Developments in Big Data in Supply Chain and Logistics
Supply chain and logistics experts were hard at work managing data long before Big Data and analytics became staples in every other industry. Today, they remain at the forefront of analytics-driven decision-making, with Big Data capabilities fueling a digital transformation.
Supply chains are incredibly complex, and the market is generating unprecedented data stores. Transactions, social media, mobile technologies, and storage and shipping sensors record a seemingly never-ending stream of information. With both internal and external data available to drive supply chain insights, the industry is evolving in tandem with technology. Data storage capacity and efficiency increase daily, and ever-more sophisticated hardware and algorithms support processing upstream and downstream. New devices are entering the market, and new solutions to old problems are cropping up everywhere. These ongoing developments represent both disruptions and evolutions in the supply chain and logistics world.
The Internet of Things
A range of IoT solutions are now being deployed to monitor and collect data along all links of the supply chain. New networked and cloud-connected devices are eliminating blind spots in the flow of goods, allowing for greater efficiency and increased transparency. The data can be used to track real-time intelligence and identify failure points and areas for improvement. Over the next year, we will likely see more pressure from governments and the public for visibility into the sources, production and distribution of the goods in the market. With new IoT tools, companies can collect previously unavailable data to develop a verified map and provide an accurate, holistic image of their supply chain to critics and consumers.
Big Data Analytics is moving warehouse management beyond RFID. New visibility platforms offer more complete insight into stocking and locations. IoT innovations are also driving new strategies: Managers can now review feedback from position sensors for on-shelf availability alongside SKU levels and BOMs. Rigorous warehouse tracking can also manage risk to unlock significant cost savings. The additional oversight can protect businesses from damage to their reputation, such as that caused by distributing spoiled or damaged goods.
Forecasts and predictions
Predictive analytics evaluates historic and real-time data to determine the likelihood of future events. Better, more robust data reserves can be used to estimate lead times based on everything from traffic and weather conditions to booking, container event and vessel voyage data. It can provide evaluations of real-time marginal costs from different channels. Up-to-the-moment optimization solutions can also analyze and model ongoing multi-stream sensor signals to optimize decision-making strategies. By reviewing long term simulations and forecasts of end-to-end production and shipping, logistics teams can select the best options for their business based on statistics and probabilities rather than guesswork or gut feel.
PK’s Analytics Practice helps organizations harness the power of data and convert it into information for better decision-making. Learn more about our services and some of our successes.