Company Context

Meta is planning Q4 production for its VR hardware business, centered on the Meta Quest line. Q4 is the most important quarter of the year because it includes holiday demand, major retail promotions, and the highest concentration of first-time headset buyers. You are the Operations Manager supporting Reality Labs leadership and must recommend how many Quest headsets Meta should produce for Q4, balancing upside demand capture against inventory risk, channel constraints, and competitive pressure from Sony PlayStation VR2, ByteDance Pico in select markets, and premium PC VR alternatives.

Strategic Situation

Meta has to lock a production plan 4 months before the quarter starts. The decision is difficult because demand is driven by a mix of replacement purchases, gifting, new-to-VR adoption, and software-led ecosystem pull from titles distributed through the Meta Horizon ecosystem and the Meta Quest Store. Underproducing risks stockouts during Black Friday and Christmas, lost software attach, and weaker ecosystem growth. Overproducing risks markdowns, excess inventory carrying cost, and channel conflict with retail partners.

Assume the production decision is for all Quest headsets to be sold globally in Q4 across Meta direct channels and retail partners.

Data Points

Additional operating assumptions:

• Meta enters Q4 with 420K units of finished goods inventory.
• Average manufacturing lead time is 10 weeks, and practical maximum Q4 production capacity is 3.0M units.
• Historical Q4 demand split: 40% October, 35% November, 25% December shipments to channel.
• If Meta runs out of stock in a key holiday week, leadership estimates 60% of unmet demand is lost permanently and 40% shifts to later weeks.
• Competitor outlook: Sony PS VR2 is expected to remain supply stable but premium-priced; Pico may be aggressive on price in Europe and Asia but has limited US retail presence.

Deliverables

1. Build a demand model to estimate how many Meta Quest headsets should be produced for Q4.
2. Show a base case, upside case, and downside case using explicit assumptions.
3. Explain how you would account for market growth, Meta share changes, channel inventory, and service-level buffers.
4. Recommend a final production quantity and explain the trade-offs between stockout risk and excess inventory risk.
5. Identify what additional data you would request before final sign-off.

Constraints

• Production commitment must be made before final holiday promotional calendars are locked.
• Meta wants to avoid ending Q4 with more than 6 weeks of forward inventory.
• Working capital is constrained; leadership prefers not to carry more than $150M of excess finished goods into Q1.
• Recommendation must be robust enough to support Finance, Supply Chain, and Reality Labs commercial planning.