Happy Friday!

At the Uncertainty Project, we explore models and techniques for managing uncertainty, decision making, and strategy. Every week we package up our learnings and share them with this newsletter!

In case you missed it, last week we talked about managing uncertainty and risk with portfolios. Now we’re back to our multi-part series on the effects of goal-setting and OKRs on decision making.

This week:

• 🔮 Today’s Topic: ‘Are OKRs overprescribed? The negative side-effects of goal-setting’

  • Previous posts in this series: Part 1 | Part 2

• 🎥 New Talk: John May sat down with Bryce Hoffman and Marcus Dimbleby to talk about decision making as a practice, the importance of strategic thinking at all levels of an organization, and how to effectively scale agile transformations. Here’s the link.

• 🎥 Upcoming Talk: Next week we’re sitting down with Barry O’Reilly to talk about decision making and uncertainty. Barry is currently the co-founder of Nobody Studios - he’s also the best-selling author of Unlearn and Lean Enterprise

💊 Are OKRs overprescribed?

This is the third (and maybe final) piece in a series about the dark side of goal-setting and OKRs.

In the last two posts in this series, we talked about the superpowers of OKRs but challenged their effectiveness in certain contexts. As a framework that inherently prescribes a ‘known end’, we covered a few arguments that they’re less effective in environments of extreme uncertainty - or in scenarios where we’re making asymmetric bets.

In this post, we’ll take a look at the small print on the prescription bottle that is OKR’s - if we look closely, we see that side effects may include:

• Goal-induced Blindness: Acquiring dangerous tunnel vision towards a particular goal.

• Escalation of commitment: Not only hold on to losing bets, but even double down on the mediocre status quo (the success trap).

• Distorted incentives and risk preferences: Taking on more aggressive risk or reducing risk based on incentives - even leading to unethical, ‘out of character’ behavior

As you’ll find in these arguments, these side effects may be more severe when OKRs are used in scenarios that lend more toward exploration and emergence.

Goal-induced Blindness

1996 was the highest death toll in Mount Everest’s recorded history. The stories from that year are often cited in explanations of goal-induced blindness.

The tragedies from that year were unexplainable - experienced mountain climbers ignored clear evidence and even pre-defined rules in their pursuit of the summit. In the most famous disaster that year, witnesses who saw climbers continue the ascent (that ended in the death of 8 climbers including one of their guides), were baffled to watch them seemingly disregard overwhelming evidence that their lives would be in danger if they didn’t turn around.

What happened?

After the disaster, Chris Kayes, an expert in management and organizational behavior, proposed they may have been ‘lured into destruction by their passion for goals.’

In his book, Destructive Goal Pursuit: The Mt. Everest Disaster, Kayes coined the term goalodicy - defined as, ‘the obsessive pursuit of goals to the point of self-destruction.’

Kayes’ argument is not that goals are inappropriate or always detrimental, but that leaders need to be thoughtful about when they are effective. In environments that revere goal achievement, research suggests that goals often lead to critical failures - disasters such as the 1996 Everest climb, the Columbia disaster, and organizational collapses like Enron.

Kayes’ alternative focuses on complimenting goal-setting with mechanisms for team learning and adaptation over goal achievement - which he summarizes in these points:

• Setting and pursuing high and difficult goals often drive failure, not just success

• Learning and adaptation, not vision alone, lie at the heart of leadership

• Effective teamwork and learning, not simply goal-setting, leads to success in the face of novel situations.

In summary, we tend to ignore how often audacious goals lead to unintended consequences and failure, learning should be the focus over achievement, and we need different approaches when we’re facing novel situations.

Escalation of commitment

There are powerful cognitive mechanisms involved that transfer from individuals to groups when goals are involved - one of which is the subject of Annie Duke’s book, Quit, where she makes the case for a disclaimer:

It’s common to reference the sunk-cost fallacy when it comes to project investments or initiatives, yet we tend to disregard our tendencies to overcommit when it comes to goals.

OKRs are typically crafted at a single point in time, where the variables in the environment are often implicit. Meaning the OKRs assume that these variables will stay the same. In economics, this is often explicitly stated as ceteris paribus or ‘all other things being equal’ to represent the constant change in other variables (known or unknown).

When this is implicit, what we’re saying is ‘given this is true’, but as variables change, we tend to retain the assumptions built on them. Some of these variables are salient - for example, of course we’re going to challenge our existing goals and strategy with the introduction of generative AI - but others are much more subtle.

The argument here is not against goal-setting - it’s advocating for goals designed to be resilient to inevitable change. As economist John Kay argues, sometimes the best way to achieve objectives is to do so indirectly.

Kay describes this concept as obliquity. The premise is that objectives are complex and rarely well-defined. Complex solutions typically emerge through trial and error - not by evaluating options and selecting the ‘right’ solutions. As we’re exploring solutions, we tend to learn more about the goals we’re trying to achieve.

Therefore, the deterministic approach to goal-setting can lead us down a predictable path - a path that tends to feed our escalation of commitment, even if it clearly isn’t working.

Why? Because a deterministic approach isn’t designed to reward the identification of what isn’t working - it rewards finding the right solution - which incentivizes doubling down on early, small wins that snowball into large mediocre initiatives.

OKRs can easily provide a facade of an outcome-driven, experimental environment when in reality, we just find something (anything) that can present as ‘on track’ towards a goal and stick with it.

John Kay’s response to this problem is pluralism over monism - meaning there are many different ‘right’ solutions that exist, not a single optimized solution. This means our choices should more often than not be between multiple good options, not a hunt for the ‘right’ choice.

Therefore, Kay argues, high-level goals should be approached indirectly through the means - or as Charles E. Linblom describes as ‘the science of muddling through’:

This is a challenge-based mindset (what would change our mind about this?) vs. a validation mindset (what is going to confirm this is right and everything else is wrong?). This is a subtle, but powerful difference.

