Benchmarking: Comparing performance over time and against industry norms
A useful and productive method for implementing new processes in your feed or grain business
Many of us have a bit of a competitive streak in us — whether it is pitting ourselves against some friends in a friendly game of cards, hitting the links on the local golf course with some acquaintances, bowling at the alley on league night or cheering for our favorite NFL team in the playoffs. We like to compare and compete against others — in fact, this is the psychological basis of the free-market system: Competition will best serve the needs of society.
A useful and productive method for implementing this concept in your feed or grain business is through the process of “benchmarking.” Benchmarking is the process of collecting performance metrics including cost, cycle time, productivity, profitability or quality measures for your business, and then comparing these to your historical performance and/or industry standards or best practices. The term “benchmark” originates from the chiseled horizontal marks that surveyors made in stone structures, into which an angle-iron could be placed to form a “bench” for a leveling rod, thus ensuring that the leveling rod could be accurately repositioned in the same place in future. These marks were usually indicated with a chiseled arrow below the horizontal line. These notches, or marks, represented a given altitude and against which other heights could be calibrated or “benchmarked.”
How can benchmarking be used?
Benchmarking is best used as part of your feed and grain business’ annual or strategic plan (or both). These metrics, some of which we will discuss in further detail, allow you to make improvements or adapt best practices with the aim of increasing your firm’s performance. Benchmarking may be a one-off event, but is better treated as a continuous process where you continually seek to improve your practices — like strategic planning.
Many performance measures can be grouped into one of the following five general categories. We will give some examples and ideas for metrics that fall into each of these categories; however, you may find developing your own additional measures may also be useful:
1. Efficiency: A process characteristic indicating the degree to which the process produces the required output at minimum resource cost.
2. Quality: The degree to which a product or service meets customer requirements and expectations, and/or legal requirements.
3. Timeliness: Measures whether a unit of work was done correctly and on time. Criteria must be established to define what constitutes timeliness for a given unit of work. The criterion is usually based on your customer’s needs and requirements.
4. Productivity: The value added by the process divided by the value of the inputs used (labor and capital consumed).
5. Safety: Measures the overall health of your organization (literally) and the working environment of your employees.
(Note: These categories are paraphrased from the “Performance-Based Management Handbook, put together by the Performance-Based Management Special Interest Group, a Department of Energy funded group interested in this area. It can be found at http://www.orau.gov/pbm/pbmhandbook/Volume%202.pdf)
The primarily focus of this column is to get you to think about benchmarks and how to track them, rather than on how to improve the measures. We know that there are lots of “roadblocks” to improving business performance — if it was easy anybody could do it. Our thought (and that of many others) is this: “What gets measured, gets done.” Intuition definitely has its place in managing, but performance measures provide a meaningful yardstick for evaluating and improving our work.
Efficiency measures
Efficiency focuses on getting the largest output at the least cost. Many efficiency measures can come from your income statement (almost every cost/expense measure can be divided into your outputs — i.e. bushels of grain or tons of feed or dollars of profit — to be analyzed as benchmark measures. You will find that some of these measures are inverse calculations of a few of the productivity measures discussed in more detail below.
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