Enterprise Decision Management (EDM)

What is Enterprise Decision Management (EDM)?

Enterprise Decision Management (EDM) is an enterprise approach that applies analytical and rule-based systems to manage and deploy all operational decisions. EDM manages and improves the decisions that create value in the business by making explicit decisions, using business rules to define them so they can be changed easily for maximum agility, and integrating them with business intelligence and data mining to put your data to work. By applying EDM and focusing on the decisions that create value, business analysts can create smarter systems that more directly tie to business objectives.

EDM uses the capabilities of analytics, artificial intelligence (AI), automation, decision science, business intelligence (BI), and visualization to build robust decision frameworks for any business process. It can automate high-volume processes of making decisions while effectively managing the decision flow across the system. With proper implementation, an organization can gain many business benefits from EDM such as enhanced efficiency in routine operational decision processes and reduced cycle times with automation. Qsutra's Enterprise Decision Management solution helps organizations understand customer perspectives as well as business trends so they can make better decisions in order to initiate better plans for their organization's success.

EDM emerged from the need to facilitate high-volume enterprise decisions. Enterprises apply EDM processes to business and technology infrastructures for the following reasons:

• To generate a higher return on older investments
• To increase business decision complexity
• To mitigate competitive stress resulting from increasingly complicated decisions
• To capitalize on the limited competitive benefit opportunity (IT struggles to keep pace with business development)

Understanding Enterprise Decision Management (EDM)

EDM is a planned, methodical approach to automating decisions. It is not about automating decisions as a side-effect of some other activity such as automating a process or implementing an ERP system but a deliberate focus on decisions. The key to doing this, in the words of Bill Fair, one of Fair Isaac's founders, is to "grab the decision by the throat and not let go". You must treat decisions, in other words, as separate entities that can be addressed distinctly. It is not enough, however, to automate a decision, you must improve it also. Simply automating bad decisions, like automating bad processes, results in a little gain in anything except speed. You want to identify how you would like to take a decision and then automate that improvement. Improving a decision means not only working on every aspect of it to see where you can improve it but also establishing processes and mechanisms for monitoring and constantly improving that decision over time. It is often this improvement over time that offers the greatest value in EDM.

EDM is focused on operational business decisions - those taken in large volume, every day. They can be clearly differentiated from "strategic" decisions such as where to open a new store or when to drop a product line that is rarely the same twice and that simply does not happen that often. Clearly, these are important, but you are not likely to automate them or try and make them in "real-time". These "blue collar" operational decisions are, though not always, part of interactions with customers or prospective customers. These decisions have the highest volume and greatest time pressure of any in your business. You can probably think of many examples including approve/decline, next-best offer to make a customer, authorization of a sale, fraud detection in a claim, account application processing, and so on. Typically you must make these decisions in real-time or near-real time. Indeed, you may find that these decisions must be automated to deliver the required throughput and timeliness. There is a gray area between strategic and operational decisions. These "tactical" decisions determine the way in which you will manage processes and customers such as decisions about which segments of a customer base will receive which precise offer. You might support these decisions with EDM systems but you are unlikely to completely automate them. Operational decisions can also be considered as those that require the shortest "decision latency", a concept developed by Richard Hackathorn. Decision Latency is the time it takes to receive an alert, review the analysis, decide what action is required, if any, based on knowledge of the business, and take action. Operational decisions require very low decision latency.

How Does Enterprise Decision Management Work?

Enterprise Decision Management (EDM) systems exploit methods and technologies to improve the efficacy and efficiency of decision-making throughout the organization. This is in contrast to traditional systems which have almost exclusively been concerned with process automation and improved efficiency through labor displacement. The technologies employed in EDM include predictive analytics, business rule management, optimization, business intelligence, and in fact any technology which reduces the uncertainty involved in decision-making and increases decision-making efficiency.

