My talk at AppDevCon discussed the Requirements Trifecta but turned it into a Quadrinella: you need leadership vision, market feedback, and technical reality to all line up as listed in the trifecta, but I’ve since added a fourth component. You also need to be able to tell the people who might be interested in paying for this thing that you have it and it might be worth paying for. If you don’t have that then, if anybody has heard of you at all, it will be as a company that went out of business with a product “five years ahead of its time”: you were able to build it, it did something people could benefit from, in an innovative way, but nobody realised that they needed it.
A 45 minute presentation was enough to introduce that framework and describe it, but not to go into any detail. For example we say that we need “market feedback”, i.e. to know that the thing we are going to build is something that some customer somewhere will actually want. But how do we find out what they want? The simple answer, “we ask them”, turns out to uncover some surprising complexity and nuance.
At one end, you have the problem of mass-market scale: how do you ask a billion people what they want? It’s very expensive to do, and even more expensive to collate and analyse those billion answers. We can take some simplifying steps that reduce the cost and complexity, in return for finding less out. We can sample the population: instead of asking a billion people what they think, we can ask ten thousand people what they think and apply what we learn to all billion people.
We have to know that the way in which we select those 10,000 people is unbiased, otherwise we’re building for an exclusive portion of the target billion. Send a survey to people’s work email addresses on a Friday, and some will not pick it up until Sunday as their weekend is Fri-Sat. Others will be on holiday, or not checking their email that day, or feeling grumpy and inclined to answer with the opposite of their real thoughts, or getting everything done quickly before the weekend and disinclined to think about your questions at all.
Another technique we use is to simplify the questions—or at least the answers we’ll accept to those questions, to make it easier to combine and aggregate those answers. Now we have not asked “what do you think about this” at all; we have asked “which of these ways in which you might think about this do you agree with?” Because people are inclined to avoid conflict, they tend to agree with us. Ask “to what extent do you agree that spline reticulation is the biggest automation opportunity in widget frobnication?” and you’ll learn something different from the person who asked “to what extent do you agree that spline reticulation is the least important automation opportunity in widget frobnication?”
We’ll get richer information from deeper, qualitative interactions with people, and that tends to mean working with fewer people. At the extreme small end we have one person: an agent talks to their client about what that client would like to see. This is quite an easy case to deal with, because you have exactly one viewpoint to interpret.
Of course, that viewpoint could well be inconsistent. Someone can tell you that they get a lot of independence in how they work, then in describing their tasks list all the approvals and sign-offs they have to get. It can also be incomplete. A manager might not fully know all of the details of the work their reports do; someone may know their own work very well but not the full context of the process in which that work occurs. Additionally, someone may not think to tell you everything about their situation: many activities rely on tacit knowledge that’s hard to teach and hard to explain. So maybe we watch them work, rather than asking them how they work. Now, are they doing what they’re doing because that’s how they work, or because that’s how they behave when they’re being watched?
Their viewpoint could also be less than completely relevant: maybe the client is the person paying for the software, but are they the people who are going to use it? Or going to be impacted by the software’s outputs and decisions? I used the example in the talk of expenses software: very few people when asked “what’s the best software you’ve ever used” come up with the tool they use to submit receipts for expense claims. That’s because it’s written for the accounting department, not for the workers spending their own money.
So, we think to involve more people. Maybe we add people’s managers, or reports, or colleagues, from their own and from other departments. Or their customers, or suppliers. Now, how do we deal with all of these people? If we interview them each individually, then how do we resolve contradiction in the information they tell us? If we bring them together in a workshop or focus group, we potentially allow those contradictions to be explored and resolved by the group. But potentially they cause conflict. Or don’t get brought up at all, because the politics of the situation lead to one person becoming the “spokesperson” for their whole team, or the whole group.
People often think of the productiveness of a software team as the flow from a story being identified as “to do” to working software being released to production. I contend that many of the interesting and important decisions relating to the value and success of the software were made before that limited part of the process.