The art of de-risking innovation: A guide for designers
By Alejandra Godó Blasco, Service & Business Designer, d.MBA alumna
What is innovation and what are innovation risks?
The word innovation is often used as a vague term. Even for us designers, it is not easy to explain what exactly we mean when we say that we work in innovation. The truth is that innovation is everywhere. For example, when we go for a run and we use our smart watch, we are directly exposed to innovation. We are not only interacting with the physical product but also being immersed in the user experience and user interaction that this product offers.
Innovation could be anything from creating a new product or service to optimizing the design and experience of an existing product or service that’s already in use. In a nutshell, innovation is, by its nature, to create something new (e.g., a new product or a new feature within an existing product) that is successful in the market (i.e., adopted by users and viable for the company).
When we create something new, we are stumbling into an unknown world of many possibilities and uncertainty. It has to be this way. If we weren't struggling with this lack of clarity, we wouldn't be innovating! With innovation, we are directly acknowledging that there's a potential risk associated with it, and that's precisely what we mean by innovation risk.
The practice of de-risking
De-risking innovation is a practice that helps companies validate ideas instead of directly jumping to development or launch. The risks of simply building products without de-risking them are all around us. Just look at what recently happened with CNN+. The company invested 300M$ only to shut down the service after just 32 days.
There are three primary reasons why products and services fail: desirability, viability, and feasibility. Desirability is when people don't want to use the product for various reasons. Viability is when people wish to use the product, so the desirability is there, but the product can't be produced cheaply or sold at the required price. Feasibility risk is when the product is desirable and viable but simply can't be built.
The key factors of risk are money and time. Spending too much of either on a product or service that will not work is what every company wants to avoid. But how do we avoid spending money and time on ideas that won't work? Let me show you an example from the fashion industry.
De-risking a fashion startup project
Imagine you are a designer working for a fashion company, and you get a new assignment. Your colleagues ask you to help define an innovative value proposition for a sustainable fashion product, knowing that the target group is Gen Z consumers.
Your first step is of course analyzing the market and target customers. For example, creating a competitor arena and doing user interviews with several GenZs to understand what their needs from a sustainable fashion platform are. This leads you to find an exciting opportunity in the market.
While many secondhand fashion companies like Vinted or Depop are focusing on platforms where users can sell any type of secondhand clothes, there is no previous curation of clothing. Moreover, these secondhand fashion platforms aren’t always convenient. Sellers still have to do a lot of work themselves. For example, taking pictures of the clothing, chatting with the buyers, creating the package, sending it to the delivery point, etc.
All in all, you end up shaping the following value propositions:
For buyers:
A secondhand fashion marketplace where you can find curated fashionable clothes in minutes. Forget about hours browsing for the perfect item or long delivery times. We will take care of it.
For sellers:
A curated secondhand fashion marketplace to sell your pre-loved items hassle-free. Forget about spending time taking pictures of the clothes and uploading them. Send your pre-loved items and we will take care of the rest.
Now, you may also understand why every company is trying to get bigger. Economies of scale give you a competitive advantage. Larger companies can produce more efficiently, negotiate better prices, achieve higher profit margins, and hence invest more in future growth.
Defining assumptions for feasibility, viability, and desirability
After the value proposition is created, you need to define the different assumptions under the three lenses of innovation risk: feasibility, viability, and desirability. Let's have a look at how we could define critical assumptions for each of these risks.
Feasibility assumptions
‘It is technically possible to create a platform that curates/filters the clothes based on a predefined criterion.’
‘It is technically possible to create a platform where buyers can filter by location to find the garments by proximity.’
Viability assumptions
’By taking a commission per transaction, this platform can create a steady revenue stream.’
’Vintage platforms have a proven business model that creates consistent revenue.’
’There are several revenue streams (e.g., commission, boosted listing, advertising, delivery fees) that could make this value proposition work.’
‘We can collect, open, photograph, post, ship for a price that is beyond the commission, advertising, delivery fees, etc.’
Desirability assumptions
‘GenZ consumers would like to use a platform that sells curated secondhand clothing by proximity instead of selling in other cities/countries.’
‘Gen Z consumers would like to sell their sustainable clothing on such a platform, instead of selling it in other competitors such as Vinted or Depop.’
