Automating Distribution Centers: How Hypercity Boosted Efficiency and Slashed Costs

Last updated on:

May 22, 2025

Walk into any big-box hypermarket and the shelves look effortless: thousands of products, neatly stacked, almost always available. That effortlessness is an illusion built on a tightly engineered supply chain working behind the scenes. HyperCity Retail, the large-format hypermarket chain founded in 2004 as part of the K Raheja Corp group and later acquired by Future Retail in 2017, discovered that keeping those shelves full came down to one number it could not afford to miss: a 95% fill rate. This is the story of how the company rebuilt its distribution centres around mobile technology to hit that target, and why the change paid off within a single month.

The distribution centre challenge behind big-box retail
Why a 95% fill rate became the benchmark
What fill rate actually measures
The vendor turnaround problem
How handheld scanners transformed the workflow
Receiving with the purchase order on a scanner
Put-away documents for correct storage
Pick documents and location-based picking
The results within one month
Where IT meets business: people and retention
What this means for retail logistics

The distribution centre challenge behind big-box retail

HyperCity operated hypermarkets spread across more than 2.2 lakh sq.ft. of selling space. In retail, floor space is one of the most expensive resources a business owns, so every square foot is reserved for products that sell. That economics has a direct consequence: store back-rooms hold only about one day’s worth of inventory. There is simply no room to stockpile.

The bulk of the inventory instead sits in large distribution centres (DCs) located on city outskirts, where land and storage are cheaper. Each DC ran to around 2,00,000 sq.ft. and handled close to one million SKUs (Stock Keeping Units, the unique codes that identify each distinct product) sourced from roughly 1,200 vendors. This split between expensive selling space and large outlying warehouses is the standard model for organised retail, and it places enormous pressure on the link between the two.

If a DC is slow or inaccurate, store shelves go empty within hours. The basic job of a warehouse is to store inventory efficiently and dispatch ordered goods on time to the next point in the chain, which here was the retail floor. When a day’s buffer is all a store has, the DC effectively becomes the heartbeat of the entire operation.

Why a 95% fill rate became the benchmark

To keep shelves reliably stocked, DC managers set a clear performance target: a minimum 95% fill rate across all product categories for store transfers. At the same time, they wanted to minimise the time vendor vehicles spent waiting at the DC, known as turnaround time. These two goals pull in opposite directions unless processes are sharp, which is exactly why technology became essential.

What fill rate actually measures

Fill rate is a core supply chain metric that captures the percentage of demand that is met directly from available stock, without backorders, delays, or lost sales. For a hypermarket transferring goods from a DC to its stores, it answers a simple question: of everything the store asked for, how much did the DC actually send, completely and on time?

The 95% figure was not arbitrary. Across retail, a fill rate in the 95% and above band is treated as best-in-class performance, with 85-90% considered the ordinary industry standard. Falling below that band shows up immediately as empty shelves, frustrated shoppers, and sales walking out the door. A consistently high fill rate, by contrast, signals strong inventory management and reliable supply chain execution, which in turn protects sales and builds customer trust.

The vendor turnaround problem

The other half of the equation was vendor vehicle turnaround. Every truck idling at the receiving dock is a cost, and slow receiving creates a backlog that ripples through the whole DC. The accuracy of the receiving process matters enormously, because all other warehouse workflows depend on goods being logged correctly the moment they arrive. An error at the dock cascades into wrong stock counts, misplaced products, and failed store orders later on.

How handheld scanners transformed the workflow

HyperCity’s head of technology, Veneeth Purushotaman, concluded that the only way to hit on-time fulfilment at this scale was to move DC processes onto automated systems running on mobile devices. The backbone of this was a Warehouse Management System (WMS), software that coordinates people, inventory, and equipment inside a warehouse and integrates with the company’s broader business systems. A WMS typically begins working the moment goods arrive, assigning each item to the right storage location and then calculating the fastest route to pick it later.

Wireless handheld scanners became the human interface to this system. Their advantage over pen-and-paper is stark: manual data entry carries an error roughly once in every 300 keystrokes, while barcode scanning pushes that error rate close to zero and can cut picking times by 20 to 40 percent. The workflow at HyperCity was built around three documents delivered straight to the scanner.

