automatically based on simple input from the user. This app could then be shared with others in similar jobs. A clearinghouse for GCSS-Army apps would accelerate the process of implementing GCSS-Army and would take advantage of considerable expertise that exists in the operating units of the Army. Most of us use apps on our phones from similar clearinghouses (i.e., app stores). This process could be adapted from the civilian world to meet the needs of the Army.
Finding 6-11. The Army currently has no processes, plans, procedures, funding, people or other resources aimed at encouraging the logistics community to develop and propagate apps and higher level tools using data from the Global Combat Support System-Army, the Logistics Modernization Program, or other data systems to improve the decision process.
Recommendation 6-9. The Army should take advantage of contributors at all levels to develop and distribute apps and other tools to fully realize the potential of the Global Combat Support System-Army. A concept similar to those used in commercial app stores should be implemented to distribute such tools and provide ratings for them.
Operations Research and Logistics Decision Making
The Army is investing heavily in an effort to fully capitalize on the enterprise-wide promise offered by IT. Although enormous sums have been invested by the corporate world in ERP solutions, these investments have had very mixed results (Brown, 2003). Emerging evidence indicates that it is possible to achieve dramatic improvements in performance and competitiveness with IT systems. This success, however, has only been achieved by companies that have applied IT solutions to appropriate, efficient, and mature business processes. Information (especially ERP) systems alone cannot compensate for the lack of such a business-practices. In fact, the evidence suggests the opposite, that attempts to implement IT solutions absent such a business practices actually lead to poorer performance (Heinrich and Simchi-Levi, 2005).
It is important to differentiate between (1) the purpose and functions of OR, which uses knowledge-based decision support systems, and (2) transaction-based ERP technology, which is used to acquire and process raw data and to compile and communicate accounting reports.
ERP solutions have increasingly been touted as a panacea for all kinds of corporate decision-making processes, but they lack the analytical capabilities needed to optimize the efficiency of those transaction-oriented processes.5 While ERP systems provide considerable visibility into events that have happened, they provide very little insight into why they happened, even less about what is likely to happen, and certainly nothing about “what should happen if current conditions either continue or change.” As Massachusetts Institute of Technology Professor Jeremy Shapiro observed, “Enterprise Resource Planning (ERP) is really a misnomer because it fails to provide insights into decisions affecting ‘resource planning’” (Shapiro, 2007, p. 35).
In contrast, OR has been described as the “science and technology of decision making” and can be traced to multidisciplinary teams applying several scientific methods to military operations during the early years of the Second World War.6 Over time OR has become recognized as the discipline of applying advanced analytic and modeling frameworks to the challenges of complexity and uncertainty, especially in large-scale systems and organizations. Utilizing principles from mathematics, engineering, business, computer science, economics, and statistics, OR has developed into a full-fledged academic discipline
5 See, for example, Hugos (2003), Essentials of Supply Chain Management, p. 127.
6 For additional information, see Fisher (2005), A Summer Bright and Shining; Nye (2004), Blackett, Physics, War, and Politics in the Twentieth Century; and Air Ministry (1963), The Origins and Development of Operational Research in the Royal Air Force.
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