Figure 7-1 shows information on policies offered by an insurance company. The simple graph shown in Figure 7-1 is a good starting point for an executive’s probing into the state of the business. Once the executive has seen the overall information, he or she can probe more deeply, as shown by the trend analysis in Figure 7-2.
In Figure 7-2, the executive has isolated new casualty sales from new life sales and new health sales. The EIS analysis alerts the executive as to what the trends are. It is then up to him or her to discover the underlying reasons for the trends. Trends are not the only type of analysis accommodated by EIS. Another type of useful analysis is comparisons. Figure 7-3 shows a comparison that might be found in an EIS analysis.
Figure 7-4 shows a simple example of drill-down analysis.
There is plenty of very sophisticated software that can be used in EIS to present the results to a manager.
Exacerbating the problem is the fact that the executive is constantly changing his or her mind about what is of interest, as shown in Figure 7-7.
The trend has been calculated from data found in the data warehouse. The trend of revenues in and of itself is interesting, but gives only a superficial view of what is going on with the corporation. To enhance the view, events are mapped onto the trend line.
In Figure 7-13, three notable events have been mapped to the corporate revenue trend line—the introduction of a “spring colors” line of products, the advent of a sales incentive program, and the introduction of competition.
Figure 7-14 shows that corporate revenues are matched against the consumer confidence index to produce a diagram packed with even more perspective. Looking at the figure shown, the executive can make up his or her own mind whether events that have been mapped have shaped sales.
Lecture 07 - Executive Information Systems and the Data Warehouse
Chapter 7: Executive Information Systems and the Data Warehouse http://it-slideshares.blogspot.com/
Agenda1. Introduction2. EIS – The Promise3. A Simple Example4. Drill-Down Analysis5. Supporting the Drill-Down Process6. The Data Warehouse as a Basic for EIS7. Where to Turn8. Event Mapping9. Detailed Data and EIS10. Keeping Only Summary Data in the EIS11. Summary http://it-slideshares.blogspot.com/
7.1 Introduction Prior to data warehousing, there were Executive Information Systems (EIS). EIS was a notion that computation should be available to everyone in the corporation, not just the clerical community doing day-to-day transactions. EIS presented the executive with a set of appealing screens. The entire idea behind EIS was presentation of information with no real understanding of the infrastructure needed to create that information in the first place. EIS has reappeared in many forms today—such as OLAP processing and DSS applications like customer relationship management (CRM).
7.2 EIS — The Promise EIS is one of the most potent forms of computing. EIS processing is designed to help the executive make decisions. EIS becomes the executive’s window into the corporation. Some of the typical uses of EIS are these : Trend analysis and detection Key ratio indicator measurement and tracking Drill-down analysis Problem monitoring Competitive analysis Key performance indicator monitoring http://it-slideshares.blogspot.com/
7.3 A Simple Example (Con’t)The few approachs thatthe manager can use EISeffectively : Trend analysis and comparison To do slicing and dicing Figure 7-3 shows a comparison that might be found in an EIS analysis.
7.4 Drill-Down Analysis Drilling down refers to the ability to start at a summary number and to break that summary into a successively finer set of summarizations.
7.4 Drill-Down Analysis (Con’t) Another important aspect of EIS is the ability to track key performance indicators. Although each corporation has its own set, typical key performance indicators might be the following: Cash on hand Customer pipeline Length of sales cycle Collection time New product channel Competitive products
7.4 Drill-Down Analysis (Con’t) The difficult part of EIS is not in the graphical presentation, but in discovering and preparing the numbers – accurately, completely, and integrated— that go into the graphics, as shown in Figure 7-5.
7.5 Supporting the Drill-Down Process Creatingthe basis of data on which to perform drill- down analysis, then, is the major obstacle to successfully implementing the drill-down process, as shown in Figure 7-6.
7.6 The Data WareHouse as a Basic for EIS It is in the EIS environment that the data warehouse operates in its most effective state. With a data warehouse, the EIS analyst does not have to worry about the following: Searching for the definitive source of data Creating special extract programs from existing systems Dealing with unintegrated data Compiling and linking detailed and summary data and the linkage between the two Finding an appropriate time basis of data (finding historical data) Management constantly changing its mind about what needs to be looked at next
7.6 The Data WareHouse as a Basic for EIS (con’t)
7.7 Where to Turn TheEIS analyst can turn to various places in the architecture to get data.
7.7 Where to Turn (Con’t) There is a very good reason for the order shown, as indicated in Figure 7-10.
7.7 Where to Turn (Con’t) Theways that EIS is supported by the data warehouse are illustrated in Figure 7-11.
7.7 Where to Turn (Con’t)The EIS function uses the following : The data warehouse for a readily available supply of summary data. The structure of the data warehouse to support the drill- down process. Data warehouse metadata for the DSS analyst to plan how the EIS system is built. The historical content of the data warehouse to support the trend analysis that management wishes to see. The integrated data found throughout the data warehouse to look at data across the corporation
7.8 Event Mapping A useful technique in using the data warehouse for EIS processing is event mapping. The simplest way to depict event mapping is to start with a simple trend line.
7.8 Event Mapping (con’t)Figure 7-12 shows that corporate revenues have varied by month, as expected.
7.8 Event Mapping (con’t) Misleading conclusions can be drawn, though, by looking at correlative information. It often helps to look at more than one set of trends that relate to the events at hand.
7.9 Detailed Data and EIS The following question must be answer : How much detailed data do you need to run your EIS/DSS environment? What, then, is so wrong with keeping all the detail in the world around when you are building an EIS/DSS environment? Summary data is an integral part of the EIS/DDS environment.
7.10 Keeping Only Summary Data in the EIS Some very real problems become evident with keeping just summary data. First, summary data implies a process It may or may not be at the appropriate level of granularity for the analytical purpose at hand.
7.11 Summary There is a very strong affinity between the needs of the EIS analyst and the data warehouse. The data warehouse explicitly supports all of the EIS analyst’s needs. With a data warehouse in place, the EIS analyst can be in a proactive rather than a reactive position. The data warehouse enables the EIS analyst to deal with the following management needs: Accessing information quickly Changing their minds (that is, flexibility) Looking at integrated data Analyzing data over a spectrum of time Drilling down The data warehouse provides an infrastructure on which the EIS analyst can build. http://it-slideshares.blogspot.com/