Currently the International Conference on E-Business Engineering (
ICEBE) is taking place in Hong Kong. I am presenting a
paper dealing with agile business process management, a joint work with Josef Schiefer.
The core consideration is, that business strategies that were successful in the 80s and 90s are not necessarily successful in todays fast changing and connected economy. We seem to be moving from traditional over dynamic/virtual enterprises to a general structure of agile enterprises. Haeckl an all suggest a move from "Make-and-sell" towards a "Sense-and-Respond" strategy.
Speaking of agility: what does agility mean: it is generally spoken the capacity of a system to react to unforseen changes in the systems environemnt. We all know, that the software industry faced and still faces issues, as meanwhile requirements often change even during the engineering process, so that it is often not clearly known in the beginning which product is needed in the end. The consequence is clear: software developers have to "embrace change", meaning that they have to develop their software in a way, that change requests during the process can be handled.
Business process management will, this is our theory, follow the same route in the next years. Top-down plannes processes will not support changes in the business infrastructure and will be a legacy. Future business IT will have to cope with ever changing processes. Adaptiveness will take precedence over short-time efficiency considerations and plan-driven operations. In other words, the faster competitor will win, not the one who is (in thery) more efficient.
This apparently also poses significant challenges on software engineers who have to deal with such infrastructures in the future.
In our paper we go into more depth and introduce the architecture and implementation of sense-and-respond systems that allow agile reaction on real-world events. To sum it up:
- We need real-time business information with minimal latency
- Automatic discovery of situations and exceptions and generation of appropriate reactions
- Generating more accurate forecasts in near-realtime using "live" and historic data
- Integration of internal and external data sources
- Not only "backend infrastructure": Focus on tool support for various target groups and problem domains
For more information, check out our
paper and also download the
presentation to get the figures.