Examples of decision support systems (DSS) aiding business decision-making
Learn how decision support systems can help the business decision-making process. Find out why decision support is needed and what IT skills business managers need for DSS.
Chapter 1: Decision support systems revisited
Because of increasing complexity, rapid change, and the escalating risks confronting managers and organizations, now is an opportune time to evaluate computerized decision support projects, especially decision support systems (DSS). In the mid-1990s, many software vendors invented new terms associated with decision support. For some vendors, DSS was too general; for others, it was associated with failed projects, unrealistic expectations, and painful memories. However, companies continued to build computerized information systems to support decision makers.
Perhaps we have learned to identify and manage our expectations. Decision support systems differ, and technology can support a wide range of decision-making tasks. There are two fundamental premises associated with computerized decision support. First, computers and information technology can help people make important decisions. Second, computerized DSS assist and support managers and keep them connected to the decision-making loop. The overriding goal is improving decision-making effectiveness and efficiency, not automating decisions.
Many organizations have integrated computerized decision support into day-to-day operating activities, like performance monitoring. Frequently, managers download and analyze sales data, create reports, and analyze and evaluate forecasting results. DSS can help managers perform tasks, such as allocating resources, comparing budget to actual results, drilling down to analyze results, projecting revenues, and evaluating scenarios. Data warehouses can create a single version of the truth for advanced analytics and reporting. More managers are using executive dashboards and scorecards from their personal workstations to track operations and support strategic decision making.
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With all of the new business intelligence and data analytics technology becoming available these days, it's the perfect time to evaluate your decision support systems (DSS) and computerized decision support projects. This excerpt is from the book Decision Support Basics, authored by Daniel J. Power and published by Business Expert Press, November 2009.
Print ISBN: 978-1-60649-082-2, E-book ISBN: 978-1-60649-083-9.
Download a free PDF of this chapter. To learn more about the book or to purchase it, visit BusinessExpertPress.com.
Decision support research has a long history, and the concepts of decision support, decision support systems, and the acronym DSS remain understandable, intuitively descriptive, and even obvious in their meaning. Related terms like analytics, business intelligence (BI), and knowledge management are ambiguous and interpreted in many different ways by vendors and consultants. Sadly, the vocabulary of decision support, including acronyms like BPM, BAM, CPM, and BI, can seem like complex techno-speak. My goal is to make some sense out of the decision support chaos and explain the current jargon.
This chapter discusses the need for decision support, the technology skills of managers, the history of decision support, and a theory of decision support. The last section identifies characteristics of modern decision support applications.
What is the need for decision support?
Today, decision making is more difficult. The need for decision-making speed has increased, overload of information is common, and there is more distortion of information. On the positive side, there is a greater emphasis on fact-based decision making. A complex decision-making environment creates a need for computerized decision support. Research and case studies provide evidence that a well-designed and appropriate computerized decision support system can encourage fact-based decisions, improve decision quality, and improve the efficiency and effectiveness of decision processes.
Most managers want more analyses and specific decision-relevant reports quickly. Certainly, we have many and increasing information needs. The goal of DSS is to create and use better information. Today, there is a pressing need to use technology to help make important decisions. Decision makers perform better with the right information at the right time. In general, computerized decision support can help transfer and organize knowledge. Effective decision support provides managers more independence to retrieve and analyze data and documents to obtain facts and results, as they need them.
From a different perspective, cognitive decision-making biases exist and create a need for decision support. Information presentation and information availability influence decision makers both positively and negatively. Reducing bias has been a secondary motivation for building DSS. Most managers accept that some people are biased decision makers but often question if a proposed DSS will reduce bias. For example, decision makers “anchor” on the initial information they receive and that influences how they interpret subsequent information. In addition, decision makers tend to place the greatest attention on more recent information and either ignore or forget historical information.
Changing decision-making environments, managerial requests, and decision-maker limitations creates a need for more and better decision support. We should consider building a computerized decision support system when (a) good information is likely to improve the quality of decisions and (b) potential DSS users recognize a need for and want to use computerized support.
Introducing more and better decision support in an organization does create changes and challenges for managers. Using a smart phone with decision support applications or a Tablet PC with wireless connectivity to the Internet and corporate databases requires new skills and new knowledge.
What technology skills do managers need?
Technology skills quickly become obsolete. Concepts and theory have a much longer “shelf life.” DSS use reasonably sophisticated information hardware and software technologies, so you need computing and software knowledge to understand such systems. In addition, you need technology skills because you may need to provide input to hardware and software choices. At a minimum in today's business environment, you need to be able to operate the software environment of your personal computing devices (e.g., a workstation, a portable computer, or a smartphone).
Your software environment is rapidly changing (i.e., new versions of Microsoft Office, new Google products, and new intra-company Web-based applications are constantly on the rise). In addition, you need to master software products relevant to your job. In some situations, you may develop small-scale budgeting or cost-estimating applications in Excel or a product like Crystal Reports. There is a growing need for “end user” development of small-scale DSS and preparation of special decision support studies.
Networks and enterprise-wide global systems are expanding. Because managers and knowledge workers are the primary users of enterprise-wide decision support systems, managers must understand the possibilities and be involved in designing the systems.
For many reasons, all managers need to understand the upside benefits and the downside risks of building a specific decision support capability. Decision support systems can solve problems and create new problems. In addition, as a manager, you need to help make informed decision support design, development, and implementation choices.
DSS, computing, and information technology (IT) knowledge and skill needs are constantly evolving. We all need to learn new concepts and new skills. Some new requirements build on previously learned materials; others force us to change dramatically and to “un” learn what we had learned.
