Deep Customer Value: Taking Optimization from the Lab to the Real World
Business Intelligence, Optimization and Predictive Modeling may evolve to a level of high sophistication within an organization but often fail to impact the bottom line because their valuable products and services are misused, watered down or simply neglected by the core processes driving daily business.
An organization will thrive when optimization methods are placed at the center of the business model, or rather when the business model is built around this analytical method. But more often, the business model existed long before optimization efforts were ever undertaken. When optimization is implanted late in the company lifecycle, certain obstacles have been erected that change agents in BI will find difficult to overcome.
Marketing or other demand side managers may rely on time-tested intuitions and resist interference from an analytical department. Efforts to measure the success of individual decisions and business rules may be obstructed by the constant buzz of unrestrained marketing activity, and there may be a dispute over who has the authority to formulate the official assessment of these measurements. Mission-critical processes often run on the oldest part of the technical infrastructure that are most difficult to connect to state-of-the-art, real-time, individualized, automatic decisioning. They have been designed to manage business rules formulated in terms of product portfolios, but not on the level of economically relevant abstractions such as customer value, affinity or legal compliance.
There exist several more issues similar to these, which threaten to confine analytical power to the lab and undermine its impact in the real world.
In this talk, we will present ways to mitigate or overcome these issues, as developed in our recent book “Deep Customer Value”.