It is no secret that one of the greatest changes in business focus sweeping organizations and, in particular, service organizations today is the focus on customers and the vital importance of optimizing the value of their customer relationships. Service organizations have a number of characteristics that are different from manufacturing organizations. Among the most important attributes is that service organizations are data and information intensive. More than in any other industry, the services industry needs to rely on the accuracy, time lines and validity of its information. Traditionally this has meant a reliance on data contained in operational systems and the extraction and transformation of that data, usually numeric data, to figure out the best approaches for efficiency and productivity of operations. But the traditional approach is not able to keep up with the demands of the business for timely access to information. Extraction, cleansing, transformation and finally processing of queries takes too long, longer than the business cycle permits. This change is the primary driver in the burgeoning business intelligence tools and technology market. It is also the primary factor that is justifying the cost of building data warehouses that has driven the growth in the number of data warehousing projects over the last five years.

Business intelligence (BI) tools and applications are heavily focused on numeric data. The customer-focused organization, however, has a different viewpoint, which until recently has not been considered and even now is not fully supported. The customer-focused organization must use marketing and campaign management strategies for different customer segments and ultimately different individual customers. These functions require new systems. Too many warehouses have been designed to satisfy decision support applications, but fail to contain enough granular details on the customers to satisfy the marketing needs. Too many warehouses have been built looking at what data is available in the operational systems. This is an "inside out" view of an organization that does not support its new customer-management focus. This is why so many expensive and lengthy data warehousing projects fail.

Customer management is essential to ways companies are thinking about business. Organizations need to put processes in place that will be able to develop an economic model of their customers. Companies need to generate new ways of thinking about their business, and these new ways require new data and new information. The enterprises of the future need to be built completely around the customer, how customers behave and the economics of customer relationships. These new systems need new infrastructures in place.

Yesterday you could build a data warehouse on customer information that with the help of OLAP tools would give you good information and some knowledge. But knowledge is worthless unless it leads to action, marketing and customer support actions which, unlike operational decisions, are very complex and have tremendous variety and variability. Neither generic algorithms nor canned OLAP reports can adequately support marketing activities. Business intelligence no longer suffices. To be successful you need a process and you need new knowledge.

Today, the new generation enterprises need an infrastructure to capture and create knowledge, store it, improve and enhance it, organize it, make it consistent and usable and disseminate it to everyone in the organization that needs it. Knowledge management is not just a set of tools. It is a set of processes, technologies, attitudes and reward systems. It is an integrated approach to identifying, collecting, managing and, most importantly, sharing the enterprise information assets with its individual employees to put that knowledge to use. Knowledge management takes advantage of the information provided by business intelligence and collaborative technologies and moves the organization into the next phase needed for effective marketing and customer management services and support. Good knowledge management needs good design, good communications, good technologies, business intelligence, satisfied customers and better production and service methods.

And as far as the technology goes, the crucial issue is to recognize that knowledge does not come only in structured media, nor does it only appear in the numerical results captured in operational systems and available through OLAP and data mining tools. Business advantage to the organization is not in the data warehouse, but in seamless and organized delivery of business intelligence and knowledge. In the language of information technology, this translates to architecture.

We will be covering these architectural elements in this column. And since architecture is broad and requires many topics, from time to time I will be drawing on the knowledge of my colleagues to address a particular point. In the months to come, we will touch on every aspect of the new enterprise and its infrastructure. These new processes require support in every phase from assessing customer segments, planning for customer-oriented actions and execution, monitoring and correcting those processes. In short, these new processes require constant learning and planning new activities.

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