Demand Planning

What will customers buy, when will they buy it, and how confident am I in the forecast?

Historical Sales & Forecast

Seasonality Decomposition

1. RAW SALES
2. TREND
3. SEASONAL
4. RESIDUAL

Accuracy Metrics

MAPE
14.2%
Target: <15100%
Mean Absolute Percentage Error
BIAS
+2.1%
Target: ±3100%
Forecast Bias
MAE
342units
Target: <400100%
Mean Absolute Error
RMSE
512units
Target: <600100%
Root Mean Square Error

What-If Scenario Planner

Marketing Spend0%
-50%Baseline+100%
Price Change0%
-20%Baseline+20%
Competitor Promotion
Simulate competitor price drop
Adj. Forecast
50,000
0.0% vs baseline
Revenue Impact₹0.00L
Inventory Req0 units
Recommendation:Maintain current supply plan

Forecast vs Actual by Category

SKU-Level Forecast

SKUCategory30d ActualNext 30d ForecastGapConfidenceAction
SKU-10001
Product 1 Name
Apparel857
1,093
27.5%
Low
SKU-10002
Product 2 Name
Home1,214
1,686
38.9%
Medium
SKU-10003
Product 3 Name
Beauty1,571
2,279
45.1%
High
SKU-10004
Product 4 Name
Food1,928
2,872
49.0%
Low
SKU-10005
Product 5 Name
Automotive2,285
3,465
51.6%
Medium
SKU-10006
Product 6 Name
Electronics2,642
4,058
53.6%
High
SKU-10007
Product 7 Name
Apparel2,999
4,651
55.1%
Low
SKU-10008
Product 8 Name
Home3,356
744
77.8%
Medium

Forecast Adjustments Log

Total Adjustments
47
Net Change
+4,200
Most Common Reason
Promotional activity (34%)
TimestampUserSKUOriginalAdjustedDeltaReasonStatus
2026-06-08 15:00ManufacturerSKU-100001,3791,282-97New customer winApplied
2026-06-11 18:00DistributorSKU-100011,7581,863+105Competitor changeApplied
2026-06-14 21:00RetailerSKU-100022,1372,543+406SeasonalityApplied
2026-06-07 12:00ManufacturerSKU-100032,5162,315-201Promotional activityApplied
2026-06-10 15:00DistributorSKU-100042,8953,040+145New customer winApplied
2026-06-13 18:00RetailerSKU-100053,2743,863+589Competitor changeApplied
2026-06-06 21:00ManufacturerSKU-100063,6533,324-329SeasonalityApplied
2026-06-09 12:00DistributorSKU-100074,0324,193+161Promotional activityReverted