These days, logistics and supply chain management is the key to success for every global business. As recent headlines have proven though, it can also be an Achilles heel as well. That’s one of the reasons that SAP has introduced an entire product line to assist their ERP customers with managing their complex supply chains.
That kind of tight integration into ERP systems has brought the power of big data and analytics to bear on supply chain management, which is enabling new levels of efficiency across the globe. Supply chain management does pose some challenges to analytical modeling, though. That’s because there are far more elements that must be included in forecasting models that are outside the realm of control of the business than is typically the case in other big data applications.
The Elements of Chance
There are some elements of supply chain management that lend themselves well to statistical modeling. Things like material availability, usage patterns, and historical lead times are all easy to use as data points for predictive analysis. What isn’t so easy, however, are things like unexpected traffic delays in shipping and disruptive accidents all along the chain. Of all unpredictable factors though, nothing has more power to create wide-scale supply chain disruption than weather.
Weather is such a large component of supply chain risk management that it is consistently ranked in the top ten of issues identified by logistics managers. The risk is so great, that billions of dollars are spent each year on contingency plans designed to deal with unexpected weather events. It’s an inefficiency that has long been accepted as a cost of doing business that can’t be avoided. That may not be the case for much longer, though.
Existing Technology Meets the Cutting Edge
To date, there have already been several attempts to integrate weather data into ERP supply chain management systems. So far, this has involved real-time weather reports and has not included predictive models. For ERP software to acquire the right data to utilize for predictive weather analytics, it needs something to act as a bridge to some old-school technology, like radar.
When most people think of radar, they likely think of the simple displays they encounter when watching the local news, but the technology is far more advanced today than many realize. In fact, even today’s best radar detectors are a higher order of technology than some of the weather radar systems of a few years ago. The newest weather radar systems are incredibly sensitive, and when combined with the latest in satellite weather analysis, they offer a reliable data source for ERP data analysis.
GIS and ERP Bridge the Divide
The feat of bringing predictive weather analysis into the ERP market could be a game changer for global supply chains. That’s why the recently announced partnership between SAP and Esri has the potential to fundamentally alter how businesses deal with the weather as a factor in their supply chains. Esri’s flagship ArcGIS geographic information system has already been put to use by partner Weather Decision Technologies (WDT) to create an advanced, cloud-based, weather analysis system. Esri’s new partnership with SAP might soon provide a native integration of WDT’s platform into SAP’s supply chain management systems.
The Future of Logistics
If the convergence of SAP software and Esri’s partner network bears fruit, it could lead to billions of dollars in savings through enhanced supply chain efficiency. In the modern global economy, that could be a critical advantage that no company can afford to miss out on. Gaining a measure of certainty about one of every supply chain’s most unpredictable elements would go quite a long way towards continuing downward pressure on costs in an era of increasing demand and flat economic growth. That kind of analytical insight may well become the big data-driven crystal ball that changes logistics forever.
This is a featured post by site supporter Andre Smith
Photo: Getty Images