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Business information systems: prepared for a class presentation at Northcentral University

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  • A presentation for the management of XYZ construction. Prepared by John Salina, President of JES Consultants; a Global Management Consulting Company, established in 1998.
  • XYZ Construction (XYZ), is a privately owned firm, which is planning an IPO. Because of the additional complexity and forecasted growth, XYZ’s management is concerned about the capabilities of the company’s information system. As XYZ grows and assumes the responsibilities of a public company, XYZ’s president is considering adding additional information system resources to supplement the firm’s current information system. However, XYZ’s director of information technology (IT) thinks the current system is outdated and incapable of handling a companywide expansion. At the last management meeting, XYZ’s president and the IT director broke into a heated argument about information systems. While all of XYZ’s management agrees they need to have an information system that can support the company as it grows, no one can agree about how to assess their current IT capabilities and determine their future IT requirements. As part of the IT management concerns, XYZ’s marketing director wants to improve customer satisfaction and is wondering what analytical tools and techniques are available. XYZ’s service direction is also interested in using quantitative techniques to improve service quality. By the end of the meeting, all of the managers agreed to bring in a consultant to provide an unbiased opinion of XYZ’s current information system and what is needed to support the company’s expansion. The managers also agreed to ask the consultants for a recommendation on quantitative techniques to help marketing and customer service. As a result, JES consultants prepared this agenda for the next management meeting: Introduction Information systems and technology Planning for technology Implementing technology systems Evaluation and Control of technology Quantitative techniques Descriptive statistics Dashboards Hypotheses Wrap-up  
  • Information systems cover a broad range of applications in both small and large firms. This slide depicts several important concepts about information systems. From an operational view, information systems facilitate the management of day to day operations, which involve customer orders, customer service, scheduling of materials, human resources, accounting, finance, engineering, production and marketing. For strategic planning, information systems provide data for decision making and forecasting. The integration of various information systems equates to a management information system or MIS. Management information systems include the actual components of the information system, development and use of information systems, and achieving business goals and objectives (Kroenke, 2009). There are five basic components , which comprise an information system: hardware, software, data, procedures, and people (Kroenke). For XZY, every component of the information must be considered as the company plans for the IPO. Often, a company will only consider the technology, hardware and software, and neglect the issues surrounding what to measure as quantified as data. Procedures are another area where firms fail to outline exactly how to use information systems. In addition, human element of information systems is very important as people must be trained and the information system requires maintenance and repairs.
  • As this slide illustrates in the two figures adapted from Rainer and Turban (2009), planning for technology must involve both the technology inside the firm and the technology outside the firm. It is important that information systems planning address the linkage issues such as control and the sophistication of organizational needs (Raghunathan & Raghunathan, 1989). Linkage issues involve the firm’s internal requirements as for example executive directors may require the same information shared by clerical users in terms of a shared data base. Linkage issues become more pronounced when dealing with the external environment as XYZ’s information system technology must be compatible and as technologically capable as those of suppliers and customers. Beyond technological compatibility and shared data resources, planning for technology must include individual users and their associated functional departments. In order to provide appropriate directions and coordination of technology planning efforts, effective planning must build consensus among each user and department within the organizations as a whole (Boyton & Zmud, 1987). From an external perspective, customers and suppliers have technological plans that can influence XYZ’s technology planning requirements. For example, horizontal construction customers may make payments at various stages of project completion. If customers use electronic commerce, XYZ must have the technology in place to serve the customer’s electronic payment requirements. In summary, technology planning must take into account both the internal and external environments and in doing so, can give the company a competitive advantage.
