Design-stein formula

When starting a design project we have some idea about what people need. Doing qualitative research can help us get a much better idea. But still, we don't always know what needs people care more or less about for our target population. We don’t know much about the priority of those needs either. We know people are willing to go to almost any length to get a top priority need met. They will spend the most energy and/or money on whatever best meets the top priority needs. 

So you'd imagine addressing this gap is also a top priority for each design project. But that’s not always the case. One reason might be that we get stuck in conventions. There are good and bad habits with every discipline and design is no different. Sometimes it could be a lack of know-how or sometimes hubris as well. Whatever the reason, not knowing peoples' needs we design for and their priority order - is a huge risk. We risk doing the wrong thing, wasting time, money and resources. But not only that, we risk trust in the organisation, loss of reputation and relevance. That's a rock bottom for any organisation. 

It's interesting that Einstein’s famous formula provides the know-how to deal with this. Interesting or a coincidence I can't say. But I’ll cover more about this a bit later. For now, it helps to start with describing what a need is. Here are some core components of needs to help unpack this:

• Context: When and where do they need this?
• Action: What steps / processes do they take to meet this?
• Medium: What do they use to take these steps?
• Direction: What is the aim of those steps?

Need statements

With these components we can better describe the need. If we jump to solutions too early, we will likely bias the process towards those solutions. For example, being convinced of a solution, can elicit confirmation bias during research. So, we want to focus on the opportunity space at the beginning. That’s why when describing needs, it’s better to separate them from any particular solution. Here is an example of such a statement. 

Need statement format

[Direction] + [Action] + [Medium], when + [Context] 

This could look like:

Reduce landing on ideas and solutions, when we first start a design project 

Did you notice we don't state an outcome? This is key. We infer some kind of outcome or a destination but we focus on the process. That is because we want to know how easy or hard the experience is in reality. And we also want to know how motivated people are in their hearts and minds to continue with this direction. Satisfaction and importance are helpful measures here. Satisfaction tells us about the ease getting the need met - in reality. Importance tells us about our inner drive to meet this need - in our awareness. Identifying least satisfied and most important tells us it's unmet and currently under-served.

Here's where Einstein's formula comes in. Let us try to apply it to our lives.

• Need or Energy: how much it is needed in target population
• Satisfaction or Mass: ease getting this need met in reality
• Importance or Speed (of light): drive and direction to meet this need in awareness

Other terms we could use to describe this are: power (1); force (2); and Value (3). We can flip this around if we want to measure the current state value of a product or service too. 

Design-stein formula survey

To use this formula we need data, but from where do we get this and from whom? First, we have a few questions to ask ourselves to help us decide:

• Subject: Who needs this?
• Desired outcome: What is their intention?
• Undesired outcome: What outcome is unsatisfactory?

When we can answer these questions, we can find the right people for our sample. With the chosen example, we could look for designers who seek to meet needs better. If we get a good sample size of people that fit this, we could send them a survey. Using a “Jobs-to-be-done” survey format is useful. This is what it looks like:

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Reduce landing on ideas and solutions, when we first start a design project 

How important is this for you?

Not important [1] [2] [3] [4] [5] Very important

How well is this currently being satisfied?

Not satisfied [1] [2] [3] [4] [5] Very satisfied

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Survey and sample size

The best use of a survey like this is to have about 20-30 statements. Otherwise, we tend to see a default response bias. That's indicated when participants answer the same way to finish the survey. For sample sizes, you can use online calculators to help. A recommended target is 95% confidence that your sample reflects reality, with 5% margin of error.

After we get our answers we can then use the structure of Einstein's formula. We'll use it to calculate how much our target population is willing to invest in each need. In other words, how much energy is behind each need or opportunity. This is the basic setup for that:

E = ((6 - median satisfaction score) x (median importance score)) x 4

A couple of explanations will help here. We use the median to be more representative of the sample - in case strong outliers skew the result. We're also interested in the amount of dissatisfaction rather than satisfaction. In other words, the weight of resistance our sample experience when they try to meet the need. The lowest satisfaction score is the same as the highest dissatisfaction.

5 for dissatisfaction and 5 for importance is the largest number (5 x 5 =25).

We multiply by 4 to get a score out of 100, the top priority opportunity. We also get a priority order based on all scores. We can also understand the priority of different need scores across many surveys. This is because each statement is stand-alone. That is helpful because we won't ever know or best describe all the needs.

Making other narrative statements

After using this scoring method, we will have a smaller set of top priorities and we know the order of priority too. We can then ask a few more questions:

• New condition: What is the proposed solution/s to change this?
• Baseline: What is the current performance indicator/s?
• Benchmark: How much are we aiming above those?

Once we arrive at this detail we can frame proper hypothesis statements, as well as many others.

Hypothesis

We believe [Need statement] will create [Desired outcome] for [Subject]. To verify we will [New condition]. We know we are right if we gain [Benchmark] compared to [Baseline].

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Value proposition

[Subject] will gain [Desired Outcome] when [Need statement]. This is because [New condition] improves [Action] and [Baseline] with this [Benchmark]. 

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How might we

How might we improve [Context] for [Subject], so they are more likely to get [Desired outcome] with this [Benchmark]?  

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Stories

As a [Subject], when [Context], I want [New condition], so that I can [Desired outcome].

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Problem statement

[Subject] experience [Undesired outcome], when [Context] because [Action + Object]. 

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Opportunity statement

[Direction] + [Actions] + [Medium], when + [Context] 

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It helps to have some crafting of these to make them sound intuitive. Each of these statements fulfils a particular purpose. But if we start collecting each narrative component, crafting these is much faster.