Most companies want to see a business case to justify a new initiative — particularly for such a big undertaking. But what good is implementing an idea if we don’t know if it is actually viable? That’s the question we took to our global quick service restaurant (QSR) client team. 

We know the instructional power of prototyping. That’s why we came to them with the idea of prototyping and testing some of the ideas we had come up  with alongside the team in a low-cost and small-scale way. This would give a better sense of whether they were viable and feasible and what possible financial savings could look like. Despite a little initial resistance, they trusted us at this point in the project and decided to go for it.

How We Did It

One idea we explored was a voice-activated digital ledger that could track waste that was being thrown away. If it worked, the tool would save the global QSR’s staff the not-so-pleasant task of hand counting waste at its stores at the end of each day. This had been the protocol for decades.

Prototyping and testing in this way helped make the ideas more concrete. Doing so meant discovering all the questions that the idea would raise, such as, how it could work in different languages, whether noise in a restaurant would affect its function, and how to allow for the correction of mistakes. 

We were no longer in the generative phase — now we had to figure out which ideas to develop and which to leave behind. To do this, the participants needed to overcome their hesitancy to tinker in the maker space as well as learn how to hold onto ideas loosely. Celebrating ‘failures’ was key. When we found out that a low-fi prototype idea, like a morning voice briefing of the supply chain’s status didn’t work, it was a great outcome! We wanted the participants to see that spending a month and only a few hundred dollars to figure out that something wouldn’t work is far better than the alternative (waiting for approval and running a full test with a much bigger price tag attached).

All the tinkering we did had a significant impact: we went from 10 low-fidelity prototypes to 4 mid-fidelity prototypes tested in the field with real people. We quantified the labor effort savings that each prototype unlocked and demonstrated that they improved the jobs of the people who worked with them. For example, one prototype saved about 30 minutes of a team member’s time per day across more than 14,000 locations.

Had the global QSR run more expensive ‘pilots’ or launched full-scale programs, they would have run the risk of finding less-than-desirable results after a year or more of effort. This approach yielded better decisions earlier and more cheaply, by relying on data — not just opinions.