This article is written by Dr Almero Oosthuizen, Prof Heike Geduld and Dr Mandy Liao, Western Cape Government Department of Health and Wellness, South Africa.

  • The Problem: Absolute performance targets are not always useful in large organisations where resources and capacity are not spread uniformly.
  • Why it Matters: Such absolute targets may be unrealistic, demoralising and not particularly good metrics to use when trying to equitably and effectively spread resources and effort across large organisations.
  • The Solution: Relative adaptive targets express performance standards as a percentage of the best real-world performance in each context and have several potential benefits.

A Challenge: Absolute performance targets don’t work well in large complex organisations

The traditional approach to performance management often involves setting absolute performance targets: specific, time-bound goals that must be met regardless of varying circumstances. While this method provides clear, measurable objectives, it can pose significant challenges in large, complex organisations where operational capacity and conditions vary widely.

For example, in a provincial department of health, the capacity and resources of different facilities may differ substantially, making it difficult to achieve uniform performance standards.

An Opportunity: Relative adaptive targets may be more useful and fairer

To address this issue, the concept of ‘relative adaptive targets’ (RAT) has emerged as a promising alternative. Unlike absolute targets, relative adaptive targets define performance goals in relation to real-world performance within a specific operational environment. Instead of prescribing a fixed time limit for a task, these targets set benchmarks based on the best performance achievable under current conditions.

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For example, rather than stating that a patient with a head injury should receive a CT scan within two hours of arrival, a relative adaptive target might specify that the patient should receive the scan within the fastest 10th percentile of performance for emergency CT scan access at that particular facility. This approach considers the unique operational realities of each facility, setting more realistic and attainable targets.

This approach has several benefits, but also risks:

Adopting relative adaptive targets requires a shift in mindset from rigid, one-size-fits-all standards to a more flexible, context-aware approach. Benefits include:

  1. Realistic Benchmarks: By considering the specific capabilities and constraints of individual facilities, relative adaptive targets provide more realistic and achievable performance standards. They would support internal and external expectation management.
  2. Quality Assurance: This approach allows for continuous monitoring and improvement of performance, as targets can be adjusted in response to changes in operational capacity and conditions.
  3. Legal Protection: Setting realistic, context-sensitive performance targets can provide legal protection by demonstrating that the organisation is committed to achieving attainable best performance standards.
  4. Engagement and Motivation: Employees are more likely to be motivated and engaged when performance targets are perceived as fair and achievable, tailored to their specific working environment.

Relative adaptive targets provide more realistic and achievable performance standards

To use relative adaptive targets, a system needs regular data collection and analysis to establish and update performance benchmarks, ensuring they remain relevant and attainable. Realistic relative benchmarks that acknowledge more absolute external evidence-based standards, as well as local capacity, could potentially more accurately identify key areas for improvement.

When considering equity across the system, relative adaptive targets give more information than traditional measures. It might more accurately identify high and low performers relative to relevant peers. It might also more accurately identify where large gaps between a RAT and an externally prescribed, absolute benchmark exist. To do this would require adequate data analysis and support. This, in turn, may require more resources invested in QA/QI than traditional measures, though automation and AI tools offer significant opportunities in this area.

We’re looking for thinking partners and inputs from both experts and novices

In our initial exploration, relative adaptive targets seem to have the most value in composite targets where the interplay of multiple system elements is responsible for the outcome.

As we further explore the potential of relative adaptive targets, we want to engage in discussions and gather insights from diverse stakeholders. Please share your thoughts and experiences on this topic. How can we refine this approach to better serve our organisations and improve overall performance? Your input will be invaluable in shaping a more adaptive and effective performance management framework.

Done reading? Make sure to share your own thoughts on how we can refine this approach to better serve our organisations and improve overall performance by leaving a comment below ⬇️

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