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Continuous Improvement Best Practices
Recognizing You Do It Well
As a continuation of last month’s article this issue looks at continuous improvement model and what are key preformane indicators or KPI.
Doing things well is just as important (and difficult) as doing the right things. Certain key questions need to be asked in this regard: Will performance that is better than your competitor expand your market base? Or it is enough to be just as good as the competition? Is there some absolute goal, like Six Sigma, that should be used as your performance standard? What about the relationship between multiple goals? Can exceptional performance in one area offset poor performance in another? Clearly, not defining the term "well" could result in lost market share if customer expectations are not met or if the product price becomes too high in the attempt to gain perfection.
Many companies turn to industry-specific best practices and KPIs [Key Performance Indicator] to figure out how "well" they need to perform. One valuable resource on supply chain metrics for planning, sourcing, manufacturing, fulfillment, and reverse logistics is the Supply-Chain Council, which has developed the Supply Chain Operations Reference (SCOR) model. Exhibit 4 shows sample KPIs adapted from the SCOR model.
Yet while such sources are helpful, they often only provide a broad approximation of how a company is doing. Different business strategies naturally lead to different performance levels on specific KPIs. In fact, the best comparisons are sometimes not to another company in the same industry but to a company with similar supply chain characteristics competing with a similar business strategy in another industry.
Most KPIs (including the SCOR model) are single-factor performance metrics—that is, a ratio of some system output quantity to some resource input quantity. For example, the output could be lines picked in a warehouse and the input could be labor hours. These metrics allow for detailed analysis of operations and can be reported in a consistent manner. However, the single-factor metrics are less suited to answering the question, "How well are we doing?"
The following example illustrates the point. If my warehouse averages 73 picks per hour and my competitor's warehouse averages 36, does that mean I am doing well and they are not? The answer is, "It depends." How much material handling equipment do I have compared to them? How big and bulky are my picks vs. theirs? It's a mistake to make comparisons based on a single-factor metric without fully understanding the respective contexts. Supply chain activities can be viewed as a system that has both inputs and outputs. The key is to devise metrics that capture those system interdependencies that provide fair performance benchmarks.
Often, qualitative best practice benchmarking proves more useful than quantitative benchmarking. In qualitative benchmarking, a company starts with a hypothesis: "We believe that we have a best-practice forecasting methodology for fashion products with long lead times." In an effort to support this hypothesis, supply chain practitioners need to do three things:
- Learn the process used by other companies with similar supply chain dynamics.
- Determine how the other companies are doing on that process. This entails identifying the metrics being used and the context in which they are being applied. When examining companies in a different industry, in-house resources can often do the research. But when companies in the same industry are part of the research, it's best to use an independent outside consultant for reasons of access and confidentiality.
- Make an informed response to the hypothesis. This step is by no means scientific; there's an element of subjectivity involved. Because the comparison companies typically have different metrics and processes, the practitioners must use their best judgment as to which lessons learned apply to their particular situation.
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