By Sarah Nicastro, Creator, Future of Field Service
Supply chain and logistics challenges have been in the news a lot the past three years, and parts availability (or lack thereof) has certainly been a challenge in the service sector. In last week's podcast, I spoke to Ivo Siebers, Senior Vice President of Global Logistics at TK Elevator about how his company has fundamentally changed the way they manage the flow of parts to technicians. Those efforts resulted in huge gains in how frequently technicians had the right part in their trunk (or readily available from the depot).
In manufacturing, supply chain management is complicated by the whims of consumer demand. Field service logistics, on the other hand, is governed by the installed base of equipment in a given industry – that makes it a little easier to predict and manage.
But knowing what equipment is installed where is only part of the challenge of service logistics. It has traditionally been difficult to forecast what parts were going to fail when, and at what locations. New technology is making it easier to analyze maintenance histories, spare parts consumption, and other data to make those predictions even more accurate. Real-time operational data can add another layer of reliability.
At TK Elevator, technicians service a wide range of elevators and escalator systems, and having the right parts on hand for a given job was a huge challenge. According to Ivo, technicians generally only had the right parts in their trunk around 10% of the time and were able to obtain them from the depot same-day for another 10% of jobs. Most of the time, they had to order parts and then wait, impacting service level agreement (SLA) compliance, first-time fix rates, and customer satisfaction.
Data-Led Approach Drastically Improves Parts Availability
Using data and analytics, the company has been able to make impressive improvements in spare parts availability. Right now, Ivo says that technicians have the right parts available 80% of the time. To get there, TK Elevator leveraged different types of data, including parts usage and failure rates. “We want to avoid breakdowns or down time of the equipment,” Ivo said. “We try to better understand our portfolio, we try to better understand each and every type of equipment that is under maintenance with us and try to use this knowledge, this big data, in order to become more predictive.”
One part of their approach has been more intelligent forecasting. The company is using the data it already has on hand about parts consumption, previous maintenance, and condition monitoring, to predict the parts the technicians are most likely going to need in their trunk stock or positioned at regional depots. That data also guides the technicians to pay close attention to certain parts during regular inspections and maintenance, so they can service those parts before a breakdown occurs.
Data analysis has played a big part in TK Elevator’s success in optimizing spare parts, but the other aspect is how the company has changed its approach to storing and delivering inventory. The technicians have access to a digital catalog of roughly 100,000 different parts that can help them accurately identify what they need. With the digital catalog, technicians can send orders directly to a central warehouse to fulfill the request instead of using the local branch office as a sort-of middleman.
“And instead of sending it to the branch as formerly done, the warehouse will send it directly to the technician. That might be a pick point, that might be the car trunk, that might be a PUDO, that might be a location close to his workplace. Wherever it suits, it'll be sent as close as possible to in order to save his travel time,” Ivo told me.
As more data is collected about the systems each technician services on their route, the trunk stock can be replenished and updated proactively, which helps reduce the number of special orders the technician has to make.
Having these capabilities can have a significant effect on SLA compliance and other critical metrics. It has also led TK Elevator to question some of its own biases and old practices when it comes to spare parts inventory. In supply chain management, inventory has been a dirty word since Lean and Just-in-Time practices came to the fore, but cutting inventory can make it hard to meet SLA requirements when you have to wait for parts.
With predictive data about what parts you are likely to need, you can improve service levels without increasing stock or obsolescence.
The key is having the right stock. TK Elevator has already cut its warehouse stock 30% while still improving SLA performance. With input from the field service operation, the ERP system, and other systems, the company has been able to rebalance inventories, so the stock is optimized based on actual utilization.
A misperception that Ivo says the company had to work around was the idea that the technicians and the depot managers would resist the new inventory management approach.
On the technician side, the worry is always that staff will see the new technology as a way to reduce employee workload or headcount. The company also feared that supervisors might feel cut out of the loop since techs could order parts straight from the warehouse.
But Ivo says that the frontline techs quickly saw the value in eliminating the aggravation of showing up on site and then not being able to complete the job because they did not have the parts. With better stocking decisions and more visibility, technicians can do a better job of keeping the customer informed and happy. Supervisors were also happy that they no longer had to manage parts logistics.
“[The technicians] feel really empowered and they took it really [as a] positive. And from the field supervisor's side, they said, "Nobody likes this task, so taking it away from us, it's great." So sometimes you are a victim to your own biases,” Ivo said.
During our conversation, we also covered a lot of ground about employee buy-in, the need for accurate data, and how TK Elevator plans to leverage condition monitoring to do a better job of predicting future part failures. You can listen to the full podcast here to find out more about how predictive inventory management can boost service performance.