Furniture Inventory Planning in Canada: Reorder Points and Cash

Build a Forecast from Your Own Sales

Start with SKU-level units delivered by completed month. Exclude cancelled and returned orders from the sales history; they did not create realized demand. For each SKU, calculate the average of comparable completed months, then adjust the forecast only for facts you can document: open orders, planned promotions, discontinued products, new variants or a changed pack size.

Keep open orders separate from historical sales. They are committed pipeline, not proof of the SKU’s normal selling rate. A simple forecast can show both figures: 18 units from the historical run rate plus 6 units in valid open orders equals 24 units expected before any promotion adjustment. Record whether an order is paid, confirmed or merely quoted so the confidence is visible.

Tag promotional months rather than silently averaging them into ordinary demand. If a chair sold 10, 12 and 30 units during a promotion, the 30-unit month should be used for a promotion scenario, not treated automatically as the baseline. For a replacement SKU, use the predecessor’s history only as a labelled proxy and track the new product separately once it has sales. ORVX can forecast a coming period’s revenue from your own completed months by arithmetic and publish the method’s backtested error; use that result to judge forecast reliability, not to promise a future outcome.

Forecasting with your own sales

Use a consistent arithmetic rule for each SKU, then test how closely it would have predicted earlier completed months. A simple average smooths uneven sales: if a sofa sold 8, 10 and 12 units across three months, the next baseline is 10. A recent-month measure would use 12, while a trend calculation might produce a higher figure. The average is useful when sales are relatively stable; a recent-month measure is more responsive when the product’s sales pattern has clearly changed. None should be treated as a promise of demand.

Forecast units at SKU level, then aggregate them to collection and store totals. This shows whether a cash requirement comes from a few large-ticket products or broad demand across the range. Pair the unit forecast with your own price and product-cost data to estimate revenue, gross profit and margin; revenue alone can make a low-margin item look like a priority. ORVX forecasts a coming period from a store’s completed months by arithmetic and publishes the method’s backtested error. Use that error to set expectations, and act on the SKU or collection whose projected sales, profitability or remaining stock position warrants review, not on a forecast that claims an action will produce a particular result.

Lead time and safety stock

Lead time answers when to place an order. Measure it from the supplier’s confirmed order date to the date sellable stock is received, including production, transit, customs and receiving time. Use the longest credible recent lead time when delays would leave a high-value sofa or dining set unavailable. A quoted 10-week lead time is not the same as a consistent 10-week lead time; record actual elapsed time by supplier and SKU.

Safety stock answers how much extra inventory to hold while demand or replenishment timing varies. The reorder point is demand expected during lead time plus safety stock. For illustration only, if a chair sells 4 units per week, lead time is 8 weeks, and the buffer is 6 units: reorder at 4 × 8 + 6 = 38 units. Increase the buffer when supplier timing is unreliable or a stockout is costly; reduce it when the item is easy to replace or sales are intermittent. Do not use safety stock to disguise dead stock.

The right action differs: revise the lead-time input when suppliers or freight are slower than assumed; revise safety stock when demand variability or service priorities change. Use the inventory reorder calculator to test both inputs. ORVX can show inventory position, dead stock and remaining stock value, so compare the proposed reorder point with units already on hand and incoming stock before committing cash.

What stock costs to hold

Purchase cost is only the first cash requirement. For each furniture SKU, separate supplier cost, freight, duties, receiving, assembly and other landed costs from the cash tied up while the item remains unsold. A $1,000 landed-cost sofa still consumes $1,000 of working capital whether it sells tomorrow or sits for six months. Add storage, insurance, damage risk, financing cost and likely markdowns when deciding how expensive stock is to hold.

Keep GST/HST separate from product cost when planning cash, and apply the rate relevant to the transaction. The Canada Revenue Agency lists 5% GST in Alberta, British Columbia, Manitoba, Quebec, Saskatchewan and the territories; 13% HST in Ontario; 14% HST in Nova Scotia from April 1, 2025; and 15% HST in New Brunswick, Newfoundland and Labrador and Prince Edward Island (Source: Canada Revenue Agency).

• Landed cost: use it to price products and calculate gross margin.
• Stock value: use it to measure capital committed across current inventory.
• Carrying cost: use it to decide whether slow stock should be discounted, transferred or stopped.
• Cash requirement: use it before a purchase order, including supplier payment timing and taxes.

Seasonal peaks to plan for in Canada

Canadian furniture demand is rarely flat across the year. Review each store’s own pattern around January clearance, spring moving and home projects, summer cottage demand, back-to-school, and November-December promotions. Treat these as planning windows to test, not assumed peaks: a dining set, patio item, mattress, and sofa can each have a different seasonal shape.

Compare three measures before committing cash. Units identify how much stock may be needed; realized revenue shows the sales value of delivered orders; gross profit shows whether a peak is economically worth supporting. Act on units when availability is the constraint, on revenue when cash timing matters, and on gross profit when a promotion could increase sales while weakening economics.

Use inventory position and remaining stock value to separate a seasonal opportunity from leftover stock. If last year’s spring demand was concentrated in one collection, plan that collection separately rather than increasing every SKU. ORVX can show product- and collection-level profitability alongside inventory, dead stock, returns, and refund value, helping you compare the peak’s sales with the stock and returns it leaves behind.