August 5, 2016
In the last issue I introduced the concept of key reporting metrics (KPMs) and laid out certain concepts that will aid you in developing a system of KPMs that will help you keep your finger on the pulse of your business. We have already discussed the necessity of keeping your various profit-center and cost-center buckets pure, the need for understanding the difference between fixed and variable costs, and the need for understanding the total amount of fixed costs that you need to cover each day to make money.
However, sometimes nomenclature gets in the way of what we are trying to accomplish. Everyone has some kind of a “cost estimation” system in their operations. The notion that we need to know how much something costs us to produce in order to determine a fair selling price is deeply ingrained in our business brains. But do potential customers really care what it costs you to make a particular product? Or are they interested in simply getting a good market-based price from a consistent and reliable supplier? If the latter is true—and I think we can all agree that it generally is—then your estimated and allocated costs are less important than the incremental profit that each order can contribute to your efforts to cover all of your fixed costs. This kind of thinking leads us to two conclusions:
- We need to be able to accurately predict the incremental profit that can be derived from each order.
- We need to know how many machine hours—and other finite resources—each order will consume, since our machinery resources are finite.
Variable Profit Prediction Systems
If you agree with this thinking, then the first thing you need to do is rename your cost-estimating system. Let’s call it your variable profit prediction system (VPPS). If you’ve gotten your cost buckets cleaned up and have reorganized your costs as discussed in the last issue of BoxScore, then it should be pretty easy. But as I have found in my travels, old habits tend to die hard, and most people fear change. If you want to become a variable profit predictor, you need to stop worrying about the allocation of costs that will be there whether or not you accept an order. If you think a customer is going to pay more for your products simply because you have more expensive machinery, think again. Presumably you bought the expensive machinery because you think it will give you a competitive advantage. Hopefully it sets up faster, runs faster, prints better, etc. So, why bother allocating the costs associated with owning, crewing, and maintaining your equipment to each order that runs over it? In a world of cost estimation, these types of allocations are essential. In a world of variable profit prediction, they are irrelevant!
The notion that we need to know how much something costs us to produce in order to determine a fair selling price is deeply ingrained in our business brains. But do potential customers really care what it costs you to make a particular product? Or are they interested in simply getting a good market-based price from a consistent and reliable supplier?
If you want to be a variable profit predictor, then you need to “dumb down” your estimating system and stop worrying so much about full cost calculations. Simply make sure that the variable costs used in the VPPS are the same costs that you actually incur—at least within a percentage point or two—and focus on the predicted variable profit (contribution) for each order. Once you take a lot of the labor and “variable” factory overhead that your cost-estimating system charges to each order and remove the rest of the fixed cost burden, you will have a pure estimate of the expected contribution of each order. By adding up the sum of all of this and comparing it to your daily fixed costs (your number), you will instantly know if you are profitable. But is this enough to enable you to make fundamentally good decisions? Is every order that has positive contribution and a decent contribution percentage a good order? I think we all know that the answer to this question is a resounding no.
Measuring Resources
We still need to evaluate how accepting an order will affect our finite resources, such as machine hours, warehouse space, delivery efficiencies, and others. Therefore, we need to devote some of our efforts to measuring the use of these resources and finding ways to relate them to the contribution dollars that they help us produce. The bulk of the capital investment that almost every converter has is in equipment, and equipment can run only a certain number of hours each day, week, and month. Most well-run converters do pay a fair amount of attention to their equipment. Lots of you measure setup times and run speeds, and devote a lot of time to analyzing downtime and waste. Some of you make overall equipment effectiveness (OEE) or other efficiency calculations, and even incentivize your labor force based upon the results of these calculations. But very few of you account for each minute of machine time and charge them to orders.
Imagine you are a two-shift operation. If you have zero downtime at a machine center—which is impossible—you have 16 hours a day that you can run each piece of equipment. If an order comes through that has $10,000 of contribution and a contribution of 50 percent, it’s probably a pretty good order. However, if it takes up 40 hours of machine time, then it will take you three full days to produce it—and nothing else—from that machine center. At the end of the day, the contribution dollars per hour will be $250 ($10,000/40). If this is a busy and important machine center for you, then this is probably not a good order to accept. If this is a machine center that sits idle most of the time, then this is probably an excellent order to accept. However, without relating the order to the machine time it will require, it is impossible for anyone to make an intelligent business decision.
Important Resources
If machine hours are your most important resource, then you need to start treating them that way. I am certain that all of you have controls in place that preclude anyone from withdrawing cash from the company without proper authorization. A purchase order needs to be cut. An invoice needs to be received and matched up with receiving documents and departmental supervisor approvals. Then a check must be cut, approved, signed, and issued. An arduous process, but with very good reason—we need to protect our very finite cash resources. We need to start treating machine hours the same way. They need to be part of our books and records each month, and they need to be reconciled and closed out every day as though they were cash resources.
Machine center 101 ran 32 jobs today, totaling 13.5 machine hours. There was downtime of 2.5 hours relating to x, y, and z. The 13.5 hours must be charged to the 32 jobs (both run and setup), and the 2.5 hours of downtime must be kept in a ledger and sorted by major downtime reason (maintenance, waiting for plates and dies, no orders to run, etc.). A database must be constructed for each order showing the sales price, the major categories of variable cost, the contribution and the machine hours (or other key resource time) utilized. This database can be keyed in or exported to a simple Excel file, set up in a database application that lies outside of your core system, custom-programmed into your existing system, or done in some combination of the three, but it must be maintained every day, week, and month that you operate.
Becoming a variable profit predictor—rather than being a cost estimator—and being able to instantly relate the variable profits to the resource hours utilized will enable you to come up with all kinds of KPMs to accurately measure the activity and profitability of your business. So, let’s change your mindset away from complicated cost allocations and focus your efforts on treating your machine hours like you treat your cash. You will begin making infinitely better business decisions.
In the next issue we will talk about taking steps to unbundle your sales to help you build profit centers within your VPPS and utilizing the information within your financial reporting systems.
Mitch Klingher is a partner at Klingher Nadler LLP. He can be reached at 201-731-3025 or mitch@klinghernadler.com .
