Digital Product & AI Solution
Combining UX and AI to take better decisions faster
We ideated, designed and developed a way for Operations in WeRoad to plan tour departures across all regions. With faster and better results.
Collaboration
Service oriented
Technologies
React, Nest, Typescript, Python
Client
WeRoad
Industry
Traveltech
01. Problem
Operations as a bottleneck of hyper growth
WeRoad is one of the fastest growing travel-tech scale-up in Europe, selling group travels in six countries with destinations all over the globe. With a growing net booking value year over year, business is blooming for them.
This rapid growth in volume of business, however, means increasing operational complexities, with consequent friction for even further growth and a risk for contribution margin.
Thanks to a series of business strategy workshops we held, we were able to identify areas of intervention with the highest impact-to-effort ratio. We worked side by side with their team and designed a solution able to make those same tasks faster, cheaper, scalable and accurate.
This rapid growth in volume of business, however, means increasing operational complexities, with consequent friction for even further growth and a risk for contribution margin.
Thanks to a series of business strategy workshops we held, we were able to identify areas of intervention with the highest impact-to-effort ratio. We worked side by side with their team and designed a solution able to make those same tasks faster, cheaper, scalable and accurate.
02. Solution
Rethinking the planning process
We followed a proven method: starting with the users. We interviewed for pain points, objectives, limitations and aspirations. We also sat down with people in WeRoad Digital looking for any reusable software asset we could leverage.
At the end of this research, it was clear that a new way of planning tour departures was needed. Choosing the volume of departures and their exact dates, across all regions and across all selling markets, was something highly expensive and critical to business success. Better planning means lower COGS, a better customer experience, more sales and higher margins.
We then proposed a series of changes in the process and a roadmap to achieve these changes, and followed it through. The result is a web app that optimises for the most common tasks of the team, integrated and talking with other platforms in the WeRoad, equipped with a state of the art Mixed Integer Programming solver able to select the best departure dates given the available information.
At the end of this research, it was clear that a new way of planning tour departures was needed. Choosing the volume of departures and their exact dates, across all regions and across all selling markets, was something highly expensive and critical to business success. Better planning means lower COGS, a better customer experience, more sales and higher margins.
We then proposed a series of changes in the process and a roadmap to achieve these changes, and followed it through. The result is a web app that optimises for the most common tasks of the team, integrated and talking with other platforms in the WeRoad, equipped with a state of the art Mixed Integer Programming solver able to select the best departure dates given the available information.
03. Achievements
Let's look at numbers
The adoption was managed in two steps: one to introduce the new app and one for the automatic planning. This helped ease the change management and receive some UX feedbacks earlier.
We held several sessions with Operations to explain and test the algorithm outcomes together. The results were so positive that we immediately received pressure to go live before peak season planning. Which we did.
As of now, automated planning has become the de-facto standard for the team. 84% of WeRoad trips depart on a day that was selected by the optimisation algorithm. Planning departures of an itinerary has moved from taking days to taking minutes.
Working side by side with WeRoad Digital (aka the Monkeys 🐒), the new app is part of the existing ecosystem of digital products inside the company. This ensures no confusion for their business users and easy maintenance for their engineering team.
We held several sessions with Operations to explain and test the algorithm outcomes together. The results were so positive that we immediately received pressure to go live before peak season planning. Which we did.
As of now, automated planning has become the de-facto standard for the team. 84% of WeRoad trips depart on a day that was selected by the optimisation algorithm. Planning departures of an itinerary has moved from taking days to taking minutes.
Working side by side with WeRoad Digital (aka the Monkeys 🐒), the new app is part of the existing ecosystem of digital products inside the company. This ensures no confusion for their business users and easy maintenance for their engineering team.
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