Receiving with the purchase order on a scanner

When products arrived at the DC, the receiving team loaded the relevant purchase order directly onto a handheld scanner. Instead of keying in product codes and quantities by hand, staff scanned items against the order. This single change removed most manual entry and the misreadings that came with it, which is precisely where accurate data capture matters most because every downstream step relies on it.

Put-away documents for correct storage

Once goods were received, the WMS generated a put-away document, again available on the scanner, that directed staff on exactly where to store each item. This is known as directed put-away, and it ensures products go to logical, system-recorded locations rather than wherever happens to be convenient. The benefit shows up later: when an item is stored where the system expects it, it can be found and retrieved without wasted searching.

Pick documents and location-based picking

For store transfers, the system assigned a pick document to a picker over the wireless handheld. The document showed the exact location and quantity for every product needed to fulfil a store’s order. Crucially, the system verified each pick in real time. If a picker tried to take an item that was not on the pick list, an error message appeared immediately, stopping the mistake before it travelled any further. This kind of real-time verification is what makes barcode picking so reliable: scanning the wrong item triggers an alert at the point of action rather than being discovered after the goods have shipped.

The results within one month

The pace of the payoff was the most striking part of the project. Within one month of implementation, the changes were already visible in the numbers. Staff costs at the DC fell by 23 percent, because the same work could be done with less manual effort and rework. Sales rose by 25 percent, a direct consequence of stores staying stocked and fewer items being out of reach for shoppers.

Vendor vehicle turnaround time dropped by 12 hours as the errors that came from misreading data effectively disappeared. This combination is exactly what a well-run system is designed to deliver: faster throughput, fewer mistakes, and lower operating cost at the same time. The pattern aligns with what the wider industry observes, where high fill rates are linked to stronger customer service, fewer lost sales, and a reputation for reliability.

Where IT meets business: people and retention

The benefits were not limited to spreadsheets. The project created a tight bond between the IT systems and the day-to-day business processes of the DC, and that connection changed how staff experienced their work. With clear, device-guided instructions and far fewer frustrating errors to chase, DC employees became noticeably more motivated and engaged. Attrition, the rate at which staff leave, dropped to near zero.

This is an outcome that often gets overlooked in technology projects. Manual, error-prone warehouse work is tiring and demoralising; warehouses increasingly turn to automation partly to reduce the physical and mental strain on their workforce. By removing the constant friction of mistakes and rework, HyperCity made the job more satisfying, and people chose to stay. Operational efficiency and employee retention turned out to be two sides of the same coin.

What this means for retail logistics

The HyperCity DC project set a useful benchmark for warehouse management in organised retail. It showed that the path to a 95% fill rate did not require exotic robotics or massive capital outlay. It required getting the fundamentals right: accurate receiving, directed storage, verified picking, and real-time data flowing through a WMS onto mobile devices in workers’ hands.

For a sector where selling space is costly and stores carry only a thin inventory buffer, the lesson generalises well. A distribution centre is not a passive storeroom; it is the operational engine that decides whether shelves stay full. When that engine runs on accurate, automated processes, the gains compound across cost, sales, speed, and even staff morale. It is a reminder that in retail, the most visible promise to the customer, a product that is simply there when they want it, is kept by systems most shoppers never see.

What do you think? If a single technology change could improve cost, sales, speed, and staff retention all at once, why do you think so many warehouses still rely on manual, paper-based processes? And where would you draw the line on automating a distribution centre before it starts to remove the human judgement that handles unexpected exceptions?

References

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Automating Distribution Centers: How Hypercity Boosted Efficiency and Slashed Costs

Table of Contents

The distribution centre challenge behind big-box retail 🔗

Why a 95% fill rate became the benchmark 🔗

What fill rate actually measures 🔗

The vendor turnaround problem 🔗

How handheld scanners transformed the workflow 🔗

Receiving with the purchase order on a scanner 🔗

Put-away documents for correct storage 🔗

Pick documents and location-based picking 🔗

The results within one month 🔗

Where IT meets business: people and retention 🔗

What this means for retail logistics 🔗