6 Degrees of Separation: Make Product Decisions with Skin in the Game

It’s not uncommon to hear that most problems are people problems. I recently heard someone in product management say that 90% of her time was spent solving the people issues that got in the way of shipping.

How do great organizations solve this?

How do you minimize friction, streamline decision-making, and develop a culture of strong, yet weakly held, opinions, which need to carry the burden of proof?

The more the merrier

When starting, you find yourself in a one or two people show, running the business, calling all the shots and figuring out what comes next. You talk to prospective customers, you test stuff out with your friends, family, and acquaintances, you find creative ways to build out the next thing you think is going to make a difference and pay the bills.

You and your business partner have taken time off the safety of your previous jobs, it’s your money on the table and you both need to do, or die. When misalignment arises in these early days, it will usually spell death, so there only 2 ways out. Either both get in line, or they get out.

This isn’t to say that you’re not going to make an insurmountable amount of mistakes or that you won’t disagree on what to build. It just means that because you’re both rightly incentivized to make smart, cheap, reversible decisions until you’ve guaranteed product-market-fit, you’re forced to operate in discovery mode and accrue gains faster than you’re running out of runway. That’s the sole goal.

As you scale, though, you need to draw up an organizational structure. You create functional/specialist responsibilities, you set up management structures and knit an intricate web of incentives, local optima, personal motivations, punishment and reward mechanisms that, even in the best of cases, will create tension, friction, and personal stress. This intricate pattern of individual behaviors will create a complex system that, if you’re not careful, will likely produce highly undesirable outputs.

So is it possible to get back to hyper-alignment, obvious criteria for decision-making, shared spidey-senses that spot risk at a distance, and where the only way to go was up?

Aligning locally

A large number of organizations have moved into a local-maxima optimization model. They’ve consolidated functions (think devops, UX, data scientists) and created x-functional teams that are accountable for their own outcomes. They need to work with the org to set their goals, but then are left free to roam the space that they’re given and go crazy in optimization mode.

Having multiple functions under the same goal removes a lot of the stress of individual/functional handovers, increases the length but decreases the cost of different functions transacting (more on this in a later post) and provides a great startup-like criterion for decision making: Will this move our needle in the right direction?

Highest Paid Person’s Opinion Syndrome is easy to avoid locally, as long as you have a mechanism to assert truth. Experimentation, impact assessment criteria like RICE, design sparring, believability-weighted voting, and peer reviews are processes one finds to align people behind any specific tactic when they’ve already bought into a goal.

Aligning globally

Bigger issues come when people need to align globally. Whereas it’s easy to give teams a mission, that’s a lot harder to do when teams are in different departments, locations, have somewhat-conflicting goals (e.g. acquisition vs conversion vs retention) and lack the mechanisms for truth-seeking at scale. This leads to a lot of escalation and very little progress on any front.

Companies begin to feel like they need to be in sync, and precious time and customer value is wasted while internal struggle ensues. Two common avenues for this to happen are when alignment is required between functions, and when alignment is required between units.

In a functional organisation where there aren’t clear decision-making frameworks, each function tends to over-optimize for their own goals, introducing waste and costly delays in unnecessary circumstances.

Product will want to avoid rework and maximize impact so they’ll produce lengthy, prematurely defined specs, which are then taken over by design/UX. These guys produce extremely polished solutions that are overly complicated to build. Engineering then takes over and optimizes prematurely, solving scalability and reusability problems that are yet to exist and hand over to release, who fit it into the lowest risk slot in their calendar. When examining outcomes, Data Analysts will then want to be extremely certain about what they’ll report back to the business as the result of the initiative, again increasing the time to inspect, adjust and adapt.

Even worse problems might arise from unit organizations trying to tackle joint problems. Often organized around features or business goals, whenever the need to interact with others emerges, teams are poorly equipped to decide together. Taking the path of least resistance, two types of cultures often arise: 1) an “ab test everything” approach, which erodes alignment and leads to Frankenstein products and experiences that follow Conway’s law to a T, or even worse, 2) an “escalate everything” approach where the nearest common boss decides which way to go and agency is removed from individual contributors and middle managers.

The truth is somewhere in the middle.

Evolving cultural traits

The first step should always be a consensus approach, where people agree on the right way to assert the truth about a hypothesis and approach designing a solution together, openly encouraging dissent and unabashed, even if inclusive, candor. It helps to have fewer, rather than many, goals, across the org at any point in time. Strong principles, widely communicated and believed, help people get to consensus.

If that fails, even slightly, each party should present their Bayesian priors, based on observation, evidence, and previous results, in order to make believability-weighted decisions.

If that fails, they should design an experiment that tests their hypotheses. They should let the data do the talking, let customer-first observation and revealed preferences make decisions.

Only when that isn’t possible should escalation be the process, as a last resort and a signal to the organization that better mechanisms need to be designed to work in the trenches.

“Quod gratis asseritur, gratis negatur”

In any circumstance, the ability to challenge, dissent and compete healthily should be an intrinsic part of the product creation process. But what is freely asserted, should be freely denied.

The Latin proverb that withstood Lindy’s test of time holds for today’s companies more than ever. It is unhelpful to engage in duels of opinion, purely grounded on instinct, vision or authority. Opinionated disagreement is useful if it can constructively be built upon.

Quarreling indefinitely over reversible, non-consequential decisions is a terrible use of people’s time and erodes trust across a company, making every subsequent decision incrementally harder than the former. Lack of clear criteria for decision-making worsens the problem.

Finally, people involved in the decision-making process need to own a stake in the outcomes. If any one person is able to block or tie-break a decision without any accountability for the potential costs of their intervention, that is an important design flaw. Skin in the game promotes group cooperation and fosters altruism.

Hitchen’s razor should always be on the table.

I’m a Product Manager at luxury fashion platform Farfetch, working out of Lisbon. I’ve previously built stuff at Skyscanner and designed urban mobility and travel products. I still think I can make people’s lives suck a little less. I’m on twitter if you want to start a conversation or keep track of what I’m reading and writing: https://twitter.com/colivetree