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H2 Cost Driver Map and Analysi s

H2 Cost Driver Map and Analysi s

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H2 Cost Driver Map and Analysi s

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  1. H2 Cost Driver Map and Analysis Table of Contents Cost Driver Map and Analysis 1. Context 2. Cost Driver Map 3. Cost Driver Analysis Appendix A - Replica of Cost Driver Map Appendix B - Collection, Classification, Industry Comparatives

  2. 1. Context This tool was created as part of a telecommunications Analysis, with no red issue and a client of questionable enthusiasm. The intention was to capture overall cost information in one easily reviewed presentation format. With 46 systems in 9 major families, tended by organizationally and geographically dispersed groups, the complexity of the situation lent itself to a full-size wall display, described below. The cost collection and analysis required to develop the display is also discussed.

  3. 2. Cost Driver Map The Cost Driver Map was a visual matrix representation of the spending by activity (development, maintenance, support, processing), for each of the relevant system families. A Cost Driver Map can be created when cost information is either available or collectable by system (the major determinant of collectability is whether individual system data is available from the data center). The purpose of the Cost Driver Map was to: - visually display overall spending by activity for each major system family - aggregate costs by system and activity - estimate "hidden" systems costs - show the major organizational units that spend system dollars - identify areas of opportunity by system and activity Major features of the Map include: - showing the level of spending for each system and each activity for the three major organizational units - indicated by colored squares within the matrix - providing total spending by system and activity- something that the client was not aware of - providing a framework for how $ are spend - indicated by the rows and columns as well as by summary pie charts placed next to the matrix - a list of assumptions for cost allocations made • highlighting areas to investigate for improvement - indicated by eyeglasses placed within the body of the map • The Cost Driver Map (shown in Appendix A) was used during presentations to frame the total cost bucket as well as lead into the opportunities for improvement.

  4. 3. Cost Driver Analysis The cost driver analysis provided the basis for the development of the Cost Driver Map. The analysis, required to develop a system support business case, was driven from the financial framework. Costs were determined for each category on a system-by-system basis through project manager/lead interviews and client documents Once costs were collected and classified, comparative percentages were applied to determine a range of cost savings possible. This range provided an overall framework for the benefits included in the business case.

  5. Appendix: AReplica of Cost Driver Map

  6. Cost Driver Map Example Who is paying for systems? What are the toal cost? How are we spending our dollars? Requires further investigation

  7. Appendix B:

  8. Appendix B contains a description of the aspects of collecting and classifying costs, as well as the use of industry comparatives to develop cost saving opportunities. • Appendix A: See attached file called Sample Cost Driver Map • Appendix B • Systems Cost Analysis • Collection and Classification The two most important aspects of the cost driver analysis are completeness and classification.

  9. Appendix B: Completeness Completeness is the art of collecting all the costs associated with systems. In most environments, less than 1/2 the costs of systems is accounted for directly. The other 1/2 represents hidden costs - a major source of opportunity. If possible, costs should be collected for at least two previous years plus the current year's budget. In this analysis, only data for the prior year could be analyzed because data came from a variety of sources and organizational changes made year-to-year comparison difficult.

  10. Appendix B: Spending Census The Spending Census, an IT discipline document, is being constructed to ensure that all systems costs are considered in the financial framework. A key completeness check for systems costs is that technology, personnel, and outside service charges have been considered for each category of costs (see below).

  11. Appendix B: Classification Classification is the art of grouping I/S costs into categories that foster comparative analysis and recommendations. Presently, the key classifications are IT Planning and Support, Systems Development, Maintenance & Enhancements, Production, User Support and End User Computing. Every systems cost should be separable into one or more of these categories. Depending on the engagement, Maintenance and Enhancement may need to be separated into Adaptive, Perfective and Corrective Maintenance, defined as follows:

  12. Appendix B: Definitions - I/T Planning and Support - All costs associated with I/T strategic planning, administration and support - Development - All costs associated with creating a system that allows the capture of new data (see Adaptive Maintenance) - Maintenance & Enhancements - All costs associated with modifying and/or enhancing existing systems - Adaptive Maintenance - All costs associated with adding/changing system functionality. The major difference between new development and adaptive maintenance is the amount of new data the system is capturing. If the amount of new data is significant, then the system is new development; if not, the system and associated costs should be classified as adaptive maintenance. Clients will often categorize projects as new development simply because they have a dedicated development team for the project. - Perfective Maintenance - All costs associated with upgrading versions of hardware/software based on vendor releases - Corrective Maintenance - All costs associated with fixing bugs in existing systems - Production - All costs associated with operating or processing systems. Primarily data center costs plus hardware purchases for minicomputers and peripheral hardware outside the data center. It is often difficult to separate production costs from end user computing costs. The most important differentiator is the percentage of the cost dedicated to accessing shared and structured data versus accessing either personal or unstructured data. - Systems Support - All costs associated with assisting and/or training system users. This number is often difficult to obtain since support can occur almost anywhere in the organization. - End User Computing - All costs associated with the installation and support of tools that allow users to increase their personal productivity. This includes the network costs that enable users to exchange data and electronic mail messages. This number is also difficult to collect.

  13. Appendix B: Industry Comparatives Industry Comparatives can then be used to develop cost saving opportunities. The first comparative, M&E/P, expresses Maintenance and Enhancement spending as a percentage of Production. The cross industry average is 38%. Therefore systems (or systems organizations) with M&E/P > 38% should be investigated to determine the extent of cost saving possible.

  14. Appendix B: percentage of Production spending The second comparative is Support as a percentage of Production spending. The cross industry average is 14%. Again, if S/P > 14%, further investigation is required.

  15. Appendix B: dropdown percentage The third comparative is the development dropdown percentage. This compares development in year n with the increase in production from year n to year n+1. The cross industry average is 45%, which means the total production costs in year n+1 should increase by 45% of the development cost in year n. Again, if >45% the difference should be investigated.

  16. Appendix B: project future system support spending It is possible to project future system support spending if reasonable estimates for future development plus growth in planning and end-user computing spending can be derived. The cost saving opportunity can be determined by showing the future cost of maintaining current percentages vs. migrating current percentages to cross industry average.