Underline the current TOC methodologies for Operations there is a basic assumption that the available capacity exists in one location. In other words, the resources don’t move!
This assumption is, of course, invalid for transportation organizations. The meaning of ‘available capacity’ has to include two additional pieces of information:
- Is there available capacity close enough to the required starting point within the appropriate time frame?
- Where to and for how long? Are there opportunities for transport from the proximity of the destination back to the usual location? How long it takes to be available here again?
These additional variables make the business of the transportation different than the environments TOC has been established in so far. The dependency on wide geographical locations causes low effective utilization of vehicles, while still suffering from lost opportunities due to lack of timely capacity. Taking into account that every vehicle is relatively expensive the challenge of finding more demand for the available capacity is a key for successful transportation business.
From TOC perspective the vehicles are the internal constraint of the organization, even though there is a lot of idle capacity.
In itself the service of carrying people, or goods, from point A to point B, is simple. It requires several resources at the same time, a vehicle, a driver, sometimes a whole crew on the vehicle and in the terminals. Supporting processes are planning the vehicles missions, maintenance, accepting orders and collecting the money.
A major simplifying factor is that there is no direct interaction between the vehicles.
Thus, exploiting the missions of every vehicle is the key business issue.
Thus, we can look at every single vehicle as an independent constraint! Exploiting one vehicle is only seldom on the expense of the other.
Do transporting companies exploit their constraining units?
In a previous post I’ve dealt with an exploitation scheme used by the airlines called “Yield Management” (also Revenue Management), which is basically an exploitation scheme of a single flight (micro-constraint) through the use of dynamic pricing. The general direction of Yield Management is right, but the airlines use it in an overly extreme way (pathetic to my view) to optimize the revenues within the “noise.”
But, optimizing the flights, or any transport from A to B, is not necessarily the same as exploiting the capacity of the vehicle! What is missed is the number of transportations the vehicle actually does in a period of time.
A key flawed paradigm of most transportation companies is that the full cost-per-km (or mile) is the only key parameter that dictates whether the specific travel is profitable. So, every kilometer travelled needs to cover its cost. The cost includes not just the truly-variable-costs of travelling one kilometer (mainly the fuel), but also the allocated fixed cost associated with the vehicle, especially the purchasing investment of that vehicle.
This paradigm causes rejecting business opportunities, preferring to leave the vehicle standing still, and certainly not letting the vehicle travel empty unless that travel is covered by a client.
An example: There is a shipping order from A to B. How should the vehicle come back to A? The obvious wish is finding another shipment to cover the full cost of travelling back. What happens when such an opportunity is required only 24 hours later? Is it obvious to keep the vehicle idle for 24 hours? The cost-per-km does not address the economics of standing idle.
The TOC solution is to use Throughput Economics to plan the business of transportation. This means, first of all, calculating the true throughput (T) of the whole travel. Certainly all TVC per kilometer have to be included.
The T-per-travel should lead the company to calculate the total T-per-specific-vehicle for a period of time, like a week or a month. The focus of management should be to maximize the total monthly T for every vehicle.
Planning the generation of next week T by Vehicle-X involves checking various options from the minute the vehicle is free taking location and time into account. It could be that the vehicle should come back empty in order to be available at point A for higher T opportunities.
Dynamic pricing should be used to encourage potential customers to allow enough time ahead, providing the planner better flexibility. There should be a price difference between flexible time given by the customer and very specific timing for the service. Certainly for an urgent service the price should be higher.
This different focus should achieve better exploitation of the constraint(s).
The company still needs to understand and implement subordination. For instance, loading and unloading might take long time, causing losing potential business. Suppose that adding people to help with the loading would significantly shorten the time. Adding people adds delta-Operating-Expenses (delta-OE). Question is: can we get additional delta-T, higher than the delta-OE, by saving time?
Isn’t this focus what made Southwest Airlines so successful? Using operational flexibility to subordinate to the most efficient use of the constraint, which is every single aircraft. The use of the same type of aircraft enables flexible use of pilots. It is just an example of effective subordination.
Strategy according to TOC has to come up with a decisive-competitive-edge, in the shape of unique value, target at big enough market segment(s). Generally speaking all transportation companies struggle to offer the clients the following key values:
- Reliability, both regarding the agreed upon timing and the safety of the shipment.
- Fast response to any request.
The difficulty to deliver the above is that the excess capacity is not enough to overcome temporary peaks of demand in one location. Improved exploitation of the pool of vehicles, including clever buffering of commitments to key clients, would improve the reliability and fast response.
There are two different modes of operation for transportation service:
- Fix schedule of transportation from A – B and back from B – A. The route could cover many intermediate points. The ultimate examples are trains, flights and ships. This way high reliability can be achieved, but there is no ability for fast response or adjust the timing. The key challenge is establishing the fixed routes and schedules in a way that maximizes the T-per-vehicle.
- Flexible routes schedule. The ultimate examples are taxis and trucks.
An overall superior Strategy can be developed using collaboration between competitors to deliver better service. Airlines use a certain level of collaboration, allowing moving between airlines for routes not fully provided by one airline. They also collaborate to provide a buffer for passengers when flights are cancelled.
It is my view that additional strategic collaborations can vastly improve the businesses of many transportation companies. For instance, a company located at point A could collaborate with a company located at B to ensure quick returns of vehicles. Answering the real needs of users, coupled with effective control on the T-per-week-per-vehicle, could make very substantial business improvement for organizations that are open for a change.