************************************************************ DSS News D. J. Power, Editor July 4, 2004 -- Vol. 5, No. 14 A Bi-Weekly Publication of DSSResources.COM ************************************************************ Check the case by Anissa Stevens "Implementing the Redland Genstar Data Mart" at DSSResources.COM ************************************************************ Featured: * Ask Dan! - What is decision automation? * What's New at DSSResources.COM * DSS News Releases ************************************************************ What is decision automation? by Dan Power Decision automation (DA) is a "hot" topic! Chapter 3 in my DSS book (Power, 2002) differentiates between decision systems, decision support systems (DSS) and special decision studies. A decision automation system is NOT a decision support system. In my book, I argue "routine decision situations should be analyzed and 'programmed' as much as is possible and they should be supported in most situations by technology. The potential rewards from improving routine, recurring decisions are usually very large (p. 39)." The concept of decision automation is deceptively simple and intriguingly complex. A narrow perspective suggests that a decision is a choice among defined alternative courses of action. Hence decision automation systems make choices among predefined alternatives. From a broader perspective, a decision involves the complete process of gathering and evaluating information about a situation, identifying a need for a decision, identifying or in other ways defining relevant alternative courses of action, choosing the "best", the "most appropriate" or the "optimum" action, and then applying the solution and choice in the situation. Hence decision automation systems help automate all or part of a specific decision process. Automation refers to using technologies including computer processing to make decisions and implement programmed decision processes. Typically decision automation is considered most appropriate for well-structured, clearly defined, routine or programmed (cf., Simon, 1960) decision situations. An automated decision process occurs without any "human" intervention. Decision making procedures are programmed and then the appropriate programs evaluate stored or "real time" data from sensors. Then using either algorithms based on quantitative models, logical or quantitative heuristics, statistical inference, or artificial intelligence technologies one or more actions are chosen to apply in the situation. The actions are taken by effectors including human or machine actors. An effector may change the value in a database, send a message or an alert, move an object or play a message. Human decision makers determine the rules, models and methods used for making choices and completing decision tasks in programmed decision situations. Conceivably decision automation programs can "learn" from successes and failures and automatically improve and update the relevant stored procedures, rules or likelihoods. Decision automation is a set of concepts, a related set of technologies, a set of methods and design tools, and an ambitious, general "goal". The range of decision tasks that can be automated has increased as technologies and design tools have improved. This technology evolution has also raised aspiration levels and created more challenging development goals. The overriding goal is to replace human decision makers in programmable decision situations where it can be demonstrated that the computer program's decision is at least as good as that of all or most human decision makers. The working assumption is that decision automation will be cost effective when compared to an equally skilled human decision maker in a programmed decision situation. The greatly expanded and evolving computing infrastructure makes it increasingly cost effective to apply decision automation in situations where that had been prohibitively costly. Decision Automation Application Areas The major improvements in computer processor speed, faster and larger capacity storage technologies, improved sensors, the ubiquity of the Internet and World-Wide Web and increased reliability of information technologies has greatly increased the number and diversity of decision automation applications and that trend is accelerating. Decision automation can assist in an air traffic control environment, in flexible manufacturing systems, in petroleum refining, in high-speed sorting systems, in tax decision automation, in intelligent monitoring and decision making in intensive care situations, in fruit grading, in real-time notification, in credit approval automation, in airborne collision avoidance systems, in building automation and facility management systems, in hardwood log breakdown, in laboratory management and automation systems, and in many other well understood decision situations. The petrochemical and refining industry association (NPRA) is sponsoring a Plant Automation and Decision Support Conference September 20-21, 2004 in San Antonio, Texas. In 2003, the NPRA Computer Conference was renamed the Plant Automation and Decision Support Conference. The automation people are also becoming more interested in decision support. AutomationWorld recently (June 2004) had a special issue titled "Decision Support: Getting a better view of your manufacturing data". Check http://www.automationworld.com/articles/Departments/744.html . On a related note, Rob Spiegel, Contributing Editor to AutomationWorld.COM, writes "Web technologies are proliferating through plant automation systems, letting managers review production and control data from anywhere they can access the Internet. So far, the bulk of Web-based plant monitoring is used to obtain production data (June 2004, page 34)." Decision Automation Topics So what are the major research and content topics associated with decision automation? The fundamental topic is machine processing, the development of the "brain" of the decision automation system. Off-the-shelf central processing units are extremely powerful and parallel processing is affordable. Development technologies that are used for automating decision processing include AI systems, Bayesian networks, intelligent software agents, and neural networks. The storage or "memory" of the system is