The final metrics I’ll address in this series are for productivity. This is a slippery slope. Frankly, I can count on one hand the plants I’ve seen with an effective measure over the last 10 years. Most are not robust enough to represent reality, if they exist at all.
I also find there is often “discounting” going on for things not directly in control of the shop floor that affect product costs. The most notable, of course, is raw materials, which can have a huge impact on the cost of goods produced. These costs must be effectively managed by the sourcing/purchasing function, which is typically overseen by the senior operations or supply chain executive.
Bottom line: I recommend three distinct productivity measurements for the operations function: shop-floor productivity, plant productivity and total operations productivity. Let’s take them one at a time.
Shop Floor Productivity Metric = OEE (Utilization x First Pass Yield x Efficiency)
OR, use the following option if you don’t yet have robust OEE reporting:
Actual Cost of Production Dollars current year compared to Actual Prior Year Cost of Production Dollars — adjusted for the new year’s volume and product mix
Our readers may remember references to OEE in previous articles. If the plant organization, top to bottom, understands the budgeted OEE that must be met on constrained work centers (as well as other critical support work centers), that’s a pretty good way for operators and first line supervision to do their part on delivering productivity.
OEE exposes yield issues on raw materials, quality cost issues and labor cost issues; and these metrics are very easily monitored visually so that reactions to unfavorability occur in real time. For example, kanbans or FIFO lanes that start drifting off the plan, i.e., are starving for material or are building inventory cause supervisor/operator intervention on the spot. So I like OEE as the shop-floor productivity measurement. The value stream managers/production managers own this one. Here’s a recent experience I had that makes the point well about how plant leaders should be thinking and responding — and it isn’t like this particular plant manager.
I counseled a young plant manager a couple of years ago who was so full of himself that he thought he was the best plant manager in the company. I know because that’s what he told me. He couldn’t understand why the corporate HR trainer had invited me in to spend some time with him. He thought he was running the best plant in what is a multi billion dollar enterprise. I suggested that his expectations of himself and his team were far too low. Of course he was offended and disagreed. I then attended his staff meeting later that morning, and his plant controller put up a graph that showed significant shortfalls in plant performance to budget for the first two months of the year. March was already more than half over and would result in the same unfavorable outcome.
No analysis of causes or any attempt at corrective action had been done. I did a quick calculation and asked the staff team if they knew how much extra productivity they must deliver each of the last nine months of the year, from April through December, to make the budget plan for the year. Of course they did not. The plant manager quickly spoke up and said that he didn’t believe in extrapolating two or three months of performance into a 12-month projection. My response: Then show me the projects and corrective action that will give us all confidence that you and your team will close the gap by year end. There were none.
OEE is often used as a measure of plant productivity, though I usually find issues with the reporting when I dig into it on my plant visits. Most plants should use the alternative shop-floor productivity measure until robust OEE accounting is in place. Further, and highly problematic, is that other functional areas typically don’t understand the mechanics of the OEE calculations and can’t tie them directly to products and mix, which is a more common language for them. Also, leaders around the entire business often think that productivity is the responsibility of manufacturing, and they become cheerleaders instead of doing their part in their own functions. These leaders also tend to think more in terms of the overall plant and business financials. The alternative method of reporting I suggested dollarizes the results and have a direct link to the financials. OEE is the shop-floor piece of the plant productivity measure. The costs of products are either going up or down when compared quarter-over-quarter, year-over-year.
But so are the “fixed/period costs.”1
Let’s Talk Fixed Costs
The fixed cost piece has the plant manager’s oversight and each functional leader is accountable for making their numbers accordingly. All staff managers are accountable for their respective pieces. And the plant manager, of course, is accountable for the sum total of the OEE and fixed costs within the plant organization.
The plant manager must expect that his/her team will remove any obstacles that cause delivery of the promised performance to be negatively affected. And, of course, that expectation is universal for anyone in a leadership position. This leads us to our second measure, the plant productivity metric, which is designed to capture the total variable cost spend and the fixed cost spend compared to prior year spending.
