Reflections on learned helplessness and what to do about it
You may have heard this one before:
A Wagoner was driving a heavy load along a muddy road. He came to a part of the road where the wheels sank half-way into the mire, and the more the horses pulled, the deeper sank the wheels. So the Wagoner threw down his whip, knelt down and prayed to Hercules the Strong. “O Hercules, help me in this my hour of distress.” But Hercules appeared to him, and said: “Tut, man, don’t sprawl there. Get up and put your shoulder to the wheel.”
One of Aesop’s fables, it speaks to some of the frictions that come with motivating teams. As data-driven transformations proliferate across all industries, so too is our realisation of the criticality of culture to their success. Unsurprisingly, my fondest experiences working with teams are those where the collective culture felt healthiest — shared curiosity, quantified decisions, and a real sense of drive. But rather than re-litigate excellent commentary already written on high-performing cultures, I want to unpack a behavioural impediment that commonly disrupts data teams.
Learned helplessness is surprisingly resilient
Learned helplessness has featured on nearly every data enablement program I have worked on. The analogue to a well-known clinical condition, it manifests as one’s ongoing inertia towards change. People simply seem allergic to trying; for instance, I recall on more than one occasion unearthing defect tickets that had been incorrectly marked as ‘resolved’ because “we needed to close tickets”. In a separate incident, I discovered that an engineer tasked with a reasonably straightforward ETL task had spent two days on Youtube instead. And then there was one evening’s memorable exchange with a weary analyst, on his 11th data mining expedition that day, feeling like he had no choice but to “keep digging” (for a tale that refused to be told).
In amidst the befuddlement of these situations, I dwelled on how it was that whole outfits of well-credentialed people would simply give up on lifting the status quo. It is tempting of course, to blame the person — “they are just futzing around” — in a sense, conveniently settling for a simple answer to a complex situation.
Learned helplessness… is still learned, somehow
If culture is the foundation of a data-driven change, and learned helplessness a foil to success, then we should at least contemplate the true nature of this helplessness beyond the individual. What if learned helplessness is actually a symptom of a deeper, systemic issue?
Take for example a “BAU-first” mantra. The inference follows that “everything else comes second” — the leadership cares little for that non-BAU process improvement piece. Returning to our expert 𝚖̶𝚒̶𝚗̶𝚎̶𝚛̶ analyst, it’s hard to fault their view: “Listen, I really don’t have time to refactor my code because I’ve got to get on with model #12!”.
Also endemic is failure avoidance, where people choose inaction over the risk of a suboptimal outcome. Pulling on any one thread almost certainly unravels a multitude of past sins — like when an innocuous request for data security policy guidance might reveal that no policy, in fact, had ever been written. Unsurprisingly, attempts at bettering conditions are met with counsel not to rock the boat.
Perhaps most corrosive, eating away quietly at many-a high-performing team is an organisation’s reward cycle. Beneath the high-performance veneer, teams are helpless in a zero-sum system favouring chutzpah over the dull practicalities of rigour. Case in point: a charismatic manager commits their tech squad to a grand(-ly intractable) solution, receives a promotion for “thought leadership”, and scoots off to the next executive plug. Meanwhile, the hapless technical team stays behind to shore up the house of cards. “Should’ve gone into management”, mutters the seasoned developer on their 51st “Cloud Intelligence” project.
These patterns are rife in Data, with its confluent disciplines and competing incentives. Facing such holding patterns, teams learn there is little reason for improving existing practices, even if their own fortunes depend on it.
Helping teams unlearn helplessness
While there is no quick antidote, there still is good news: learned helplessness can be unlearned. In a sublime piece of work, Clayton Christensen wrote about the rewards from building people up; for those unafraid of making hard choices, I’d proffer two interpretations.
First, clear air in the space between short- and long-term returns can lift entire teams. If we agree with Steve Jobs’ sentiment about hiring smart people to tell us what to do, we should first enable them to figure out… what to do. Thus, the enabling leader holds the tension between revenue and build demands, owns discovery failures and maintains tough budget conversations as the price wagered for a team to build quality things — like enduring platforms that don’t fall over after contractors leave.
Second, few things say more than what a leadership is consistently seen doing. This idea is not new, but we must examine it carefully if we are to help teams unlearn helplessness. In fact, if we want to inspire curious, driven, high-integrity teams — then our grasp of these values must be made systematically visible.
It takes effort. Appraisal frameworks must attribute no less value to sound engineering than it does smart sales (and differentiate the latter from charismatic dross); further, all promises, however big or small, must be kept. But these are the sorts of actions that speak volumes over words — a skilled engineer recognised is also a craftsman respected; a promise kept is also a person valued — the privilege of a leader really is to reap the good seeds they sow.
So, these principles not only serve as a bulwark against learned helplessness, but also give license to a team to do their best work. Recently, a wise colleague simply stated, “What we need to figure out is time and effort, but really, we can pick and solve any problem we want”. In its tone and substance, it reflected the ethos I want my teams, and even more so, our community of practice to have. Most problems worth solving are hard, but people given license to solve the problems that matter — tend to solve the problems that matter.
