SCM

A plan that survives the lead times you actually get

Planning fails when it runs on quoted lead times and last year’s demand. We build the plan on what your suppliers and your orders have actually done.

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Called about

The forecast is a spreadsheet one person maintains.

Purchasing buys to a lead time nobody has checked in two years.

Every shortage is a surprise, and every surprise is expedited by air.

Sales, operations and finance each hold a different number.

Demand planning

Statistical baseline, promotion and seasonality overlays, and a place for the judgement call to be recorded.

Supply and sourcing

Material requirements, purchase planning, approved vendor lists and multi-source allocation rules.

Supplier collaboration

Purchase order confirmation, shipment notice and schedule sharing, without an email chain.

Sales and operations planning

One monthly number the three functions sign, with the assumptions attached to it.

Included in every planning scope

  • History cleanse and outlier review
  • Lead time measurement
  • Segmentation and policy rules
  • Safety stock model
  • Forecast accuracy reporting
  • Exception and alert design
  • Planner runbook
  • S&OP meeting pack

The seams we design first

SCM · ERP Purchase requisitions, orders and receipts
SCM · IMS On-hand, on-order and allocated positions
SCM · OMS Open demand and promise dates
SCM · MES Capacity and actual production output
Assisted layer

What AI does in planning, specifically

It proposes and explains. A planner still owns the number that goes into the plan.

Demand signal

Forecasts that take in promotions, seasonality and open orders, and show which assumption moved the number.

Lead time learning

Actual supplier performance measured per item and site, replacing the quoted figure in the planning parameters.

Supplier risk flags

Deteriorating confirmation and delivery behaviour surfaced early, with the orders exposed to it listed.

Scenario compare

Two plans side by side with the service, stock and cost consequence of each stated in the same units.

The integration layer

Show us last quarter’s forecast miss.

We will trace it back to the assumption or the data that caused it.

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