The teapot model: how to explain a fuzzy design process to anxious clients.
Just like me, you probably have a hard time making your clients feel comfortable with a design process that starts with a big fuzzy mess, not knowing entirely what comes out in the other end. That is why I came up with the teapot model.
Using design methods to solve critical problems has professionalised the design industry to a point where designers now find themselves in the boardrooms of multinational corporations. Design thinking (letting creatives and suits think together) has put a strain on the traditional design processes, making it hard to describe what is actually going on. After all, it is a mess of research, ideas, data, drawing, crafting, testing and failing.
Design Thinking is the decoupling of Design from any specific toolset (Industrial Design, Architecture, Graphic Design) and recognising that the process can be applied to any problem space. ~Matt Cooper-Wright
I have tried explaining it to my clients again and again: “I need you to be open minded and stay in a state of uncertainty while we try and fail a couple of times. It will be alright in the end. Trust me.” It doesn’t resonate well. That’s why I came up with the teapot model to demonstrate why it makes sense to let a skilled team of designers lead you into the unknown.
Long perspective. Low insight.
This analogy requires a bit of imagination. With use of simple illustrations everyone gets it. Now, imagine the project is like a journey where all you know is the approximate direction and that your destination is beyond the horizon. This is supposed to describe a project with a start and a finish, but where the solution is unknown. What do you do? You either start planning or you start walking, right?
High insight.
Planning equals gathering insights — you try to get to an elevated position to see the terrain ahead. So, in the teapot model, you would climb something high enough to see what the destination looks like. This would give you a better understanding of the journey ahead, but at the cost of spent time and energy.
Shorter perspective.
Walking, on the other hand, equals start working on the solution — you try walking down the path that feels right. This is like starting off a project with an hypothesis. You try and fail. If your path is a dead end, you have still gained insights and experienced the terrain even though it has cost time and energy. If your path was the right one, you are closer to the destination and have a better understanding of what it looks like.
Both strategies seem to solve the same problem. Starting with insights gives you a better overview of the road ahead and the end destination, while walking gives you first hand experience of the terrain and move you closer to the end destination. In the third person view both strategies achieve the same result. To see the difference between the two we have to enter first person view.
First person view.
Imagine yourself on the ground, looking towards the horizon. What do you see? A ball? You can now do one of the following: 1) establish Project ball and climb a tree to gain insights, or 2) establish Hypothesis ball and move towards the object to see if you’re right.
Now the ball looks like a head on a pair of shoulders. Yikes! Our Project ball has to be rescoped and renamed Project Man. If you went with the hypothesis on the other hand, you have actually achieved something: you have tested the hypothesis and are smarter than you were. AND you were prepared that you might fail, so you only have to rule out hypothesis number one and move on to number two.
By now you probably get the point. You may keep climbing the tree or hill and get stuck in the million dollar question “when do we know enough?”, or you can work your way towards the ever changing destination, hypothesis by hypothesis. By doing the latter you treat the insights part of your project as an integrated part of the ideation process, adding to your insight every step of the way.
Just like this analogy, and the design process, I’m hypothesising my way towards a better way to explain what is going on. It isn’t perfect, but it’s a step away from the complete messy process model towards something that is less intimidating and gives an understanding of why we’re doing what we’re doing.
