Case Study: Shelf +
Project Overview
Challenge: Retailer was struggling with the time-consuming, error-prone process of manually translating digital planograms into properly merchandised shelves. Furthermore out of stocks for items that "should have been" on the shelves was costing millions in lost revenue.
Solution: Led the development of an automated planogram-to-print system that seamlessly converted digital planogram files into ready-to-print shelf strips, dramatically reducing implementation time and ensuring 100% accuracy.
My Role: Product Owner & Project Lead
The Problem I Solved
Retailers invest heavily in planogram optimization to maximize shelf space and drive sales, but the disconnect between digital planning and physical execution was creating significant challenges:
Time-intensive process: Store teams spent 4-6 hours per category when performing a reset and 1-2 hours to perform a weekly category update.
Inconsistent execution: Human interpretation led to variations in product placement across locations during resets, and products that should be on the shelf weren’t due to no
Delayed rollouts: Complex planograms took weeks to implement chain-wide
Lost revenue: Suboptimal product placement directly impacted category sales performance
Discovery & Requirements Gathering
Working closely with retail merchandising teams, analysts, category managers, and directors I conducted extensive stakeholder interviews to understand the end-to-end planogram workflow. Key insights emerged:
Variable planograms: Planogram files varied significantly in format across different stores for each category
Variable shelf hardware and configurations: Print files needed to accommodate various shelf hardware configurations and fringe case obstacles such at support beams being part of the category in some stores.
Weekly product changes: Store teams required weekly delivery of kitted rolls of strips containing updated planogram info
Shelf composition data: Store mapping data was required to determine category lengths, segment lengths, and other info about the fixtures used
Multiple planogram creation platforms: Reading planogram files generated by multiple planogram programs was critical
Technical Architecture
I collaborated with our development team to design a robust system that could:
Parse multiple planogram formats: Support files from major planogram software (JDA, Apollo, Nielsen)
Intelligent formatting: Automatically adjust strip dimensions based on shelf specifications
Quality validation: Built-in error checking to catch data inconsistencies before printing
Batch processing: Handle multiple planograms simultaneously for chain-wide rollouts
User Experience Design
Recognizing that operations people had varying technical expertise, I prioritized simplicity, and intuitive layout in the user interface:
Drag-and-drop file upload: No technical training required
Visual preview: See exactly how strips would look before printing
One-click printing: Streamlined workflow from upload to physical output
Error messaging: Clear, actionable feedback for any parsing issues that would cause errors.
Implementation & Results
I led the agile development team through 24 two-week sprints, maintaining close collaboration with pilot store locations to gather real-world feedback. Regular sprint demos with stakeholders ensured we stayed aligned with business objectives.
Key Metrics Achieved
Implementation efficiency: Planogram implementation dropped from 4-6 hours to 1.5 – 2 hours minutes
100% accuracy: Virtually eliminated human error in product placement
Faster rollouts: Chain-wide planogram updates now completed in days rather than weeks
Annual savings: Reduced labor costs and improved sales performance by eliminating out of stocks
Stakeholder Impact
Store Operations Teams: Freed up staff time for customer service and inventory management
Merchandising Teams: Faster implementation of promotional strategies and seasonal resets
Executive Leadership: Measurable ROI through improved operational efficiency
What Worked Well
Early stakeholder engagement: Regular feedback sessions prevented costly late-stage changes
Pilot program approach: Testing with select stores identified edge cases before full rollout
Focus on error detection and messaging: running a strict regiment of data validation and clear error messaging was key in maintaining accuracy, and problem solving
Challenges Overcome
Data format complexity: Invested significant time in robust parsing algorithms to handle inconsistent file formats
Hardware integration: Worked closely with print partner to ensure compatibility with existing printer infrastructure and substrates
Change management: Developed comprehensive training materials and support processes for smooth adoption
Key Takeaways
This project reinforced my belief that the best product solutions emerge from deep understanding of user workflows and pain points. By spending time with store teams and merchandising professionals, we built a system that didn't just automate an existing process – it transformed how the retailer approached planogram execution.
The success of this project demonstrated the power of thoughtful product management: combining technical capability with genuine user empathy to create solutions that drove the required business impact.
Technologies Used: Custom parsing algorithms, print optimization engines, web-based interface, API integrations
Project Duration: 12 months (development) + 3 months (rollout) 24 months (product management)
Team Size: 2 developers, 1 QA engineer, 1 SME, 1 Ops Manager