Volume 14, No 1, 2017
The Role Of Manufacturing Finance Applications In Driving Predictive Analytics For Improved Vehicle Production And Cost Efficiency
Shakir Syed , Vishwanadham Mandala
Abstract
Manufacturers today are dealing with data on an unprecedented scale. As data volumes grow, manufacturing finance and IT organizations are challenged with how to best capture and deliver value through real-time visibility. Understanding and interpreting the massive, ever-expanding data ensemble generated in modern manufacturing and procurement helps executives grasp the real cause-and-effect relationships by which companies can execute process enhancements that, in turn, drive competitive advantage. In the world of manufacturing and production, cost visibility and predictability are paramount. Manufacturing finance applications and their development of new predictive analytics are therefore not merely the latest wave in business improvement for the production and service manufacturer; they are essential for survival. Unattuned business models for manufacturers increase their vulnerability in responding to disruption. In addition to the rise of serial supply chain risk, manufacturers have seen many dramatic legislative and regulatory changes over recent years, enacted to curb or even prevent a repeat of the disasters receiving much publicity. This is a direct result of the oft-repeated cycle of being driven by the imperative of achieving liability cost reductions and accelerating profitability, and thus beginning to undervalue the current systems for control and re-establishment of key performance indicator objectives. In zero-sum terms, it is somewhat obsolete for businesses to concentrate solely on production cost reductions via better capital utilization, thus leaving the rest of the prime price impact versus direct cost leverage. This leads to a decidedly shortsighted approach to production activities. The reasonable first step is to adopt performance-based finance applications in manufacturing, bring real-time visibility, minimize risk, increase predictability, reduce costs, and install a safety network that enhances long-term planning, compliance, and responsiveness. These help position manufacturers as the low-cost, high-quality, high-flexibility producers of choice.
Pages: 105-116
Keywords: Manufacturing finance, automotive, TA costs, big data, predictive analytics, and cost forecasting..