Goodhart’s Law is named after British monetary policy theorist and economist Charles Goodhart. Speaking at a conference in Sydney in 1975, Goodhart said that “any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” Goodhart’s Law states that when a measure becomes a target, it ceases to be a good measure.
Aspect | Explanation |
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Concept Overview | – Goodhart’s Law is a fundamental concept in economics and social sciences that highlights a potential pitfall when using metrics or indicators as a basis for decision-making. The law states: “When a measure becomes a target, it ceases to be a good measure.” In other words, when people or organizations set specific metrics or indicators as targets to achieve, they may change their behavior in ways that undermine the original purpose of the measure. Goodhart’s Law was formulated by economist Charles Goodhart and has implications in various fields, including finance, economics, business, and public policy. |
Key Principle | – The key principle of Goodhart’s Law is that using a metric as a target can lead to unintended consequences. When individuals or organizations are incentivized to achieve a particular metric, they may focus solely on optimizing that metric, even if it comes at the expense of other important factors or the original goal. This can result in distorted behavior, misaligned incentives, and outcomes that are counterproductive or contrary to the intended purpose. |
Examples | – Examples of Goodhart’s Law in action include: 1. Financial Markets: When stock prices or earnings per share (EPS) become the primary focus for a company, management may engage in financial engineering or short-term strategies to boost these metrics, potentially at the expense of long-term growth and sustainability. 2. Education: In education systems where standardized test scores are used as a primary metric for evaluating schools or teachers, educators may “teach to the test” rather than providing a well-rounded education. 3. Healthcare: In healthcare, if hospital performance is measured based on patient satisfaction scores, healthcare providers may prioritize patient comfort over necessary medical procedures or treatments. 4. Corporate Performance Metrics: When organizations set specific quarterly revenue targets as key performance indicators (KPIs), sales teams might push for aggressive sales tactics, discounting, or revenue recognition manipulation to meet the targets. |
Applications | – Understanding Goodhart’s Law has applications in various fields: 1. Business Metrics: Business leaders should be cautious about relying solely on a single metric as a performance indicator and consider potential unintended consequences. 2. Public Policy: Policymakers need to design policies and regulations that account for the possibility of metrics being manipulated or distorted. 3. Financial Markets: Investors and analysts should consider how companies may be influenced by financial metrics in their investment decisions. 4. Education and Healthcare: Administrators and policymakers should use a balanced set of metrics to evaluate performance rather than relying solely on one measure. |
Mitigation Strategies | – To mitigate the negative effects of Goodhart’s Law, individuals and organizations can consider the following strategies: 1. Diversify Metrics: Use a combination of metrics rather than relying on a single measure to assess performance. 2. Scrutinize Incentives: Carefully examine the incentives created by performance metrics to ensure they align with the intended goals. 3. Regularly Review Metrics: Continuously assess whether the chosen metrics are still relevant and meaningful for evaluating performance. 4. Encourage Transparency: Foster a culture of transparency and open communication to reduce the likelihood of gaming the metrics. 5. Monitor for Unintended Consequences: Actively monitor for any unintended consequences or distortions resulting from the use of metrics as targets. |
Impact and Relevance | – Goodhart’s Law is significant because it underscores the complexity of human behavior and decision-making in various contexts. It serves as a reminder that setting targets based on metrics requires careful consideration and monitoring to avoid perverse incentives and unintended outcomes. The concept has broad implications in finance, economics, education, healthcare, and public policy, and it continues to be a critical element in decision-making and performance evaluation worldwide. |
Understanding Goodhart’s Law
Goodhart would later admit that his quip was intended to be a humorous, throw-away comment. But it was nevertheless an accurate and perceptive observation about how the modern world functions.
It’s important to note that Goodhart himself had no role in naming the law for which he is named. That distinction goes to anthropologist Marilyn Strathern, who argued in a 1997 paper that the law had uses beyond statistics to evaluation in a broader sense.
An oft-told story of Goodhart’s Law at work can be described by the cobra effect. In India under British colonial rule, the government was troubled by the number of venomous cobras. To reduce their population, the government placed a bounty on every cobra the locals could catch. This strategy worked for a while, but some individuals began breeding the cobras only to kill them later and collect a higher bounty.
Eventually, the colonial government caught on and scrapped the scheme, causing many of the bred cobras to be released into the wild. The key takeaway of the cobra effect story is that incentives designed to solve a problem end up rewarding people for making the problem worse.
The four forms of Goodhart’s Law
There are generally accepted to be four variations on Goodhart’s Law:
- Regressive Goodhart – here, the measures individuals use for their target (goal) are imperfectly correlated with that goal. For example, weight is imperfectly correlated with health because it encourages skipping meals or weighing oneself in the morning with an empty stomach.
