Never have I heard a better description of the challenge that faces Product Managers than a quote that I overheard at this year’s ProductCamp Seattle — “Humans are hard…” spoken by none other than my fellow General Assembly Product Management instructor Tricia Cervenan, as part of a panel discussion. Those simple words struck a chord with me, as it made me think about all of the different ways in which we as Product Managers attempt to understand, document, and predict human behavior. Every single day I can come up with some variation on the idea that “humans are hard” impacts us in some way.
Humans are hard…to convince.
A big part of our jobs as Product Managers is to lead through influence, and this means that we have to convince others of the direction that we want to take. And this can be really hard. Everyone in our organization has a different spin on the product, the strategy, the company, the culture — and often these only truly “mesh” at their core, with the radiating effects or impacts of these goals pushing us in a wide variety of directions. Add to this the fact that different people learn, think, and decide through different paths makes it even harder. We need to take time as Product Managers to understand how it is that the influencers in our company do these things, and when, where, and how we should approach them in order to move things forward. Some people respond to data, others to emotional appeals, and still others strictly on financial motivations — we must know who is swayed by what appeals, and use those to our advantage on a daily basis.
Humans are hard…to predict.
Another big part of our jobs is trying to predict how human beings will react — what features they will find compelling, what positioning will make them more likely to buy our product, or even what price points will motivate upgrades to greater levels of value. We use a lot of tools to do this — A/B testing, demographic analysis, user statistics, heat maps, big data analytics, UX studies, you name it. All with the end goal of reaching that Holy Grail of predicting what people will do in the future. Sometimes we’re right, sometimes we’re wrong, and sometimes we split the difference. Sometimes we look to the past to see what we think people will do in the future; sometimes we look at emerging trends to see what people are likely to do in the future; sometimes we just make purely random guesses about what they will do. But the truth is, all of this is entirely hypothetical — the single best predictor of what someone will do is what they are doing. Asking someone if they will pay for your product is conjecture — showing them something and asking them to pay now will tell you exactly what you need to know. When that isn’t possible, we make predictions — but we must know that these are mere conjecture — that we can, and will, be wrong. Hopefully less often than we’re right, but predicting future behavior is always a risk.
Humans are hard…to train (or untrain).
Almost all of our products are intended to be used by other human beings. But somehow we seem to forget just how difficult it can be to “train” people to use our products. And all too many companies short-cut their user experience analysis, to supplement it with training and support and technical services teams. But that’s entirely backward thinking — our products simply shouldn’t be so difficult and unapproachable that we require users to go through training. Even the most complex of systems can and should be able to be used by the most novice user without resorting to training, support, or post-sales technical services. Because whenever we’re trying to train someone how to use our products, we’re also trying to untrain them from whatever other solution they’ve been using, even if it was manual. And that is hard — hard for us, hard for them, and hard on the product. If someone can open up your product and not know immediately what they should do, you’ve lost half the battle, and the rest is uphill through gunfire and artillery. The modern era requires products that are simple to engage with and which grow in complexity as the customer needs it — not from the first ten seconds. Think of how Slack works — easy to engage, very simple to start with, but incredibly complex if you feel the need to build integrations or plugins. That’s the bar that your product should be meeting — not how much can it do but rather, how much can be done with it.