As a tech entrepreneur, Dan Keto has a history of creating innovative companies in the logistics and labor management space. Today, he serves as president and chief technology officer of one of those companies, Easy Metrics, a provider of labor management software.
Keto is a distinguished graduate of the U.S. Naval Academy and holds an executive degree from the Harvard Business School. During his naval career, he served with the National Security Agency as a Russian linguist and cryptologic officer.
After leaving the U.S. Navy, he co-founded Integrated Management Systems, a fourth-party logistics (4PL) provider with multistate operations, in 1996. Following that company’s acquisition in 2013, Keto co-founded Easy Metrics.
Q: How would you describe the current market for labor management systems used in supply chains?
A: The overall supply chain market has shifted from a top-line growth focus, largely due to the big CapEx [capital expenditures] spend during Covid and low interest rates, to one of bottom-line growth focus. The latter requires cost optimization, which plays in favor of labor management since it is a strong technology to drive efficiencies and bottom-line savings.
We find our industry tends to perform better than the overall supply chain market during market consolidations. Even though there is a big push for automation, labor in the warehouse will still be instrumental, and optimizing warehouse performance is important. Labor management plays a critical part in making operations as efficient as possible.
Q: You have a background working with the U.S. Navy on security issues. What experience did you gain there that you bring to your work at Easy Metrics?
A: Paranoia about data! I worked with the National Security Agency, and security was taken very seriously around data. That mentality has now found its way into all areas of commercial technology. Companies have finally realized the value of data and are now focused on protecting it. When we initially designed Easy Metrics, we invested heavily in building a very robust and secure technology platform, which has proved to be the right choice.
Q: What are the major challenges distributors face in managing labor?
A: Warehouse labor continues to be tight, and I expect it to get tighter with the current administration’s immigration policies. Thirty years ago, most companies were quicker to terminate employees because you could replace them with a phone call to a temp staffing firm. Covid and societal trends have changed this dynamic substantially.
Because warehouse labor is tight, companies now are focusing more on training and coaching their employees. Labor management plays a key role in this because it gives managers a data-driven approach to identify training opportunities with their associates. In the long run, this strategy—investing in your people—is a much better approach than managing a high employee turnover rate. And although it puts more pressure on supervisors and managers to properly train and coach employees, artificial intelligence tools are making this process easier.
Q: What are the advantages of using cloud-based services?
A: It substantially reduces the upfront hardware systems and management costs and flips the model to a pay-for-what-you-use model. The cost to try to replicate what a large Amazon or Google data center can do is cost-prohibitive for most.
Also, with cloud-native products like Easy Metrics, users are always given the latest version of the software, and managing version deployments and updates becomes a thing of the past because the vendors now handle it. Cloud-native solutions have a much lower true cost of ownership than on-premise solutions. I think in 10 years, there will be few on-premise application products available due to these cost and performance advantages.
Q: In what ways can pay-for-performance and gamification aid in employee engagement and retention?
A: We are big fans of pay-for-performance and gamification. Prior to founding Easy Metrics, we ran a 4PL for large cross-docking operations. A properly designed incentive system, whether it is pay-for-performance or gamification, gets the employees focused on what’s important and gives them a strong sense of accomplishment when they do well. With the cross-docking operation we ran, we took the warehouse from last in the network to first in the network within six months and more than doubled productivity. Employee wages went up over 80% and turnover dropped by 90%.
The key is in how you design the program. A poorly designed system can create unintended consequences and actually hurt morale and productivity. The design is both an art and science, and all key stakeholders should be involved in the design process to ensure maximum buy-in.
Q: Is there one initiative you can point to that has the biggest potential to improve a company’s labor management practices?
A: Labor management is not just a technology. It is a comprehensive business practice that can help companies achieve very high results. It should be incorporated into a company’s SOPs [standard operating procedures] and should have full management engagement from the top down to the supervisors. We have consistently seen companies that take this approach reduce their operating costs by 10% to 20%, which is an amazing ROI [return on investment].
Q: With all the new technology entering the marketplace, how do you see labor management evolving?
A: We see labor management becoming even more critical going forward as new technologies come online. One of our very sophisticated customers always goes to its LMS [labor management system] data to diagnose engineering and process problems because the LMS data set is highly transformed and gives you amazing insights into your workflow.
We see LMS evolving into a more comprehensive category of warehouse performance management. If you look at all the systems in a warehouse (automation, robotics, telematics, WMS, WES, MRP, etc.), it is all time-series data. Modern systems like Easy Metrics are able to ingest and merge all of those data sets into a unified data model where each transaction is appended with cost-to-serve, engineering information, performance calculations, and profitability. This data foundation gives a facility or network of facilities full visibility down to the transaction level. Once this data model is in place, you can then layer in artificial intelligence and machine learning to find savings and performance opportunities that would otherwise take months to discover.
