The previous chapters have given you some background on the core components of corporate IT systems along with software technology that promotes “business intelligence” throughout an enterprise. This included a good foundation on the high end analytical portion of information systems, namely data mining technology. All this sounds fantastic, state-of-the-art software that helps increase the flow of value-added information which leads to a reduction of uncertainty in a given business environment. However, the bottom line to the productivity enhancing process from IT implementation really entails proper management and utilization of this technology. In other words, an organization can spend huge sums of dollars on the best systems available, but if they are not implemented properly, their value and dollars invested become useless. Data mining technology is no exception. In fact, because of the more complex nature of the technology (e.g., statistics and mathematic underpinnings), the potential for underutilization or improper utilization is probably greater than other types of analytical applications. The following chapter provides some helpful hints on how to manage the mining process as it illustrates some common pitfalls that exist in conducting a high-end analysis. Remember, today’s technology is good, but it doesn’t do all the work for you.