Resilient, cost-efficient operations that scale without breaking.

The operations director knew the company's logistics cost had climbed from 8.2% to 11.1% of revenue over two years. What he couldn't tell the CFO, because he genuinely didn't know, was why. The 14 distribution points across Maharashtra and Gujarat had been accumulated over a decade of growth and two small acquisitions. No two of them had been designed to work together. Stock levels were tracked in separate spreadsheets. Transit times were estimated, not measured. When the CFO asked why logistics costs were up, the honest answer was: we don't know.

We built a network model using two years of transaction data, the kind of model the operations team had wanted to build for 18 months but had never found time to do properly. The output was uncomfortable: four of the 14 distribution points were handling less than 8% of combined volume while sitting on fixed costs that were eating the margin. Two strategically located hubs replaced them. Carrier contracts were renegotiated using real volume data rather than the informal arrangements that had been in place for years. A basic S&OP cadence was introduced, not sophisticated, but consistent.

The company had grown from 200–600 people through organic hiring and two acquisitions, and had never stopped to standardise how work actually got done. Each site had its own approach to order management, its own escalation path, its own way of handling errors. New employees learned the job by watching whoever sat next to them, which meant the errors spread as consistently as the good habits. Managers spent their days correcting mistakes that shouldn't have happened. The CEO used the phrase 'firefighting' in three consecutive board presentations.

A four-week process diagnostic across five core functions, not to document every variation, but to rank 42 identified gaps by error-to-output impact. The redesign was executed in phases, starting with the three functions where errors were costing the most. Process guides were written by the people doing the work, not by the consultants. That's the only way they actually get used.

This reflects the type of challenge our consultants are built to solve, drawn from real industry experience. The cost-per-delivery had crept to ₹68 against a ₹55 target. Every month the operations head would present the number, the CFO would ask why, and the honest answer was a mix of things that were true but not actionable: traffic, failed deliveries, re-attempt loops. What nobody was tracking, until we mapped it, was that 14% of deliveries were failing on the first attempt, each generating a ₹29 re-attempt cost that nobody had named or owned.

Three weeks of diagnostic work across five delivery zones, focused not on confirming costs were high but on tracing exactly where each overage rupee came from. Route density was the main driver: too few drops per kilometre on high-cost zones. Route clustering was applied. A pre-delivery WhatsApp confirmation was built, simple, not sophisticated, that cut the category of failed deliveries that should never have failed: wrong address, recipient absent, gate closed during delivery window. Micro-warehousing was piloted in two dense postcodes.

This reflects the type of challenge our consultants are built to solve, drawn from real industry experience. Energy represented 19% of the company's total operating costs, and grid power had risen 28% over three years. The CFO had set a 15% reduction target and handed it to the operations team, a team with deep expertise in textile manufacturing and almost none in energy procurement. The gap between the target and the team's current capability wasn't small.

An energy audit across three plants identified peak-load patterns and contractual inefficiencies that the company had been paying for without realising. A competitive tender was structured for rooftop solar across two sites. A Power Purchase Agreement was negotiated for the third, a structure the operations team hadn't previously considered because they didn't know it was available at their consumption scale.