  • XYZ’s strategic plan lies in the forthcoming IPO. Implementing a new technology or other changes within the company require a road map similar to a strategic plan. For example, changes or enhancements to XYZ’s information systems requires a plan and the plan must be aligned to the firm’s overall strategic plan and include the following elements as proposed by McLean and Soden (1977), to include: establish a technology mission statement, assess the internal and external environment, set goals and objectives, derive strategies and policies, develop long-term, medium-term, and short-term plans and implement plans and monitor results. There are two aspects that concern the implementation of technology, organizational and application. The organizational aspect includes the economic stability of the firm and management orientation towards technology, where the application aspect includes functional systems gaps relating to the degree of change from old to new (Whyte, Bouchlaghem & Thorpe, 2002). As XYZ plans to implement the needed technology to support the firm’s growing information systems needs, management should consider the technological gaps as well as managing the organizational issues. In other words, XYZ’s management must consider both the technology required as well as developing an implementation plan that gives the employees of XYZ an understanding of how the changes will benefit them and their part in making the change a success.
  • The evaluation and control of technology, related to information systems, starts with a determination of what you are going to measure. For example, XYZ may implement a new intranet order entry system. In the new order system, both customers and employees of XYZ have access to an internal website or portal where orders are entered and received. As depicted in Figure 1, to verify the performances of the new system, measurements are taken, compared against a standard, and corrective action is initiated (Wheelen & Hunger, 2006). In the case of an order entry system some typical metrics are order accuracy, cycle time, and ease of use. While defining a particular metric is straightforward in concept, in application the design of measures is a multi-faceted endeavor as described by Neely et al. (1997), see Figure 2 in this slide. The key points for XYZ to consider are the establishment of metrics that define the systems performance as related to meeting the objectives of the newly implemented system. Using the example of the new order entry system, the evaluation and control mechanism should ensure that the system is improving the order entry process from the customer’s perspective and from XYZ’s perspective. In addition, the implementation of a new order entry system must align to XYZ’s strategic plan and the IPO. The next part of this presentation covers specific quantitative techniques that XYZ can use to measure various aspects of the business operation and integrate into their information management systems.
  • Measurements of various business operations are necessary to monitor the quality of a specific operation and establish a baseline for comparison. There are two types of data that is normally gathered from a business operation, qualitative and quantitative. Qualitative data is measured using either a nominal or ordinal scale. Nominal scales have no order or distance relationships and ordinal scales include an order relationship (Cooper & Schindler, 2003). Qualitative data is most useful in exploratory research where the objective is to find relationships rather than the more precise measurements (Cooper & Schindler). Quantitative data normally uses interval and ratio data. An example of interval data is a date or temperature. Ratio data is the highest level of data and includes a true zero point. Ratio data is the actual amount of a variable, a bank account balance is an example of ratio data. From XYZ’s perspective, quantitative data can provide more meaningful information and allows precise calculations in analyzing and summarizing operational data. The next slide explains how descriptive statistics are derived from quantitative data and the benefits of using statistical techniques to convert data to information.  
  • The word statistics is frequently misused as numbers and facts are often referred to as statistics and the analysis and interpretation of data is also called statistics. For a business, numbers and facts comprise what is known as data. Data is a collection of measurements, most often in the form of ratio level numbers. Weekly sales numbers are an example of data. While data can be useful, information is needed to make decisions. Information is distinguished from data in the sense that information is an interpretation of the data. For example, plotting weekly sales data for specific period of time is a way to add relevance and comparisons of the sales data. Descriptive statistical techniques provide the methodology to transform data into information by using tabular, graphical, and numerical methods to summarize and illustrate data. In descriptive statistics, tables and charts illustrate the key attributes of the data and numerical calculations such as the average or mean help to mold the data into a more meaningful form. Descriptive statistics can also describe the dispersion or degree of variability in the data. The next slide discusses the various types of descriptive statistics and the notion of dashboards as a management tool for XYZ.
