Decision management

Last updated

Decision management, also known as enterprise decision management (EDM) or business decision management (BDM) entails all aspects of designing, building and managing the automated decision-making systems that an organization uses to manage its interactions with customers, employees and suppliers. Computerization has changed the way organizations are approaching their decision-making because it requires that they automate more decisions, to handle response times and unattended operation required by computerization, and because it has enabled "information-based decisions" – decisions based on analysis of historical behavioral data, prior decisions, and their outcomes.

Contents

Overview

Decision management was described in 2005 as an "emerging important discipline, due to an increasing need to automate high-volume decisions across the enterprise and to impart precision, consistency, and agility in the decision-making process". [1] Decision management is implemented "via the use of rule-based systems and analytic models for enabling high-volume, automated decision making". [1]

Organizations seek to improve the value created through each decision by deploying software solutions (generally developed using BRMS and predictive analytics technology) that better manage the tradeoffs between precision or accuracy, consistency, agility, speed or decision latency, and cost of decision-making within organizations. The concept of decision yield, for instance, focuses on all five key attributes of decision-making: more targeted decisions (precision); in the same way, over and over again (consistency); while being able to adapt "on-the-fly" (business agility) while reducing cost and improving speed, is an overall metric for how well an organization is making a particular decision. [2]

Organizations are adopting decision management technology and approaches because they need a higher return from previous infrastructure investments, are dealing with increasing business decision complexity, face competitive pressure for more sophisticated decisions and because increasingly short windows of competitive advantage means that the speed of business is outpacing speed of information technology to react.

Other terms used include "intelligent process automation" (where decision management is combined with business process management). [3]

Approach

There are a number of different approaches used to apply decision management principles. In general, these follow three steps:

  1. Decision identification and decision modeling using either open standards such as Decision Model and Notation or proprietary approaches such as The Decision Model [4]
  2. Development of a system or service (often called a Decision Service) that automates all or part of the decision
  3. Ongoing monitoring and management of the decision to keep the business rules and predictive analytics or machine learning models used up to date

Decision management often involves the use of A/B testing and experimentation as well.

See also

Related Research Articles

<span class="mw-page-title-main">Data warehouse</span> Centralized storage of knowledge

In computing, a data warehouse, also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is considered a core component of business intelligence. Data warehouses are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating reports. This is beneficial for companies as it enables them to interrogate and draw insights from their data and make decisions.

Business intelligence (BI) consists of strategies and technologies used by enterprises for the data analysis and management of business information. Common functions of BI technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics.

A management information system (MIS) is an information system used for decision-making, and for the coordination, control, analysis, and visualization of information in an organization. The study of the management information systems involves people, processes and technology in an organizational context. In other words it serves, as the functions of controlling, planning, decision making in the management level setting.

A business process, business method or business function is a collection of related, structured activities or tasks performed by people or equipment in which a specific sequence produces a service or product for a particular customer or customers. Business processes occur at all organizational levels and may or may not be visible to the customers. A business process may often be visualized (modeled) as a flowchart of a sequence of activities with interleaving decision points or as a process matrix of a sequence of activities with relevance rules based on data in the process. The benefits of using business processes include improved customer satisfaction and improved agility for reacting to rapid market change. Process-oriented organizations break down the barriers of structural departments and try to avoid functional silos.

<span class="mw-page-title-main">Decision support system</span> Information systems supporting business or organizational decision-making activities

A decision support system (DSS) is an information system that supports business or organizational decision-making activities. DSSs serve the management, operations and planning levels of an organization and help people make decisions about problems that may be rapidly changing and not easily specified in advance—i.e., unstructured and semi-structured decision problems. Decision support systems can be either fully computerized or human-powered, or a combination of both.

Business process automation (BPA), also known as business automation, similar but separate from business process management (BPM), is the technology-enabled automation of business processes.

Business rules are abstractions of the policies and practices of a business organization. In computer software development, the business rules approach is a development methodology where rules are in a form that is used by, but does not have to be embedded in, business process management systems.

A BRMS or business rule management system is a software system used to define, deploy, execute, monitor and maintain the variety and complexity of decision logic that is used by operational systems within an organization or enterprise. This logic, also referred to as business rules, includes policies, requirements, and conditional statements that are used to determine the tactical actions that take place in applications and systems.