- Extremal Goodhart – this occurs when a measurement is picked because it correlates with a goal in normal situations. In extreme circumstances however, the measure is erroneous. The human relationship with sugar is a classic example. While sugar was correlated with survival thousands of years ago, the same cannot be said of modern, sedentary lifestyles where sugar promotes obesity.
- Causal Goodhart – where the behavior of an individual does not directly affect the goal but has some causal effect on the measure. The number of times a gym membership is renewed does not directly impact how often an individual exercises, for example.
- Adversarial Goodhart – where other goals confound the goal a measure is trying to accomplish, such as the cobra effect mentioned above.
Avoiding the impact of Goodhart’s Law
Of the four variations of Goodhart’s Law, only the Regressive Goodhart is unavoidable.
For the remaining three, here are some simple avoidance tips:
- Conduct regular checks to ensure the measure is still incentivizing in line with the desired outcome or goal.
- Become aware of Goodhart’s Law and how it operates.
- Maintain a focus on the end goal while using the measures as a guide only.
- Reduce bureaucracy and formalism.
- Use a combination of diversified metrics. A balanced scorecard can be useful here.
Examples and Case Studies
- Academic Performance: In education, the use of standardized test scores as the primary measure of academic performance can lead to unintended consequences. Schools and teachers may be incentivized to focus solely on improving test scores, leading to teaching to the test and neglecting other important aspects of learning and development.
- Business Metrics: In business, focusing solely on financial metrics like revenue or profit can lead to adverse effects. For example, if a sales team is rewarded solely based on revenue, they may engage in aggressive sales tactics or offer steep discounts to close deals, even if it negatively impacts long-term profitability.
- Healthcare: In healthcare, the use of certain performance metrics to assess the quality of care can create unintended outcomes. For instance, a hospital that prioritizes reducing patient wait times may discharge patients prematurely or prioritize less critical cases to improve wait time metrics, potentially compromising patient outcomes.
- Employee Performance: In the workplace, setting individual performance targets without considering the broader context can lead to unintended consequences. Employees may focus solely on meeting their targets, neglecting collaboration and teamwork, or engaging in unethical behavior to achieve their goals.
- Government Policies: When governments set specific targets to measure the success of policies, such as reducing unemployment rates or increasing GDP growth, there is a risk of distorting efforts and focusing on short-term gains rather than addressing long-term challenges.
Key takeaways:
- Goodhart’s Law states that when a measure becomes a target, it ceases to be a good measure.
- Goodhart’s Law was informally coined during a speech by Charles Goodhart. Although the economist was speaking in the context of statistics, the law has broader evaluative applications.
- Goodhart’s Law is generally categorized into four variations: Regressive Goodhart, Extremal Goodhart, Causal Goodhart, and Adversarial Goodhart.
Key Highlights
- Goodhart’s Law: Named after economist Charles Goodhart, the law states that when a measure becomes a target, it loses its effectiveness as a measure.
- Understanding the Law: Despite Goodhart’s original comment being meant humorously, it accurately describes how measures can be manipulated when used as targets.
- Origin of the Term: Anthropologist Marilyn Strathern is credited with naming the law and extending its relevance beyond statistics to broader evaluation contexts.
- The Cobra Effect: An example illustrating Goodhart’s Law is the cobra effect, where government incentives to reduce cobra populations backfired when people started breeding them for the rewards.
- Four Variations of the Law:
- Regressive Goodhart: Measures used for goals have imperfect correlation with those goals.
- Extremal Goodhart: Measures that correlate with goals in normal situations fail under extreme circumstances.
- Causal Goodhart: An individual’s behavior indirectly affects the measure but not the actual goal.
- Adversarial Goodhart: Conflicting goals interfere with the desired goal of the measure.
- Avoiding Goodhart’s Law:
- Regularly reassess measures to ensure they align with the intended outcomes.
- Understand and acknowledge the operation of Goodhart’s Law.
- Keep the focus on the end goal while using measures as guides.
- Minimize bureaucracy and formality.
- Use a combination of diverse metrics, such as a balanced scorecard.
- Examples and Case Studies:
- In education, focusing solely on standardized test scores can lead to neglect of broader learning aspects.
- In business, prioritizing financial metrics can lead to short-term gains at the expense of long-term profitability.
- In healthcare, emphasizing certain metrics can compromise patient care quality.
- In the workplace, setting individual performance targets can undermine collaboration and ethical behavior.
- In government policies, setting specific targets may lead to neglect of long-term challenges.
- Key Takeaways:
- Goodhart’s Law highlights the problem of using a measure as a target.
- Named after Charles Goodhart, the law has broader applications beyond statistics.
- The four variations of the law explain different ways the law manifests in various contexts.
Connected Thinking Frameworks
Convergent vs. Divergent Thinking
Law of Unintended Consequences
Read Next: Biases, Bounded Rationality, Mandela Effect, Dunning-Kruger Effect, Lindy Effect, Crowding Out Effect, Bandwagon Effect.
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