Capital-heavy finished goods, long-lead components and configure-to-order variety mean every forecast error is tied-up cash. DemandIntel right-sizes components, finished units and service parts on your own data, deterministically.
In equipment and machinery, each unit is a large amount of cash and each build depends on long-lead components ordered months ahead. A forecast miss is not a markdown; it is capital frozen in the wrong subassembly or a line idled waiting for a part.
Add configure-to-order variety and a service-parts obligation that outlives the product, and planning on averages quietly ties up working capital you cannot afford to lose.
Each unit carries significant cash. Over-build and the money is frozen; under-build and you miss the order window.
Key parts are ordered months ahead. The forecast has to hold over a long horizon, not just next month.
Options multiply the parts you must plan. Averaging across configurations hides the component you will actually be short of.
You must support installed machines for years. Spare demand is intermittent but non-negotiable.
Customer investment comes in waves. Demand is lumpy and tied to their budgets, not a smooth trend.
With high unit and component value, a small planning error becomes a large working-capital problem.
of OEM aftermarket inventory is slow-moving, yet must be held
of a part's cost is recovered when obsolete stock is scrapped
Source: McKinsey, Turn slow-moving inventory into fast profits (2019).
DemandIntel plans components and subassemblies against real demand and long, variable lead times, so you commit to the right parts instead of the average ones. Service and spare-parts demand is modelled as the intermittent signal it is, protecting installed-base uptime without blanket over-stocking.
Safety stock and reorder points are sized on real error per item, and the whole plan runs on-site, beside your ERP, with nothing to rip out. Because every number is reproducible and auditable, your S&OP and finance teams work from one defensible plan rather than three competing spreadsheets.
DemandIntel plans at the component and subassembly level, so option variety does not hide the part you will be short of.
It accounts for lead-time length and variability directly, so commitments reflect reality over the full horizon, not a one-month view.
Spare demand is modelled as intermittent and service-critical, so you protect installed-base uptime without over-buying the long tail.
That lumpiness is exactly where reproducible, non-smoothed forecasting beats a moving average.
Picture your next S&OP meeting: one number on screen that nobody argues with. See it free, on your own data, in 45 minutes; and if it does not hold up, we part as friends.