# Decision Making as a Component of Problem Solving

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Decision Making as a Component of Problem Solving

Programmed versus Nonprogrammed Decisions
Structured situations with well defined relationships Quantifiable Management information system Easy to computerize Nonprogrammed decisions Rules and relationships not defined Problem is not routine Not easily quantifiable When selecting an alternative in the choice stage, various factors affect the decision. We saw in the airport transportation example that resource constraints, such as time, money, or availability, are factors. Another factor is whether the decision can be programmed. Programmed decisions are made by following rules, procedures or quantitative methods that can be described in advance and regularly used, since the situations are recurring and well-structured. Management information systems are designed to provide information to address programmed decisions. Many simple programmed decisions can be completely automated – for example, inventory control systems can be programmed with reorder points and automatically trigger an order for more merchandise when the reorder point is reached.

Problem Solving Approaches
Optimization: find the best solution Satisficing: find a good solution Heuristics: rules of thumb Computerized decision support systems can usually be used for both optimization and satisficing modeling. An optimization model finds the best solution in relation to the constraints, assumptions, and goals it was given. For example, an optimization model can find the optimal labor cost to produce a particular product and meet a specific level of profit, subject to the cost of raw materials and machinery. Profit level is a goal and costs are a constraint in the model. A satisficing model finds a good, but not necessarily the best, solution. Satisficing is used when optimization is too difficult, costly, or complex. Satisficing looks only at solutions that are likely to produce a good solution and can thus be done more easily and quickly than optimization, which involves an exhaustive search of all possible solutions. Heuristics, or rules of thumb, are often used in decision making. Heuristics are generally accepted guidelines, or guidelines developed through experience, that usually find a good solution. For example, you might follow a heuristic of taking an umbrella if it is cloudy, windy, and humid when you leave the house. Your experience has shown you that generally this results in having an umbrella when it rains. However, this isn’t an optimal solution – since sometimes you carry an umbrella unnecessarily and sometimes it rains on days when you don’t have an umbrella. But the cost of finding an optimal solution is far too great in terms of time and money.

Inputs to an MIS

Characteristics of an MIS
Fixed format, standard reports Hard-copy or soft-copy reports Uses internal data User-developed reports Users must request formal reports from IS department As mentioned earlier, all reports from an MIS have been predetermined – that is, management information systems do not generally produce ad hoc reports, or unique reports done only once. Most recipients get the same report, although they may use it for different purposes. Output from an MIS may be printed, or hard-copy, or viewed on a screen, called soft-copy. Most output from an MIS is hard copy. The primary source of input data for an MIS is internal data stored in internal databases, generally data collected and maintained by a transaction processing system. Sometimes data from external databases is added, such as general economic data or data about competitors’ actions. Since an MIS create an application database, end users can request their own simple reports to access the information stored in it. However, if many users develop the same report, it may be more efficient for the IS department to produce it. More complex reports are generally requested from the IS department and developed by specialists.

Functional Aspects of an MIS

Financial MIS

Manufacturing MIS Design engineering Process control
Computer-assisted manufacturing (CAM) Computer-integrated manufacturing (CIM) Flexible manufacturing system Quality control and testing Inventory control programs are one component of a manufacturing MIS that relies on the production schedule. Inventory control programs can forecast future production, automatically reorder items when a certain threshold is met, determine manufacturing costs, and develop resource requirements plans from the production schedule. Manufacturing Requirements Planning (MRP) programs help coordinate thousands of inventory items when demand for one item depends on demand for another. MRP systems determine when finished products are needed, then work backward to determine deadlines and resources needed to complete the final product on schedule. When high inventory levels are kept, a company’s money is tied up in unused inventory. This means higher costs for the company. A Just-in-time (JIT) inventory approach ensures inventory and materials are delivered only when they are needed. This maintains inventories at their lowest possible level, but insures materials are on-hand in time for production. Although JIT is beneficial, it also makes a business vulnerable to supply chain disruptions – whether internal or external. For example, if a machine breaks down that makes a component another unit needs to assemble the product, assembly may need to stop due to lack on components. Technologies have been developed to control and streamline the manufacturing process. Computers can directly control manufacturing equipment using computer-assisted manufacturing software. Computer-integrated manufacturing software connects all aspects of production together, including order processing, product design, manufacturing, quality control, and shipping. For example, after an engineer designs a product using CAD software, MRP systems can use information from the design as input to plan and order materials. Production scheduling systems can use the design specifications as an input into the scheduling process. And computer-added manufacturing systems can use the design specifications as input for setup. This greatly improves manufacturing efficiency. A flexible manufacturing system allows a facility to quickly and efficiently change from making one product to making another, often using robotics and other automation. Generally the changeover is computer-controlled. Finally, quality control has become paramount for manufacturing firms. Control charts or sample testing is used to monitor product quality.

