Most companies are sitting upon a goldmine of unutilized supply chain data that has the ability to give organizations a competitive edge, according to a white paper released by logistics company DHL.
While this wealth of supply chain data already runs the day-to-day flow of goods around the world, the white paper documents a small group of trailblazing companies that are using this data as a predictive tool for accurate forecasting.
“The predictive enterprise: Where data science meets supply chain” is a white paper authored by Lisa Harrington, President of the lharrington group LLC that was commissioned by DHL to identify the opportunities available to companies to anticipate and even predict the future. It encourages companies to get ahead in their business and direct their global operations accordingly.
Data mining, pattern recognition, business analytics, business intelligence, and other tools are coalescing into an emerging field of supply chain data science. These new intelligent analytic capabilities are changing supply chains – from reactive operations, to proactive and ultimately predictive operating models.
Blueprint for the next-generation global company
The implications extend far beyond just reinventing the supply chain; they will help map the blueprint for the next-generation global company – the insight-driven enterprise.
“The old ways of doing business are changing as a result of data analytics. No longer can companies run their businesses by looking through the rear-view mirror – they must now look ahead and use the supply chain data available to them to foretell the future if they are to keep up with the competition. Technology has provided a new means to achieve that possibility.
“In any global company, the supply chain is one of the largest sources of big data. It carries and produces information that affects almost every area of the business. However, most businesses do not tap into this potential treasure-trove of information effectively, despite the fact that they recognize the potential value of doing so,” said Lisa Harrington.
While supply chain analytics technologies and tools have come a long way in the last few years, integrating them into the enterprise is still far from easy. Companies typically progress through several stages of maturity as they adopt these technologies. The descriptive supply chain stage uses information and analytics systems to capture and present data in a way that helps managers understand what is happening.
Descriptive tools have been effective in helping companies cut costs and eliminate waste in their supply chains, but leading companies are moving beyond the descriptive phase towards a more predictive supply chain. The predictive supply chain allows companies to start to sense and shape demand, streamline networks, and improve agility and responsiveness. Essentially, the predictive supply chain is a vital underpinning of a re-imagined, predictive enterprise.
Gary Keatings, Vice President Global Solutions Design Center of Excellence and Product Development, DHL Supply Chain, said, “A good way of thinking about the opportunities supply chain data provides is comparing it with the maintenance of cars. Historically, drivers would visit a garage when their vehicle broke down, then came regular checks to identify problems before they deteriorated.
“Nowadays, smart vehicles are providing diagnostics in real-time. By working collaboratively with our customers we can help them set up a similar curve in the supply chain context. Through data analysis we can run a diagnostic that identifies existing trends and constraints in the supply chain, and use it to predict future pain points or failures caused by shifting demand patterns. Through better prediction of demand we have seen companies successfully cut 20 to 30 per cent out of inventory, depending on the industry, while increasing the average fill rate by 3 to 7 percentage points.