- Self Assessment
How your organization makes decisions drives the rest of the business environment - processes, events, data and the org-chart. A decision-centric view of Business Architecture is an essential organizing principle to deal with the data-driven, knowledge-based economy of the times.
There is no generally accepted definition or common understanding of business architecture because it is essentially a set of 'views', 'perspectives' or 'lenses' that consider how a business operates. Some views are common, like a process-based view - and others not as much, like an event-based view. The choice of business architecture views to be created and managed is generally dependent on current business priorities or concerns. And this practical approach to business architecture is certainly appropriate and prudent.
Most architectures have evolved over time but reflect the original problem and solutions that triggered the establishment of that architecture. If we look closely, each architecture has at least one strong component that serves as the organizing principle for other components of the architecture. Legacy Business Architectures are generally process centric or data centric, since those were the important things to manage in ages gone by. These are now 'managed' reasonably well, thank you.
Culturally, most enterprises are evolving from a process driven, industrial assembly line structure to a more knowledge driven, networked and collaborative structure. Decision making is much more distributed, and therefore much more sophisticated in the knowledge economy. Our systems are making more and more decisions for us. Even the manufacturing facilities are driven by specialized software that makes decisions for all aspects of the manufacturing, control and management processes.
Decisions are taken in the context of an enterprise and there are multiple points of view to consider. Organization structure and culture dictates the formality with which various parts of the enterprise consider decision management. Programs and projects influence how enterprise decision management evolves - incrementally or structurally. Business Architecture aligns enterprise processes, events and data with decisions. And finally Business Strategy relies on exploiting the knowledge economy and big data using decision management for digitization, transformation, scale-up, scale-out and other exotic strategies.
The modern Business Architecture is therefore necessarily based on decisions as a lynch pin.
Despite the clear case for decisions being the core driver for Business Architecture, organizations are just now starting to formally discover and describe the decisions that make and break them. The transition to a decision-centric modern Business Architecture requires that enterprise decisions be formally captured, described and managed 1.
Fortunately, the industry has now adopted the Decision Model and Notation (DMN) Standard to establish the vocabulary and language of decision modeling. Describing decisions formally gives them life and an existence, outside of people's heads. And then we are a hop and skip away from installing decisions into the modern Business Architecture.
Decisions are first class objects in a business architecture, with interdependent relationships with other components. The main components of interest include Processes, Data, Events, Metrics, Org-Charts and Knowledge. The relationship of these components to decisions is as important as the decisions themselves.
Almost all enterprise processes are executed as a response to a decision having been made. The processing logic describes how the decision needs to be made, and the conclusion of that decision drives the activity. A process definition is not complete without describing the goals and the decision making logic on how to achieve them.
The data required to be created, stored and managed for enterprise operations depends on how the data will be consumed in making decisions - whether the decision is embedded in an automated process, or is made manually by subject matter experts with aid of reports or dashboards. Data management would be inefficient or ineffective without describing the decisions that are going to consume that data.
Most events affecting an enterprise require an appropriate response, even if the response is no-response. And generally there are multiple responses possible requiring a decision to be made about the 'best' warranted response. It is important that this decision be described formally using all available information, knowledge and probabilities.
A robust set of metrics are essential for Enterprise Performance Management (EPM). These need to be Specific-Measurable-Achievable-Relevant-Timely, or SMART in order to be a true barometer of enterprise performance. Generally, a good performance is a result of making a smart decision every time an action is undertaken - and therefore the best way to improve metrics is to describe and manage all decisions that can affect those metrics.
Enterprises make countless operational, tactical and strategic decisions every day. These decisions are made by people and systems in various functions, departments, locations and hierarchical levels. All variations of responsibility, accountability and reward structures in organizations are essentially formed around the values and risk-impact of these enterprise decisions. An effective organization structure generally maps to enterprise decision hierarchy and network.
Enterprise knowledge is generally codified in the form of policies and rules - and increasingly now, in terms of analytics and algorithms. In order to exploit existing knowledge and to identify knowledge gaps, it is important to describe the purpose of this knowledge. Decisions require knowledge, and describing enterprise decisions formally enables knowledge management for enterprises.
Legacy business architectures predominantly based on processes or data can be dragged into the modern, knowledge based economy by considering Decisions First.
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