Overview of a Manufacturing MIS

Marketing MIS

Human Resource MIS

Other MIS Accounting management information systems
Geographic information systems (GIS) There are many other kinds of management information systems used in organizations, including accounting MISs and geographic information systems. While an organization’s transaction processing system captures accounting data, the accounting MIS provides summary information on various aspects of the accounting system, such as accounts payable or accounts receivable. A geographic information system can collect, store, manipulate and display geographic information. In a geographic information system, data are displayed according to their locations. Has a sales clerk ever asked you for your zip code as you pay for a product? When a retail store or restaurant chain is considering opening a new location, they may use a geographic information system to determine where their potential customers are located. By displaying a map, with zip codes color coded to show the number of customers traveling to the current store location, a business can place the new store close to the area where most of them live.

Characteristics of Decision Support Systems
Handle large amounts of data from various sources Provide report and presentation flexibility Offer both textual and graphical orientation Support drill down analysis Not all decision support systems, or DSSs, are alike – some are very small in scope, with only a few of the following attributes; others are comprehensive and powerful. A DSS can analyze information stored in a data warehouse or a database that is distributed across multiple locations. External sources of data, such as those available via the Internet,can also be incorporated into a decision model. Users can see their output in an appropriate format – whether that is a chart, image, table or even map – on a printout or on the screen. In some systems, managers can also drilldown to more detailed data.

Characteristics of a DSS
Perform complex, sophisticated analysis Optimization, satisficing, heuristics Simulation What-if analysis Goal-seeking analysis Many of a DSS’s analytical programs are standalone programs, integrated by the DSS. Decision support systems often support all types of decision-making approaches to allow the user great flexibility. For example, even simple spreadsheets support “what-if analysis”, which allows the user to make changes to input variables to see the result on outcomes. For example, if you can increase production either by adding a new machine or upgrading different combinations of existing machines, you can change the appropriate costs and capacities on a spreadsheet and see which increases output the most and/or costs the least. Simulation allows a user to model a problem by duplicating features of a real system. This generally involves some uncertainty or probability. For instance, perhaps we can increase production by either adding a new machine or by adding additional employees to set up and reconfigure existing machines between production runs. A simulation would model the complex interaction of all these variables, based on estimates of how long it takes one person to reconfigure a machine and how additional people change the time, production time of one machine, and so on.

Capabilities of a DSS Support all problem-solving phases
Support different decision frequencies Support different problem structures Support various decision-making levels Although a specific DSS might only support one or a few phases, decision support systems can support decision makers in all the phases of the problem-solving process – that is, in the intelligence, design, choice, implementation, and monitoring stages. As we’ve seen in this chapter, decisions can range from one-of-a kind to recurring. An ad hoc DSS is useful for one-of-a kind or less structured decisions, while an institutional DSS handles situations that happen on an ongoing basis. Institutional DSSs are refined over time. For instance, deciding where to locate a regional airport is likely a one of a kind decision, whereas investment decisions are recurring. Thus, a DSS can support decisions ranging from unstructured to structured.

Selected DSS Applications

Support for Various Decision-Making Levels

Components of a DSS

The Model Base Financial models Cash flow Internal rate of return
Statistical analysis models Summary statistics Trend projections Hypothesis testing Graphical models Project management models Decision makers use a DSS to model problems or situations in various ways. For instance, financial models can show the relationship among variable in investment analysis. The model base gives DSS users access to a variety of built-in models they can use, so users don’t need to write lengthy programs to create their own models. Often, model management software coordinates the use of models in a DSS. For example, consider the examples of financial models listed on the slide. Rather than a decision-maker trying to remember how to calculate the internal rate of return for an investment and then figure out how to enter commands for the DSS to perform the calculations, it is far more efficient to use the built in internal rate of return model. Although some businesses create complex financial models unique to their situation, DSS software contains powerful financial models. Statistical models perform many tasks, including summary statistics, trends, and hypothesis testing. Although there are powerful software packages dedicated to statistical modeling, such as SPSS and SAS, today’s spreadsheets contain a large set of statistical analysis models.

Executive Support Systems

Executive Support Systems (ESS) in Perspective
Tailored to individual executives Easy to use Drill down capabilities Support need for external data Can help when uncertainty is high Future-oriented Linked to value-added processes Although executive support systems have much in common with decision support systems, they have important differences. Generally, a DSS provides a number of modeling tools and is designed to help a user answer a question. Executive support systems allow executives to ask the right questions. An ESS is interactive and helps an executive focus, filter and organize data and information. Unlike a DSS, an ESS is usually customized for a specific individual. Content and format can both be customized. Since executives are typically busy, an ESS must be easy to learn and to use – or it won’t be used.

Capabilities of an ESS Support for defining an overall vision
Support for strategic planning Support for strategic organizing & staffing Support for strategic control Support for crisis management Most executive support systems are designed to give the user a top-down view of business processes and allow him to drill down to greater levels of detail. This capability, as well as access to external databases and to DSS modeling tools, allows top-level managers to work on long term, strategic issues that affect the whole company.

Summary Decision-making phase: includes intelligence, design, and choice Problem solving: also includes implementation and monitoring Decision approaches: optimization, satisficing, and heuristic

Summary Management information system (MIS) - an integrated collection of people, procedures, databases, and devices that provide managers and decision-makers with information to help achieve organizational goals Decision support system (DSS) - an organized collection of people, procedures, software, databases, and devices working to support managerial decision making Executive support systems (ESSs) - specialized decision support systems designed to meet the needs of senior management