The Easy Metrics team returned from this year’s Modex in Atlanta very excited about the transformation taking place in the Supply Chain industry. The datafication of the supply chain is firmly under way which opens up tremendous opportunities as well as competitive challenges. It has been our thesis since we started the company that the industry needs to move beyond single data source analytics and towards integrated and correlated data set analysis. IoT (Internet of Things) is a real game changer and the importance of good analytics is rising to the top of importnance in the industry. Over the next series of blogs we will discuss the various new data sources coming on line and how we are using them for our clients to give visibility into their operations they have never had before and drive real change and performance improvement.
The recent industry focus has been on datafying as much as possible. In transportation, the federal government mandated that all commercial vehicles have a telematics system by the end of 2017. Telematics are now becoming common on material handling equipment. Automated conveyor systems have complex WES systems that track and route products in the warehouse. Employee wearables that track hundreds of movements each second are available. Soon we will see drones enter the warehouse with RFID readers that can scan all of your inventory in minutes. Robotic caddies roll along with pickers to assist them in their efforts. New WMS systems now can use iPhones as their scan guns versus traditional RF systems. iPhones have a wealth of information that comes native with the system.
The industry is seeing an exponential growth of data as profound as what we are experiencing in our personal lives. The challenge though is what to do with all of that data. It seems the focus of each system is to continue to come up with as many data points as you can measure without any real contextual understanding on how that data can be applied and of what value it is. This is a classic engineer paradigm. If 10 data points are good, then 100 data points must be 10x better. Unfortunately that is not the case. In our review of many of the BI tools that these data providers have applied to their data systems, they fail to solve real business problems. This is not the fault of the engineer. Their job is to datafy the system and they generally lack the operational experience of those that use the equipment in their daily work routine.
The next phase of development we see is the application of that data to solve real world problems. For our industry, we call this Performance Analytics of Supply Chain Operations. This is the marriage of deep operational understanding of the supply chain with the data sources available. The result is highly useful information that distills all the data into actionable information for the company. These analytics will need to integrate and correlate these disparate data sets, something Easy Metrics has really focused on the last few years.
An example of this method is merging forklift telematic data with WMS data to calculate true time spent traveling versus estimated time. Instead of developing expensive and high maintenance discreet travel standards, why not just use the travel distance/time on the forklift data and eliminate that requirement? That data is more accurate and calculated distance and eliminates an expensive engineering cost.
In future blogs, we will discuss how we have integrated and used various data sets. As well, we will show the predicted evolution of performance analytics from the current descriptive analytics to prescriptive analytics then eventually to predictive analytics. We live in exciting times!