MARKET VIEWS

Exchange of information as a tool to improve performance by Andrea Zanoni Full Professor of Business Management at the Faculty of Engineering of the University of Bologna.

In the latest years growing interest was showed in the availability of information on market data to improve the definition of supplying and production schedules. The development of technologies to elaborate and transmit information, by making the related activities easier and less expensive, has boosted the realization of evolved forms of inter-company communication. Researchers’ attention to this phenomenon can be summarized in three main periods:
1. the origin dates back to 1958 with Forrester study. With an approach based on industrial dynamics, he determined the amplification of demand variations on the inventories of the organizations at the source;
2. some experimental studies followed. These can be referred to the science of decisions, in which choices of inventory reorder and measurement are simulated to check their consequences in the production chain;
3. finally, on the basis of evidences coming from Procter and Gamble production chain, Lee and others in 1977 provided a mathematic model for the phenomenon and supported it by determining its causes.
These three contributions, although starting from different ends and assumptions, all lead to a univocal definition of the dynamics of a ‘multi-echelon’ system. This is made up of four independent organizations, which can represent a supply chain. The typical elements of this dynamics are fluctuation, amplification and bad timing. Virtually, when an unexpected increase in demand occurs, the source organizations’ response is amplified, and they get prepared to face this phenomenon with increased production. This leads to a growth in undesired stock on hand. Its reduction depresses the size of orders and once again the effects return cyclically. The decisions’ time sequence at the various stages of the production chain and the delay with which information are transmitted generates bad timing among the inventories’ peaks in the different stages.
The distortion effects which follow can be ascribed to four main causes:
1. When real demand’s visibility lacks, the actors interpret the order received as a ‘sign’ on the course of future demand. The order extent thus mirrors a distortion, which is amplified climbing back the chain, adding the real increase in demand but also the part restoring the inventory safety level, which dropped because the increased demand had been dealt with.
2. The second driver comes from the mode with which orders are generated at the various stages of the production chain. This is affected by criteria of local advantage. For example, actors pursue economy when issuing orders by unifying their needs and limiting the number of orders. Alternatively, they can follow the rhythms imposed by MRP systems. Such a behavior, however, brings an irregularity, in which peaks and lacks of orders alternate. The real demand does not know such irregularity and this leads to its distortion.
3. Third, the purchase behavior of the various actors is not based on the dynamics of the single final demand. Promotional activities prompt wholesalers and retailers to purchase earlier than the real demand, thus bringing an additional distortion effect.
4. Finally, gaming behaviors can occur. The purchaser can suspect imbalance between demand and supply and, thinking that only a part of his order can actually be filled, he will probably overestimate it. The sum of these opportunistic behaviors leads to distortions when the producer has to determine the extent of real demand.
The lengthening of production chains, which occurred in the latest years, has emphasized the importance of the phenomenon described so far. As a matter of fact, the possession of reliable and prompt information on the sales’ course and on the flows of materials from the various actors of the supply chain has become a success factor.
The adoption of tools and modes to achieve evolved exchange of information also leads to other possible consequences on the organization and management of the relationships between customers and suppliers. Such instruments could allow real time monitoring of the supplier’s performance and of the dynamics of the purchaser’s demand, thus favoring more efficient forms of contracts. Thinking of a more advanced hypothesis, then, they could ease the determination of innovative metrics to evaluate the performances of the firms in the supply chain, thus creating new modes to distribute the value created at the various stages.

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