Mining spares forecasting for slow-moving and intermittent demand
Mining spare parts forecasting differs significantly from consumer and manufacturing forecasting. Most mining inventory has intermittent, irregular and highly variable demand.
The challenge
Sparse history, failure-driven demand, shutdown-driven demand, slow movers, erratic patterns, missing metadata and “squirrel stores” all combine. A common mistake is to over-rely on statistical methods.
What is required
Understanding the split between planned and unplanned demand, and embedding it in policy
Evaluating BOMs for forward planning
Handling shutdowns and stock building
Identifying and managing outliers
Validating strategies
Collaborative demand planning between end users, maintenance and materials management
Some demand patterns are not suitable for forecasting at all. Some items carry acceptable risk. Others are best planned with maintenance teams.
Multiple forecasting approaches, plus other ways of establishing a view on demand. Planning teams and end users work together on inventory problems, using the most suitable tools and learning how to balance service with working capital.