.
Are you having trouble keep track of and analyzing all this information on your own in spreadsheet software or on paper? Do you see the world of production analysis the way our experts do? Let’s talk. Call us today 1-800-668-1284.