EDM uses the computer as an uncertainty reduction machine, employing statistics, machine learning, data mining, optimization, and business rules engines to fine-tune decisions and massively increase the speed at which they are made. In fact, the current surge of interest in business intelligence (BI) tools and techniques is a testament to the urgent need to have technology help in the decision-making process, although BI is labor-intensive and prone to misinterpretation. As always the leaders in the use of EDM can be found in financial services with decision systems employed in loan approval, the detection of fraud, customer targeting, and so on. The ‘digitization’ of business processes, an era that has persisted for fifty years, is now being complemented by the ‘digitization’ of decisions, and this new use of information technology will dwarf what has gone before it.

Any technology capable of reducing decision uncertainty, and reducing decision latency qualifies as an EDM enabler. Predictive analytics technologies scour historical data, looking for patterns that might be reliable enough to employ in future activities. Typical applications include reduction of customer churn, better sales targeting, and other applications such as prediction of machine failure, or even the likelihood of hospital readmission. Technology startups are providing SaaS types of services where business users, with little technical skill, can upload data and create their own predictive models. There are dangers associated with a ‘black box’ approach of this type, but it does at least indicate the way things will go. Larger organizations can afford to employ a team of data scientists and analysts to create bespoke predictive models and methods.

Optimization is another technology usually bundled in with EDM. This is primarily concerned with determining how resources should be deployed once the question of what will happen in the future is determined (the province of predictive analytics and statistics). Given a set of resources and constraints, optimization will work to maximize a given objective – usually profit and/or revenue. It answers the question ‘how’, given we know ‘what’.

Finally, the use of business rules engines complements both predictive analytics and optimization by saying what is, and is not permissible. A predictive model may suggest selling a given item at a certain price for example. However, if the product has already been offered at a lower price to a subset of customers, it simply cannot be used in their cases. And optimization may suggest working practices that are unpopular or even illegal.

EDM is a sea-change in the way businesses use information technology and the benefits that might be derived from it. Its effective use will distinguish the winners from the losers in a way we haven’t seen before. Needless to say, this all requires awareness at the very top of the organization, and there are profound organizational and cultural implications. We will after all be increasingly handing over the decision-making process to machines – so we really do need to know what we are doing. Greater reward always implies greater risk, and EDM is no different. The risk mitigator is skill and knowledge – in a world of change, some things never change.

Enterprise Decision Management Systems

Organizations need EDM to:

• have a robust decision support system,
• assess critical current conditions and
• minimize the risk.

Enterprise Decision Management is a holistic approach to enhancing decision support systems. Organizations can take advantage of Decision Science to make Smarter & Timely Decisions for all aspects of their Operational Business Processes. With proper implementation, organizations can gain a lot of business benefits from Enterprise Decision Management. EDM can be applied in all departments of an organization whether it’s Manufacturing, Finance, Marketing, R&D, Logistics, Production, Sales, etc. Implement our Decision Frameworks to enhance your existing Decision Support System and make Smarter Business Decisions. Decision Frameworks can be customizable, scalable, and easily adaptable to a workforce environment and operational infrastructure.

Enterprise Decision Management Systems can transform the way businesses make decisions. They enable businesses to use the information they already have to make better decisions—decisions that are based on predictive analytics rather than on past history. Decision management systems automate the process of making decisions, particularly day-to-day operational decisions. They improve the speed, efficiency, and accuracy of routine business processes, in part by reducing the need for human intervention. By automating decisions, organizations in every industry can improve interactions with customers, partners, suppliers, and employees. In addition, organizations that are highly regulated, such as financial services, health care, and insurance, can more easily achieve compliance as a result of repeatable, traceable decisions.

Benefits of Enterprise Decision Management

Combing enterprise decision management with other requirements techniques have a number of advantages. Use cases have always had decision points in them. Applying EDM externalizes the definition of the business decisions behind these decision points. This keeps the use cases simple and clean while allowing the specifics of the decision to be defined and managed. A strong, rules-based definition of these decisions means that the final system can replace embedded decision points with true Decision Services – components that make decisions. Simpler, more concise use cases are the result.

Making these decisions stand out from other kinds of requirements helps in other ways too. It enables requirements for performance, compliance, and audit to be mapped specifically to the decisions involved rather than being applied loosely to the whole system. Separately managed decisions can be mapped to Key Performance Indicators and other business objectives so that the analyst can specify exactly how improvements to or problems with that decision will impact the business.

See Also

Decision Engineering