  • Descriptive statistics covers methods to display, summarize and interpret data. However, managers require information on a regular basis and gathering data, computing, and constructing charts and graphs can be time confusing and inconsistent. A common method, employed by most large firms, is the use of a management dashboard to provide a timely, and real time, display of key business parameters. The illustration in this slide, which is adapted from, depicts a common type of dashboard used to monitor company wide performance. Notice the various types of descriptive techniques used in the dashboard. Pie, line, gage, and bar charts are used to describe various metrics as related to sales revenue by industry, customer backlog, projected sales, and marketing campaign effectiveness. Tables are also used in the dashboard to illustrate various lead generation activities. For XYZ, dashboards can provide an effective tool for management to monitor and control the various activities in the company. As part of XYZ’s information system enhancement, dashboards are an essential part of the information systems output that can provide various types of dashboards for different levels in the organization and each functional department. While descriptive statistics provide a method to interpret data leading to corrective actions, for the most part dashboards are reactive as the data is a result of something that has already occurred. From a proactive perspective, as explained in the next slide, inferential statistics is another important quantitative tool for XYZ.
  • Beyond descriptive statistics are inferential statistics. As the name inferential statistic suggests, inferential statistics infer to all on the basis of some based on probability (Cooper & Schindler, 2003). To understand inferential statistics, one can start with two measures used in descriptive statistics that are defined as measures of central tendency and variance. Central tendency is represented by the mean or average of the data and variance is represented in units on each side of the mean. In this slide, a data set is represented in the form of a curve where the mean is the center point and variability of the data is represented in the areas under the curve on each side of the mean. Variance is normally defined in units of standard deviation, the square root of the variance. Without going into a lengthy dissertation about statistical mathematics, measures of central tendency and variance set the stage for applying probability concepts to predict and model specific behaviors from a set of data.
  • If one knows the mean and standard deviation of a data set, a prediction can be made about data from other data sets. For example, if XYZ wants to test the viability of a new product or service the company can conduct a survey on a small set of their current customers. By just sampling a small set of their entire customer base, XYZ can save time and costs as compared to sending a survey to all of their customers. Using inferential statistical techniques known as hypothesis testing, XZY can infer that the results from the customer sample represent those of all of their customers. The key point in hypothesis testing is statistical significance. Statistical significance is best described as asking the question: is the difference because of chance or is it because of some cause and effect relationship? The actual methodology of hypothesis testing is outside the scope of this presentation, but for XYZ hypothesis testing represents a powerful tool for predicting the behavior of customers, employees, process improvements, and quality. For a more comprehensive discussion on inferential statistics and hypothesis testing, JES consultants suggest this Six Sigma site as an additional resource:
  • In summary, in planning for technology XYZ should consider both the present and future business needs and technology planning must take into account both the internal and external environments. For the implementation of technology systems XYZ’s management must consider both the technology required as well as developing an implementation plan that gives the employees of XYZ an understanding of how the changes will benefit them and their part in making the change a success. As discussed in the section concerning the evaluation and control of technology, evaluation and control of technology starts with a determination of what you are going to measure. With regard to descriptive statistics, dashboards represent a significant opportunity for XYZ to monitor and control operations at various levels in the organization and each functional department. Finally, inferential statistics and hypothesis testing is an area where XYZ can develop the necessary tools and skills to help management predict and test products, service and internal processes.
