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ALISON: Diploma in Project Management


Comments about The planning phase - The planning phase - establishing control mechanisms

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- Module: The planning phase
- Topic: The planning phase - establishing control mechanisms

Latest Comments

  • Md Shohel Mahmud Bangladesh for proper controls procedures and techniques must be established. The planning phase is now clear to me.
    2014-11-17 05:11:49

    • Md Shohel Mahmud Bangladesh A clear set of procedures and techniques must be established to ensure that proper controls exist on any data gathered in subsequent stages to ensure that it is valid.
      2014-11-17 05:11:45
  • Caroline Omoro Kenya It is important that clear procedures and controls be put in place in order to ensure that data gathered in subsequent stages still valid.This can be done by follow up interviews and surveys. A matrix can also be developed to highlight economical, technical and operational areas,
    2014-11-16 10:11:41

  • Cyrus Wanjohi Kenya Module understood.
    2014-11-16 07:11:51

  • Cyrus Wanjohi Kenya A clear set of procedures and techniques must be established to ensure that proper controls exist on any data gathered in subsequent stages to ensure that it is valid.
    2014-11-16 06:11:34

  • Cyrus Wanjohi Kenya A clear set of procedures and techniques must be established to ensure that proper controls exist on any data gathered in subsequent stages to ensure that it is vali
    2014-11-16 06:11:11

  • Janvier Nyandamu Rwanda the example is not clear for me!!
    2014-11-09 17:11:28

    • Cyrus Wanjohi Kenya A clear set of procedures and techniques must be established to ensure that proper controls exist on any data gathered in subsequent stages to ensure that it is valid. For example, it is often necessary to follow-up an interview or survey with direct observation to confirm your findings
      2014-11-16 07:11:55
  • Nothando Gumpo United Kingdom A clear set of procedures and techniques must be established to ensure that proper controls exist on any data gathered in subsequent stages to ensure that it is valid. For example, it is often necessary to follow-up an interview or survey with direct observation to confirm your findings.
    2014-11-06 12:11:14

  • Ralph Webster South Africa A clear set of procedures and techniques must be established to ensure that proper controls exist on any data gathered in subsequent stages to ensure that it is valid. For example, it is often necessary to follow-up an interview or survey with direct observation to confirm your findings.? THE RESULT??
    2014-10-19 07:10:30

  • George Fragos Greece how often is necessary to follow up an interview or survey with direct observation to confirm your findings?
    2014-09-29 10:09:51

  • Christian Festus Qatar What are the issues that a feasibility study will look at ?
    2014-08-30 09:08:20

    • lyatuu oscar Tanzania Thank you Mr. Z. Bhanji. Am satisfied with your answer.
      2014-10-08 09:10:32
    • Zulfikar Bhanji Kenya 1) What is the current problem with the system. 2) What will solve this current problem 3) Modify the old system or build a new one 4) If you go on to build a new system many things come into play. 5) What are the constrains of the new system 6) Do you build or buy a system work are the figures 7) After evaluating this decision can be made. 8) Going forward then goes into time frame, costs of buying and running the system training personnel upgrading the system final using the data from that system to improve what was the original problem
      2014-09-24 08:09:50
  • Samuel Kofi Odoi Ghana How many people must take care of this positions and how would the interviews be?
    2014-08-17 23:08:16

    • Zulfikar Bhanji Kenya Historical data is the best and then the people who use the system are the ones which will give you an idea of what you need to know and then make the decision
      2014-09-24 08:09:24
    • Yai Deng Yai South Sudan Through follow up, supervisors and manager.
      2014-08-25 15:08:11
  • Vikram Vasant Rotkar United Kingdom What if the control system goes hay way?
    2014-07-21 17:07:23

    • Zulfikar Bhanji Kenya All systems have teething problems experience is your best hope hire the best and you will the avoid the pitfalls
      2014-09-24 08:09:31
    • Yai Deng Yai South Sudan It can be improved.
      2014-08-25 15:08:42
  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:02

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:53

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:45

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:33

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:17

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:04

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:00

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:45

    • Yai Deng Yai South Sudan What are you trying to explain here?
      2014-08-25 15:08:50
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