One step ahead: How data science and supply chain management are driving the predictive enterprise

Posted on by Teddy Nee

DHL, the world’s leading logistics company, today launched its latest white paper highlighting the untapped power of data-driven insight for the supply chain. The white paper has revealed that most companies are sitting upon a goldmine of untapped supply chain data that has the ability to give organizations a competitive edge. While this wealth of supply chain data already runs the day-to-day flow of goods around the world, the white paper has revealed a small group of trailblazing companies are utilizing this data as a predictive tool for accurate forecasting.

“The predictive enterprise: Where data science meets supply chain” is a white paper 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 of 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. 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.

Jesse Laver, Vice President, Global Sector Development, Technology, DHL Supply Chain, said, “At DHL, we’re helping our customers get ahead of the competition by working with them to harness the wealth of data information from across their businesses, allowing us to develop smarter supply chain solutions that factor in their wider business operations. For our technology customers, we use data analytics to predict what’s going on in the supply chain, such as what products are in high demand, so we can tailor our solutions accordingly.”

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.

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Visibility Is Key when Driving Supply Chain Performance

Posted on by Teddy Nee

At its heart, supply chain management requires a balancing of operational efficiency, customer satisfaction and quality. Managing the true cost to serve for each and every order is the aspiration to allow better negotiation and value creation across the supply chain. Customer- and consumer-centricity helps anticipate product and service requirements. Supply chains are becoming more extended and complex with a consequent increase in risk and the need for resilience. There are multiple data sources making it difficult to manage and measure end-to-end processes and metrics. Aligning priorities through integrated planning remains pivotal, but there is an explosion of data available that needs to be incorporated and the value extracted to understand how supply and demand issues impact profit and revenue targets.

New technology provides greater supply chain transparency. Strategic supplier engagement continues to be important as a way of reducing costs and mitigating risk. Effective supply chain management can be either a compelling competitive differentiator or, conversely, a source of risk, cost and poor customer service.

Organizations are looking to enable better and more consistent decision-making across complex processes with diverse systems and data. Many are leveraging business intelligence (BI) platforms to give them the capability to make decisions across the organization, including environments in which mobility and access to decision-critical information on the go is crucial. Putting the information in the hands of the people on the front line—those managing supply chain processes—is key to enabling decision-making at the point of decision. But this requires synchronizing an enormous amount of data that comes from many systems and sources in a way that it can be easily consumed by people who need to act on the insights.

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Risk management in an evolving global supply chain

Posted on by Teddy Nee

Risk management in an evolving global supply chain

The festive season has ended, and the retailers can breathe a collective sigh of relief. Their busiest time of the year means their operations have had to be resilient and robust. The supply chain is at the heart of this and it has been used to plan the Christmas period for months. But what lies at the success of this supply chain and what lessons can be learned?

Managing a supply chain in today’s global economy is fraught with difficulties. Supply chain managers have to maintain a balance of cost, agility, and sustainability, as well as manage the logistics and the manufacturing footprint. All these issues come with their own problems, but overall the trade-off is cost versus risk.

To strike a chord between cost and performance, supply chains have to be inventive. That means essentially going out into new markets, using new local suppliers, and accessing new customers. Invention comes at a cost, as these are new, unexplored areas of risk. So risk management is an important part of supply chain management in a global context.

As organisations strive for new opportunities for a more effective supply chain, so risks are more prominent. Who is that new local supplier? Can they be trusted with your product? The new country you’re now operating from – what are the geographical risks? The political risks? The legal risks?

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