important, but major improvements have temporarily reduced the need for new breakthroughs. The goal for enhancing storage is always higher capacity in smaller devices with faster read/write capabilities. Sensors, the "input" devices of decision automation, are an important research area. We need better visual systems and more automated data collection. Radio frequency identification (RFID), global positioning systems (GPS), and environment monitoring technologies are all contributing to the expansion of sensing technologies. Finally, decision automation requires a means to communicate the machine's decision. This task is the realm of "effectors", the "output" devices, that can modify a database, control a robot arm, or stop a production line. Bucklin, Lehmann, and Little (1998) predict that in the coming decades, a growing proportion of marketing decisions will be automated. In 2001, Henry Morris, IDC Vice President, wrote "Only when decision support moves to decision process automation, can we improve quality of decisions." Randy Fields in a DSSResources.COM Thought Leader Interview expressed a similar, but more sophisticated view of the need for decision automation. Randy noted "What we have done is to take control away and let machines make the decisions. It is a fundamentally different view of the role of technology. We haven't built thermostatic systems that flash to people, little engineers running around, and tell them in better real time or audibly what the temperature in the room is. We have the sensors, coupled with processors make decisions and implement them. The humans just set the strategy." Decision automation is important and it has an expanding role in organizations, but there still remains a major role for human decision makers and hence for decision support systems. Decision support can often improve decision quality in semi-structured situations where decision automation is not feasible or is undesirable. To support the growth of this knowledge area, we initiated a new website Decision Automation Resources (DecisionAutomation.COM). This site focuses on using quantitative models, heuristics, statistical approaches and Artificial Intelligence technologies to make decisions in highly structured and routine decision situations. DSSResources.COM remains the "flagship" website for people interested in improving decision making and planning, but now Web users can also visit DecisionAutomation.COM and PlanningSkills.COM. Please tell your friends. NOTE: DecisionAutomation.COM is still under construction. If you have any suggestions with regards to types of content you would like to see there or know of related resources, please email us at power@dssresources.com . ********************* References Bucklin, R.E., D.R. Lehmann, and J.D.C. Little, "Decision Support to Decision Automation: A 2020 Vision", MSI working paper, 1998. Morris, H., "Decision Support vs. Decision Process Automation," IDC Viewpoint, August 2001, http://www.idc.com/getdoc.jsp?containerId=VWP000060 Power, D. J., Decision Support Systems: Concepts and Resources for Managers, Westport, CT: Greenwood/Quorum, 2002. Power, D. J., "Randy Fields Interview: Automating 'Administrivia' Decisions", DSSResources.COM, 04/09/2004. Simon, H.A. (1960). The New Science of Management Decision. New York, NY: Harper and Row. ************************************************************ Put your ad here! Reach hundreds of people interested in DSS with information on your product Email power@dssresources.com for details ************************************************************ What's New at DSSResources.COM 07/02/2004 Posted case by Anissa Stevens, "Implementing the Redland Genstar Data Mart". Check the cases page. ************************************************************ DSS News - June 21 to July 2, 2004 Read them at DSSResources.COM and search the DSS News Archive 07/02/2004 Nextel Partners delivers new mobile workforce management tool with ActSoft Comet Tracker. 07/01/2004 Cognos honors Niteo Partners again for outstanding achievement in solution and channel sales. 07/01/2004 Fair Isaac's Fraud Management tools and best practices help clamp down on UK payment card fraud. 07/01/2004 Agile Software makes grant to University of Texas at Dallas School of Management. 07/01/2004 Business Objects announces BusinessObjects 6.5. 07/01/2004 Actuate to host Eighth Annual International User Conference. 06/30/2004 Harrah's wins national award for return on information technology investments. 06/30/2004 Hyperion Essbase 7.1 generally available. 06/30/2004 Darden Restaurants implements kitchen technology from QSR automations. 06/30/2004 DRS Technologies selected by the U.S. Army for production of Battlefield Digitization System. 06/30/2004 Evolution Robotics expands product line with ERSP 3.0 for Windows. 06/30/2004 Airlines distinguish themselves with service, leveraging Sabre Airline Solutions' new technology for the Travel Industry. 06/30/2004 Teradata announces Basel II and risk-management enhancements in latest Teradata Financial Services logical data model. 06/29/2004 Boeing showcases net-centric operations capabilities at newest node. 06/29/2004 Lockheed Martin demonstrates improved human alerting capability for U.S. Navy. 06/29/2004 Microsoft Windows SharePoint Services powers unprecedented collaboration opportunities for and adoption by customers worldwide. 06/29/2004 Informatica continues to lead data integration market, says independent research firm. 06/29/2004 SIG standardizes on the Documentum platform. 06/29/2004 Cognos Enterprise Planning series enhances and extends the accessibility, functionality, and usability of Excel into the planning process. 06/29/2004 Jostens standardizes on Siebel Analytics for business intelligence. 06/29/2004 U.S. Army National Guard expands Polycom Voice and Video Network as part of communications modernization plan. 06/29/2004 Oracle(R) Database 10g sets performance World Record for Linux on non-clustered systems. 06/29/2004 Owens Corning delivers $1.8 Million in savings in just seven months using Emptoris' ExpenseMap. 06/29/2004 MAPICS and Cognos partner to deliver powerful business intelligence solution for world-class manufacturers. 06/29/2004 Verticalnet releases Supply Management 5.1 Suite; 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