Beijing, 2008. Around the globe, people breathlessly follow the achievements of the best athletes at the Olympic games in China. Who doesn’t remember Michael Phelps winning an astonishing number of eight golden medals in the Beijing athletic center, or Frank Hoy’s massive legs that brought him three golden medal at the cycling track, or the three world records run by Usain ‘The Lightning’ Bolt? In the Netherlands the race of Maarten van der Weijden, who survived cancer and won the 10 kilometer open water race, has become part of our collective memory.
Not only athletes compete against each other at the Olympics. Also countries are trying hard to win as many medals as possible. Traditionally, this is a contest between the United States and Russia (or its predecessors). However, in Beijing the Chinese successfully beat both old giants. The traditional medal table is organized lexicographically by the number of golden medals, then by the number of silver medals, and then by the bronze medals. Especially at the top of the ranking, this boils down to the question who wins most golden medals. In Beijing, China won no less than 51 golden medals, against 36 for the United States and 23 for Russia. Together, these three giants won over one third of the 302 Olympic events. Using the measure, the Netherlands finished in eleventh place with seven golden medals.
This way of measuring countries’ Olympic success is not free of controversy, since it large disregards silver and bronze medals. A popular alternative is the concept of so-called medal points. Under this method, a golden medal earns a country three points, a silver medal two points and bronze one point. For Beijing, this didn’t change the top rankings, but for example the Netherlands finishes only in fourteenth place of the medal points ranking. And Cuba, which won ‘only’ two gold medals, but an impressive 22 silver and bronze medals would rocket up from rank 28 to the twelfth place.
So was China the best performer at the Olympics? The medal table certainly suggests this, but we may ask ourselves if it is really fair to compare the medals won by China or the United States and, for instance, Benin or New Zealand. Such a comparison can only be made fair if important factors such as the economic status, population etc. of a country are also put into the equation. Another aspect is the number of athletes that are actually participating at the Olympics. After all, you can’t win a competition if you don’t compete…
The problem with incorporating additional factors is that the picture is quickly blurred by the increased number of dimensions. Luckily, mathematics can help here. And more specifically: Data Envelopment Analysis (DEA). DEA is a fractional programming method used to evaluate and compare the performance of a set of similar companies, institutes, species, or in this case countries. DEA then indicates a set of best performers, i.e. the most efficient countries from the set. Subsequently, it measures the relative efficiencies of the remaining countries based on how they compare to these efficient countries.
We used DEA to reevaluate the performance of countries at the Beijing Olympic Games. If we add the number of participating athletes, population and Gross Domestic Product (GDP, for economic status) to the analysis to predict the number of golden medals, the three best performing are not China, the United States and Russia, but rather Ethiopia, Jamaica and Panama! These countries all won gold medals but did so with far less people and with a far smaller economy than their larger counterparts. For example, Panama only had five athletes at the Games, but still succeeded to win a golden medal (Irving Saladino at the long jump). That is a score of 20%, as compared to a score of 3.8% by China. Ethiopia reached the same impressive result: with 21 athletes they won four golden medals. And when looking at GDP, Jamaica won exactly 100 times more golden medals per billion of GDP than the United States. Of course, Usain Bolt played a great part in this achievement.
Now what does this have to do with logistics? At first sight, nothing much of course. But also in logistics, such questions can be asked as: Which are the best performing depots in my network?, Which subcontractor is best when both service quality and cost is taken into account?, What are the most fuel efficient truck drivers when customer density and congestion are taken into account? Too often attention of logistics managers is focused on only a single or a few performance indicators, such as costs per pallet, fuel consumption per kilometer, IT costs per site, etc. These are the logistics ‘golden medals’. They are all important and interesting indicators, but they cannot explain the complete picture of logistics efficiency. At Argusi we take all the different indicators into our calculations. We can answer the questions such as the above and also the potential savings are calculated on the assumption that every depot or company etc. can achieve the efficiency level of a better performing peer. In such a way, ‘learning combinations’ can be installed between efficient and less efficient peers so that the one can learn from the other. By doing so the overall performance of a company’s supply chain can be made transparent and directions for improvement can be found systematically.