Enhancing Decision Making - Management Information System
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The document discusses how chain retailers can enhance decision-making through management information systems and business analytics software to analyze sales and pricing patterns across different regions. It outlines the decision-making process, types of decisions, and challenges in leveraging information technology for improved outcomes. Furthermore, it describes the business intelligence environment, including data sources, infrastructure, and tools required for effective analysis and reporting to various managerial levels.
Enhancing Decision Making - Management Information System
- 2. Scenario Problem: Chain retailers need to determine what products will sell at what prices at different locations Solutions: Business analytics software to analyze patterns in sales data, create pricing profiles and buyer profiles for different regions, locales, even times of day
- 3. Business value of enhanced decision making Senior managers: – Make many unstructured decisions – E.g. Should we enter a new market? Middle managers: – Make more structured decisions but these may include unstructured components – E.g. Why is order fulfillment report showing decline in Lahore? Operational managers, rank and file employees – Make more structured decisions – E.g. Does customer meet criteria for credit?
- 4. Business value of improved decision making – Improving hundreds of thousands of “small” decisions adds up to large annual value for the business Types of decisions: – Unstructured: Decision maker must provide judgment, evaluation, and insight to solve problem – Structured: Repetitive and routine; involve definite procedure for handling so they do not have to be treated each time as new – Semistructured: Only part of problem has clear-cut answer provided by accepted procedure
- 5. Senior managers, middle managers, operational managers, and employees have different types of decisions and information requirements.
- 7. 4 stages of decision making process 1. Intelligence Discovering, identifying, and understanding the problems occurring in the organization 1. Design Identifying and exploring solutions to the problem 1. Choice Choosing among solution alternatives 1. Implementation Making chosen alternative work and continuing to monitor how well solution is working
- 9. Three main reasons why investments in information technology do not always produce positive results 1. Information quality High-quality decisions require high-quality information 1. Management filters Managers have selective attention and have variety of biases that reject information that does not conform to prior conceptions 1. Organizational politics Strong forces within organizations resist making decisions calling for major change
- 10. Business Intelligence Business intelligence – Infrastructure for collecting, storing, analyzing data produced by business – Databases, data warehouses, data marts Business analytics – Tools and techniques for analyzing data – OLAP*, statistics, models, data mining Business intelligence vendors – Create business intelligence and analytics purchased by firms * Online Analytical Processing
- 11. Business intelligence and analytics requires a strong database foundation, a set of analytic tools, and an involved management team that can ask intelligent questions and analyze data.
- 12. Six elements in the business intelligence environment 1. Data from the business environment Businesses must deal with both structured and unstructured data from many different sources, including big data. The data need to be integrated and organized so that they can be analyzed and used by human decision makers. 1. Business intelligence infrastructure The underlying foundation of business intelligence is a powerful database system that captures all the relevant data to operate the business.
- 13. 3. Business analytics toolset A set of software tools are used to analyze data and produce reports, respond to questions posed by managers, and track the progress of the business using key indicators of performance. 4. Managerial users and methods Business intelligence hardware and software are only as intelligent as the human beings who use them. Without strong senior management oversight, business analytics can produce a great deal of information, reports, and online screens that focus on the wrong matters and divert attention from the real issues.
- 14. 5. Delivery platform – MIS, DSS, ESS The results from business intelligence and analytics are delivered to managers and employees in a variety of ways, depending on what they need to know to perform their jobs. 5. User interface Business people are no longer tied to their desks and desktops. They often learn quicker from a visual representation of data than from a dry report with columns and rows of information.
- 15. Today’s business analytics software suites emphasize visual techniques such as dashboards and scorecards. They also are able to deliver reports on BlackBerrys, iPhones, and other mobile handhelds as well as on the firm’s Web portal. Software is adding capabilities to post information on Twitter, Facebook, or internal social media to support decision making in an online group setting rather than in a face-to-face meeting.
- 16. Business intelligence and analytics capabilities – Goal is to deliver accurate real-time information to decision-makers – Main analytic functionalities of BI systems 1. Production reports – These are predefined reports based on industry specific requirements (examples next slide) 2. Parameterized report – Using filters/conditions to complete report processing
- 18. 3. Dashboards/scorecards – These are visual tools for presenting performance data defined by users. 4. Ad hoc query/search/report creation – These allow users to create their own reports based on queries and searches. 5. Drill down – This is the ability to move from a high-level summary to a more detailed view. 6. Forecasts, scenarios, models – These include the ability to perform linear forecasting, what-if scenario analysis, and analyse data using standard statistical tools.
- 19. BI users Casual users are consumers of BI output, while intense power users are the producers of reports, new analyses, models, and forecasts.
- 20. Over 80 percent of the audience for BI consists of casual users who rely largely on production reports. Senior executives tend to use BI to monitor firm activities using visual interfaces like dashboards and scorecards. Middle managers and analysts are much more likely to be immersed in the data and software, entering queries and slicing and dicingthe data along different dimensions. Operational employees will, along with customers and suppliers, be looking mostly at prepackaged reports.
- 21. Examples of BI applications – Predictive analytics Use patterns in data to predict future behavior E.g. Credit card companies use predictive analytics to determine customers at risk for leaving – Data visualization Help users see patterns and relationships that would be difficult to see in text lists – Geographic information systems (GIS) Ties location-related data to maps
- 22. Questions??