Bet small and learn fast
Launch your innovation project to new heights together with a co-pilot from Pollen. Our process is iterative and welcomes placing small bets to maximize learning and minimize risk. Your team members will solve a defined challenge based on real problems using key behaviors throughout the project. You choose the degree of commitment ranging from several loops for wicked challenges down to single iterations of insight collection, creative workshops and user testing. The end game is to create a success story that not only deliver user driven innovation but inspires your organisation to follow.
Challenge assumptions, empathize with users, dig into IP landscape and map unspoken truths in the organization. We do this to answer What is? and to scope the challenge with hypothesis, motivating questions and problem definition. Here it is crucial to carve out a challenge that is specific enough to create drive but wide enough to welcome all possible solutions.
You have probably been in many brainstorming sessions, unfortunately most of those have been a waste of time. So we do things differently. As facilitators we wrap the participants in the mysterious creative cloud of uncertainty, misinterpretation, random input and association. Too fluffy? How about our track record averaging 3 patent applications per workshop!
In this phase we develop ideas through prototypes and test key assumptions in user tests. It’s a delicate process where we need to be fully aware of our bias to collect true data for informed decision making.
Exploring the future of basket-2-bag shopping with ITAB
Challenge: This story starts in looking into the grocery industry. How will stores change with automation? How will tomorrows shopping experience respond to evolving consumers’ purchasing habits and what role might basket-to-bag have?
Solution: We started with the consumer and observed how we are using current systems to buy food. We then mapped tomorrows’ needs over today’s frictions and found a number of attractive opportunities. One of them asked questions around how multi modal sensors could be used to reduce time through the checkout process.
Results: We ended up with a number of compelling concepts on how to use intention prediction and multi senses guidance to enhance human-machine interaction. These concepts are now being tested on users for feedback. The client also express a positive change in behaviors both by observing users to define problems, experimenting to explore solutions and prototyping to learn.