lying person Thinkstock

Are Your Scrap Metrics Lying About What Happens on the Shop Floor?

Manufacturing plants need metrics that tell the truth about performance so management intervention can occur when performance commitments aren’t being met.

I was recently working with a new client, conducting a review of the current state metrics for the plant and thought this was worth sharing with my readers. When we got to the charts on scrap, I was surprised to see that the plant is measuring scrap against sales revenues instead of cost of production. The reason given for this plant measure was that the corporate office requires use of that formula for reports from the field.

I don’t know what the purpose of that metric is since it does not tell the truth about plant scrap performance. It’s certainly the wrong metric for the factory.

My advice to the client was this: Have dialogue with corporate, explain the issue from a plant point of view and why it isn’t the correct metric. Suggest they rethink it. Maybe it’s been reported that way for years or decades, and no one has asked the question: “Why do we report scrap that way in the factories?” This is a great example of a paradigm that needs to be blown up. Here’s why:

Every plant needs metrics that tell the truth about performance so management intervention can occur when performance commitments aren’t being met. Safety measures are a good example of results that are reliable because there are standard formulas provided by OSHA so that every plant in the country (and often in North America) can track it the same way and react directly to the reported numbers. I know of no other metric that is so consistently reported and trustworthy in manufacturing. Scrap measurements need to be just as accurate and actionable on the shop floor.

Let me walk you through a simplistic model of how the plant scrap number varies based on the two formulas noted above. Let’s assume that sales revenues are $10 million/month, cost of goods sold is $7 million and plant scrap for the month is $1 million. Against sales revenue the scrap result would be 10%, i.e. $1,000,000 ÷ $10,000,000 = 10%.

Now let’s say the sales department put in a 3% price increase that was effective the first day of the new month and scrap remained at the same $1 million. The scrap rate for this particular month is now reported as $1 million ÷ $10.3 million = 9.7% scrap. Now let’s see what happens when the following month has a broad-based discount of 10% off the regular sales price. Now sales revenues are reported as $9.0 million vs. the same $1 million of scrap for a scrap rate of 11.1%.

This demonstrates how the scrap rate can move around even though the plant’s performance each month is exactly the same. Can you hear the kudos from the corporate office, “Way to go plant guys; good month on scrap improvement to 9.7%!” Then the next month: “What happened that your scrap jumped up to 11.1%?” The answer in both cases is absolutely nothing different happened in the plant.

I’ve also assumed so far that the cost of goods sold exactly matches the cost of goods produced, which we know never happens in real life. The cost of goods produced reflects the impact of product mix/cost differences made in the month. This also causes fluctuations to the report that are irrelevant.

The metric recommended is this: gross scrap for the month divided by the cost of goods produced (NOT sold) for the month. My aforementioned client will continue to send the obligatory report up the ladder if they won’t agree to change it, but the new report for the plant is being generated from the plant controller’s office and is being used to analyze and attack the priority issues.  Again, gross scrap ÷ cost of goods produced = scrap %.

To repeat: The most important thing about every metric used in the plant is that is tells the truth about what’s really going on in the shop. Secondly, metrics need to be actionable and level specific. For example, the tracking of scrap, OEE and schedule performance may be a report the plant manager wants to see weekly. The first line supervisor, however, needs to know hour-to-hour how his/her area is doing relative to the promised outcomes so the level of detail in the metrics must be appropriate to the structure of the organization charts. Pareto charts should also accompany the results so the responsible person can immediately know where to put the focus for recovering and making the commitments for the week and month.

 Seems pretty basic, but most of the plants I visit for the first time aren’t doing this. Maybe you’ll find improvement opportunities here for your own operations.

Larry Fast is founder and president of Pathways to Manufacturing Excellence and a veteran of 35 years in the wire and cable industry. He is the author of "The 12 Principles of Manufacturing Excellence: A Leader's Guide to Achieving and Sustaining Excellence." A second edition is planned for release in 2015. As Belden’s VP of manufacturing Fast led a transformation of Belden plants in the late '80s and early '90s that included cellularizing about 80% of the company’s equipment around common products and routing, and the use of what is now know as lean tools. Fast is retired from General Cable Corp., which he joined in 1997. As General Cable's senior vice president of operations, Fast launched a manufacturing excellence strategy in 1999. Since the launch of the strategy, there have been 34 General Cable IndustryWeek “Best Plants Finalist awards, including 12 IW Best Plants winners. Fast holds a bachelor's degree in management and administration from Indiana University and is a graduate from Earlham College’s Institute for Executive Growth. He also completed the program for management development at the Harvard University School of Business.

TAGS: Operations
Hide comments


  • Allowed HTML tags: <em> <strong> <blockquote> <br> <p>

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.