Marketing engineering is currently defined as "a systematic approach to harness data and knowledge to drive effective marketing decision making and implementation through a technology-enabled and model-supported decision process".
That approach has its limitations though: experience is unique to every individual, there is no objective way of choosing between the best judgments of multiple individuals in such a situation and furthermore judgment can be influenced by the person's position in the firm's hierarchy.
Leeflang and Wittink (2000)[5] have identified five eras of model building in marketing: How to build market models and how to develop a structured approach to marketing questions has been an issue of active discussion between researchers, L. Lilien and A. Rangaswamy (2001)[6] have observed that while having data gives a competitive advantage, having too much data without the models and systems for working with it may turn out to be as bad as not having the data.
One the driving factors toward the development of marketing engineering are the use of high-powered personal computers connected to LANs and WANs, the exponential growth in the volume of data, the reengineering of marketing functions.
The effectiveness of the implementation of marketing engineering and MMSSs in the firm depend on the decision situation characteristics(demand), the nature of the MMSS (supply), match between supply and demand, design characteristics of the MMSS, characteristics of implementation process.