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- Davenport, Tom
- Decision Diary
- Decision Making
- Decision Support Systems (DSS)
Data SlamRefers to meaningless pieces of data which can clog corporate intranet sites and databases. They make systems slow, unwieldy and difficult to navigate. In the process, they slow down decision making. Data WarehousingA data warehouse facilitates integrated access to a company’s information. A data warehouse stores both current and historical data that are of interest to managers across the organization. The data may originate in different operational systems and external sources. They may be in different forms. These data are standardized and consolidated so that they are accessible to users through simple commands. A data warehouse provides data to decision makers without interfering with the transaction processing operations. Selected items are regularly pulled from transaction data files and stored in a central location. This may be done on an hourly, daily, weekly or monthly basis. What makes a data warehouse different from other databases is its purpose. Most data are collected to manage day-to-day business activities. The systems used to collect such operational data are referred to as OLTP (Online Transaction Processing). On the other hand, the distinguishing feature of a data warehouse is analysis. A data warehouse makes data available for the purpose of analysis. The main aim of a data warehouse is to hold in one place all the data needed for managerial decision making. So the starting point is determining the data needs. Indeed, the success of a data warehouse largely depends on how well the needs of managers have been identified. The next step is to establish the sources of data. Then the data must be transformed and integrated so that it can be searched and analyzed efficiently by decision makers. Instead of building a link to the original data files, it is easier to copy the data into new files. Once the data warehouse has been defined, programs are written to transfer the data from the legacy systems into the data warehouse. One problem with a data warehouse is that managers will not always have the most current data. Often data is stored as collections of files and data items and not in relational database management systems (RDBMS). So, the system is relatively easy to use but is less flexible compared to RDBMS. (See also: Data Mining, Data Marts) Davenport, TomOne of the leading knowledge management gurus in the world, Davenport has been associated with Ernst & Young, McKinsey & Company, and Accenture. He has written, co-authored or edited several books on business process reengineering, knowledge management, and the business use of enterprise systems. Working Knowledge: How Organizations Manage What They Know, coauthored with, Laurence Prusak (2000) is one of the most popular books ever written on knowledge management. His book, What’s the Big Idea: Creating and Capitalizing on the Best Management Thinking, was named one of the three best books of the Spring 2003 season by Fortune magazine. His most recent book, Thinking for a Living, has also received highly favorable reviews. Davenport has also written hundreds of articles and columns for such publications as Harvard Business Review, Sloan Management Review, California Management Review, Financial Times, Information Week, CIO and many others. His other books include: The Attention Economy: Understanding the New Currency of Business coauthored with, John C. Beck (2002); Mastering Information Management coauthored with, Donald A. Marchand (2000); Mission Critical: Realizing the Promise of Enterprise Systems (2000); Information Ecology: Mastering the Information & Knowledge Environment coauthored with, Laurence Prusak (1997) and Process Innovation: Reengineering Work Through Information Technology (1992). Decision DiaryA diary which gives an account of decisions taken, along with the assumptions and reasoning behind them. This kind of knowledge facilitates experiential learning and future decision-making. (See also: Learning History, Causal Knowledge) Decision MakingKnowledge is of little use if it is not used to make decisions. Knowledge management systems are increasingly being applied to decision making. Such systems should take into account how people take decisions in real life. According to Nobel prize winner Herbert Simon, decision making takes place in four stages: “Intelligence” involves discovering, identifying and understanding the problem. “Design” includes identifying and exploring solutions to the problem. “Choice” consists of choosing among solution alternatives. “Implementation” means making the chosen alternative work. These stages explain how decision making should take place logically. In practice, the influence of various behavioral issues cannot be overlooked. Moreover, the four steps may not happen sequentially; they may overlap to some extent. And in many cases, decision making takes place in an iterative fashion, accepting things that work and rejecting those that do not. Three key factors that are an impediment to good decisions are information quality, human filters and resistance to change: Information may not be accurate, complete, consistent or available on a timely basis. Managers have selective attention, various biases and focus on some dimensions of the problem while ignoring others. Last, but not the least, people are resistant to change. So, decisions often tend to be a balancing of the firm’s various interest groups rather than the most optimal solution. A knowledge management system should take into account all these factors if it is to become an effective aid to managerial decision taking. Decision Support Systems (DSS)Decision support systems support managers in data collection, analysis and presentation of output. Such systems help managers in retrieving, summarizing and analyzing data for the purpose of decision making. DSS may support a large group of managers in a networked environment with a data warehouse or a single user, desktop application. A computer program churns through data and with human interpretation, reveals previously hidden trends and patterns, allowing managers to make smarter and faster decisions. Data collection is typically performed by a transaction processing system. This data is transferred to a model for analysis using the appropriate software. Finally, the DSS presents the results in a format that is easy to understand. Graphs are often a useful way of presenting the result. Often, the reports generated by the DSS are used to build a business case or to persuade other people. So the reports must be concise, accurate and visually appealing. DSS must be designed carefully based on customer requirement. Even the best DSS will not eliminate bad decisions. It goes without saying that if managers ask the wrong questions or draw the wrong conclusion, DSS will be ineffective. DSS have not taken off as rapidly as expected because of the difficulties involved in laying down decision rules, or algorithms, from human experts. Moreover, many managers, have a mental block about the ability of a computer to take decisions on their behalf. Directory: books books -> The English Arrive in America books -> Active Vocabulary books -> Books we finished XIV books -> The theology of the balaam oracles: a pagan diviner and the word of god books -> The rhetoric of the father books -> Sra: Imagine It!, Themes, Taking a Stand, Ancient Civilizations Ecology, Great Expectations, Earth in Action, Art and Impact, Level 6 books -> You Can If You Try Unit 7 Nonfiction books -> The tregenza family books -> Unconditional hatred Download 0.91 Mb. Share with your friends:
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