The tyre industry has an orchestration problem. Here is the cost of leaving it unsolved.

It is 6:30 AM at a tyre manufacturing plant in Maharashtra. The ERP has released overnight dispatch orders. The logistics team has two hours to convert them into a workable truck plan: right vehicle, right load, right transporter, right route, right time. By mid-morning, three trucks have left with avoidable gaps in their loads. Two transporter indents went unconfirmed until the window closed. A priority dealer order in Tamil Nadu was deprioritised because nobody flagged its urgency. A vehicle dispatched northward is heading toward a depot already sitting on weeks of slow-moving inventory.

Nobody made a bad call. The system was not built to make good ones at this speed, across this many variables. This is precisely the execution layer Enmovil was designed to operate in.

Most tyre manufacturers have invested heavily in procurement. Freight rates are negotiated. Transporter panels are managed. Rate contracts are in place. And yet, total logistics cost as a proportion of revenue stays elevated, well above what contracted rates alone would suggest. The contracts are clean. The execution is not. This article is about that execution layer, and what closing the gap actually looks like in practice.

Every sector has complex logistics. The tyre industry carries a specific combination that makes standard supply chain software consistently underperform, and leaves a disproportionate share of value unrealised every quarter.

A Tier-1 tyre OEM manages thousands of active SKUs across passenger cars, truck-bus radial, two-wheeler, OTR, and agri segments. Each carries different dimensions, weight profiles, stacking constraints, and regional demand patterns. Dispatch planners' default to what is familiar rather than what is optimal, loading trucks based on what is staged at the dock rather than what produces the lowest landed cost.

Tyres are physically awkward freight: heavy, hollow in the centre, and resistant to ideal stacking. A truck that appears full by volume is often well below its permissible weight limit. Generic TMS platforms optimise for one dimension. Tyre logistics demands simultaneous optimisation across both, for every SKU, every load, every day.

A large tyre OEM may serve several thousand dealer touchpoints, spanning metro distributors, C&F agents, regional hubs, and rural sub-dealers, each with different order frequencies, credit terms, and service-level expectations. Without centralised execution intelligence, coordination becomes reactive and fulfilment delays quietly erode secondary market share.

Freight represents a meaningfully higher proportion of total logistics spend for tyre companies than for FMCG or pharma. This makes fleet utilisation a strategic variable, not a scheduling detail. Even a modest fill-rate improvement across a large OEM's network translates to significant recoverable cost at scale.

Multi-plant, multi-depot networks feeding distribution hubs across geographies create chronic inventory imbalance. Without real-time network intelligence and adaptive rebalancing, inter-depot transfers are triggered by dealer escalation rather than proactive sensing.

These are not one-off failures. There are structural gaps in the execution layer, recurring across every shift, at every plant, every week. Each one is measurable. Each one is recoverable.

Execution Gap 01
What is actually loading on the truck every morning.

Fleet utilisation is one of the most consistently under-recovered cost lines in OEM tyre logistics. Trucks are dispatched based on what is physically staged and available at the dock, not on what produces the optimal load across weight, volume, and SKU stacking geometry. The result: vehicles departing daily with avoidable unused capacity. At the scale that large tyre manufacturers operate, that gap is not a rounding error.

Execution Gap 02
The planning problem no spreadsheet was built to solve.

The tyre dispatch planner's job is a combinatorial optimisation problem handed to humans with spreadsheets and a two-hour window. Hundreds of daily orders. Multiple vehicle types. Dozens of transporters with contracted rates, Share of Business allocations, and availability windows. Dealer priority tiers. Regional delivery deadlines. They solve it adequately, not optimally, using the transporter who responded first, missing the SoB contract because nobody tracked it in real time. The cost is systematic across every dispatch cycle.

Execution Gap 03
When the secondary leg becomes a visibility black hole.

A delayed delivery to a priority dealer is not just a service event. It is a cash flow event, a relationship event, and , compounded over time, a market share event. In most tyre distribution networks, the secondary leg from C&F to dealer runs on verbal confirmations and manual documentation. Visibility is zero until the regional manager gets an escalation call. By then, the delivery window has already passed.

Execution Gap 04
The freight invoice that nobody has time to fully verify.

Tyre freight invoices are genuinely complex: distance, toll, vehicle type, waiting charges, fuel surcharges, loading fees. Most finance teams audit a fraction of total invoices, checked against rate sheets rather than GPS data. What is not audited is paid. Transporters bill for kilometres the GPS does not confirm. Waiting charges appear for delays that were never logged. Most tyre manufacturers are absorbing 4 to 7 percent of gross freight spend as undetected leakage every quarter.

Execution Gap 05
When ERP shows green and the dealer is already out of stock.

A high-demand truck-bus radial SKU sits in excess at a Western depot while dealers in South India are stocking out. Both positions appear normal in the ERP. No alert has been triggered. No transfer has been recommended. The imbalance surfaces only after dealer escalation, well after the stockout has already cost revenue. This is not a forecast failure. It is the absence of a network intelligence layer that identifies the imbalance before the dealer raises an urgent order.

Execution Gap 06
The coordination tax that accumulates before a single truck moves.

Tyre logistics involves more coordination stakeholders than most manufacturing verticals: plant dispatch teams, C&F agents, regional hubs, primary transporters, sub-transporters, dealers, and the central supply chain function. Without a connected intelligence layer, all of this runs on phone calls, WhatsApp groups, and email threads. Exceptions surface only after the damage is done. A significant share of supply chain team bandwidth is consumed in status-chasing that should not require a human at all.

Most supply chain platforms were built for general manufacturing and configured for tyres as an afterthought. Enmovil was built for operationally complex, margin-sensitive, SKU-intensive industries from the ground up. For tyre manufacturers specifically, that means four capabilities that generic platforms cannot deliver out of the box.

The six gaps described in this article do not exist independently. They compound. A missed SoB allocation forces reliance on uncontracted freight. Uncontracted freight creates invoices that go unverified. Unverified invoices generate leakage that accumulates silently. Fixing one gap in isolation recovers partial value , closing all six through a connected, AI-native intelligence layer is where the compounding effect changes the cost structure of the operation.

Enmovil is not a TMS bolt-on or a visibility layer added to an existing system. It is an AI-native supply chain and logistics operations layer that treats planning and execution as a single, self-correcting intelligence system. CADDIE AI reads across demand sensing, dispatch planning, in-transit execution, and freight settlement simultaneously. ERP-agnostic by design, it integrates with SAP, Oracle, and custom environments without requiring a rip-and-replace.