When I was responsible for developing new ‘knowledge products’ for a major professional services firm, we did it the old fashioned way. We identified all the content that was available and asked the practice leaders (the guys footing the bills) which content they wanted. We didn’t talk much with the front-line people or find out what jobs they did, or wanted to do, using knowledge. The practice leaders, ignorant of what was possible, told us, often, what they thought we wanted to hear. Then we went away and had fun designing sophisticated multi-functional Intranet websites and tools that would accommodate all this stuff, in the way that made sense to us as ‘information architects’. Then, we flooded their e-mails and newsletters with messages telling them what content was now available (messages few people read), and developed training courses and CBT to show them how to use the fancy tools we’d bought or built (training few people took). And we were surprised when most of our ‘users’ didn’t use or like the content or tools very much. Duh.
A recent article in Business Week (thanks to Paul Graham for the link) describes the importance of getting your new technology product approximately right fast, and fine tuning it once it’s out in the market. Traditional product developers would be aghast at such an idea, since it sounds hasty and unprofessional. But today, with the appropriate caveats (“this is still in beta”) it makes sense (and not just for technology products) because rapid iteration is the best way to perfect a product, and because customers are essential to that process.
As I’ve explained before, ‘finding a need and filling it’ entails finding the intersections of ‘jobs to be done’ and communities of people who do (or want to do) those ‘jobs’. This is illustrated in the need/affinity matrix above. This is not the way designers and marketers (“the customer doesn’t know what he wants”) usually think. Designers think in terms of features and benefits. Customers think in terms of the job to be done. They don’t want a 1/4″ drill bit (even if it plays iTunes music); they want a 1/4″ hole. It’s the jobs to be done that the entrepreneur should be looking for — jobs that existing products and services, for some reason, don’t satisfactorily do. (And a reminder: make sure you understand that reason — it can save you a lot of grief.)
Likewise, marketers think in terms of demographics. But these days demographics is no longer a good way to parse your market: The days when a product could be made for a certain specific homogeneous age group, cultural group, or gender are long gone. Our affinities — the people or communities with whom we share a particular need or want — are now extremely complex, and getting more so.
So you need to find the intersections of (unmet) needs and affinities. In the example in the matrix above, vendors have recently (in the last decade or so) discovered a need for decks and fences that require virtually no maintenance. People don’t have time to keep these structures looking beautiful. The solution the inventors came up with was moulded plastic (or wood/plastic composite) decking — no cracks because of thermal resilience and no painting because the colour is baked right in. The vendors discovered two main communities interested in such products — people with no time (or, if they were to be honest, lousy carpentry skills), and people worried about the newly-discovered health and environmental dangers of creosote and other wood preservatives.
Once they’d found the intersections, the next step was to develop a strategy canvas (this is a Blue Ocean Strategy term, but I’ll use Kathy Sierra’s intriguing ‘equalizer‘ metaphor to demonstrate it) that would differentiate, in the eyes of the identified customer communities, their product from traditional wood decking and fencing materials:
So what does this have to do with iteration and the wisdom of crowds? Well, as designers and marketers are quick to point out, the customer’s needs and wants are never that clearly articulated. They probably don’t know what they want or need (most of us are not very imaginative), especially if it’s something that hasn’t been invented yet.
The vertical axis of the need/affinity matrix is therefore initially fuzzy. Iteration clarifies it. Show people something that meets what they think they need, and with enough iterations, they and you together will hone in on what they really need that you can produce.
The inventors of plastic decking and fencing (back in the 1980s) didn’t do very well, because people couldn’t imagine using it. They couldn’t visualize it. The iterators like Eon and Trex who developed prototypes, installed a few free of charge so that customers and neighbours could see what they were getting, and kick the tires, and suggest improvements — those were the vendors who made money filling this need.
Likewise, the horizontal axis of the need/affinity matrix is also initially fuzzy. With less time available each year, customers were clearly clamouring for lower-maintenance products. But those customers probably would be loath to admit that, compared to previous generations, they just don’t have the skills to build, repair or maintain such structures. And who would have guessed, if they hadn’t done a lot of research ‘in the crowd’, that consumer concerns about health, safety and the environment would lead to an aversion to, and then a ban on, creosote and other toxic wood preservatives, throwing the entire industry into chaos? And what about people in struggling nations who don’t have electricity? Snap-together decking does away with the need for power tools. Tapping the wisdom of crowds entails interviewing and surveying as many people as possible to get a consensus not only on the need, but on the categories of customer, the affinity groups, who have that need. Such primary research (which requires wearing out a lot of shoe-leather) would ask questions on issues such as:
This is hard work, but as long as you have the time and passion for it, it’s not expensive. It will give you a lot of information about the communities of customers who will buy your product, and, by iteration, exactly what they would prefer to buy. That puts you light years ahead of traditional companies, who invent in a lab, design in a vacuum, andthen advertise to anyone who will listen and hope for the best.