Several factors will drive the next generation warehouse, including a drive for more visibility.
By Matt Davidson
Supply chain operations are largely based around when events are expected to happen in a controlled environment, with little or no ability to react in real-time to the millions of micro disruptions that may occur. These daily disturbances, even as simple as delayed arrival of a shipment due to traffic, create billions of dollars of lost productivity every year in the supply chain.
As the perception of supply chains shifts from a cost burden to a competitive differentiator, optimization and efficiency have become essential to success in today’s world focused on fast delivery. To support this transition, the importance of real-time data and analysis is rising rapidly.
Moving Garbage In and Out
The vision towards the future of the fully autonomous warehouse is simply not there yet (with some very high-profile prototypes as exceptions). In the meantime, many operators are taking a step-by-step approach to increasing efficiency and improving operational insight through data-driven analysis to solve specific problems. This explains why Forrester predicts the broadly titled “IoT Solutions” market will reach over $400 billion by 2023, with inventory and supply chain management responsible for over a quarter of that.
Both human and machines’ decision-making capabilities are narrowed due to the quality of data available. By leveraging the advances in sensor technology to allow quicker, lower-cost deployments, operators can collect a wider range of data, such as visual and spatial, at a much lower cost than past solutions. The ability to collect data at a large scale, with higher quality and better context, has the power to release artificial intelligence to manage real-time operational decisions in logistics.
Where Should You Begin?
Loading docks are an obvious place to start when looking to enhance operational efficiency, given that all goods are transferred through them. Inefficiency and lost productivity at the dock have been estimated to cost in the billions of dollars per year in the United States alone.
To increase visibility into truck dock operations, there are a variety of solutions that allow sensors and other devices to be placed there, to monitor dwell time and feed information back to the dock scheduling systems in real-time. Some of the more interesting solutions go one step further by taking a visual approach to monitoring both inside and outside the truck dock, then using artificial intelligence and visual analytics to analyze the efficiency of every event and asset while the truck rests at the dock.
While these solutions provide significant value as standalone deployments, the output can be transported back into transportation and warehouse management systems, which creates an opportunity for productive adjustments and task prioritization based on the real-time data from the truck or distribution center.
Activity and Productivity
Another valuable use-case in the logistics center is worker and equipment monitoring. Workers can suffer from periods of inactivity due to the unavailability of key equipment to complete a given task, similar to the truck “dwell time” issue mentioned above. Today’s technologies are finally enabling highly accurate GPS-like information indoors. With the ability to determine the locations of both people and assets, workers can be paired with available, optimal equipment to accomplish their task in the least amount of time.
Further, worker and equipment paths can be analyzed over time to see broader patterns and density. Machine learning can identify “hot spots” and “cold spots,” providing insight into better resource distribution and inventory location.
What’s To Come?
These are just a couple of ways that real-time data can begin to transform warehouse operations, but this is only the beginning. As more data is collected and analyzed about the actual real-time physical space, the data will enable instant adjustments to priorities, tasks, and assignments in response to “on the ground” conditions, generating significant productivity and efficiency improvements.
Matt Davidson is the vice president of Product and Marketing at Locix, Inc, a Silicon Valley-based startup focused on revolutionizing the supply chain and logistics industry through unique, cost-effective data collection and analysis. Matt has an extensive background as a product and marketing leader focused on value creation at the intersection of the physical and digital worlds – solving complex problems through data collection and cloud-based analysis. He holds a B.S. in Electrical Engineering from University of Texas at Austin and an M.B.A. from Harvard Business School.