Data-informed Design to reduce uncertainty
As a product designer, it’s easy to focus only on the creation of beautiful prototypes and pixel-perfect design. However, if the solution does not solve the user’s problem or if it doesn’t fit the purpose it was meant to serve, the design and all the work behind it will be pointless.
“Design is increasingly associated with beautification. I hate the term beautification. We never just wanted to make something beautiful. We wanted to make things better.”
~ Dieter Rams
At my work, we help doctors and clinic managers handle more than 2.5 million bookings per month, and more than 30 million patients from 10 different countries. What we design in our tech offices in Barcelona or Warsaw, have a huge impact on the life of real human beings looking for specific health specialists. This adds a lot of responsibility on our design team but also gives us motivation to do the best job possible.
While every company works in a different way and have access to different amount and type of data, in this article I will share the philosophy that we follow at Docplanner when providing solutions to our users.
Data-driven vs. Data-informed Design
The Data-driven Design approach refers to making design decisions based solely on quantitative data. While there are a lot of benefits to following this approach, some limitations should also be considered.
For example, you could end up throwing away some good design solutions that resulted as a failure from a data point of view. Or you could be loosing completely the connection with the reality and design improvements only to move the number up in the short term without thinking long term.
The Data-informed Design approach has a subtle but crucial difference. I think it could be considered an evolution of the Data-driven approach. It is more flexible and adds qualitative data (human inputs), instinct, and experience to the quantitative (data inputs) mixture. The combination of all these factors is the superpower that every product designer should willing for.
“Design helps us know the possible; the world as it might be. It’s a mechanism for exploring, evaluating, and shaping the future.” ~ Karl Fast
The Importance of Human Inputs
Our mission is clear and bold: “Make healthcare more human”. The focus on people is an essential part of our company. Observing the user to understand why, how, when and where they use our product is crucial; it provides us great feedback to constantly improve our product.
Forgetting or skipping the user inputs is more common than you might think. When the time is short or the pressure to release something is high or when we think we already know the users, here is where the biggest design mistakes happen and where we design something beautiful that doesn’t improve the user’s life. These type of mistakes are expensive in terms of time and money for the company and result in a decreasing level of trust in the design role.
No matter how much expert knowledge and experience you have, you can’t know everything.
At Docplanner we have a UX research team that is focusing on providing strategic researches and insights on user problems. This helps us to make better design decisions and it’s our starting point when we approach any kind of problem.
Although our UX research team is in close contact with our users to provide us valuable insights to rely on, we, as product designers, should also look to have direct contact with the users. I believe this is essential to create a connection with them and better understand their needs. That’s why we always get as close as possible to the users, having in person meetings with doctors and clinic managers, doing usability testing sessions, collecting and analyzing feedback, etc.
The goal of every product designer is to solve real user problems, this is why, acquiring and analyzing user inputs becomes a fundamental part of your design process.
Data Inputs
Digital innovation has already reshaped the way most industries and businesses are functioning today and data collection and analysis are becoming more accessible than ever. The Product Design World has also changed and decisions are now based on data and human input, not gut feelings or personal tastes.
At Docplanner, we have embedded product analysts (PAs) in our product teams. They help us to analyze data to find insights, problems, or opportunities. We use data mainly on 2 particular moments of our design process:
- At the beginning of the process, data help us to spot the problem and give us an idea of the size of it, how many users are affected by it and so how much our business gets affected by it.
- We use data also at the end of the design process to validate our design solution. To do that, we set some UX metrics before creating the solution and we track data when the solution is on production. By comparing the data tracked with the UX metrics, we can determine if the solution works or not.
Tracking UX metrics is also important because with it you can show the value of design to the management and the team. There is a lot of talking around the idea that designers should “have a seat at the table”, that’s easy to achieve if you can show the huge value that your work is bringing to the business with simple and un-refutable numbers.
Here’s an internal Docplanner example of being data-informed. Recently, we released our new Dashboard for doctors and clinic managers. The results were very positive +26% satisfaction rate compared to the previous version, with engagement staying neutral. Even if the result was positive, with the help of our product analyst, we evaluated the page more in depth and we found low usage of a tab component that we introduced to display more content to users without having to scroll down.
From the user feedback and the user tests, we could confirm some of our assumptions: users don’t see the tabs as clickable and some information displayed in the tabs component are not clear enough. We combined all this information and decided to remove the tabs and improve how we present some content that was not clear. Below the final result that we will test soon.
Conclusion
Data inputs tell you what is/isn’t happening. Human inputs help you better understand why is/isn’t happening. The main dangers are to not use them or to rely on one part too heavily; as product designers is our responsibility to use them in a balanced way and design the best solution based on all the factors combined.
It’s easy to think that with more years of experience you don’t need data or user inputs anymore, because you can follow your gut feeling or because you already solved similar problems in the past in other companies. The reality is the opposite, the experience teaches you that it’s so easy to be wrong and that you should always start from data and user inputs to reduce the possibilities to make expensive mistakes.