  • Is Sks7000

    1. 1. Information management systems & quantitative techniques XYZ Construction Prepared by John Salina, JES Consultants
    2. 2. Agenda <ul><li>Introduction </li></ul><ul><li>Information systems </li></ul><ul><ul><li>Planning for technology </li></ul></ul><ul><ul><li>Implementing technology systems </li></ul></ul><ul><ul><li>Evaluation and Control of technology </li></ul></ul><ul><li>Quantitative techniques </li></ul><ul><ul><li>Descriptive statistics </li></ul></ul><ul><ul><li>Dashboards </li></ul></ul><ul><ul><li>Hypotheses testing </li></ul></ul><ul><li>Wrap-up </li></ul>
    3. 3. Information systems Hardware – desktops, laptops, PDAs Software – operating systems, application programs Data – facts and figures entered into computers Procedures – how the other four components are used People – users, technologists, IS support
    4. 4. Planning for technology Technology supports both the external and internal business operation (Rainer & Turban, 2009) (Rainer & Turban, 2009 Planning for technology must include the firm’s alignment to the technology used by suppliers and customers. Inside the organization
    5. 5. Implementing technology systems A information technology strategy and implementation is a sub-set of the firm’s overall strategic plan Establish a technology mission statement Assess the internal and external environment Set goals and objectives Derive strategies and policies Develop long-, medium-, and short-range plans Implement plans and monitor results Firm’s overall strategic plan
    6. 6. Evaluation and Control of technology Figure 1 Figure 2 <ul><li>Be derived from strategy </li></ul><ul><li>Be simple to understand </li></ul><ul><li>Provide timely and accurate feedback </li></ul><ul><li>Be actionable: based on quantities that can be influenced or controlled </li></ul><ul><li>Reflect the business process: both customer and supplier should be involved in defining </li></ul><ul><li>Relate to specific targets </li></ul><ul><li>Be relevant </li></ul><ul><li>Be predictive: part of a closed management loop </li></ul><ul><li>Be clearly defined </li></ul><ul><li>Have visual impact </li></ul><ul><li>Should focus on improvement </li></ul><ul><li>Be consistent (i.e. should maintain significance as time goes by) </li></ul><ul><li>Provide fast feedback </li></ul><ul><li>Have an explicit purpose </li></ul><ul><li>Be based on explicitly defined formula and source of data </li></ul><ul><li>Employ ratios rather than absolute numbers </li></ul><ul><li>Use data which are automatically collected as part of a process </li></ul><ul><li>Be reported in a simple consistent format </li></ul><ul><li>Be based on trends rather than snapshots </li></ul><ul><li>Provide information </li></ul><ul><li>Be precise – be exact about what is being measured </li></ul><ul><li>Be objective – not based on opinion </li></ul>
    7. 7. Quantitative techniques Qualitative Data Quantitative Data Types of Data
    8. 8. Descriptive statistics Data Information
    9. 9. Descriptive statistics & Dashboards
    10. 10. Inferential Statistics Mean Standard deviation
    11. 11. Hypotheses Testing
    12. 12. Wrap Up <ul><li>Planning for technology </li></ul><ul><li>Implementing technology systems </li></ul><ul><li>Evaluation and Control of technology </li></ul><ul><li>Descriptive statistics </li></ul><ul><li>Dashboards </li></ul><ul><li>Hypotheses testing </li></ul>
    13. 13. <ul><li>Boynton, A., & Zmud, R. (1987). Information technology planning in the 1990's: Directions for practice and research. MIS Quarterly, 11 (1), 59-71. Retrieved from Business Source Complete database. </li></ul><ul><li>Cooper, D.R., & Schindler, P.S. (2003). Business research methods. New York, NY: McGraw-Hill Irwin </li></ul><ul><li>Kroenke, D. (2009). Using MIS. New York, NY: Pearson Prentice Hall. </li></ul><ul><li>McLean, E.R. & J.D. , & Soden, J.D. (1977). Strategic planning for MIS. Hoboken, NJ: Wiley-Interscience, </li></ul><ul><li>Neely, A., Richards, H., Mills, J., Platts, K., & Bourne, M. (1997). Designing performance measures: A structured approach. International Journal of Operations & Production Management, 17 , 1131-1152. Retrieved from MasterFILE Premier database. </li></ul><ul><li>Raghunathan, B., & Raghunathan, T. (1989). MIS steering committees: Their effect on information systems planning. Journal of Information Systems, 3 (2), 104. Retrieved from MasterFILE Premier database. </li></ul><ul><li>Rainer, R.K., & Turban, E. (2009). Introduction to information systems: Supporting and transforming business (2nd ed.) Hoboken, NJ: Wiley </li></ul><ul><li>Wheelen, T.L., & Hunger, J.D. (2006). Strategic management and business policy. New York, NY: Pearson Prentice Hall. </li></ul><ul><li>Whyte, J., Bouchlaghem, D., & Thorpe, T. (2002). IT implementation in the construction organization. Engineering Construction & Architectural Management ,9 (5/6), 371-377. doi:10.1046/j.1365-232X.2002.00266.x. </li></ul>References