Marked technological advancements during the past decade equipped supply-chain analysts with the power to glean deeper data detail and create more sophisticated supply-chain modeling. Today's experts tap into this new generation of data to help companies reach beyond supply-chain cost reduction to address the most prevalent logistics pressures in the marketplace - unyielding demand for faster delivery and better service. Compounding the challenge is a parallel demand for human capital and a level of expertise only gained through day-in and day-out analysis of supply-chain data produced in an ever-changing business environment.

As we approach 2020 and the quantity and quality of available data increases, analysts are focused on developing more meaningful metrics to target areas of improvement that boost efficiency and profitability for their clients. Detailed SKU-level data becomes even more critical to inventory management and service-level programs that effectively position the right products in the right place at the right time. Capacity to meet unprecedented service and delivery expectations will define a company’s ability to compete. In this environment, it's no longer sufficient for companies to complete optimization-driven supply-chain network reviews on a cyclical basis. Instead, an essential shift toward a more continuous analysis process - for network design, transportation and inventory - enables companies to implement data-driven adjustments to market changes. As companies establish data and analysis centers of excellence, the resulting supply-chain flexibility becomes the key to competitive advantage.

The Outlook

Looking ahead, the ability to leverage non-structured data in progressive ways will continue to set the stage for improvements across the industry. Forecasting and simulation capabilities will advance, giving rise to predictive strategies for mitigating risks caused by market forces, weather, traffic or natural disasters. Meanwhile, as first- and second-generation supply-chain designers and optimization practitioners retire and demand increases for their services, industry talent likely becomes limited and concentrated within 3PLs and consulting companies. To address the talent gap, more large companies relying on supply-chain and business-analysis expertise will partner with universities to groom the next generation of professionals. This trend likely extends to partnerships involving optimization software providers and creates teaching opportunities that focus on analyzing supply-chain data to produce more meaningful metrics that further enhance companies’ abilities to make network improvements.