Business Intelligence and Knowledge Management

Founded in 1967 by two rock climbers, Eastern Mountain Sports (EMS) has grown into one of the leading outdoor specialty retailers in the United States, with more than 80 retail stores in 16 states, a seasonal catalogue, and a growing online presence. EMS designs and offers a wide variety of gear and clothing for outdoor enthusiasts.

Until recently, however, the company’s information systems for management reporting were dated and clumsy. It was very difficult for senior management to have a picture of customer purchasing patterns and company operations because data were stored in disparate sources: legacy merchandising systems, financial systems, and point-of-sale devices. Employees crafted most of the reports by hand, wasting valuable people resources on producing information rather than analyzing it.

After evaluating several leading business intelligence products, EMS selected WebFOCUS and iWay middleware from Information Builders Inc. EMS believed WebFOCUS was better than other tools in combining data from various sources and presenting the results in a user-friendly view. It is Web-based and easy to implement, taking EMS only 90 days to be up and running.

IWay extracts point-of-sale data from EMS’s legacy enterprise system running on an IBM AS/400 midrange computer and loads them into a data mart running Microsoft’s SQL Server database management system. WebFOCUS then creates a series of executive dashboards accessible through Web browsers, which provide a common view of the data to more than 200 users at headquarters and retail stores.

The dashboards provide a high-level view of key performance indicators such as sales, inventory, and margin levels, but enable users to drill down for more detail on specific transactions. Managers for merchandising monitor inventory levels and the rate that items turn over. E-commerce managers monitor hour-by-hour Web sales, visitors, and conversion rates. A color-coded system of red, yellow, and green alerts indicates metrics that are over, under, or at plan.

EMS is adding wikis and blogs to enable managers and employees to share tips and initiate dialogues about key pieces of data. For example, in identifying top-selling items and stores, EMS sales managers noticed that inner soles were moving very briskly in specialty stores. These stores had perfected a multi-step sales technique that included the recommendation of socks designed for specific uses, such as running or hiking, along with an inner sole custom-fit to each customer. Wikis and blogs made it easier for managers to discuss this tactic and share it with the rest of the retail network.

Longer term, EMS is planning for more detailed interactions with its suppliers. By sharing inventory and sales data with suppliers, EMS will be able to quickly restock inventory to meet customer demand, while suppliers will know when to ramp up production.

Eastern Mountain Sports’ executive dashboards are a powerful illustration of how information systems improve decision making. Management was unable to make good decisions about how and where to stock stores because the required data were scattered in many different systems and were difficult to access. Management reporting was excessively manual. Bad decisions about how to stock stores and warehouses increased operating costs and prevented EMS stores from responding quickly to customer needs.

EMS management could have continued to use its outdated management reporting system or implemented a large-scale enterprise-wide database and software, which would have been extremely expensive and time-consuming to complete. Instead, it opted for a business intelligence solution that could extract, consolidate, and analyze sales and merchandising data from its various legacy systems. It chose a platform from Information Builders because the tools were user-friendly and capable of pulling together data from many different sources.

The chosen solution populates a data mart with data from point-of-sale and legacy systems and then pulls information from the data mart into a central series of executive dashboards visible to authorized users throughout the organization. Decision-makers are able to quickly access a unified high-level view of key performance indicators such as sales, inventory, and margin levels or drill down to obtain more detail about specific transactions. Increased availability of this information has helped EMS managers make better decisions about increasing sales, allocating resources, and propagating best practices.

12.1 Decision Making and Information Systems

Decision making in businesses used to be limited to management. Today, lower-level employees are responsible for some of these decisions, as information systems make information available to lower levels of the business. But what do we mean by better decision making? How does decision making take place in businesses and other organizations? Let’s take a closer look.

BUSINESS VALUE OF IMPROVED DECISION MAKING

What does it mean to the business to make better decisions? What is the monetary value of improved decision making? Table 12-1 attempts to measure the monetary value of improved decision making for a small U.S. manufacturing firm with $280 million in annual revenue and 140 employees. The firm has identified a number of key decisions where new system investments might improve the quality of decision making. The table provides selected estimates of annual value (in the form of cost savings or increased revenue) from improved decision making in selected areas of the business.

We can see from Table 12-1 that decisions are made at all levels of the firm and that some of these decisions are common, routine, and numerous. Although the value of improving any single decision may be small, improving hundreds of thousands of “small” decisions adds up to a large annual value for the business.

TYPES OF DECISIONS

Chapters 1 and 2 showed that there are different levels in an organization. Each of these levels has different information requirements for decision support and responsibility for different types of decisions (see Figure 12-1). Decisions are classified as structured, semistructured, and unstructured.

TABLE 12-1 BUSINESS VALUE OF ENHANCED DECISION MAKING

EXAMPLE DECISION

DECISION MAKER

NUMBER OF ANNUAL DECISIONS

ESTIMATED VALUE TO FIRM OF A SINGLE IMPROVED DECISION

ANNUAL VAUE

Allocate support to most valuable customers

Accounts manager

12

$ 100,000

$1,200,000

Predict call center daily demand

Call center management

4

150,000

600,000

Decide parts inventory levels daily

Inventory manager

365

5,000

1,825,000

Identify competitive bids from major suppliers

Senior management

1

2,000,000

2,000,000

Schedule production to fill orders

Manufacturing manager

150

10,000

1,500,000

Allocate labor to complete a job

Production floor manager

100

4,000

400,000

FIGURE 12-1 INFORMATION REQUIREMENTS OF KEY DECISION-MAKING GROUPS IN A FIRM

Senior managers, middle managers, operational managers, and employees have different types of decisions and information requirements.

Unstructured decisions are those in which the decision maker must provide judgment, evaluation, and insight to solve the problem. Each of these decisions is novel, important, and nonroutine, and there is no well-understood or agreed-on procedure for making them.

Structured decisions, by contrast, are repetitive and routine, and they involve a definite procedure for handling them so that they do not have to be treated each time as if they were new. Many decisions have elements of both types of decisions and are semistructured, where only part of the problem has a clear-cut answer provided by an accepted procedure. In general, structured decisions are more prevalent at lower organizational levels, whereas unstructured problems are more common at higher levels of the firm.

Senior executives face many unstructured decision situations, such as establishing the firm’s five- or ten-year goals or deciding new markets to enter. Answering the question “Should we enter a new market?” would require access to news, government reports, and industry views as well as high-level summaries of firm performance. However, the answer would also require senior managers to use their own best judgment and poll other managers for their opinions.

Middle management faces more structured decision scenarios but their decisions may include unstructured components. A typical middle-level management decision might be “Why is the reported order fulfillment report showing a decline over the past six months at a distribution center in Minneapolis?” This middle manager will obtain a report from the firm’s enterprise system or distribution management system on order activity and operational efficiency at the Minneapolis distribution center. This is the structured part of the decision. But before arriving at an answer, this middle manager will have to interview employees and gather more unstructured information from external sources about local economic conditions or sales trends.

Operational management and rank-and-file employees tend to make more structured decisions. For example, a supervisor on an assembly line has to decide whether an hourly paid worker is entitled to overtime pay. If the employee worked more than eight hours on a particular day, the supervisor would routinely grant overtime pay for any time beyond eight hours that was clocked on that day.

A sales account representative often has to make decisions about extending credit to customers by consulting the firm’s customer database that contains credit information. If the customer met the firm’s prespecified criteria for granting credit, the account representative would grant that customer credit to make a purchase. In both instances, the decisions are highly structured and are routinely made thousands of times each day in most large firms. The answer has been preprogrammed into the firm’s payroll and accounts receivable systems.