Stagnant innovation in the retail space commonly happens for at least one of these reasons: lack of business alignment, unclear strategy and metrics, the wrong team, or siloed resources and budgets. In-house innovation labs help accelerate innovation by creating micro-use cases, then building solutions to solve them.
In our retail data lab engagement, we’ll build out a process and a framework, then work alongside our clients to innovate – showing you the ropes as we build scalable solutions and help your internal teams become self-sufficient.
We’ll stand up a cross-functional team, either embedded or fully independent, within your organization to vet and execute ideas for innovating with your data. With our innovation frameworks, you’ll get to data ROI faster.
We’ll start by taking a look at use cases for driving retail innovation through a series of discovery workshops. Whether you already have an idea in mind, or need help uncovering an opportunity, our strategy team can help you identify and prioritize an innovation initiative. Whether it's surfacing recommendations to employees on the floor, a new way of looking at predictive financial data, creating a visibility tool for your supply chain, or anything else — we'll help your team sort and prioritize the right projects to make an impact.
Depending on the identified opportunity, we will then map out a strategy for testing. Our teams use agile frameworks to build a small experiment to test our theory, be it a prototype, pilot AI model, or something else. Once we prove out the innovation model, we’ll help you “sell” the idea to the rest of your organization.
Once we get the greenlight and have a proven model, we’ll build out the first iteration of the initiative. Working closely with anyone affected, we have proven ways of gaining buy-in along our build process, so change management isn’t a painful afterthought.
An innovation lab (also known as accelerators, innovation spaces, incubators, or research hubs) is typically a dedicated team, space, and budget focused on accelerating new retail products, understanding market trends, and developing solutions for users — either internally or end consumers. We apply that same concept to data: working with our clients to uncover new ways of leveraging their existing data, prototype concepts for innovative retail software products, and prioritizing data initiatives.
We start every project with a workshop, what we call a Go! Sprint, where we’ll identify a vision for the lab and define the core problems your organization is facing — then put together a proposal for continued engagement.
From there, we typically work as a retained team for innovation labs. We’ll work with you to build a cross-functional team (usually including representatives from operations, tech, and data) to own the innovation lab within the organization. Integrating with the team, we will establish ways of working and frameworks to ideate, vet, and build data innovation solutions to give you a competitive edge and drive change, faster.
It will take us about 3 months to get the lab practice established. From there, we recommend at least a year of our team integrating with yours — so we can tailor the ways of working to your team and transfer any knowledge or skills needed to make sure the lab provides value into the future.
Improve the in-store experience for customers and employees by delivering actionable data to managers.
Manage and prioritize tasks across all store locations to gain more efficiency and control of your store operations.
Create adaptable assortment planning that leverages AI to help your planners create profitable, unique assortments.
Gain visibility into deliberate or inadvertent inventory shrink so you can make informed decisions on where to invest.
How one of the world’s largest retailers created a scalable digital platform that’s now used each day by more than 1.5 million team members in six countries
Listen into our virtual panel where leaders from Walmart, Microsoft, Chick-fil-A, and Divergent Technology Advisors walk through their insights and experiences in creating change with data.
The best data tools may not even feel like a data tool, but instead an informative or process management tool that makes employees’ jobs easier.