Recently I had a morning appointment at the depot of a utility company. Parking spaces were limited and I barely could get rid of my car, as the parking lot was full of service trucks from the field service crews. They were there to pick up the parts needed to complete the jobs on their work schedule for that day.
They had left early morning from their hometown and they may have had some traffic jams before reaching the depot. Later, after the coffee, when they had loaded the parts into their service trucks, they were able to leave and head towards the location of their first assignment. If the traffic would hold for a while, they would be able to complete the first ticket before noon.
Utility companies, telecom providers, installation companies and equivalents have one thing in common: for their business activity, they have to rely on a large service team traveling to the locations of their assignments with a service truck. A large part of the available working time is spent “on the road”, so the job scheduler has the difficult task of distributing the jobs optimally so that the time spent working represents the largest part of the available working time. In a production environment, OEE (Overall Equipment Efficiency) is often used for this purpose, whereby the machine assignment and order sequence are planned optimally, and where the largest part is used for production, where another part is used for maintenance or breakdowns, another part for changeovers, etc. Where in a production environment, a number of techniques are used to minimize the changeover, techniques can also be used to minimize the “travel time” (read: the changeover time between 2 jobs) of a service team.
The first thing that comes to mind is the travel time that service teams use in the morning, when driving from their homes to the depot, and later from the depot to the location of the first assignment (sometimes even close to their homes). It would be a noticeable improvement if we could eliminate even half of these trips to the depot. The service team could for example drive in the morning directly from the place of residence to the location of the first assignment (if possible near the place of residence). Practice shows that service teams can easily have an extra hour of effective work time available this way, especially if the depot is in a somewhat urbanized area. The only question is: how do we ensure that the service teams get the necessary parts onboard so that they are able to perform their assignments?
We want to suggest 3 concepts for managing supply efficiently.
All concepts have proven to be operationally effective (and efficient) in operational circumstances.
1. Overnight supply delivery
A first way is to deliver the parts to the service truck at night while it is parked in front of the driver’s home. In this concept, each team’s schedule for tomorrow is completed around noon today. This leaves plenty of time to determine what parts the team will need, and to pick those parts from the warehouse. An Overnight Delivery Service (ODS) picks up each team’s parts (in separate crates) at the depot by the end of the day. Via the ODS’s distribution center, ODS supply trucks deliver the crates to the customer’s service trucks at night. The ODS driver has a key or a security code for the service truck, so that they can open it and can transfer the crates via the cargo door of the van. In the morning, the service team can leave their residence with the service truck, directly to the location of the first assignment, and equipped with the components for the assignments of the day.
2. Unmanned hubs
A second way is to set up a number of unmanned hubs, supplied by the central depot. These hubs act as transfer points for parts. Their location is chosen in such a way that they can be reached by the service teams with a minimum of travel time. They are located close to where the service teams live, or close to the locations where the jobs need to be executed, or close to both.
The hubs are unmanned. Access is granted to the service teams via their staff badge (or alternatively, via e.g. a smartphone). The service team retrieves the crate(s) intended for them from the hub. They may also be able to return items to the central depot if they don’t need it anymore. If it concerns valuable parts, the crates can also be made available to the service team via lockers. The service team then only receives the access codes for their locker(s). In these unmanned hubs, service teams can resupply grab-and-go items, a small number of which are stored in their service trucks anyway.
To conclude this concept, we would like to state that ideally the hub can be housed in an (existing) building. If not available, a 40-foot refurbished container can also serve.
3. Fewer visits to the central depot
A third approach is based on the principle that a substantial portion of service trucks no longer need the supply of specific parts for the jobs for the next day. The company can classify all types of jobs, and a large number of them can be executed with a standard set or kit of identical parts each time again (e.g. the installation of utility meters). All the service trucks that do these jobs are supplied on a weekly basis and are not given any jobs other than the ones they can do with the on-board kits. Thus, they do not have to go to the depot every morning to get supplies. In this way, only the service trucks that do not execute standard jobs have to get supplies. These latter service trucks are often only a fraction of the total number.
As you can see, there are several ways to improve efficient access to parts. Depending on the specific situation, a certain approach is preferred. The key lies in being able to bridge the distance between the service team and the stock in an optimal way.