MGF5690 Chap.8 Forecasting and Inventory
Forecasting and Inventory
Forecasting converts incomplete demand signals into a planning view; it does not remove uncertainty. Managers should choose a useful horizon, combine historical patterns with contextual judgement, document assumptions and update the view as evidence changes. Inventory can buffer timing differences for supporting goods, but excess stock ties up cash and risks obsolescence while shortages damage availability and trust.
In services, managers must also plan non-stock resources such as labour, information and partner access. The unit treats these choices qualitatively rather than requiring quantitative forecasting calculations.
What this chapter covers
- 01
Forecast purpose, horizon and decision owner
- 02
Historical signals and contextual judgement
- 03
Assumptions, scenarios and forecast revision
- 04
Availability, shortage and excess exposure
- 05
Supporting goods and non-stock service resources
- 06
Learning loops and balanced planning measures
Worked example · free
Plan for an uncertain campaign
- +2Define the decisions, horizon and signals, then state base, high and low demand assumptions.
- +2Secure flexible clinical, support and information capacity while protecting critical supplies.
- +2Set review triggers using arrivals, mix, wait, availability and waste.
Key terms
- Forecast horizon
- The future period for which a demand estimate is prepared to support a decision.
- Scenario
- A coherent possible demand condition used to test plans under uncertainty.
- Inventory exposure
- The service and financial risk created by shortage, excess, damage or obsolescence.
Forecasting and Inventory FAQ
Why should forecasts include assumptions?
Assumptions reveal what must remain true for the forecast to guide action. They allow managers to monitor change, revise the plan and distinguish a poor method from an unexpected external shift.
Is more inventory always safer for service availability?
No. Extra stock may lower shortage risk but increases holding, expiry, obsolescence and complexity. The appropriate buffer depends on consequence, replenishment flexibility, uncertainty and the customer's availability promise.
What replaces inventory for an intangible service?
Managers can reserve flexible labour, cross-trained capability, partner access, information or customer self-service options. These arrangements buffer demand indirectly, but each has lead times, quality limits and coordination costs.
Assessment move
Begin an answer by naming the operating decision rather than discussing forecasting in the abstract. State the horizon, demand signals, important contextual changes and uncertainty. Use scenarios when a single estimate would hide material risk, and link each scenario to a staged response or trigger.
When discussing inventory, balance availability with cash, waste and obsolescence, and remember the service system's labour, knowledge and partner constraints. Required quantitative techniques are excluded, so do not invent calculations unsupported by the case. Build each forecast argument backwards from a decision.
Staffing next month, ordering supplies and reserving partner capacity use different horizons and tolerate different errors. State who decides, when commitment becomes difficult to reverse and which demand aspect matters, such as total volume, timing, location or case mix. This keeps the analysis operational. Inventory the available signals before selecting a view.
Transactions reveal realised demand but can omit customers lost through stockouts or excessive waiting. Enquiries, bookings, cancellations, search patterns, promotions, calendar events and frontline knowledge may reveal change earlier, though each also carries bias. Explain what a signal represents and what it misses rather than treating more data as automatically better. Separate a recurring pattern from a contextual shift.
Historical behaviour may help when the process and market remain stable, while a new channel, campaign, regulation or competitor can weaken that relationship. Document the judgement used to adjust expectations and invite challenge from people with different information. Forecast accountability improves when assumptions are visible.
Construct base, high and low scenarios around the uncertain driver with the greatest operational consequence. For each scenario, state a staged commitment, an observation that would trigger it and the lead time required. This avoids both false precision and passive uncertainty. A useful plan changes when evidence changes.
Evaluate supporting-goods inventory through availability, shortage consequence, replenishment flexibility, cash, storage, expiry, obsolescence and recovery options. Critical or slow-to-replenish items may justify a buffer, while fragile or rapidly changing items increase excess exposure. Name the service promise that the stock protects. Remember that intangible capacity cannot be warehoused.
Cross-trained labour, partner agreements, remote support, information and customer self-service can create flexibility, but these buffers need preparation and have quality limits. Explain the trade-off rather than calling them free capacity. Compare forecast quality with decision quality.
A small error may be harmless if the plan is flexible, whereas a plausible estimate can still produce a poor decision if it ignores lead time or consequence. Track availability, waste, expedited work, wait and forecast revision alongside the chosen operational outcome. After an event, review which assumption failed and whether the response trigger worked.
In assessment writing, resist unsupported numerical forecasts because the required content is qualitative. A transparent scenario, evidence map and revision process shows stronger managerial judgement than an invented point estimate.
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