How is management automation developed today? “Well, there are many ways,” you might say. And you’d be absolutely right. Today it is still an art rather than a science. Companies had to invent their own methods of development, make mistakes, learn from those mistakes, and later repeat them all over again. While doing research in C2/GOMA, we saw a lot of typical mistakes as well as many good solutions. As a result of our work, we formulated 9 principles to guide the development of management automation.
While some of these principles may seem obvious, we believe all of them are critical for creating a good management automation system.
Here are our 9 principles:
1. Organization Wholeness. Any organization is an open system created with the intent to perform work in the outside world. Irrelevant to its size and industry, the organization must have different management levels and functional areas, working together to accomplish the organization’s intended purpose.
2. Continuous Management. Any activity in an organization can be considered as a continuous management process that transforms information through 4 distinct states: Observe, Orient, Decide and Act. Even the simplest work can be viewed as the management of a particular piece of equipment or one’s own body.
3. Functional Completeness. Any complete management automation system must have 5 tightly integrated functional groups: Sensing, Analysis, Management, Execution, and Communication & Collaboration.
4. Goal-Orientation. Most interactions in an organization are driven by goals. Higher-level goals are detailed, broken down into sub-goals, and propagated throughout management levels until they are executed. The outcomes are then composed together and included in the overall achievements of the organization.
5. Information Integrity. Any decision in an organization has reasons and consequences. An analysis, based on the information and outcomes of previous goals, is used to drive new decisions. The management automation system, in order to help its users make logical and correct decisions, must provide an infrastructure to keep the information whole and complete.
6. Shared Situational Awareness. Decisions in an organization must be based on actual situational information. Because of this, the management automation system must provide shared situational awareness based on validated and consolidated data. The situational information can be represented in different forms, graphically or textually, and visualized by the use of Common Operational Pictures (COP views).
7. Standard and Unambiguous Communication. Communication in a management automation system must be based on commonly understood languages and standard protocols through all aspects and levels of the organization. This will aid understanding and the seamless integration of automation processes.
8. Automated Decision Making. Any decision in an automated system will be made by Decision Support Systems (DSS). DSS can be analytical or statistical and may operate at different levels, gradually increasing from manual levels in an organization to fully automated levels.
9. Complementary Information Types. The management automation system, in addition to having formal and structured information, must also support informal and unstructured data in order to respond to unpredictable real-world situations. The structuring of information in this way will enable the management automation system to respond realistically to real-world circumstances, make informed decisions, and effectively increase the level of automation.
These 9 principles of management automation, if implemented, will greatly aid in the formation of management automation systems. In this post, I mainly wanted to present the 9 principles and give a general overview. In my next posts, I will discuss them in further detail.