Supply chain management has been slow to leverage advances in data science. It's time to play catch up. Although supply chain management has been slow to the game, advances in data science are now quickly changing the way supply chains are managed. With free and powerful tools like Python and R now routinely being used to solve some of the most complex business problems, as evidenced on the data science competition site Kaggle.com, the days when you could develop deep insights and competitive advantage using spreadsheet models are long gone.
Industry 4.0 is quickly becoming a reality, transforming not just production processes but also the way logistics managers operate. Experts say we’ve reached a tipping point in technology, with rapid adoption forcing changes across the supply chain. Data-driven strategies, involving robotics and the internet of things (IoT), are now commonplace.
As consumers increasingly turn to e-commerce for all their shopping needs, speedy fulfillment isn’t just a “nice to have” — it’s the expectation of every online shopping experience. And if logistics companies and their retail partners want a shot at thwarting the ever-looming threat of Amazon Prime, it needs to be a priority.
Reaping the benefits of a technology-based supply chain used to be a luxury reserved only for the biggest enterprises. But buoyed by IT advancements and increasingly complex market conditions, businesses large and small are now getting in on the game.
Global logistics spending is expected to reach $10.6 trillion in 2020, with transportation accounting for the majority at 70 percent. Emerging technologies such as cloud computing, big data, and crowdsourcing, coupled with an influx of tech-savvy start-ups, are unbundling the value chain and transforming delivery models. Those are among the conclusions in Frost & Sullivan’s recent analysis, “Urban Logistics Opportunities—Last-Mile Innovation.”