When it comes to maintenance budgets, many companies plan on the basis of the previous year. The problem with this tactic is that old budget figures don’t reveal much, if anything, about current and future maintenance needs. So it’s high time to switch to data based financial planning – with the right strategy and appropriate software.
The maintenance budget is perhaps the most underestimated aspect of asset management. To complete the budget planning process for the next fiscal year as quickly as possible and with minimum effort, the maintenance manager in charge generally uses the previous year’s expenditures. Afterwards, they usually add potential cost increases on top just to be safe, and there you have it – the new budget is done. As simple and appealing as this method of budget planning may seem, it isn’t without consequences. The most dramatic financial consequence is that the maintenance budget increases year after year. This is a strategy that companies have to both want and be able to afford. After all, in the era of big data and smart companies, it could be significantly optimized. Upon closer inspection, the maintenance budget provides reliable facts and figures about the company’s own performance and efficiency – and therefore also about areas with scope for improvement. In other words, effective data analysis and adapted budget planning methods facilitate more accurate calculations, more efficient cost control, and a financially sound allocation of maintenance resources.
New Budget, Old Problems
Most companies’ maintenance teams have long since come to this realization. So why do they still largely rely on the traditional approach by using the past fiscal year to plan the upcoming maintenance budget, instead of using actual plant data? The short answer is that plant-based budget planning primarily fails due to the processes required, and insufficient plant data. For example, maintenance sub-budgets are still frequently tracked in Excel spreadsheets. How about taking maintenance plans into account? Not a chance. In addition, the use of different IT systems and software tools makes it difficult or even impossible to aggregate and analyze the figures. Difficulties also arise in maintenance budget planning as a result of a top-down/bottom-up approach. In maintenance practice, this means that each plant engineer calculates the financial requirements for their own area of responsibility – a classic bottom-up procedure.
In contrast, the maintenance manager has to take the top-down targets defined by management, especially the overall budget, into account. This means that ultimately, every maintenance budget is a compromise – but one that is essentially based on wishes, abstract targets, and the past. What about current, future, and above all, actual maintenance requirements? The expected market trends that will have an impact on plant utilization and availability, and therefore also directly on maintenance? These are all aspects that have been largely ignored up until now. Which means the end result of this kind of cost planning strategy – countless inefficiencies – isn’t surprising. Or as the saying goes: “Maintenance at any cost” instead of “maintenance at the right cost.”
Demand Determines Maintenance Strategy
The good news is that Industry 4.0, with its many ways to analyze data, offers opportunities to conduct budget planning at a much more sophisticated level. The first step, however, is finding the right strategy and method – such as demand-driven budgeting (DDB). As the name suggests, instead of defining fixed, relatively imprecise (annual) budgets for a production line or individual plant areas, maintenance budgets can be flexibly planned and adjusted on the basis of DBB. The biggest advantage is that budgets can be allocated anti-cyclically to availability, meaning that the order situation can be taken into account in production. For example, if it becomes clear that lower availability will be sufficient a few months down the line due to declining orders then maintenance measures – and therefore expenditure – can be reduced in advance. Conversely, if a foreseeable increase in demand requires maximum availability then maintenance can react in a timely manner in order to achieve the desired availability at the designated time using intensified measures. Demand-based, anti-cyclical budget optimization therefore ensures that companies achieve the necessary availability at all times, and at optimal cost.
Budget Planning “Starting from Scratch”
For a strategy based on demand-driven budgeting to work in day-to-day maintenance practice, companies need to have the right budgeting tool and data. In this context, many companies rely on zero-based budgeting (ZBB). Compared to traditional maintenance budget planning, ZBB takes the opposite approach. Past budgets do not play a role. Instead, all of the cost factors are analyzed and calculated from a “zero base,” i.e. from scratch, every year. The benefits of this approach are obvious: maintenance services that are no longer required can be systematically identified and cut from the budget, making it possible to identify and prevent unnecessary “standard items” from creeping in. Important plants and associated critical maintenance tasks can be pinpointed and therefore adapted to the required level. In addition, cost increases can be critically analyzed and assessed according to need. If you want to use ZBB for maintenance, you have to consider five fields of action in your budget planning: preventive, condition-based and fail-safe maintenance, as well as individual/special measures and continuous improvement (CI) projects. In addition, ZBB offers a dual planning strategy consisting of the following two components:
1. Individual Equipment Strategy
By definition, every system and sometimes even a single piece of equipment or component in maintenance constitutes a technical unit. Within the framework of ZBB, each of these units is examined “from zero,” before the appropriate and necessary maintenance measures are calculated. As valid and important as this strategy is, because it enables extremely targeted budget planning, its full implementation requires a long-term approach. This is due to the fact that many production systems consist of individual pieces of equipment running into the thousands. As a result, preparing cost-related individual strategies requires a lot of resources and takes time.
2. Equipment Category Strategy
This part is the short-term component of the equipment strategy. In contrast to the individual strategy, this entails equipment being grouped into suitable categories – for example “pumps” or “tanks.” The maintenance requirements for a small number of pieces of equipment are then determined and extrapolated for the appropriate category, calculating a kind of average. Although the latter is less accurate than the value for an individual piece of equipment, it still produces more accurate figures compared to the planning methods used to date, and is relatively quick to implement and operate.
The Perfect Tool for the Perfect Budget
Despite its significant additional value, zero-based budgeting is not easy to implement in practice. The planning tools currently used by most companies aren’t powerful enough to identify the complex interrelationships between maintenance strategies and measures, anticipated availability, and the required budgets, by means of data analysis. For example, a suitable tool has to be capable of simulating possible correlations between anticipated availability and the anticipated costs for different scenarios. Thousands of simulations can then be run for each maintenance strategy to evaluate the impact on the overall availability of a production system. This, in turn, makes it possible to achieve the overall objective – with a demand-driven budgeting approach, production’s business objectives are directly linked to the maintenance strategy required to achieve its goals.
Together with Deloitte, T.A. Cook has now developed just such a tool: an app with functionality based on the demand-driven and zero-based budgeting approach. It offers numerous benefits when determining the optimal maintenance budget. For example, the app can be used to evaluate equipment strategies and link them to financial and availability information. In addition, it automatically analyzes every budget-related item, such as CI measures and postponed maintenance activities, so that their effect is factored into future maintenance requirements. This multifunctional tool facilitates the change towards demand-driven and professional maintenance budget planning.