Quarterbacks, Power Forwards, Olympians and Benchmarking

What if there was a way to determine how we are performing financially compared with companies similar to our own? What if we could compare our results with theirs on an even playing field? What if we could determine where others are outperforming us and then take steps to improve in those areas?


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Enter benchmarking, a process whereby we do compare our performance with that of similar organizations.
Benchmarking effectively takes some work. Perhaps the most challenging hurdle is finding like organizations that are willing to share their financial information. Trade associations and coating products user groups are great places to look for partners, and, although nothing could equal comparing our performance to a specific company or known group, resources such as Bizminer provide amalgamated financial reports by industry that can be helpful. Once a partner or other resource is identified, we need to have the discipline to compare our performance with that of the other organization on a regular basis, to identify gaps between our performance and theirs, and to take action to shore up our performance in those areas where we are deficient.
Perhaps the biggest hurdle of all, however, presents itself when we begin to compare data. For instance, if I ask who won the 2012 Super Bowl, who the 2012 NBA champions are or who won the individual all-around gold medal in women’s gymnastics at the 2012 Olympics, many would correctly answer the New York Giants, the Miami Heat and Gabby Douglas, respectively. If I ask the same group to name the greatest NFL quarterback ever, the best NBA power forward of all time or the greatest Olympian in all of history, there would be no clear answer.
We run into the same issue when it comes to the subjective nature of financial calculations. Cost of goods sold and its close cousin, gross profit, can mean different things to different organizations. Some put supervision above the gross profit line, and others put it below; some allocate overhead to labor and materials calculations, and some do not; and so on.
Thus, we need to level the playing field by measuring performance the same way for each company that is being benchmarked. I have previously written in this space about the five drivers behind the financial performance of any finishing operation: revenue, direct labor, direct materials, energy and maintenance expense. During my days running a custom coating operation, I knew that if I met my goals in each of these areas for an entire month I could have a great month. Three months in a row, and I had a great quarter. Four quarters in a row, a great year. If I missed my goal a little bit in one area, I struggled. If I missed in two more or areas, I was in big trouble. So I focused maniacally on making sure these items were all in control.
Since these are the same drivers for every finishing organization, we can benchmark how one operation’s performance compares with that of another by measuring and comparing performance in each of these areas, and by doing so with a consistent measurement. For instance:
Revenue: Measure revenue growth year over year by dividing this year’s performance by last year’s performance, and calculating the difference between the resulting quotient and 100 percent.
Labor: Divide labor expense by total revenue or production volume to determine labor as a percentage of revenue or output. Dividing revenue dollars by labor hours produces a dollar-per-labor-hour metric that removes the impact of variances in pay rates.
Materials: Add up all materials costs such as paint, powder, plating anodes and pretreatment chemical costs, and divide the amount by total revenue.
Energy: Determine revenue produced per therm of natural gas, per kW of electricity consumed and per gallon of water purchased to measure each of these resources relative to volume.
Finally, I love reviewing an organization’s Z-Score.  In 1968, Edward I. Altman, a then-assistant professor of finance at New York University, used a statistical method to devise a simple equation that has been determined to be in the range of 80- to 90-percent accurate in predicting the bankruptcy of an organization a full two years before the event occurs. I use the Z-Score when determining the relative financial stability of any business. If you’re interested in calculating your company’s Z-Score or using it for the purposes of benchmarking, you can find the equation online quite easily.  
Once performance in the five key drivers mentioned above have been measured using metric calculations that are consistent among all operations being benchmarked and Z-Scores have been determined, the respective scores can be plotted on a scorecard, and gaps in performance between two or more organizations can be easily identified. From there, determine what the higher performers in each category are doing right, model their best practices and enjoy the results.


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