The Data Team at Imperfect Foods Delivers Data From the Center

Imperfect Foods is a grocery delivery service that buys groceries that would normally go to waste and resells them to consumers—delivering them directly to their door. The data team supports the entire organization, from the teams buying the food, to the teams responsible for packing and delivering, to the marketing team and all of the functions in between.

Adam Smith is the Analytics Manager at Imperfect Foods. When he first started, the data team was operating under the product division and reported to the CTO. In this structure, the data team operated with more of a technology-based workflow, responding to ticket requests across the org.

While this round-robin ticket system helped the data team address requests in an organized way, it kept them more distant from the teams they were directly serving.  Each analyst was getting a request from a different team each week, which was not helping build consistency and knowledge with data team members. With this type of workflow, they were viewed as more of a help desk that serviced tickets to teams, rather than partners in analysis.

Now, the data team reports directly to the Chief Financial Officer, who oversees finance and strategy. This shift has resulted in the data team becoming fully centralized within the organization; they are operating from the center. And with this new structure, the data team transitioned from a round-robin ticketing system to a system of tightly-linked partnerships between analysts and business teams. Each business team now has a single, dedicated analyst, which has resulted in analysts having much more context about the projects they’re working on.

“Now we have a much more collaborative process. We meet with business teams weekly and partner together to drive the business forward,” Adam Smith, Analytics Manager at Imperfect Foods, told us. “We’re not building a dashboard and giving it to them; it's a much more iterative, feedback-based process—‘You asked us this big question, what do you think about this?’”

To improve this partnership structure, the data team regroups regularly to review what’s been working well and what hasn’t to inform a proactive analytics strategy. This has dramatically increased collaboration, trust, and contextual knowledge about data in their org.

In this new structure, the data team has increased collaboration, trust, and influence across the organization, in addition to being able to be more proactive on projects.

As a result of the new analyst-business team pairings, Smith is seeing that business teams are reaching out to the data person as soon as they start thinking about a new initiative, instead of at the end of a project. This is helping each project have better data. In these tighter partnerships, the data analyst is also able to make recommendations on what kinds of data would be useful and iterate on dashboards with more context, which is also helping build data literacy.

Sitting under Finance and Strategy has made the data team more centralized—allowing them to play a much bigger role than they could by only reporting to the technology team. This shift has also increased the visibility of the data team’s work across the organization and has helped business teams be closer to the data in the process. “Stakeholders feel like they’re more involved in the process and getting data in a way that’s most useful to them,” Smith said. “They’re also seeing that the highest value work is getting done.”