Predictive business – fresh initiative or old wine in a new bottle

Abstract

Purpose The purpose of this paper is to present a conceptual analysis of the theoretical and managerial bases and objectives of predictive business. Predictive business refers to operational decision‐making and the development of business processes on the basis of business event analysis. It supports the early recognition of business opportunities and threats, better customer intimacy and agile reaction to changes in business environment. An underlying rationale for predictive business is the attainment of competitive advantage through better management of information and knowledge. Design/methodology/approach The approach to this article is conceptual and theoretical. The literature‐based discussion and analysis combines the perspectives of business performance management, business intelligence, and knowledge management to provide a new model of thinking and operation. Findings For a company predictive business is simultaneously a practical challenge and an epistemic one. It is a practical challenge because predictive business presupposes a change in the company's modes of operation. It is also an epistemic challenge, since it concerns the company's ability to find appropriate balance between knowledge exploitation and knowledge exploration. Research limitations/implications Further research should be carried out on the functionality of practical applications as well as the attitudinal and technical preparedness of companies to adopt a new mode of operation. As a subject of investigation, the world of business events offer interesting methodological possibilities, since the basis of the work is the gathering and analysis of large quantities of information on operational activities. Originality/value There has been little research concerning business events in knowledge management context. This article presents a theoretically founded basis for predictive business, combining the concept of analysing business events with previous research in the field of knowledge management.

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