Enterprise Applications Portfolio Management Utilizing COTS

Introduction Enterprise applications and their associated data offer a crystallization of business processes whose cost-effort metrics, such as Function Point (FP) method, have been well defined over the past 35 years of software engineering and development. In a typical manufacturing enterprise of medium size, the applications portfolio is sized to average 200,000 Function Points of software, which translates to 8000 man-months of software engineering effort. Desktop spreadsheet programs, by contrast, are mere 50FPs. Software development costs for enterprise applications occupy a substantial portion of investment decisions. As the investment size of information systems has grown, C-level (CEO/CFO/CIO) strategic decision-making for complex build-new, enhance-existing, and retire-obsolete processing hardware-software operations is necessitated. Today, new product introductions must take place each quarter, minor adjustments in sales strategies are frequent, and strategic alliances for completing smooth-lined supply chains are forged. Such a management environment demands a rapid reflection of changing business processes in the implementation of information systems. Sales divisions require speedy updates of system services, but investment priority decisions often yield distorted service offerings to end users. As a result of limited information system budgets, this time-race is, all too often, not won. Practitioners often resort to budgets "proportional to revenue amount," but little correlation can be expected between "revenue size" and "system investment amount". Once an industry benchmarking of information system expenditures is considered to reveal a high correlation with "net earnings", a homogeneity of industry members can be established, but stakeholders are more likely to notice a lack of unique efforts on a management team's behalf. Return-on-investment (ROI) analyses of discrete IT projects have been worked upon by virtually all IT consulting firms, but a decision- making framework to tackle the issue of IT projects portfolios is nonetheless necessitated since decision-makers lack a tool for investment optimization that integrates discrete cost and return estimates with timing decisions. Toward this purpose, to grasp the total project cost, we should include, for example, end-user activity-based cost improvements resulting from IT improvements. Additional traditional estimates of total cost of ownership (TCO) consist simply of development and maintenance costs. We should also valorize development speed in cost evaluation, considering the man-month equivalency of the time savings which results. Applying these considerations, software of traditional development projects and the large-scale commercially off-the-shelf software COTS can be applied to portfolio configuration decisions. An estimation of investment returns requires templates for process definition in order to keep it immune from fluctuations caused by individual characteristics. We often witness the contingent fee bonus method for rewarding business strategy success. This suggest that the evaluation of project returns should be flexible to accommodate Real Option methods over and above the standard Net Present Value/ Discounted Cash flow valuation methods. With the Real Option method, we are able to valuate each selection of a decision tree in a high uncertainty environment, and furnish documented rationales for selections made. Applying Real Option Evaluation, we can limit the evaluation horizon to a few years for practicality and period of present-value, discounting accordingly. In addition, as this option is exercised, the retirement of related portfolio elements can be considered and decided. Real Options valuation can be applied to delaying, phased implementation, enhance/scale-down, abort, resume, disposition, combining project, and combining options. We will focus on project staggering and disposition decisions with DCF adjustment. …