Beating a Five-Year Seasonal Sales Decline With ₹2.2 Crore in Quarterly Revenue
Forecasting around the highest-revenue product–customer pairs let the company plan finished goods ahead of demand and act early on a recurring weak quarter.
ITChamps implemented an AI-enabled sales forecasting and finished-goods planning solution for a technical textile manufacturer, addressing both demand volatility and a recurring quarterly sales decline observed over roughly five years.
The Challenge
Demand swings and a recurring quarterly dip put revenue at risk
Fluctuating finished-goods demand created both excess inventory and shortages, and the company faced a recurring sales decline during a particular quarter each year, persisting for approximately five years.
- Finished goods sometimes went unsold because demand had been overestimated.
- At other times, sudden demand couldn't be fulfilled because goods were unavailable.
- A recurring quarterly sales decline had persisted for roughly five years.
- The company needed to identify customers and products with the highest revenue potential.
The Solution
Forecast, plan finished goods, and act early on the weak quarter
The solution mapped high-revenue products and customers, forecast demand at monthly and quarterly levels, planned finished goods accordingly, and monitored the recurring weak quarter to enable early commercial action.
Identified and mapped the products and customers contributing approximately 70% of revenue.
Analyzed historical demand for priority combinations and identified the recurring quarterly decline.
Incorporated historical sales, product, customer, and demand variables into the forecasting process.
Generated product-level forecasts at monthly and quarterly levels, supporting ~45–60 day lead times.
Converted forecasts into finished-goods requirements ahead of expected demand.
Monitored the historically weak quarter closely and used targeted commercial actions, including appropriate discounting, to protect revenue.
Results
Measured business impact
Share of revenue covered by the priority product–customer combinations.
Additional revenue generated during the targeted quarter.
Length of the historical seasonal decline the model helped counter.
Reduced risk of both overstocking and lost sales from stock-outs.
Highlights
- Gained better visibility into future finished-goods requirements.
- Proactively planned production and inventory ahead of demand.
- Monitored and responded to the historically weak quarter more effectively.
- Generated additional sales through targeted cross-sell and upsell.
Services and technology
Want to know more about this story?
More Stories
Related case studies
Turning Service Interactions Into a 7% Lift in AMC Conversion
ITChamps implemented an AI-enabled customer and service intelligence solution for a leading air-conditioner manufacturer, identifying why customers weren't opting for OEM AMCs and enabling targeted conversion engagement.
Read case studyRight-Sizing Spare-Parts Inventory Across 30 Service Locations
ITChamps built an AI-enabled location-wise spare-parts demand forecasting and inventory planning solution for a medical equipment manufacturer servicing approximately 30 locations with around 10,000 unique spare-part SKUs.
Read case studyTracking Compressor Health Before It Becomes a Failure
ITChamps developed an AI-enabled equipment-state degradation and predictive maintenance solution for a critical rotary compressor at a leading petrochemical company, predicting transitions from desirable to undesirable operating states.
Read case study