The Challenge
The Client, a mid-sized pharmaceutical company, needed to improve accuracy in forecasting sales for a product line. Traditional forecasting methods produced inconsistent results, particularly when seasonality and market fluctuations came into play. Leadership required a solution that could:
- Accurately project demand 12-18 months in advance
- Support inventory and supply chain planning
- Adapt to new market variables
The Solution
Aspect was engaged to implement its Forecasting Engine, which compares traditional algorithms with machine learning models to determine the most accurate method for each dataset.
For this particular product, we ingested three years of historical sales data, consisting of:
- Date of Sale
- Sales Value
The model detected a steady upward trend and identified seasonal fluctuations that previous methods had missed.
Results
- Accuracy Increase: +23% improvement over previous forecasting approach
- Planning Confidence: Supply chain and sales teams could plan 18 months ahead with a high degree of certainty
- Operational Impact: Reduced risk of overstocking or product shortages, supporting both revenue growth and customer satisfaction
Features & Benefits
- Dual-Model Evaluation: Comparing outputs from traditional algorithms and ML models to select the most accurate fit
- Scalability: Capable of handling small or large datasets without loss of performance
- Expandability: Ready to incorporate additional variables like territory, product type, and channel for more granular predictions
Conclusion
By leveraging a hybrid forecasting approach, Aspect empowered the client to transition from reactive to proactive decision-making, a capability now being explored across other product lines.
“The clarity and accuracy we gained from Aspect’s forecasting solution have been game changing. We can now anticipate market shifts and align our strategies accordingly.” – Director of Business Intelligence, Pharma Client
Learn more about how predictive analytics can transform your forecasting process – Contact us.