Item-Level Accuracy ThroughDefensive Design
For Pluckk (SAFresh Technology Pvt Ltd), India
How we achieved 32% inventory accuracy improvement through defensive digital design.
For Pluckk, a leading Indian fresh produce platform, scaling to 500+ daily orders meant managing thousands of individual items with zero room for error. This case study explores the implementation of a custom Picker App built on "defensive design" principles. By replacing manual paper lists with barcode-verified, digitally-guided workflows, we transformed an error-prone warehouse function into a high-precision operation capable of supporting exponential growth.
The Quick Read
Overview & Background
Pluckk (SAFresh Technology Pvt Ltd) delivers farm-fresh, ozone-washed produce to thousands of households across Mumbai, Delhi, Bengaluru, and Pune. As they scaled, the warehouse picking process—selecting individual items for customer orders—became a critical risk factor. Pluckk partnered with us to digitise this core function, ensuring that every avocado, potato, and exotic fruit is tracked from the shelf to the delivery basket with 100% accuracy.
The Challenges
Manual picking was struggling to keep pace with 500+ daily orders. Errors in item selection and quantity were compounding as they moved downstream, leading to customer complaints and operational friction. Furthermore, the lack of real-time inventory visibility meant managers were often "flying blind" regarding actual stock levels versus allocated orders.
The Solution
We developed a custom Picker App that enforces "Defensive Design"—the system assumes human error will occur and builds mandatory verification into every step. The app guides pickers through route-aware sequences, requires barcode scanning for every single item, and enforces strict quantity verification before an order can be finalised.
The Impact
The shift to digitally-verified picking delivered a 32% improvement in inventory accuracy and a 25% gain in efficiency. By catching errors at the source, Pluckk reduced rework to under 2% and gained the real-time visibility needed to manage 1000+ partner farm supplies effectively. The warehouse is no longer a bottleneck; it is a scalable engine for growth.
The Full Story
Pluckk, operating under SAFresh Technology Pvt Ltd, is an India-based farm-to-fork fresh produce food-tech platform (D2C and B2B) headquartered in Mumbai. Pluckk has rapidly expanded its market presence across major Indian cities including Mumbai, Delhi, Bengaluru, and Pune. The company focuses on delivering safe, fresh, and clean fruits and vegetables, distinguished by its commitment to traceability, ozone-washing for hygiene, and a "farm to door in 24 hours" promise. As of FY24, Pluckk has achieved an Annualized Revenue Run Rate (ARR) of ₹100 crore and has successfully raised $10 million in Series A funding. As Pluckk scaled from small pilot operations to handling 500+ daily orders, the picking process—the warehouse function of selecting individual items from shelves and assembling them into customer orders—became increasingly complex. With hundreds of orders containing thousands of individual items, manual picking processes became error-prone and inefficient.
Challenges
Accuracy at Scale
Errors multiply with volume. A 1% error rate on 500 orders leads to significant downstream friction, returns, and customer dissatisfaction.
Limited Inventory Visibility
Without real-time tracking, the system couldn't reliably answer critical questions about stock availability or allocation.
Complex Edge Case Management
Real-world picking involves items running out mid-day, damaged produce, and substitutions that manual systems struggle to track.
Manual Handoffs and Bottlenecks
Working from paper lists meant warehouse managers had to track progress manually through informal channels.
High Cognitive Load on Staff
Pickers had to remember shelf locations, quantities, and sequences, leading to fatigue and increased error rates.
Lack of Audit Trails
Manual workflows made it impossible to investigate where errors occurred or hold specific stages accountable.
Solution Architecture
Barcode-Driven Verification
Every interaction is verified. Items are identified by barcode, not manual selection, eliminating the risk of picking the wrong produce.
Defensive Design Principles
The app assumes pickers will make mistakes. It enforces mandatory scanning and visual feedback (green checkmarks) for every action.
Route-Aware Sequencing
Orders are assigned in the sequence determined by the route-first architecture, ensuring baskets are ready for loading in the correct delivery order.
Strict Quantity Enforcement
Pickers cannot close an order until they have scanned the exact quantity required. This prevents underpicking and overpicking.
Real-Time Inventory Sync
As items are scanned, the system updates status from "available" to "allocated" to "picked," providing a live view of warehouse stock.
Intelligent Exception Handling
If an item is unavailable, pickers mark it as "short." The system automatically alerts managers and adjusts the order fulfillment path.
The Impact, Measured
32% Improvement in Inventory Accuracy
Real-time tracking and scanning reduced discrepancies between expected and actual stock, matching industry leader benchmarks.
25% Increase in Picking Efficiency
Digitally-guided workflows reduced double-checking and manual corrections, allowing more orders to be picked per hour.
<2% Error-Driven Rework
Catching mistakes at the source reduced the rate of incorrect items reaching the delivery stage by over 70%.
Seamless Scalability
The system handles workload distribution automatically, allowing Pluckk to add pickers without increasing management overhead.
100% Auditability
Every action is logged and timestamped, creating a complete audit trail for compliance and quality control.
Reduced Staff Training Time
The app's intuitive prompts reduced the need for extensive warehouse knowledge, allowing new staff to become productive faster.
Comprehensive Before & After
| Impact Area | Before | After | Improvement |
|---|---|---|---|
| Inventory Accuracy | Frequent discrepancies; manual logs | Real-time barcode-verified tracking | 32% improvement in accuracy |
| Picking Efficiency | Slow, paper-based, double-checks required | Digitally-guided, verified process | 25% increase in efficiency |
| Error Rate (Wrong Items) | 5-12% rework from manual errors | < 2% with mandatory scanning | 70-80% reduction in rework |
| Inventory Visibility | Limited; updated end-of-day | 100% real-time visibility | Live stock & allocation tracking |
| Staff Cognitive Load | High; required memory/discipline | Low; follow app-guided prompts | Faster onboarding; fewer fatigue errors |
| Edge Case Handling | Manual alerts; caused delays | Automated "Short Order" alerts | Rapid exception resolution |
| Audit Preparation | Days of checking scattered records | Instant, timestamped audit trails | > 80% reduction in prep time |
| Overall Efficiency | Error-prone manual picking | High-precision digital engine | 35-45% improvement |
Project at a Glance
Client
Pluckk (SAFresh Technology Pvt Ltd)
Industry
Food-Tech / E-commerce
Capabilities
Engagement Model
Jetbro ScaleOther Case Studies
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