There is no doubt that most organizations, in particular service organizations, are undergoing major changes as a result of the focus on customers and customer relationship management. A significant implication of the customer-focused organization is that it requires a shift to process orientation since the primary product and output of a service organization is the added value that is created through its business processes. The more optimized the business processes, the more successful the organization. But, optimizing the business processes requires expertise in knowledge management and in effectively bringing people, processes and technology together. This process orientation is highlighted by the recent tendency to adopt the terminology of process-intensive organizations, such as manufacturers and distributors. The terms "information supply chain" and " value supply chain" are coming into vogue. But effective supply chains require effective infrastructures. A properly built data warehouse and the suite of business intelligence, data mining and knowledge management tools and analytical processes are the infrastructure needed to support the information supply chain. What we need is a data warehouse designed and developed with optimization of business processes in mind.
Unfortunately, most data warehouses are not developed with the goals of knowledge management in mind. Most data warehouse developers will start the project by determining the user requirements. This determination usually takes the form of asking, "What information do you need to drive your business?" This is undoubtedly a significant and mandatory step in the process of developing a data warehouse, but it is not enough. The information needed to monitor and control business performance is the first step in using and managing knowledge to obtain value for the business. In-depth knowledge of the business process and means to optimize the process is needed. Not only should the data warehouse developer seek to find the information needed to drive the business, he must focus on the knowledge required to choose how to execute the business processes once the business has received the information it needs.
A data warehouse that is not integrated with the business performance of the organization cannot deliver the return on its investment, which is usually the justification for building it in the first place. The information supply chain needs to be managed to deliver the right information to the right user at the right time, as well as deliver value by executing and taking action based on that information. Information that does not contribute to selecting appropriate business behavior cannot deliver value. Acting on information requires knowledge of the business process and the goals for business performance and the ability to manage the knowledge embedded in the business processes.
The proper actions to be taken are part of the organizations' intellectual capital and knowledge base. An effective data warehouse is part of this integrated information supply chain management. But the warehouse is usually used to support structured data and develop business intelligence. Business intelligence and knowledge management need to be delivered to the user together in order to complete the necessary closed loop in the information supply chain.
To illustrate my point, I will use the example of the retail industry, which is highly customer focused as well as an early adopter of data warehousing and data mining technologies. The most successful retail organizations, such as Wal-Mart, have figured out long ago that there is inherent value in information, and using it effectively can materially change the profitability of the business. The trick is to use information and knowledge as a product and integrate the process of acquiring knowledge into the business process.
A simplified description of the savvy retailers' business process is that they use information to monitor and control business processes and then feed that knowledge back into their operational systems. On a daily basis they monitor the behavior of their customers, look for their preferences and capture the detailed data at the point of sale. This detailed data not only updates the operational systems, but is used for analytical purposes. The analysis includes monitoring the daily performance of each store, making adjustments for seasonal realities and forecasting the next day's performance. The forecast is fed back into the operational systems to determine what products need to be shipped and which suppliers need to be electronically informed. When the products arrive at the store, additional information, perhaps from unstructured knowledge management repositories, is used to determine how and where they should be placed in the store to maximize profitability. A well-developed infrastructure (data warehouse and OLAP/mining tools), capitalizing on intellectual capital (knowledge management repositories and processes) and an integrated approach to managing the information supply chain have resulted in profit margins of three to four times their industry's average for organizations such as Wal-Mart. They clearly show that the value of knowledge can be measured in concrete monetary terms.
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