Overstocked on the wrong things. Out of stock on the right ones.

It costs retailers 6.2% of sales every year — more than many of them make in net profit. Plavista is planning software for the retailers and consumer brands the enterprise platforms were never built for. Runs on the ERP you already have.

Inventory distortion — the combined cost of out-of-stocks and overstocks — runs at $1.7 trillion a year worldwide, equal to 6.2% of global retail sales.  IHL Group, 2026
01  /  The size of it
8.3%

Worldwide out-of-stock rate. It has barely moved in twenty years.

Gruen, Corsten & Bharadwaj, GMA
72%

Of out-of-stocks come from the retailer's own ordering and forecasting — not from suppliers.

Kaizen Institute
4 in 10

Empty-shelf encounters where the sale is gone: 31% buy it elsewhere, 9% don't buy at all.

GMA worldwide study
4–8%

Sales uplift from correcting inventory-record accuracy alone, even off a strong baseline.

ECR Retail Loss

None of this is bad luck, and most of it isn't the supplier. It's forty thousand ordering decisions a week, made by people who don't have the time or the tools to think about them.

02  /  Why this exists

“I helped build one of the enterprise planning platforms, then spent fifteen years implementing the others. They're excellent — and they were never designed for you.”

Ranga Mallipudi, founder — twenty years in retail planning, on both sides of the software
$700K–1.1M

A year, for forecasting and replenishment alone, at a 300-store grocer. Two modules out of a suite.

VendorBenchmark, 2026
+45–80%

Implementation, on top of the first-year subscription. The partner bill is usually the same order as the licence.

VendorBenchmark, 2026
12–24 months

A typical enterprise deployment, before any of it reaches a planner's screen.

Published implementation timelines

So a ₹2,000 crore retailer gets the quote, does the arithmetic, and goes back to spreadsheets. Given those numbers, that is usually the right decision — and it is exactly why this exists.

03  /  What it does

Four things, every morning.

Decides what to order

Every product, every store and DC, every day — with lead time, shelf life, case packs, supplier reliability and shelf capacity already accounted for. And it shows its reasoning on any line you question.

Hands your planners a short list

Thirty decisions that genuinely need a human, ranked by what's at stake in rupees — out of forty thousand that don't. The rest is handled, logged and reversible.

Catches what your reports hide

Stock that exists in the system and not on the shelf. Demand that never reached your sales report because you were out. Suppliers whose stated lead time and real lead time are different numbers.

Proves what it was worth

Availability, waste and working capital, measured weekly against stores still running the old way. Your finance team signs the number. We don't.

04  /  How we work

Four commitments, written into the contract.

We sit on top of your ERP

We read from it and write orders back into it. We never become your system of record, and nothing you have already invested in gets thrown away.

Eight weeks, three of them in shadow

Before anything is released, the system runs alongside your buyers for three weeks proposing orders nobody acts on. You see exactly what it would have done, on your own data, before you trust it with a rupee.

Your policy, your dials

How much availability, how much waste, category by category — these are commercial decisions, so your category managers set them on screen. Not parameters buried in a config file by a consultant.

Part of what we charge is the outcome

A share of what we actually save you, measured against a control group locked before go-live and agreed with your finance team. If it doesn't work, we don't earn it.

05  /  The platform

One platform, built in the order that pays for itself.

We'd rather be honest about what exists today than show you a brochure. Everything below goes into the same data model, for the same buyer, in this order.

Building nowDemand forecasting · Store and DC replenishment · Allocation
NextAssortment planning · Store clustering
ThenMerchandise financial planning · Open-to-buy
LaterMarkdown · Promotions · Space

Connects to SAP, Oracle, Microsoft Dynamics, Ginesys, GoFrugal, Unicommerce, Tally — or a nightly file drop, if that's what you have.

06  /  Where to start

The diagnostic. Problem first, product second.

We work with retailers and consumer brands to find where the 6.2% actually goes in their business — across stock, availability, returns, expiry and channel — before selling anyone software. How the diagnostic works

What we need

Twelve months of sales, stock, purchase order and write-off data. Under NDA.

Please don't clean it. Send it exactly as it comes out of your system — the mess is usually where the findings are.

What you get

A written analysis of where the money went, broken down by cause, with the top ten fixes ranked by what each is worth.

Yours to keep and act on, whatever happens next.

What it costs

A fixed fee, agreed before we start — and credited in full against your first year if you decide to go ahead.

Three weeks from the day the data lands. No obligation at the end of one.

Or write to [email protected]
07  /  Who

Ranga Mallipudi

Founder · Hyderabad, India

LinkedIn

I began in the R&D team of one of the major enterprise planning platforms, helping build its merchandise planning suite — merchandise financial planning, assortment planning and size profile optimisation — largely from the ground up. Retailers around the world still run it today.

Then fifteen years on the other side of the table, implementing the leading enterprise planning platforms for grocery, hypermarket and fashion retailers across the US, UK, Middle East, South Africa and India, with TCS, Cognizant, Zensar and Tech Mahindra.

Those platforms are very good, and they are built for a scale of retailer most of the industry will never reach. Everyone else is left with spreadsheets and instinct. That's the gap Plavista is being built into.

Alongside the platform, I advise retailers and consumer brands on planning transformation, platform selection and operating model design, whichever platform they run. About advisory