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instituting kanban countermeasures Implementation of smart data and arti cial intelligence methods, within the SOE paradigm, could solve many of these perceived backorder delays in customer wait time This case demonstrates that modeling an enterprise, such as the DLA, is not an end game We show that modeling is a vital step that is made relevant in context with the enterprise engineering discipline and the SOE paradigm that accounts for dynamic relationships between governance, processes, data, and enablement The case further illustrates our concern, from an executive perspective, that applying the engineering discipline to an enterprise is a big effort that never ends Enterprise executives, such as those found in the DLA, are equipped with the disciplines and strategy for optimizing performance However, they must parse the days such that they are making the right tactical decisions while guiding the ship on the right course We want executives to embrace the idea that they need an enterprise performance optimization support system that serves them both tactically and strategically Our case gives an example of how behavioral perceptions can cloud decision making that would be better served by applying the correct methods and algorithms We show that a perceptual system is the manifestation of a need for enabling technology that embraces a smart data strategy implementation Getting the enterprise performance optimization support system in place requires rapid execution such that its daily service to executives justi es its continuous development and re nement Our case study illustrates how improvements are needed by the DLA and how adoption of the three legs of the smart data paradigm will help them to improve their processes We show that a war room mentality is not a substitute for a smart data strategy We want the DLA to adopt our smart data strategy to encompass a method or algorithm to which they can point and say this or that is serving me well or not so well, so that IT professionals can address improvements with precision and ef ciency Algorithms and methods are needed to accomplish these tasks, not a bullwhip effect While what goes on in the IT background is necessarily complex, we cannot let the complexity interfere with the necessity for executive clarity in executing complex responsibilities There has been much interest in coordinating these complexities among the manufacturers, distributors, wholesalers, and retailers in the supply chain management In this case, we studied the behavioral misperceptions of feedback due to information distortion and distorted demand signal processing from a war room and compared un lled backorders from operational time delays and lead-time variability involving forecast error, during replenishment lead time A Bayesian network was employed to show that items perceived to be on backorder were in fact no more likely than any other item to increase customer wait time This phenomenon is called the bullwhip effect because of the rippling panic that can occur in distribution channels when there is a real or perceived shortage of a product In industry, such distribution quirks happen frequently, but they rarely trickle down to the consumer level
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These largely psychological panics typically unwind when consumers regain con dence that supplies remain plentiful However, in a war room environment, perceptions of a time delay in un lled backorder, which do not exist at the operational level, give false feedback that shortages exist, when in fact the operational supply chain is robust Because the war rooms are dominated by feedback from high ranking decision makers, these misperceptions, due to distorted signal processing, are elevated to a level that sends a reverse ripple effect through the supply chain This reverse bullwhip effect leads to a bull in a china shop syndrome, where a high-level decision-making consumer sends reverse ripples, upstream through the supply chain Left unabated, the supply chain will react in a manner that is not indicative of the true picture and show variations between orders and sales that do not exist This case study illustrated possible problem types within the DLA The case illustrated a de ciency in leadership and integration by relying on a war room mentality, whenever an algorithm mechanism shows contrary results There was also a de ciency in mission, values, policy, regulations, and rules The hardware, software, databases, and communications systems of the system were working well; it was the failure of the people, following policies and procedures of the system, to listen to the smart data, which led to poor decision making A de ciency in strategy, framework, planning, sense making, systems, skill, pro ciency, execution, balance of consequences, tools, equipment, processes, infrastructure, and organization were evident as sources of errors in determining backorder aging These customer wait times would have been decreased through the various opportunities of better use of capital, better use of people, better use of technology, better use of materials, and better competitive advantage The importance of supply chain management (SCM) cannot be overemphasized SCM is the tracking and coordination of the ow of material, information, and nance in the supplier customer network We present an empirical study of the determinants of backorder aging for the Battle eld Breakout Backorder Initiative (B3I), which studies the effects of the ow of material, information, and nance through the main supply chain agents: supplier, manufacturer, assembler, distributor, retailer, and customer Since supply chains are complex systems prone to uncertainty, statistical analysis is a useful tool to capture their dynamics By using statistical analysis of acquisition history data and case study reports, regression analysis was employed to predict backorder aging using National Item Identi cation Numbers (NIINs) as unique identi ers Over 56,000 NIINs were identi ed and utilized for our analysis The results of this research led us to conclude that it is statistically feasible to predict whether an individual NIIN has a propensity to become a backordered item There are two types of applications in an SCM system: planning and execution Planning applications use statistics and advanced algorithms to determine the best way to ll an order Analysis of overhead times obtained from each of the suppliers can be used to nd the fastest resource for their needs On the other hand, execution applications implement the day-to-day activities of the supply chain ows They track the physical status of goods, the management of
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