Overview

Whereas the Double Diamond model is suitable for any human centered problem solving context, the four questions approach puts business growth at its center.

Thinking about innovation and growth, Jeanne Liedtka and Tim Ogilvie proposed the four questions and then methods approach in their book Designing for Growth. In the following paragraphs I will outline the main concept and the proposed methods except one – visualization – as visualization is at the heart of everything. In Design Thinking you don't just talk about concepts but rather make them as tangible and concrete as possible. Therefore, visualization is at the core of the whole process. Be it as a rough sketch, prototype or just the grouping of some post-its. We always try to structure and organize information in a visual way.

The Business Model Canvas is for example another tool that can be used in either of those approaches and I use this to hightlight that Design Thinking is a very flexible and dynamic approach. The core principles highlighted earlier at this article are what binds Design Thinking together. It is up to the concrete problem and your organizational context, what techniques you apply.

What is?

In this stage you want to understand and explore the current reality of your users. What problems do your users face with regard to your business?

It is advised to stay open minded and to not focus on specific problems already. The outcome of this stage is a better understanding of problems which you can then turn into opportunities.

Techniques applied at this stage:

• User Journey Mapping: understand your users journey when they try to get a specific job done
• Value Chain Analysis: understand your organization's interactions with partners to produce, market, distribute and support your products and services. As an equivalent to the User Journey Mapping you want to understand the opportunities in the whole production value chain. This is particularly useful when exploring growth potential.
• Mind Mapping to immediately start visualizing your data in order to detect patterns.

What if?

Once you have a better understanding of the user problems, you will phrase hypotheses of how those problems can be solved:

Techniques applied at this stage:

• Brainstorming to generate as many ideas as possible without evaluation. Brainstorming can help to create something completely new and it is done together to utilize different perspectives on the problems.
• Concept development starts with choosing the best ideas from brainstorming. It's about making those ideas concrete to evaluate them from a user and business perspective.

What wows?

Now that we have a good understanding of the problem we need to solve and we have created many possibilities, we need to identify and test those assumptions that hit the sweet spot and will lead to a product/market fit.

Techniques applied at this stage:

• Assumption testing: Any new concept is a hypothesis that needs validation. You treat each concept as a well-informed guess about solving a problem. Therefore, those assumptions are tested in the field (often as rapid prototypes) or confirmed with available data.
• Rapid prototyping is creating visual representations of those assumptions. This can be simple paper prototypes or rough clickable prototypes. Anything, that helps to validate assumptions with users. Important: a prototype is not a goal in itself. It is just a tool to make our concepts testable.

What works?

In this stage we confront our hypotheses with reality: usually we start with low-fidelity prototypes that we refine based on our learnings before we start implementation.

Techniques applied at this stage:

• Customer co-creation: Invite potential users and test your prototypes together, observe their reactions and follow-up on the findings with iterations on those prototypes. You start with low fidelity prototypes and once the confidence grows you move towards high fidelity prototypes.
• Learning launch This is an experiment that is executed in the intended market. There are always some critical assumptions left and a learning launch helps to get a deep understanding how much for your users is at stake. Are they really using it. Why or why not? What learnings can you gather to improve it further before it hits the full market?