Strategic planning software is a category of software that covers a wide range of strategic topics, methodologies, modeling and reporting.

Operational intelligence (OI) is a category of real-time dynamic, business analytics that delivers visibility and insight into data, streaming events and business operations. OI solutions run queries against streaming data feeds and event data to deliver analytic results as operational instructions. OI provides organizations the ability to make decisions and immediately act on these analytic insights, through manual or automated actions.

Business analytics (BA) refers to the skills, technologies, and practices for iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. In contrast, business intelligence traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning. In other words, business intelligence focusses on description, while business analytics focusses on prediction and prescription.

Business agility refers to rapid, continuous, and systematic evolutionary adaptation and entrepreneurial innovation directed at gaining and maintaining competitive advantage. Business agility can be sustained by maintaining and adapting the goods and services offered to meet with customer demands, adjusting to the marketplace changes in a business environment, and taking advantage of available human resources.

<span class="mw-page-title-main">Decision intelligence</span> Subfield of machine learning

Decision intelligence is an engineering discipline that augments data science with theory from social science, decision theory, and managerial science. Its application provides a framework for best practices in organizational decision-making and processes for applying Artificial Intelligence technologies as machine learning, natural language processing, reasoning and semantics at scale. The basic idea is that decisions are based on our understanding of how actions lead to outcomes. Decision intelligence is a discipline for analyzing this chain of cause and effect, and decision modeling is a visual language for representing these chains.

Business process management (BPM) is the discipline in which people use various methods to discover, model, analyze, measure, improve, optimize, and automate business processes. Any combination of methods used to manage a company's business processes is BPM. Processes can be structured and repeatable or unstructured and variable. Though not required, enabling technologies are often used with BPM.

Agile Business Intelligence (BI) refers to the use of Agile software development for BI projects to reduce the time it takes to show value to the organization in comparison to other approaches. It helps in quickly adapting to changing business needs. Agile BI enables the BI team, business people or in general stakeholders to make better business decisions, and to start doing this more quickly.

Business-oriented architecture is an enterprise architecture approach for designing and implementing strategically aligned business models.

In business analysis, the Decision Model and Notation (DMN) is a standard published by the Object Management Group. It is a standard approach for describing and modeling repeatable decisions within organizations to ensure that decision models are interchangeable across organizations.

BPM Everywhere (BPME) represents a strategy for coping, and possibly exploiting, the disruption that is anticipated as a result of structural changes due to technical progression known as the Internet of Things (IoT). IoT will substantially increase the number of devices connected together and will increase the complexity of those connections.

An intelligence engine is a type of enterprise information management that combines business rule management, predictive, and prescriptive analytics to form a unified information access platform that provides real-time intelligence through search technologies, dashboards and/or existing business infrastructure. Intelligence Engines are process and/or business problem specific, resulting in industry and/or function-specific marketing trademarks associated with them. They can be differentiated from enterprise resource planning (ERP) software in that intelligence engines include organization-level business rules and proactive decision management functionality.

<span class="mw-page-title-main">ModelOps</span>

ModelOps, as defined by Gartner, "is focused primarily on the governance and lifecycle management of a wide range of operationalized artificial intelligence (AI) and decision models, including machine learning, knowledge graphs, rules, optimization, linguistic and agent-based models". "ModelOps lies at the heart of any enterprise AI strategy". It orchestrates the model lifecycles of all models in production across the entire enterprise, from putting a model into production, then evaluating and updating the resulting application according to a set of governance rules, including both technical and business KPI's. It grants business domain experts the capability to evaluate AI models in production, independent of data scientists.

References

  1. 1 2 "Enterprise Decision Management - Cutter Consortium".
  2. http://custom.hbsp.com/b01/en/implicit/product.jhtml?login=FAIR060805&password=FAIR060805&pid=F0506F%5B%5D
  3. Fisher, Layna, ed. (2013). iBPMS – Intelligent BPM Systems. USA: Future Strategies Inc. ISBN   0984976469.
  4. Von Halle, Barbara; Goldberg, Larry (2010), The Decision Model. A framework for business logic and business-driven SOA, CRC Press, ISBN   9781420082814