Imperfect Foods Centralizes Data Team to Enhance Collaboration and Decision-Making
公司规模
Mid-size Company
地区
- America
国家
- United States
产品
- Snowflake
- dbt
- hightouch
- Fivetran
- Mode
技术栈
- Snowflake
- dbt
- hightouch
- Fivetran
- Mode
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Customer Satisfaction
- Digital Expertise
技术
- 分析与建模 - 数据即服务
- 分析与建模 - 预测分析
适用行业
- 零售
- 电子商务
适用功能
- 商业运营
- 销售与市场营销
服务
- 数据科学服务
- 系统集成
关于客户
Imperfect Foods is a grocery delivery service committed to reducing food waste by purchasing groceries that would otherwise go to waste and reselling them to consumers. The company delivers these groceries directly to customers' doors. The data team at Imperfect Foods supports the entire organization, including teams responsible for buying, packing, delivering, and marketing. Adam Smith, the Analytics Manager, plays a crucial role in managing the data team, which initially operated under the product division. The company aims to enhance collaboration and decision-making by restructuring its data team to report to the Chief Financial Officer, focusing on finance and strategy.
挑战
Imperfect Foods, a grocery delivery service focused on reducing food waste, faced challenges with its data team structure. Initially, the data team operated under the product division, reporting to the CTO. This setup led to a technology-based workflow where the team responded to ticket requests across the organization. While this system organized requests, it distanced the data team from the teams they served. Analysts received requests from different teams weekly, hindering consistency and knowledge building. The data team was perceived more as a help desk servicing tickets rather than partners in analysis.
解决方案
Imperfect Foods restructured its data team to report directly to the Chief Financial Officer, who oversees finance and strategy. This shift centralized the data team within the organization, moving from a round-robin ticketing system to tightly-linked partnerships between analysts and business teams. Each business team now has a dedicated analyst, allowing for more context and collaboration on projects. The data team meets regularly with business teams to drive the business forward, engaging in an iterative, feedback-based process. This new structure has increased collaboration, trust, and contextual knowledge about data within the organization.
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