Effective fleet performance is essential for distributors and can have significant financial and competitive implications - both positively and negatively - depending on how it is carried out.
Route planning is among the essential elements in that performance. And while distributors inherently understand this, experience shows that fleet performance varies widely across distribution organisations - even for similar businesses using the same route planning solutions. Yet, the performance advantage for top performing distributors is considerable, as they often require fewer people and vehicles, have shorter planning cycles and better productivity. The key metrics that underscore this advantage include:
So why the performance variation? The simple answer: Poorer performers don’t employ route planning best practices for measurement, processes, organisation or education. The telltale signs of a distributor not leveraging route planning best practices are
The good news, however, is that all these challenges have straightforward solutions. Here are key route planning best practices that turn poor fleet performers into top ones.
These two points are fundamental in the implementation of route planning best practices.
However, many distributors face challenges in obtaining comprehensive performance data or metrics due to manual processes or legacy solutions. To address this, distributors should adopt a route planning solution that combines route execution and GPS-based mobile applications to establish a performance baseline. Then, focus on improvement. Assigning weighting metrics financially is also important because not all metrics carry the same financial value and improving performance involves making trade-offs between miles, resources and vehicles. For example, one mile may cost 80 pence while a driver hour may cost £40 and a vehicle £100,000 annually. This shows that it may make sense to drive more miles if the result is less time and vehicles.
It’s also wise to be aware that certain route planners will make subjective changes to the optimised plan based upon their “tribal” knowledge, which can negatively impact financial performance.
Therefore, it’s crucial to measure the impact of these changes, especially when route planners come from manual or legacy system planning environments. For example, the route planner may want “petal” routes but doesn’t understand that the optimiser determined that non-uniform routes were the most efficient. The lesson here is that if the route planner adjusts the routes for greater uniformity, this can lead to - and often does - sacrificing efficiency gains.
Inconsistencies in planner performance can have a substantial financial impact on your organisation.
All the time there is a significant difference in the quality of route plans across the planners, businesses need to identify the best planning process, document it and institutionalise it across the planner community. The end result of this will be higher plan quality and reduced performance leakage.
All modern route planning solutions have automation capabilities.
The key is to effectively utilise these by taking planning best practices, embedding them into the solution and executing without human intervention. In doing this, planners become more productive due to the fact that they can focus on the plan review and exceptions, ultimately ensuring planning consistency and better results. This also reduces the amount of planning resources needed as well as planning latency.
Planners no longer have to be in the field to have the necessary local knowledge to make the best plans.
In fact, the best planning occurs when it is centralised. By centralising everything, organisations will build greater domain expertise, more effectively leverage planning resources, improve planner productivity and allow for more focus on continuous improvement. This approach also minimises the impact of the loss of a resource and their replacement.
A clear indicator of route optimisation performance degradation over time is the neglect of maintenance of configuration and operational data. Failing to adjust the solution to your business’ ever-evolving needs or to enforce quality standards on items such as dimensions and weights will impact the optimiser’s performance.
A knock-on effect is that planners then start to lose faith in the results and turn to more manual adjustments, leading to performance spiraling downward. Data maintenance is an on-going process; however, machine learning can offer a valuable solution. By constantly analysing actual performance data and making recommendations or configuration changes that maintain or improve route plan performance, your data quality will improve drastically.
Route planning can often seem like rocket science and the knowledge that a planner has about route planning techniques and systems directly impacts plan performance, especially when so much effort is put into training the initial resources during implementation.
However, over time, planners change and there is often not the same level of training for new planners. The situation is analogous to planning system enhancements when there is no focus on education on new releases. So, continuous training must be non-negotiable when it comes to fleet management and that is one of the reasons why centralised planning consistently outperforms distributed planners.
Route planning stands as the lynchpin of fleet performance, and the pathway to improving route planning performance is a logical set of steps that can be applied to any organisation, at any time.
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