Replenishment

Replenishment forecasts demand and then simulates an inventory-replenishment policy period by period against that demand. It lets you see how different forecasting methods and ordering policies affect inventory levels and stockouts, so you can compare them side by side.

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Replenishment is a separate module from Network Optimization and Inventory Optimization. Open it from the Replenishment (refresh) icon in the left sidebar.

For each location × product and each period, the engine:

1. Forecasts demand — projects demand from historical actuals, and optionally extends it into future periods.
2. Simulates replenishment — walks period by period, tracking on-hand inventory, deciding when and how much to order (per the chosen policy), receiving orders after a lead time, fulfilling demand, and recording any shortfall.

The two headline outputs per period are the inventory level and the stockout rate (unmet demand ÷ demand).

Screens

The module has three tabs:

Tab	Purpose
Data	Manage scenarios, import input data, and browse the input tables.
Comparison	Compare stockout rates and inventory trends across scenarios.
Results	Review the Forecasts and Simulations tables.

Before You Start

Prepare an Excel workbook with your input data. The easiest way to start is from the sample file.

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Download the Replenishment sample workbook and edit it with your own data.

Input sheets

Sheet	Purpose
Periods	Time buckets. Validated against the scenario's weekly or monthly granularity on import.
Products	Product master.
Product Individuals	Per-product selling price and value. Required for the Comparison tab's Sales / COGS / Profit.
Locations	Location master. Forecasts are produced per location × product.
Facilities	Facilities (DCs / warehouses) that hold inventory.
Facility Constraints	Per facility × product × period; carries the period-initial inventory.
Inventory Policies	Per facility × product carrying-cost rate; drives the inventory-holding-cost part of Cost in the Comparison tab.
Customers	Customer master.
Flows	Product movement per period (from, to, product, quantity, period).

For column-level details of each sheet, see the Excel File Format reference.

1. Create a Scenario

On the Data tab, click the New scenario (+) icon, then set:

• Scenario name
• Period granularity — Weekly or Monthly (default Monthly). This is the interval between rows in the Periods sheet, and imports are validated against it.

Click Create scenario. You can later change the granularity from Edit scenario, add a description, and delete scenarios with the Delete scenarios icon. Each scenario holds its own data and results.

2. Import Your Data

With your scenario selected, click Upload data, choose your .xlsx file, and click Import. Once imported, the sheets appear under Tables in the left sidebar; click any table to review its rows.

If you get an error during upload

3. Configure and Run

Click Run to open the run dialog and configure five settings.

Forecast method

Method	Parameters
Naive (previous period actual)	None — uses the previous period's actual as the next forecast.
Moving average	windowSize (default 3) — average of the last N periods.
Simple exponential smoothing	smoothingFactor (default 0.3) — exponentially weighted recent actuals.

Replenishment policy

Policy	How it orders
Periodic order-up-to (RS)	Every reviewPeriod periods, order up to orderUpToLevel.
Order point order-up-to (sS)	When inventory position ≤ reorderPoint, order up to orderUpToLevel.
Reorder point fixed quantity (sQ)	When inventory position ≤ reorderPoint, order a fixed orderQuantity.
Fixed cycle fixed quantity (RQ)	Every reviewPeriod periods, order a fixed orderQuantity.

All policies also take initialInventory (starting on-hand) and leadTimePeriods (periods between ordering and receipt). Selecting a method or policy fills in its default parameters, which you can edit.

Forecast horizon

The number of periods beyond the last actual period to extend forecasting and simulation (0 = no future forecast). Future periods are labeled F+1, F+2, and so on.

Click Run to start. The button shows Running with a spinner, and a toast appears when the job finishes: Check results on success, or View errors on failure.

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Run settings are chosen at run time and remembered per scenario in your browser, so you can re-run the same data with a different forecast method or policy without editing the scenario.

If you get an error during optimization

4. Review Results

Open the Results tab. A summary strip shows the forecast method, policy, parameters, forecast horizon, and run timestamp for the latest result.

• Forecasts — location, product, period, forecastValue. The demand forecast per location/product/period, including future F+N periods.
• Simulations — location, product, period, inventoryLevel, orderCount, stockoutRate. The period-by-period simulation: ending on-hand inventory, whether an order was placed, and the stockout rate.
• Errors — shown only when a run fails.

5. Compare Scenarios

On the Comparison tab:

1. Select the scenarios to compare with the checkboxes.
2. Choose a Location and Product.
3. Click Compare.

The tab then shows:

• A comparison table with each scenario's total stockout rate.
• An Inventory Level Trend chart overlaying three lines per scenario for the selected location/product:
  • Inventory level (solid line)
  • Order quantity (dashed line)
  • Forecast demand (dotted line)

Each scenario has its own color. The chart splits each line at the last actual period — the future (forecast-horizon) segment is dimmed so you can see where forecasting begins. Click any entry in the legend to toggle that single line on or off.

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The trend chart's on-screen labels are currently in Japanese: 在庫レベル (Inventory level), 発注量 (Order quantity), 予測需要 (Forecast demand), and 将来予測 (future forecast).

Related Documentation

• Excel File Format — sheet and column specifications for the import file
• Inventory Optimization — compute optimal safety stock across the network
• Comparing Scenarios — the scenario comparison workflow