Complex Technology to Streamline Decision-making

The most important trend that will continue in the future is that applications will get more and more complex in functionality, from a business and a technology perspective. What this means is that the business analysis and customization configuration activities will take up more time than low-level programming (construction). This trend makes sense because businesses are different from one another in their pursuit of a competitive advantage. Moreover, they require flexibility in the software solutions implemented for them, and at the same time would not like to see the lag that exists between thought and action.

Applications will move toward application construction by using business widgets (like billing widget, order entry widget, etc.). These widgets will be able to collaborate to form systems using flexible interchange protocols. We already see the first generation of this collaboration in XML-, SOAP-, and UDDI-based solutions. This will allow for a very rapid development of applications, already quite evident in decision support, where you started with canned reports with custom programs to database-centered decision-support systems. In these systems a report can be created in days or a week. Today BI reporting systems take only minutes to produce a complex and effective report - the near-future business view is increasingly one of self-reliance for managers to run their own reports.

Another trend that will appear is the introduction of new paradigms of computing technologies into mainstream business. Technologies such as recursive, neural network programming and genetic programming that exist in video games and simulation today will probably mature in five to seven years. There is tremendous momentum in ease of use and reach, also. Intelligent devices, kiosks, smart cards, etc., will make access to this technology ubiquitous and easy.

Cutting-edge and futuristic companies have started using some of these technologies. In one of the applications I have heard about, genetic programming is being used to predict stock prices. These types of systems do not necessarily require someone to write the program logic for the entire system, but instead are using "self-learning" technologies that grow based on inputs provided and the program's ability to arrive at the output.

As you can see, the cutting edge of empowerment technologies is quite a bit ahead of the mainstream, and the envelope of technologies and solutions available is expanding at a rapid pace.