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The limits of mandate planning in audit and assurance: Can they be overcome?

Updated: Mar 12

"Many auditors are already operating at the efficiency limit."

In audit and assurance planning, there are various conflicting objectives to consider.

Audit firms must deal with a variety of different planning parameters and metrics to create a satisfactory audit plan. These metrics typically conflict with each other, requiring constant balancing and adaptation to the specific situation.

For example, a company may want to optimize margins but not at the expense of employee satisfaction. Other conflicting objectives may involve on-site availability versus employee home office requirements. Some may prioritize continuity (using familiar talent for the same audit year after year), but some of these experienced talents may have been promoted, leading to higher costs and lower engagement margins

Many are already operating at the efficiency limit.

In economics, this limit describes a state where existing methods cannot improve one objective without worsening one or more other objectives. When a company is at the efficiency limit, it can only operate in trade-offs, representing a classic conflict of objectives.

However, if a company is below the efficiency limit, it can improve two or more objectives simultaneously to reach the efficiency limit. Depending on the underlying planning methodology and technological capabilities, a company can bring itself to the efficiency limit and maneuver on it depending on the situation. This means that in a specific situation, one objective is prioritized over another.

Abbildung 1: Wie hier schematisch dargestellt ist, stellen die Punkte A, B und C verschiedene Mandatspläne einer Unternehmung dar, deren Qualität (z.B. Brutto-Engagementmarge und Überstunden) in zwei Dimensionen gemessen wird. Ein Unternehmen, das auf der Effizienzgrenze arbeitet (“Efficient Frontier”), kann keine Zielgrösse steigern, ohne dass eine andere verschlechtert wird. Ein Unternehmen, dass Pläne unterhalb der Effizienzgrenze erstellt, kann durch bessere Mandatspläne auf die Effizienzgrenze kommen und sein volles Potential schöpfen.

Figure 1: As schematically illustrated here, points A, B, and C represent different audit plans of a company, whose quality (e.g., gross engagement margin and overtime) is measured in two dimensions. A company operating on the efficiency frontier ("Efficient Frontier") cannot increase one target without deteriorating another. A company that creates plans below the efficiency frontier can reach the efficiency frontier and maximize its full potential through better audit plans.

What are these conflicts of interest in mandate planning?

An example is the Busy Season in auditing, where employees must handle an enormous workload in a short time. It is important to ensure that individual peak workloads do not reach extreme levels to avoid losing valuable talent. In some countries, overtime must also be compensated with additional payments (partly 150% of the regular gross wage per hour worked).

For a simple example of a conflict of interest, consider an auditing firm that wants to maximize two key metrics:

  • Metric 1: Employee satisfaction and individual peak workload

  • Metric 2: Gross engagement margin

These two metrics typically conflict with each other, especially during the Busy Season. Improving the margin can lead to higher workloads, and vice versa.

If the company is operating at the efficiency frontier, it can only act in trade-offs that represent points on the efficiency frontier. This means that it has found the optimal combination of margin and peak workload.

Wie hier an einem realen Beispiel dargestellt ist, konnte durch den Resourcenplanungs KI-Copiloten aspaara MatchingCore® eine Wirtschaftsprüfungsgesellschaft in der Mandatsplanung auf die Effizienzgrenze gebracht werden (“Efficient Frontier”). Mit Erreichen der Effizienzgrenze können zwei oder mehr Mandatsplanungen verglichen werden und die Zielkonflikte anhand verschiedener Dimensionen an die jeweilige Situation und Unternehmensausrichtung angeglichen werden.

Figure 2: As illustrated here with a real-world example, the resource planning AI copilot aspaara MatchingCore® brought an auditing firm to the efficiency frontier in mandate planning. By reaching the efficiency frontier, two or more mandate plans can be compared, and conflicts of interest can be adjusted according to various dimensions based on the specific situation and company orientation.