Distorted incentives and risk preferences

The fact that audacious goals can promote unethical behavior and lead to disastrous outcomes shouldn’t come as a surprise.

If we assume positive intent in all scenarios, we still wouldn’t argue that the ends justify the means.

If we imagine that Sam Bankman Fried, the founder of FTX currently facing a possible life sentence for financial fraud, was truly acting in accordance with his audacious goals aligned to ‘effective altruism’, we wouldn’t justify the alleged misappropriation of customer funds to do so - even if it had gone unnoticed.

This is a concept that famed management researchers and professors Ordóñez, Schweitzer, Galinsky, and Bazerman describe as ‘Goals Gone Wild: The Systematic Side Effects of Over-Prescribing Goal Setting’.

They have a provocative opening to their paper:

The paper details the areas of vulnerability with goal-setting frameworks. This is different than ‘pitfalls’ that suggest a framework is implemented incorrectly - meaning it’s important to point out that we can assume a framework like OKRs is done correctly and still observe these possible side effects.

Granted, in my experience, I think something like OKRs has likely had more real-world adaptation to these issues than goal-setting has in the past (this paper was published in 2009), but it’s interesting to dig into the criticisms made here:

• When goals are too specific and narrow: The argument is that narrow goals can cause systemic inattentional blindness - the concept that we’re unaware of the power of our focus. Studies show that when we’re faced with specific tasks, we often ignore obvious stimuli as shown in the classic ‘awareness test’ of a team passing a basketball.

• Too many goals: When multiple goals are present, there may be unintended consequences as we tend to only focus on one single goal. For example, in a multi-goal situation, we tend to sacrifice ‘quality’ goals when ‘quantitative’ goals are present.

• Inappropriate time horizons: “Goals that emphasize immediate performance prompt managers to engage in myopic, short-term behavior that harms the organization in the long run”. People and teams tend to see goals as a ceiling of performance rather than a floor.

• Level of challenge and risk-taking: “Goal-setting distorts risk preferences … People motivated by specific, challenging goals adopt riskier strategies and choose riskier gambles than do those with less challenging or vague goals.”

• Learning and cooperation: “Locke and Latham recommend that ‘learning goals’ should be used in complex situations rather than ‘performance goals.’ In practice, however, managers may have trouble determining when a task is complex enough to warrant a learning, rather than a performance goal. In many changing business environments, perhaps learning goals should be the norm.”

• Harming intrinsic motivation: “Although people recognize the importance of intrinsic rewards in motivating themselves, people exaggerate the importance of extrinsic rewards in motivating others. In short, managers may think that others need to be motivated by specific, challenging goals far more often than they actually do. By setting goals, managers may create a hedonic treadmill in which employees are motivated by external means (goals, rewards, etc.) and not by the intrinsic value of the job itself.”

OKRs, as an evolution and adaptation of ‘Management by Objectives’ (MBO), takes many of these side-effects into account. The framework makes recommendations to reduce the number of goals (recommending groups stick to a 3-5 limit), break down time horizons with check-ins, and take a fail-fast learning approach to achieve goals, but even when implemented ‘by the book’, the psychological effects of goal-setting can have unintended side-effects.

As Ordóñez, Schweitzer, Galinsky, and Bazerman suggest, OKRs should be handled as a potent prescription - it’s an incredibly powerful method for influencing motivation, cooperation, and ultimately outcomes, but it should be prescribed with caution and consideration of the negative side effects.

As I’ve said throughout these posts, I’ve seen first-hand how powerful OKRs are; both as a practitioner and while building OKR management experiences for Atlassian’s largest customers. I believe OKRs have a place in every organization, but I do believe they are overprescribed into contexts where they may not be as effective - for example, when used as a substitute for strategy or in problem spaces where the focus should be on the means, not the ends.

As with anything that builds a strong following and becomes unquestioned standard practice, it’s helpful to humble our perspectives and look at the counterarguments.

In the case of OKRs, there are decades of research on goal-setting in management practices. I’ve found healthy new perspectives in exploring these arguments, and I hope you did as well.

Thoughts on this post? Let us know! You can reply directly to this email or leave a comment:

✨ Highlights (Interesting reads from around the web):

• The Decision Stack, Martin Eriksson: “If you find yourself struggling to make effective decisions in your role as a product leader, or if you're having difficulty coming up with a cohesive product strategy, you're not alone. Perhaps your direct reports are constantly turning to you for guidance and direction, unsure of which path to take? Sound familiar? If so, you may benefit from leveraging the Decision Stack - I've seen firsthand how powerful and effective this framework can be in helping product leaders and their teams make smarter, more informed decisions.”

• Curiosity eats creativity for breakfast, Helge Tennø: “Outperforming your competition is not as much about who is the most creative or who has the deepest data. It’s as much about who can see something nobody else can. Currently the trend is to apply a lot of data to buy our way out of this problem. Hoping that the machine will magically see connections our human brains can’t. But machines are only reflections of our own values, ideas and biases. If we are staring down one rabbit hole the machine will only help us dig deeper.”

• What would have to be true, Roger Martin: “A key problem with ‘what is true’ is that the question focuses entirely on the here and now. Determining ‘what is true’ requires the combination of logic and data, and there is no data about the future — yet. Thus the ‘what is true’ question focuses on analyzing what is currently happening and declaring the truth about the present. Focusing on ‘what is true’ is fine if you are confident that the future will be identical to the past. However, in the world of business, the future has the capricious habit of being different than the past, often in fully unpredictable ways. As a business, you want to create that future — not let someone else do it to you. WWHTBT helps you ask what we have to make happen to make the things true that would need to be true to create the future.”