Forecast competitor service strategy with service taxonomy and CI data

Purpose - The paper aims to develop a service taxonomy model and a mathematical process to forecast a competitor's service business strategy in a multiple service business context by inputting Cl data such as the profits of existing core services. Design/methodology/approach - A qualitative method of literature review is adopted to build a service taxonomy model and form two propositions. Based on the multiple business process integration concept of the resource-based view, a mathematical process constituted by service modules and weights is developed. Salient components of the competitor's service business are identified to forecast the competitor's service business strategy after utilizing optimization heuristics of 80/20 and large number rules. Findings - The model is able not only to forecast a competitor's service business strategy, but can also help develop the firm's own new service strategy. The resources of the firm can then be realigned to counteract the competitor's strategy. Research limitations/implications - The developed model is mainly applicable to service businesses. The collection and use of Cl data must consider ethical issues, which might limit the sources of data. Practical implications - To forecast a competitor's strategy correctly, good quality Cl practice is necessary. Experienced people in the Cl department are critical to the production of good quality forecasts. Originality/value - The contribution to Cl impact studies is that the mathematical forecasting process is developed based on qualitative service taxonomical research. Key elements of the service process are identified as salient elements, which serve as the main focusing points in forecasting competitors' strategy.