Project overview
Implemented a KPI tracker, updated job descriptions, integrated machine learning for inventory prediction, and established an SOP database to improve accountability, efficiency, and knowledge retention.
Problem we were solving
437 faced challenges common to many eCommerce stores: difficulty predicting inventory needs and timing purchases. This resulted in reactive rather than proactive buying.
Operating in a constant state of reactivity hinders a team's ability to develop and implement a long-term strategy, which is essential for a brand's success in a rapidly changing marketplace.
Solution & outcome
To address these challenges, we implemented several strategic changes:
- KPI Tracker: We introduced a KPI tracker to align the team on key metrics to track and manage. This resulted in specific outcomes for which each team member was accountable.
- Updated Job Descriptions: We revised job descriptions to accurately reflect each team member's current role and align personal and company incentives.
- Machine Learning Inventory Software Implementation: With a structured team and consistent meeting cadence, we integrated machine learning software to predict future inventory needs more accurately. This prevented overbuying low-velocity items, cleared "dead" inventory, and invested wisely in lines without acute demand spikes. TLDR: Less money tied up in inventory.
- SOP Database: To mitigate the risk of knowledge loss due to employee turnover, we created a comprehensive SOP database and recording process using Notion and Loom. This ensured that operating procedures were documented and accessible to all team members.
Testimonial from client