These are just a few examples of the hypotheses/assumptions that could define this value proposition. But once the assumptions are defined, what is the right approach to test them?
First of all, we need to define which assumptions are the riskiest ones. As the image below from Strategyzer explains, there are two key considerations when mapping the assumptions: criticality (how important it is for the business to validate this assumption) and evidence (how much evidence do we already have about this assumption). As a result, we need to focus on those assumptions that are critical for the business to work and we don’t have any evidence at the moment to know if they can be validated or invalidated, aka we need to define experiments to test them.
Designing experiments to test our assumptions
In the next step, we need to design experiments. This process consists of defining an assumption or hypothesis, an experiment (i.e. what will we actually do to test an assumption), and the main metric. Since we already have a list of assumptions, I’ll share a few examples of experiments we could run for them.
Desirability: We could execute user interviews with several GenZs consumers who are already using apps like Vinted or Depop to explain the idea and measure their appetite. Another way of testing the desirability could be by running ads that are linked to a landing page with a call to action to a ‘waiting list’ to become a member of the platform.
Feasibility: We could test the feasibility of the services offered by sending a package of clothes to one of the company members and letting them unpack, photograph the clothes, and create a listing on the platform, to then measure how long it takes them to execute these actions. Moreover, we could organize expert interviews with several developers to understand the technical limitations of such ideas. For example, interviewing developers of similar platforms such as Maarktplaats, Depop, or Uber eats to understand what is and isn’t possible.
Viability: We could look at the different business models and revenue streams of similar ideas or potential competitors, such as Vinted, Sellpy, or Depop, to understand what their key revenue streams are and see if it’s possible to imitate them. For example, Vinted makes money per transaction by taking a commission, through their shipping costs or their wardrobe spotlight feature. On the other hand, Sellpy makes money by collecting the clothing from customers and getting paid for it, then curating the clothing and selling it directly to the buyers. We could do some research to see if any of these companies are already profitable, which would be a good early sign of a viable business model. Also, it's essential to understand the costs of the different services the competitors currently offer (shipping, taking pictures of the products, etc.) and if these costs are covered by the customers' fees.
For each of these experiments, we need to define success metrics. In other words, what result do we want to achieve to confirm or reject our hypotheses?
So, let’s bring it all together. Let’s say our riskiest assumption is desirability. So, we may start our de-risking with the following experiment:
Hypothesis
GenZ consumers would like to use a platform that sells curated secondhand clothing by proximity instead of selling in other cities/countries
Experiment
Creating a landing page with the new value proposition. We invite website visitors to subscribe to the waiting list if they like the concept.
Main metric
10% of website visitors subscribe to the waiting list.
Learning from experiments
All in all, defining and executing experiments can be a long and iterative process that helps refine and de-risk the value proposition. The more critical we are with defining the assumptions and defining solid experiments with solid metrics, the higher the chances are of our ideas succeeding in real life later on.
It could be that during the experiment round, we identified that the only way that Vinted or Depop generates revenue is by taking a commission from each transaction. If items will be sold in your city, you need to find a way for transactions to go through the platform instead of directly from the buyer to the seller. Creating an offline space in the city, like a secondhand hub where people can bring and pick up their clothes, could be a great solution to ensure this idea is profitable from day 1. This is just an example of how the value proposition keeps evolving as we keep experimenting and de-risking the assumptions.
So, after the experiment, our initial value proposition could evolve into: “The first curated secondhand fashion online and offline marketplace in your city. Find or sell sustainable and stylish pre-loved items in minutes, hassle-free.
The power of testing business ideas in innovation
Testing business ideas can be helpful for many different reasons. It is not only about de-risking to save money and time but also about creating a product or service that people will use and won’t be there to saturate the market. This time could be used for creating something else that the world needs.
Testing business ideas has a significant impact on sustainability. Imagine that all the businesses in the world decide to produce all the ideas that they have. Testing helps ensure that everything we create is going to be used and have a positive impact on the world.
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Alejandra is an Amsterdam-based Service & Business Designer with over five years of experience working on corporate innovation projects and creating new ventures, products, and services. With a solid foundation and understanding of key drivers behind markets, strategic innovation, and customer-centric design. Alejandra currently works as a Service Designer at Accenture Song (previously named Accenture Interactive) and has previously worked for other innovation agencies like oneUp Venture Studio and Loop New Business Models.