Analytical applications are becoming increasingly important to organizations trying to find a competitive advantage in a tight economy. Organizations want (and need) the benefits of analytical tools, but may not have the resources to commit to learning a specialized tool, conduct formalized training programs or hire outside experts. This situation exposes a significant dichotomy – while the market appears to be saturated, it remains largely untapped when it comes to resolving the analytically-unsupported decisions that happen throughout organizations.

This market evolution from analytical specialization to analytical ubiquity is a painful transition for both users and vendors. Within organizations, traditional power centers find themselves marginalized by the pace of adoption of analytical applications by operational business units. Simultaneously, vendors offering analytical tools struggle to make the transition from providers of best-in-class capabilities that appeal to the few, to providers of capabilities relevant to the masses.

To help organization make the most of analytical applications and make sense of the crowded market, start by reading the "Hype Cycle for Analytic Applications, 2008." This document tracks 38 categories of analytical application and shows their relative maturity and importance to different organizations. Then, continue on to "Q&A: Customer Experiences With SPSS's Analytics Applications" which tracks the experiences of two insurance companies as they move toward packaged analytical applications.

"Case Study: Caixa Galicia Understands Customer Profitability" shows a Spanish bank's experience with the adoption of a customer profitability analysis application and the pervasive impact this had on their customer relationships and organizational performance management processes. "Arvato Uses Analytics to Reduce Out-of-Stock Exposure" is a case study of the development of a vendor managed inventory system in the retail music industry. Finally, the latest "Magic Quadrant for Customer Data-Mining Applications" shows the evolution of the data mining market as it moves from workbenches to packaged applications that address the key elements of the customer relationship.