A study on time series pattern extraction and processing for competitive intelligence support

In the era of rapid growth and high competition, a company must possess an information/knowledge advantage in order to hold the upper hand in the indu stry. Therefore, the company has to continuously monitor its competitors in order to get enough information and convert the information into competiti ve knowledge. Although information technology has been used in many areas a nd has many successful examples, it is rarely the case that information tec hnology was used for the task of competitor intelligence. Accordingly, this study devises a method of time series pattern extraction and processing fo r the task of obtaining place-prospect competitor intelligence in order to advance an enterprise with a competitive knowledge advantage. The purposes of the method are two-fold: (1) For a product manufactured by the company, the gathered data are mined into a knowledge advantage-an appropriate amoun t of the stock to be allocated at a timely fashion at a retailer in face of competition. (2)This knowledge advantage alerts the company's decision mak ers to what is unknown and forces them to make good decisions on the stock allocation problem, freeing them from the dilemma of over-stock or under-st ock with respect to competitors' stock. Our approach differs from tradition al inventory management in the grounds they are based: traditional inventor y management is based on the perspective of cash flow while our approach is based on the perspective of competition encountered. The results show our method is quite promising to this end, obtaining the intelligence to gain c ompetitive advantage. (C) 2001 Elsevier Science Ltd. All fights reserved.