From cfce00cd6346385f55dd04365089b0842fcd202b Mon Sep 17 00:00:00 2001
From: Christian Vidal Wolf <christianvidalwolf@gmail.com>
Date: Wed, 28 Jan 2026 13:11:08 +0100
Subject: [PATCH] Fix seasonality bias: Default to flat weighting if history is
 sparse (<4 months)

---
 services/dataProcessor.ts | 12 +++++++++++-
 1 file changed, 11 insertions(+), 1 deletion(-)

diff --git a/services/dataProcessor.ts b/services/dataProcessor.ts
index cb501eb..54eadb5 100644
--- a/services/dataProcessor.ts
+++ b/services/dataProcessor.ts
@@ -1628,15 +1628,25 @@ export const calculateForecastViewData = (
     const getWeights = (records: SalesRecord[]) => {
         const weights = new Array(12).fill(0);
         let total = 0;
+        const seenMonths = new Set<string>();
+
         records.forEach(r => {
             const m = r.month.split('-')[0];
             const idx = MONTH_ORDER.indexOf(m);
             if (idx !== -1) {
                 weights[idx] += r.units;
                 total += r.units;
+                if (r.units > 0) seenMonths.add(m);
             }
         });
-        if (total === 0) return new Array(12).fill(1 / 12);
+
+        // Safety Fallback: If we have sparse data (e.g., only Jan loaded), 
+        // using it as 100% seasonality skews the forecast entirely to that month.
+        // We require at least 4 months of history to trust the curve; otherwise, we assume flat seasonality (1/12).
+        if (total === 0 || seenMonths.size < 4) {
+            return new Array(12).fill(1 / 12);
+        }
+
         return weights.map(w => w / total);
     };