The unit of work for many information workers and managers is the decision. Call center operatives spend most of their time deciding which products and services to offer a customer, and the deals that might be attractive. Managers move from one decision to another on an ongoing basis. In fact decisions are ubiquitous at all levels of the organization.
Business processes on the other hand are concerned with the flow of information, money and materials as various linked activities are executed. Business process management (BPM) provides a framework for the analysis, design, deployment, execution and monitoring of business processes, and has done much to enhance operational efficiency over the last decade.
Yet – BPM says nothing about the mechanics of decision making, nor does it say anything about its ultimate function as a means of reducing uncertainty in business operations. Fortunately, various methods and technologies have emerged over the last decade which explicitly address the automation of decision making, opening up a significant opportunity for businesses to realize greater efficiency and efficacy. Traditional transaction oriented systems, and business process management systems (BPMS) do not address this domain. Big data, predictive analytics, business rules management, optimization and business intelligence all assist and automate the decision making process. Clearly this facility needs to be integrated into the business process if we are to realize the benefits in a manner that is manageable.
In reality we have always embedded some level of decision automation into our systems. Decision logic is embedded into program code, and may be eighty per cent or more of the coding effort. There are many problems associated with this approach. The business rules are hidden from the business user, they are difficult (and expensive) to change, prone to errors, and often inefficient. Decision automation and decision management cannot be treated as an ‘add-on’ to activities within the business process. Indeed not all decisions happen within well-defined processes in any case. And so it is important that the ‘decision’ is elevated to the same status as the ‘transaction’ or the ‘process’. In this way it can be given appropriate and relevant treatment, instead of using a paradigm that is inappropriate and largely irrelevant. What does this tell us? In practice this means we need decision management methods and tools to deal with decisions in an efficient and effective manner. More importantly, we also need supporting technologies and methods which allow us to embed the decision within business processes – in other words, be able to execute the decision – when this is relevant.
Fortunately the technology suppliers and standards bodies seem to agree with this position. While anyone involved with BPM will know of the Business Process Model and Notation (BPMN), they may not be so aware of the Decision Model and Notation (DMN) standard which has been recently ratified. Like BPMN, DMN is an executable modelling notation. With DMN, simple diagrams provide the much needed link between the business process, the decisions made in the process, the data supporting those decisions, and the models created to automate and aid decision making. These “business knowledge models” may be composed of business rules, or be the result of data mining activities which classify, cluster or predict numerical values. In any case such models are increasingly used for decisions in loan approval, upselling, fraud detection and many other activities relevant to individual businesses and industries. It is important that these models are well managed, that their effects can be measured, that they can be easily modified, and that business users and managers can directly access them instead of having to wait for technical assistance.
The automation of the decision is new territory available to organizations wishing to improve productivity and effectiveness. Unlike the automation of transactional activity, which peaked in the last decade with ERP, CRM, SCM and other systems, decision automation has profound effects on the efficacy of operational activities. Better decisions mean a more effective organization. It is crucial that decision automation is treated with appropriate methods and tools, since the decision automation wave will eventually dwarf the transaction automation wave which preceded it. Businesses embracing decision automation often see returns significantly larger than those associated with more traditional applications. Once again technology is providing the business with an opportunity to transform its operational activities. And with the appropriate methods and tools, decision automation and decision management is already proving itself to be a powerful differentiator.