The Clarix
Governance Chain.
A governed, six-step process that takes every planning decision, expresses it in rupees, and makes it traceable — before the order is placed, not after it shows up on the balance sheet.
Why Inventory Keeps Rising Despite Forecast Reviews
Most manufacturers already have a planning process. They have a team. They run monthly reviews. They use a forecast. Yet inventory stays high, working capital stays locked, and the situation does not improve. This explains why:
Because the forecast is being reviewed — but the decisions are not.
A forecast review tells you how accurate last month's numbers were. It does not tell you what each decision cost. Your team knows the forecast was 12% off. They do not know that this error translated into Rs 4.2 Crore of avoidable inventory in three specific SKUs. Forecast reviews create awareness. Only decision governance creates accountability.
Because different planners are making different decisions on the same data.
When two planners look at the same forecast signal and reach different conclusions, the problem is not the forecast — it is the absence of a governed decision process. One increases stock. One holds. One overrides the model entirely. Without a governance layer, the best decision and the worst decision look identical on a planning report. Neither is traceable six months later.
Because safety stock policy is set once and never challenged again.
Most manufacturers set safety stock levels during an ERP implementation or an S&OP redesign — and then those levels persist, untouched, for years. Demand patterns change. Lead times change. Customer behaviour changes. The safety stock policy does not. The result: crores of working capital locked in inventory buffers that the current demand pattern does not justify. This is a structural problem, not a planning error.
The Traditional Question
The question is not:
“Is our forecast accurate enough?”
The Governance Shift
The question is:
“Are our planning decisions governed — and do we know what each one costs?”
Protocol Execution
Phase 01
Detect
Identify forecast bias per product. Finds which products are consistently over- or under-planned and by how much.
Phase 02
Correct
Bias calculated and removed before any model is applied. Garbage-in is cleaned first.
Phase 03
Evaluate
Proprietary framework selects the model that performs best on business impact — not just statistical accuracy. This is Clarix's unique IP. No competitor in India's mid-market offers model selection based on business impact.
Phase 04
Simulate
Base, high, and low demand scenarios simulated against inventory and working capital impact for each product.
Phase 05
Decide
For each product: Increase (by X units), Reduce (by Y units), or Maintain. Every recommendation comes with full audit trail and reasoning.
Phase 06
Quantify Impact
Every decision converted into a working capital number — Rs committed or Rs released. The MD sees the financial consequence before the order is placed.
The Shift to Decision Accountability
Download our 14-page technical white paper detailing the mathematics and attribution behind the Clarix Governance Chain. Essential reading for supply chain managers and planning teams evaluating decision governance.