Possible approaches to conflict resolution

There are various ways to resolve conflicts of interest. One approach is to prioritize the goals. This means that one goal is considered more important than the other. In this case, the company would prioritize margin but accept a high peak load. However, this could potentially result in the loss of good talent.

Another approach is to resolve conflicts of interest by collaborating with other companies and using outsourcing or shared delivery centers (SDCs), for example. In this case, the company could work with a supplier to reduce the workload on its own employees without affecting the margin. However, this usually entails additional external costs (for the SDC) and internal costs due to additional coordination, which must be compared with the overall cost ratio.

A relatively new approach is to use artificial intelligence (#AI) in workforce planning, which utilizes holistic planning methods. These holistic planning methods consider the entire workforce planning problem at all times and can therefore bring the entire company to the efficiency frontier or maneuver around trade-offs on the efficiency frontier that best fit the company's strategy.

How can a company maneuver on the efficiency frontier?

The use of artificial intelligence and the significant computing power available today can help solve these complex planning problems for auditing firms. However, it is important to use holistic payment procedures, as it is difficult to reach the efficiency frontier with sequential, dialogue-based planning procedures (see article "The Importance of Holistic Workforce Planning in Auditing"

Using holistic planning methods to reach this efficiency frontier requires a detailed analysis of the planning challenge, including the planning rules and objectives set for optimization. Based on this analysis, a tailored optimization profile can then be compiled to integrate holistic planning.

With an AI copilot, planners can immediately optimize the overall planning and balance these conflicts of interest according to management's specifications. This assists planners in making complex planning decisions not in terms of particular individual interests, but holistically for the benefit of the company and all employees alike. In planning situations where multiple influencing factors are at play, artificial intelligence finds the best solution holistically with the available information, especially in situations that are too complex for humans.

What makes it particularly interesting and surprising is that AI can come up with solutions that a human cannot find. As an example, consider the so-called roll-forward in mandate planning. In this roll-forward, last year's plan is taken and transferred to the new financial year, with only the holidays adjusted, along with other minor adjustments.

Due to the high complexity, no consideration can be given to whether the plan that may have worked well last year is still appropriate this year. This creates path dependencies that have negative impacts on planning. Only through a holistic planning method that calculates many billions of possibilities holistically (and not just sequentially finds individual pairs) can the overall result be improved and the auditing firm brought to the efficiency frontier. If it is already on the efficiency frontier, conflicts of interest can be weighed to achieve the best result according to management's specifications.

Especially for employee satisfaction, it is very important to incorporate employees' personal preferences into planning. Because only when an employee is heard and their wishes are taken into account in the planning, is the employee satisfied with the employer and remains with them. It is essential, therefore, that soft factors as well as individual preferences are considered in this holistic planning.

What conflicts of interest occur repeatedly?

In our collaboration with customers at aspaara AG over the past eight years, we have identified the following conflicts of interest that occur repeatedly:

Efficiency of the plan

  1. Utilization is not optimal (particularly painful during the busy season and peak times).

  2. The planning quality meets the formal requirements (according to PCAOB, ISA, etc.) regarding skills, operating unit, skill-grade mix, and continuity (intra-year, inter-year).

  3. The project margin falls short of expectations.

Satisfaction of the talent

  1. Employee preferences cannot be met and considered with existing solutions.

  2. A balanced mandate plan that fairly distributes the workload across all talents (especially for newcomers) cannot be achieved.

  3. Overtime is very unevenly distributed (fairness among employees).

Planning efficiency (planning function)

  1. The planning effort is too high (especially SDC, CC, Remote Worker Integration) with existing solutions.

  2. The planning process takes far too long to respond appropriately to changing situations (it takes too long from the start of planning to the first plan).

  3. Lack of AI support (shifting the heavy lifting to the machine) and existing solutions are too cumbersome.

In sequential planning, where only availabilities and hard factors such as skills and qualifications can be considered, employees' personal preferences can only be included to a limited extent. This leads to a WIN-WIN situation, where in the sense of a conflict of interest, optimization also incorporates employee preferences as a legitimate goal in conflict resolution.


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