Management Information Systems

Transaction processing systems automate routine and tedious back-office processes such as accounting, order processing, and financial reporting. They reduce clerical expenses and provide basic operational information quickly. Management support systems (MSS) use the internal master database to perform high-level analyses that help managers make better decisions.

Information technologies such as data warehousing are part of more advanced MSSs. A data warehouse combines many databases across the whole company into one central database that supports management decision-making. With a data warehouse, managers can easily access and share data across the enterprise to get a broad overview rather than just isolated segments of information. Data warehouses include software to extract data from operational databases, maintain the data in the warehouse, and provide data to users. They can analyze data much faster than transaction-processing systems. Data warehouses may contain many data marts, special subsets of a data warehouse that each deal with a single area of data. Data marts are organized for quick analysis.

Companies use data warehouses to gather, secure, and analyze data for many purposes, including customer relationship management systems, fraud detection, product-line analysis, and corporate asset management. Retailers might wish to identify customer demographic characteristics and shopping patterns to improve direct-mailing responses. Banks can more easily spot credit-card fraud, as well as analyze customer usage patterns.

According to Forrester Research, about 60 percent of companies with $1 billion or more in revenues use data warehouses as a management tool. Union Pacific (UP), a $19 billion railroad, turned to data warehouse technology to streamline its business operations. By consolidating multiple separate systems, UP achieved a unified supply-chain system that also enhanced its customer service. "Before our data warehouse came into being we had stovepipe systems," says Roger Bresnahan, principal engineer. "None of them talked to each other. . . . We couldn't get a whole picture of the railroad".

UP's data warehouse system took many years and the involvement of 26 departments to create. The results were well worth the effort: UP can now make more accurate forecasts, identify the best traffic routes, and determine the most profitable market segments. The ability to predict seasonal patterns and manage fuel costs more closely has saved UP millions of dollars by optimizing locomotive and other asset utilization and through more efficient crew management. In just three years, Bresnahan reports, the data warehouse system had paid for itself.

At the first level of an MSS is an information-reporting system, which uses summary data collected by the TPS to produce both regularly scheduled and special reports. The level of detail would depend on the user. A company's payroll personnel might get a weekly payroll report showing how each employee's paycheck was determined. Higher-level mangers might receive a payroll summary report that shows total labor cost and overtime by department and a comparison of current labor costs with those in the prior year. Exception reports show cases that fail to meet some standard. An accounts receivable exception report that lists all customers with overdue accounts would help collection personnel focus their work. Special reports are generated only when a manager requests them; for example, a report showing sales by region and type of customer can highlight reasons for a sales decline.