Plant Productivity Metric = OEE results dollarized +/- Actual Period Costs spent vs. Prior Year Actual Spend
This simple measurement collects all of the plant spending except for capital spending, which is excluded. Capital is appropriated project by project and has to meet certain pay back criteria. The productivity that results from capital spending is calendarized into the budget calendar and captured according to the actual reporting compared to how it was included in the budget process.
The final measurement I propose is the Total Operations Productivity Metric:
Shop Floor Productivity +/- Year-Over-Year Changes in Fixed/Period Costs +/- Raw Materials Cost Changes (adjusted for the new year’s product mix)
These three measurements clearly assign productivity metrics for which very specific groups are accountable. It’s not surprising that if you hold plant managers accountable for unfavorable purchase prices, they’ll protest and become discouraged since they have little if any influence on them. Holding the sourcing team accountable for purchase prices is where it belongs and eliminates the frustration of factory people. Thus purchase price changes + or – are reported in the Total Operations productivity number. The VP of operations is accountable for all of this.
For those of you who may be struggling to create a viable productivity metric, I hope you’ve found some help here to put reality-based productivity plans together that you can track all year long to a successful outcome at three levels of operations accountability. Finally always remember this: If the productivity you report can’t be found on the income statement and/or balance sheet, then it didn’t happen. From a financial standpoint that’s the final word.
Forget Sales Dollars
Some of you may be wondering by now why there is no measurement here that compares plant performance to any kind of a sales number as many of the measurements I’ve seen in the field measure manufacturing output vs. some form of sales dollars. Here’s why.
The biggest mistake I see in manufacturing organizations is the tracking of manufacturing production costs as a percentage of sales dollars. It doesn’t matter whether the scorecard is on net sales or gross sales. It’s just the wrong way to think about it. There are three compelling reasons why this is true.
- First, the amount of sales dollars in a specific period has no relevance to the shop floor’s cost performance. Even if your plant is delivering on a very short lead time, the accounts payable cycle alone usually puts the recording of a sales dollar into a different month or quarter from when the goods were produced. Sales dollars simply have no connection to the actual time of when the product was manufactured.
- The second reason is that several non-manufacturing causes affect the calculation. Marketing may be running a promotion and selling at discounted prices. Does a lower sales number have anything to do with today’s cost of manufacturing? What if the mix of product sales is significantly different than what was being produced in the factory? (See previous article re: poor S&OP planning.) This could result in windfall productivity or unfavorability. Neither has anything to do with the period’s production costs.
- The third reason for a 35-year manufacturing guy like me is just short of criminal. Too often companies still measure cost by the long outdated formula of “standard cost + margin = price.” So the factory team busts their tails delivering year-over-year cost reductions, which should flow directly to the bottom line (Isn’t that the goal?). The effect: Cost reductions get passed straight through to the customer. Pretty discouraging for factory folks and a very negative outcome for the business. I’ve seen this occur time after time.
The only formula I know of that really works is to expect sales and marketing people to be close enough to the market that they know what the market price is that is being supplied by their best competitors. Sales and marketing people are the final implementers of manufacturing productivity by using the formula “market price – cost = margin.” If the prior year margin on a product was 30%, and manufacturing is coming off a 5% productivity year, the new calculations yield a margin of 35% using the market price – cost = margin formula. It’s a simplistic example, but you get the point. When the cost + margin = price formula is used, sales/marketing/accounting take the new 5% lower manufacturing cost and add a 30% margin and the entire amount of productivity gets passed straight through to the customer.
In the above example, if margins had dropped from 30% down to 25% the productivity gain would result in simply getting margins back to the desired 30%. In either case, Total Operations Productivity would be calculated the same way.
“There are so many people who can figure costs, and so few who can measure values.” –