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.

32%
Inventory Accuracy Increase
25%
Picking Efficiency Gain
<2%
Error-Driven Rework
Executive Summary

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.

Deep Dive

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

1

Accuracy at Scale

Errors multiply with volume. A 1% error rate on 500 orders leads to significant downstream friction, returns, and customer dissatisfaction.

2

Limited Inventory Visibility

Without real-time tracking, the system couldn't reliably answer critical questions about stock availability or allocation.

3

Complex Edge Case Management

Real-world picking involves items running out mid-day, damaged produce, and substitutions that manual systems struggle to track.

4

Manual Handoffs and Bottlenecks

Working from paper lists meant warehouse managers had to track progress manually through informal channels.

5

High Cognitive Load on Staff

Pickers had to remember shelf locations, quantities, and sequences, leading to fatigue and increased error rates.

6

Lack of Audit Trails

Manual workflows made it impossible to investigate where errors occurred or hold specific stages accountable.

Solution Architecture

1

Barcode-Driven Verification

Every interaction is verified. Items are identified by barcode, not manual selection, eliminating the risk of picking the wrong produce.

2

Defensive Design Principles

The app assumes pickers will make mistakes. It enforces mandatory scanning and visual feedback (green checkmarks) for every action.

3

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.

4

Strict Quantity Enforcement

Pickers cannot close an order until they have scanned the exact quantity required. This prevents underpicking and overpicking.

5

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.

6

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 AreaBeforeAfterImprovement
Inventory AccuracyFrequent discrepancies; manual logsReal-time barcode-verified tracking32% improvement in accuracy
Picking EfficiencySlow, paper-based, double-checks requiredDigitally-guided, verified process25% increase in efficiency
Error Rate (Wrong Items)5-12% rework from manual errors< 2% with mandatory scanning70-80% reduction in rework
Inventory VisibilityLimited; updated end-of-day100% real-time visibilityLive stock & allocation tracking
Staff Cognitive LoadHigh; required memory/disciplineLow; follow app-guided promptsFaster onboarding; fewer fatigue errors
Edge Case HandlingManual alerts; caused delaysAutomated "Short Order" alertsRapid exception resolution
Audit PreparationDays of checking scattered recordsInstant, timestamped audit trails> 80% reduction in prep time
Overall EfficiencyError-prone manual pickingHigh-precision digital engine35-45% improvement

Project at a Glance

Client

Pluckk (SAFresh Technology Pvt Ltd)

Industry

Food-Tech / E-commerce

Capabilities

Digital TransformationWarehouse OptimisationCustom Mobile Development (React Native)Defensive Design

Engagement Model

Jetbro Scale

Have a Similar Challenge?

Let's discuss how we can help transform your warehouse operations.