Customer Case Study · Procurement & Finance · Cost Intelligence
Fuel and raw materials are the biggest controllable costs in a cement plant, and their prices swing every month. HMC gave the cement company's procurement and finance teams one view of it: where every tonne comes from, where its cost enters the process, how prices move, and what that does to cost per tonne and to the budget.
Figures indicative; validated metrics available on request.
Procurement buys fuel and additives for many plants from many sources. Finance has to explain cost per tonne against budget. Each team had its own spreadsheets, and the two rarely agreed on the same number at the same time.
Petcoke and imported coal prices move with global markets and the rupee; a few dollars a tonne changes margin per bag.
Fly ash, slag, gypsum, coal and petcoke reach each plant from different sources by rail, road and sea.
Base price, freight, handling, moisture and calorific value sat in different files, so true landed cost was hard to compare.
Finance learned why cost per tonne missed budget weeks after month end, too late to act.
Built with both teams, so the buyer and the controller look at the same rupee.
Select a step to see what happened.
Traced every input from source to kiln.
Deliverable: Supply network inventory and cost tree.
Agreed the rules once.
Deliverable: Cost model specification.
Four tools on one data model.
Deliverable: Dashboards and models.
Used in buying and close.
Deliverable: Review cadence and playbook.
The model extends.
Deliverable: Roll-out roadmap.
Where materials come from, where their cost enters the process, how their prices move, and how finance explains the result. All data on this page is synthetic.
Plants and their sources across India, with material flowing by rail, road and sea. Filter by input, click a plant for its supply mix, or switch on a disruption to see lanes reroute and what it costs.
Plant locations approximate; sources, lanes, volumes and costs synthetic. Boundaries: Survey of India outline via DataMeet (CC BY).
Follow limestone from the quarry to the dispatch bay. Drag to orbit, scroll to zoom, and click any stage to see what it consumes and what it costs per tonne of cement. Switch on the cost lens to heat-map the plant.
Schematic plant; cost per tonne figures indicative.
Three years of synthetic input prices, indexed. Brush the timeline to zoom. Then shock the inputs and watch cost per tonne, cost per bag and annual impact move, and find the cheapest kiln fuel mix the chemistry allows.
Balance is imported coal. Above the sulphur limit, petcoke raises SO₃ in clinker beyond what the kiln can handle without bypass; the shaded zone is off-limits.
Synthetic price series and cost structure; not market data.
The finance view of the same data: compare suppliers on true landed cost, see what contracts saved against spot, explain cost per tonne against budget, and balance stock cover against cash.
Synthetic suppliers, prices, contracts and stocks.
Fuel mix, sourcing and contract levers took cost out; the shared model meant variances were understood while there was still time to act.
₹ per tonne of cement, by category and input
Share of monthly variance attributed to a driver
Figures indicative; validated metrics available on request.
The cheapest price at the source is often not the cheapest tonne at the plant gate.
Knowing what a price shock does to a bag of cement turns market news into a buying decision.
When procurement and finance share the cost tree, variance stops being a debate and becomes an action list.