A Design Sprint is a fast-paced process that helps companies validate and solve challenges through a system of prototyping and testing ideas with customers. This testing allows businesses to generate data that helps them figure out if their solution solves problems for their customers.
Originally, the Design Sprint was developed by Google Ventures to help startups create products and services (especially digital ones), but here at Echos we have run projects on multiple challenges (for a variety of industries): we created digital products for financial services, experimented products and services for adhesives and sealants, developed services for benefit and allowance companies, products for the food industry, strategy for medical devices, among others.
A well-executed Design Sprint generates data that was once only possible to collect when a solution or idea was put out to market. Rather than launching a fully resolved product, the process lets us take sneak peek into the future through a well-designed prototype. This gives customers the opportunity to provide feedback on the mocked-up version of the solution that doesn’t exist yet.
On the other hand, running a Design Sprint is a complex task. Due to its central characteristics (speed and boldness to build a functional prototype in such a short time), the project challenge its participants and the facilitator, especially when running the project at bigger companies. When there are flaws in its execution, we may face some severe side effects, such as biased data, shallow feedbacks and the team might get frustrated when a solution fails. This month we are sharing som important lessons learned on how to avoid some flaws and traps when running Design sprint.
The Design Sprint was conceived as a presencial and immersive 5-day process. But as we all know, the pandemic accelerated the online version of everything, and this is not different for design sprints. At Echos we are conducting design sprints in shorter intervals that demands a lot less dedicated time of our clients and combat ‘Zoom fatigue’. The new format has been working out sharply, especially with large organisations who want to leverage innovation during this time of change and transformation.
Failures that drive us towards success
When teams run Design Sprints they are often trying to learn about their users problems and about what is desirable for them, so they can make decisions that put their solutions on the verge of innovation. But again, as we all know, innovation is a really challenging path, where the line between failure and success is really thin.
This sneak peak into the future through prototyping helps us to run away from highly hypothetical fields (such as would you buy this? would you recommend it? would you share it on instagram?) and make the scenarios we want to study a lot more tangible, so the users and customers can interact with something concrete and tell us their opinions about it.
Alberto Savoia, former director of engineering at Google, says that there are two different data sets: the first is other people’s research or Other People’s Data and the second is from Your Own Data or YODA. The value of YODA is knowing the context in which the data was generated and more importantly the exact steps behind the experiments. Prototyping and getting customer feedback provide data that no one else could generate: reactions to the team’s hypothesis and assumptions, in a specific context, with the market segmentation that team believes in, at a specific time frame. Well, YODA.
At the end of a good design sprint, the team will have direct feedback from clients that will essentially help them make decisions about their next steps. This can mean being closer to getting things right and building a desirable product, or being further away from building something that doesn’t solve a real problem or that nobody wants. In this thin line between failure and success, rejecting the product of a Design Sprint (or a part of it) can be the team’s greatest success.
Yes, failure is expected in a Design Sprint (and in any product development or innovation process). When you find out soon enough that the solution doesn’t solve a real problem or is not desirable, it means that you are saving big bucks (and that Design Sprint was successful).
Failures that don’t drive us towards success
As I said before: running such a fast-paced and challenging project demands a lot from the team and from the facilitator. In order to have trustworthy results by the end of the week, we need to assure we are methodologically thorough.
It is important to look out for failures that stop teams from gathering good data. They can come from different sources in a design sprint. Based on my experience, these common failures (that we should avoid) in a Design Sprint:
- Problem framing: If the challenge isn’t to establish desirability for a solution, then it isn’t a good fit for a design sprint. The goal of a Design Sprint is to generate data from customers and help the team understand an audience and if the solution solves a problem for them.
- Alignment and clarity: Especially with large siloed companies, we often deal with participants with very different points of view on the problem. The Design Sprint process is designed to leverage everyone’s intelligence and background, but it is also critical to achieve clarity and alignment on how the problem was framed and to move on to the design decisions. If the team keeps diverging about what the challenge is, your design sprint will become a week-long discussion about the problem itself. It’s the facilitators job to keep everyone on the same page and build clarity when there are disagreements.
- The team: Design Sprint teams need the right skills and the autonomy to make decisions in order to make progress. For example, if a decision maker from management must approve the project, then they must be on the team. There is no time during a design sprint to go through a standard approval process. The whole team must be confident that they are the best people to work on the problem and make decisions on their own. The size of the team is also important, a design sprint should have no more than seven people. Any more than seven should be split into small groups.
- Process and methods: A Design Sprint is a very challenging and fast paced project. The team must make fast daily decisions and there is very little space for second guessing or changes. It is important to have a skilled facilitator who not only understands the methods, but also can steer the team away from decisions that could jeopardise the project.
- Confirmation bias: The design sprint is a process that allows for learning and conducting experiments on a possible solution. The goal isn’t to confirm and prove that you were right at the first place, but to experiment and reveal something that was not previously known. If you only find out stuff that you already knew, you most likely designed experiments only to confirm your beliefs.
- Obvious ideas: For most teams coming up with ideas comes easily and people are eager to share them (especially when they are not supposed to). The difficult part is pushing past the obvious ideas that appear right away to dive deeper into the details of the problem. This is where people start to lose momentum or give up. Good design lives in details, not broad genius style ideas. To create innovative solutions, we must get into the specifics and it is important to remember that when things get harder, we must not give up.
When a Design Sprint falls into these traps and has methodological flaws, we question its results (both positive and negative) and teams tend to be frustrated. There is little point in celebrating the skewed validation of an idea, as we are deceiving ourselves and the market does not forgive.
For those who have tried design sprints and were not happy with the results, it is important to understand what went wrong. We are always happy to share our knowledge, please get in touch to schedule a conversation. Or if you would like to accelerate into a productive problem-solving space, reach out to see if a design sprint could work for your challenge.
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