Efficiency and optimization seem to go hand in hand and they really do. Efficiency is the driving force in reducing operational costs and Optimization is the engine with which to achieve this goal.
When discussing workforce management solutions, the first thing to discuss is the return on investment (ROI). What value can a service organization strive for when implementing such a solution? The value is indeed related to efficiency in all levels of operations, from reducing mileage and fuel consumption to saving on overtime and balancing work between field technicians. The efficiency is measured ultimately in how much you affect your bottom line in terms of expenses.
Service organizations are first faced with the need to get the basics right. Collecting the right data, implementing processes and connecting everyone to the same system, once every field resource has a mobile and is connected, it is time to work on changing the organization attitude, to adopt the system and the new processes.
Only once the system is fully integrated and adopted can you start discussing optimization. The first reason for this is down to information. There is no way to improve (optimize) if there is no information about the current state of operations. Once the system is implemented and run for some time the data becomes available and you can start looking into the details more closely and suggest ways of improving the current system or process. The second reason is that optimization removes control from the users and replaces it with automated computer thinking. This is a huge step forward, from a world of total control to a new world of decision-making that is not based on any human factor. This step should not be taken before a level of trust is established between the human operator and the new system, otherwise, implement too soon and the users will simply override the system or reject it all together.
Efficiency is really down to each organization to define but lets look at the most common ones based on the wide range of service organizations we have worked with.
Balancing work load
All work should be spread fairly and evenly across the board. Field resources should not feel there are any favourites so they should all be happy with their work loads. There is no reason for one resource to go into overtime while another is sitting idle. Most organizations consider overtime expensive and struggle to avoid it.
This optimization process is simple to understand and produces a schedule that is efficient and balanced. However, it does conflict with other forces that might drive the schedule to be less balanced but more efficient in other ways, (such as travel time) so this should be taken with caution and not forced in but be more of a guideline.
Reducing Travel Time
Directly linked to the operational costs and very visual to the human users as it is very easy to look at the schedule on a map and see how far field technicians are traveling throughout the day. Optimizing the routes is a very challenging task and involves not just looking at geographical co-ordinates but also at other hidden constrains such as job requirements (skills, tools & parts) and time constraints.
Although humans can potentially do a great job in identifying these situations (when the schedule is not optimized) the automated process normally achieves better overall results than any human can do in a short span of time. The efficient schedule is directly driven by the cost of mileage and it is easy to measure the improvement in each optimization cycle.
Doing more with less
This is the holy grail, everyone would like to get more business, complete more tickets per day with the same (or less) people out in the field. When you become more efficient you become more optimized and can therefore do more with the same number of resources. You are more organized, and have better visibility but in total you squeeze out more performance without changing your actual workforce capacity (same number of resources).
Looking at the previous points (that are a small sample part of the overall picture) you can see how different efficiencies can contribute to this overall profitability. Optimising each section (may be small) of the larger picture directly contributes to this benefit. For example, reducing the travel time (while maintaining the same work load) clearly reduces the overall time wasted and frees up time to take on more work. Another efficiency example may include reducing return visits, this normally happens when a technician arrived un-prepared for the job (missing parts or tools) and therefore another technician needed to be dispatched, this is clearly wasted time and reduces capacity.
Optimization may be partial and in a limited area and may involve a process of continues improvement, however, the bottom line will have an immediate impact.
What is the future?
After running optimization for some time with a close look at your efficiencies, a better picture is becoming visible, now you have accurate and complete information about your operations.
The future is improving on that and it may be that you will need to relocate resources between territories (some times permanently and sometimes according to seasonality). It is also possible to get recommendations for improved coverage in terms of skills (send technicians on training to gain certifications in specific areas) or better equip them with the necessary tools.
As we have seen, efficiency is driving optimization but optimization might look like it is improving one factor while reducing the others. It is very much a balancing act to get the right overall efficiency using an optimization process. In this short article we have just touched on some of the aspects, and obviously don’t have the time to discuss all of them and how they interact.