November 20, 2003
Decision support systems, simply known as DSS, are often narrowly defined as highly flexible and interactive IT systems that are designed to support decision-making when the problem is non-structured (Haag, 2004). This definition expresses several keywords: support and non-structured. This means that although DSS greatly enhance the business processes, they do not do the business work itself. The DSS will bring speed, information, and unmatched processing capabilities to “the table,” but the final overall decisions will have to be made by the knowledge workers involved, which will use the information provided by the DSS, along with his/her experience, intuition, and judgment. The other main keyword in the definition is non-structured. A non-structured decision is a decision that may have several “right” answers, but there is no logical path to find only one exact answer, unlike a structured decision (Haag, 2004). Decision support systems are in action in nearly every meaningful, or more appropriately, successful, business organization for not only cost savings, but also for other attributes not involving price, which include better relations with suppliers and customers.
Another aspect of technology that many organizations are now taking advantage of is the science of Artificial Intelligence (AI). Simply stated, AI is used to allow machines to imitate or duplicate, not only human thinking, but behavior as well. Whether it is to suggest products or services (expert systems), based on known information, or the recognition of patterns (neural networks), largely in the security sector of society, artificial intelligence is used on an everyday basis to achieve an organization’s goals.
As one can easily see, both of these concepts, decision support systems and artificial intelligence, are critical factors in an organization’s success in today’s highly competitive and adaptive market of society. Without doubt, Unilever, a world leader in consumer goods, is no exception to the rule. Two divisions in particular, its Foods and Home & Personal Care Divisions, have been involved in recent news in regards to the critical areas of DSS and AI. Unilever has implemented several decision support systems and artificial intelligence systems to help benefit the decision making of its respective Foods and Home & Personal Care divisions, which include a MicroStrategy business intelligence platform, a web-based distribution module, and a contract-management module. In addition, two forms of artificial intelligence are also being used, a request-for-information bidding process and a request-for-pricing process, both expert systems. Each DSS and AI serves a different, and critical role in the way the organization carries out its tasks.
The MicroStrategy business intelligence platform was selected to increase internal operational efficiency and employee productivity globally (MicroStrategy, 2003). This DSS will benefit Unilever because it will be capable of processing much more information/data, and at a faster rate, than any human possibly could. This will allow Unilever to staff less knowledge workers in this area, and will still achieve the same end goal. Again, the system will not make the decision for the organization, but will give the knowledge worker involved greater insight on making the best decision possible. In summary, the MicroStrategy platform will allow for more accurate decisions, and at a faster rate, thus, carrying out the goal it was selected for, to increase efficiency and productivity levels.
In order to maximize its resources, Unilever implemented a request-for-information bidding process (Bacheldor, 2003). This expert system allowed Unilever to cut the number of its carriers from 100 down to 30, by examining the all of its...