Da’s logisch (That’s logical )

Last Tuesday the Dutch national soccer team played against Hungary. As with any match of the national team, it was on television, encapsulated in a programme in which various self pronounced soccer experts discussed and analysed the match and accomplishments of the team. It is fun to listen to the soccer gibberish used by these experts in their comments on the actions of the coach and team performance. They are always able to tell what went wrong and what would have been a better option (as could any other inhabitant of the Netherlands). A famous expert in soccer gibberish is soccer legend Johan Cruijff. He is famous for quotes like “Every disadvantage has its advantage”, “If they have the ball, you can’t win” or “That’s logical". So, being a coach is tough, especially when it concerns the nation soccer team, because the complete nation is watching you. Since much of the decisions in soccer are made through intuition and common sense it might be a good idea to put some numbers to beliefs/convictions and introduce some rigour in the decision making.

The decisions a coach needs to make are complex. Think of scouting for a new team member to fill in an open position and improve the overall quality of the team. Or deciding on the overall composition of the team selection; which players, how many for each position, etc. A decision a coach needs to make often is the line-up for the next match. A simple calculation shows that there are 308.403.583.488.000 possible combinations for the line-up for a soccer game, given 26 players in the team selection. How will a coach be ever able to identify the best possible line up?

Given that a player performance will differ depending on his assignment to a certain position in the field (a goalie is not much good in a forward position), a certain attractiveness score good be given to such an assignment. Identifying the best possible line-up can than be seen as finding the assignment of players to field positions that maximises the total score. Because every position in the field must be filled in and a player can have at most one position in the field the so called maximum-weight bipartite matching problem comes forward. Introducing a source (supply side 11) and sink (demand side 11) and giving the arcs from the source and towards the sink a maximum capacity of 1, this bipartite matching problem can be solved as a transportation problem. It could be easily implemented as an App on the coach’s iPad. The tricky part in this approach is the scoring of the assignment of players to positions. This is where sports analytics come in.

By keeping track of the player performance during matches, the effectiveness of the player can be measured. This score could than be used in the optimisation of the next match line-up. By measuring the number of intercepts, the number of safes, the number of passes, etc all kinds of statistics can be calculated. Using these statistics an overall efficiency score can be calculated, see for example the Match index of SoccerLab. Not only after the match, but in real time as well. The score gives an indication of the players’ ability and effectiveness of the assignment to a position in the field. Companies like ORTEC TSS provide the kind of statistics to calculate this kind of efficiency scores. So instead of listening to the soccer gibberish of the experts, the facts can be used and the actual performance evaluated. The coach could use the statistics together with the line-up model, during the match, to decide on which player the exchange (a much discussed subject in the Netherlands; Bosvelt for Robben EC 2004) and decide on the line up for the next match. With an analytical approach and structural analysis of player performance, deciding on the line-up becomes more fact based leading to more sustainable team results. It doesn’t however offer a guarantee on winning championships, but that’s logical.

Fuel for thought

With the struggle for a more democratic regime in Libya and other North African countries and the debate on nuclear power given the trouble in Japan, oil prices have risen in the last couple of months to the highest values since august 2008. To illustrate; a barrel of North Sea Brent has gone up from about $80 per barrel in March 2010 to about $110 per barrel today. That’s an increase of nearly 40% in just one year. How does this rapidly increasing oil price effect supply chains and their operations? Should companies just endure this increase in transportation costs, or are there alternatives?

Since the mid-1990’s the focus of many companies has been to lower operations cost, focussing on off-shoring and consolidation of production capacity. As a result many of them set up large plants in countries like China and India because of the low cost of labour and low cost of transporting the finished goods to Europe and the US. Also just-in-time inventory and continuous replenishment strategies emerged, especially in retail (causing inner-city areas to get congested). This was all possible due to low oil prices and therefore low transportation cost. With oil prices rising, things become different. A straightforward analysis of changes in Brent oil price versus changes in diesel price shows that a 10% increase in crude oil price will result in an increase in diesel price of 8.7%. The increase of the past year therefore resulted in 36% diesel price increase, or a € 0.12/km cost increase (assuming 3 km to 1 litre fuel consumption, current diesel price €1.329/litre). Although labour cost is still the highest cost component in transportation, the relative part of cost of fuel has risen drastically.

This increase in transportation cost is significant enough to rethink supply chain strategies especially for makers of products with low profit margins and long product life cycles. Think of consumer packaged goods and chemicals. Higher transportation costs will reduce their profits significantly. So what can they do? Without changing supply chain infrastructure, transportation cost will go down when shipping larger quantities and therefore achieving more economies of scale, but inventory costs will go up. Transportation costs will also decrease when using slower modes of transport; from air to road and from road to rail. This will however increase lead time and inventory. Math modelling can make the trade-off clear and lead to the optimal choice. Using 3^rd party logistics providers will potentially reduce cost, because they have better consolidation possibilities. Last but not least better utilisation of truck capacity using efficient packaging, load and pallet building capabilities will decrease cost. A nice example is the improvement E-Logistics Control (part of Ewals group) was able to achieve. They managed to increase the truck utilisation by 10%.(Dutch) This was not easy, remember playing 3D-Tetris? Special optimisation models and software, like LoadDesigner, is required to get the best possible truck utilisation. It is not only stacking the goods as efficient as possible on the truck, you also have to think about the order in which the goods will be delivered. Otherwise you have to completely rearrange the truck at each stop. It is a combined routing, packing and stacking challenge.

As transportation costs continue to rise optimisation of the supply chain infrastructure might be interesting. Reducing the length of the final leg in the supply chain and consolidation of shipments will reduce transportation cost but will require additional and larger warehouses, which implies more stock, hence higher inventory levels and costs. Deciding on the number of locations to add, requires finding a balance between transportation costs, inventory cost, handling cost and warehouse costs. The best supply chain design can only be found with the use of a supply chain infrastructure optimisation models. Using these models different supply chain designs can be modelled, evaluated and optimised, taking into account not only the costs involved but the impact on lead times and inventory levels as well. So oil price increases are fuel for thought. Supply chain managers have all kinds of options to deal with oil price induced cost increases. Operations Research can assist them, whether a complete supply chain redesign is considered or just better using the available assets.