September 6, 2017
Every new technology brings with it a period of exploration. This exploration is crucial for mastering the tech and uncovering potential, but solutions at this stage are often less than ideal for solving real user problems. For example, is speaking our grocery list one by one into our Amazon Echo really substantially better than jotting it down on a piece of paper?
Purely technological decisions and experimentation within tight constraints can overshadow user experience (UX) goals, which can create convoluted design that does not effectively address a real problem. Also, when an exciting new technology emerges, it’s tempting to incorporate cutting-edge technical elements into design solutions without an eye on solving a painful problem in the most effective way.
When we prioritize the ‘cool factor’ of technology during periods of exploration, it becomes more difficult to execute strategies that address the real needs of end users.
Start By Problem Hunting
At its core, design centers on a critical question – how can we effectively solve problems?
It requires discipline to focus on the problem space and not get tangled up in all the possibilities of a new or emerging tech. If this happens, we find ourselves retrofitting a need into a pre-defined solution. This is often referred to as “a solution shopping for a problem.” In which case, it begs the question, “Is it really a solution then?”
We always start by asking these two questions to keep users and their real-life needs at the center of our decision making:
- Where do users need help making decisions?
- Where are users overwhelmed with choices and information?
This first set of questions helps you uncover pain points. Pain points are synonymous with opportunities to serve and make a positive impact on users. Always start here.
Use AI to Serve the Problem, Not Vice Versa
Once you have a handle on the problem space, begin narrowing your focus on opportunities to apply AI capabilities. Start by asking these questions:
- How can we supercharge our users’ ability to make better decisions faster?
- How can we supercharge our users’ ability to achieve a goal or satisfy their knowledge gap?
- What are the immediate ways we can help users do less work?
Earlier we mentioned the value of technology exploration without the constraints of a specified challenge; formulating these questions is where that gained knowledge comes in. These questions take the value statements from AI (speed, personalization, massive data-sense-making power) and put them in context of user problems.
Identifying real problems to solve first—then blended with a baseline understanding of AI’s capabilities—will allow you to create a business case for AI that both serves users and ultimately generates ROI for the business. The further you are from understanding the problem space, the more difficult it is to build a viable business case.
AI gives customers a superpower to make quick decisions in a sea of complex data and an abundance of choice. It’s an exciting time for business leaders and designers alike; we now have a powerful set of capabilities to help us untangle once unsolvable problems. The organizations that stand to benefit the most are ones that invest energy in understanding the problem space first and then capitalize by moving quickly into testing and learning through experimentation.
Read more about how we blend AI, UX and other technology investments throughout the digital transformation process here.