Thomas Bergmans and Dirk Schlemper, INFORM GmbH, Germany, examine the use of metrics-driven logistics in the cement industry for optimising the distribution network.
In the modern world of cement production, there is no shortage of numbers; the problem is having the right numbers. Key performance indicators (KPIs), combined with the latest business intelligence (BI) tools, provide granular visibility as never seen before. How can these insights be used to drive logistics performance and decision-making?
“Most people use statistics like a drunkard uses a lamppost; more for support than illumination.” When Mark Twain wrote this quote more than one hundred years ago, the second industrial revolution saw electricity replace steam as the main source of power. Today, data drives industries around the world and is replacing uncertainty. With the latest digital technologies one can measure almost anything, but just because they can measure something, does not mean they should. The challenge is to count the things that really sales, financial, and operational departments. The use of KPIs in cement logistics and supply chain management is often neglected, even though these departments are mission critical in maximising efficiencies, customer satisfaction, and profit margins. Depending on one’s region, logistics costs equate to 15 – 25% of a cement producer’s sales revenue. What is interesting is, if you ask senior managers in the cement industry, it is likely that they will struggle to come up with the percentage for their company. Even if they know the figure, some will find it difficult to define the metrics behind it. KPIs help to identify negative trends in performance, and subsequently costs, and allow companies to take corrective action at an early stage.
What is right, what is wrong?
Numerous logistics KPIs have been developed over the years, and many of them have proven to be successful. In some cases, multiple KPIs are available to measure a specific activity. Each KPI views the same topic from a slightly different angle that makes it difficult to select the right one. For example, if a cement producer wants to analyse the productivity of a cement truck, there are several ways of measuring this: tonnes per day per truck, logistics unit costs, or revenue per truck per day.
The productivity KPIs of the truck shown in Figure 1 are all based on the same scenario and timeframe. Depending on which KPI one uses, different conclusions may be reached as to whether the performance of this particular truck is good, acceptable, or bad. Further, even if that number reaches an all-time high, the question remains: how much value does it contribute to the success of the company?
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