Customer Stories / Healthcare / United States 

2024
Amazon Pharmacy logo

Amazon Pharmacy Increases Forecast Accuracy and Reduces Manual Efforts Using AWS Supply Chain

Amazon Pharmacy implemented AWS Supply Chain to improve demand planning processes and increase forecast and planning accuracy.

Saved approximately 13%

of weekly planning time through reduced manual efforts

Achieved 50% better forecasting

accuracy than the industry standard MAPE target, using AWS Supply Chain

Enabled seamless scalability

to handle increasing prescription volumes and business growth

Overview

Amazon Pharmacy is working to get medications to customers when and where they need them, including Same-Day Delivery in eight cities, with plans to expand to more than a dozen cities by end of year. To meet this objective, Amazon Pharmacy uses advanced logistics, including daily forecasts to accurately project prescription volumes and demand. This enables precise operations planning for resources, staffing, and labor allocation. Overestimating demand leads to unnecessary costs from excess staffing, while underestimating results in increased risk to meeting customer promise. Amazon Pharmacy implemented AWS Supply Chain to improve demand planning processes and increase forecast and planning accuracy. Building on Amazon Web Services (AWS) using AWS Supply Chain transformed the company's end-to-end demand planning process that increased forecast accuracy and reduced manual efforts that saved approximately 5 hours per week in planning time.

person working in pharmacy

Opportunity | AWS Supply Chain Leads the Digital Transformation

Amazon Pharmacy is licensed in all 50 states to fill and ship prescriptions directly to customers. To do this successfully, Amazon Pharmacy must forecast demand across the entire journey of a prescription—from order intake to fulfillment. Prior to AWS Supply Chain, different teams managed separate forecasting processes, which resulted in longer cycle times, higher resource needs, and limited data granularity. AWS Supply Chain Demand Planning provided the flexibility to generate forecasts at a granular daily level, a capability that enabled Amazon Pharmacy to improve planning agility and meet customer demands effectively.

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AWS Supply Chain has enabled us to easily integrate our forecasting processes and reduce time-consuming manual tasks, resulting in substantial time savings of approximately 5 hours per week."

Sachin Pahuja
Sr. Manager of S&OP and Labor Planning, Amazon Pharmacy

Solution | Increased Automation and Improved Accuracy

AWS Supply Chain Demand Planning automates numerous manual tasks such as data entry, calculations, and adjustments, eliminating non-value-added efforts. It leverages machine learning (ML) to analyze historical sales and current data, like open orders, to create accurate forecasts and dynamically adjusted models. This improves forecast accuracy, reduces stockout and limits excess inventory risks.

Amazon Pharmacy now utilizes daily forecasts, applying ML to detect correlations, trends, and seasonality factors previously too complex to determine manually. AWS Supply Chain automatically refreshes forecasts with the latest data and publishes them to downstream and upstream processes, mitigating handoff errors and accelerating critical data refresh cycles.

Amazon Pharmacy emphasizes two key forecasts: T-1 (one week out) and T-5 (longer-term). The T-1 forecast guides immediate staffing decisions to support customer demand, while the T-5 forecast facilitates capacity planning for labor adjustments. The advanced forecasting capabilities of AWS Supply Chain, powered by machine learning, have substantially improved Amazon Pharmacy's forecast accuracy as measured by the key metric of Mean Absolute Percent Error (MAPE). Using AWS Supply Chain, Amazon Pharmacy has seen a significant reduction in its MAPE, demonstrating the solution's effectiveness in generating precise forecasts.

MAPE is a widely used statistical measure to evaluate the accuracy of forecasting methods. It calculates the average absolute percent error between the forecasted values and the actual values, expressed as a percentage. MAPE provides a relative measure of how far the forecasts are from the actual values. A lower MAPE indicates better forecast accuracy. In demand planning and inventory management, MAPE is commonly used as a key performance indicator (KPI) to evaluate and compare the accuracy of different forecasting models or methods, set acceptable forecast error targets such as the industry standard MAPE target of 10 percent or less, and monitor forecast accuracy over time to identify areas for improvement. Amazon Pharmacy achieves a daily MAPE of 5 percent using AWS Supply Chain, indicating strong performance and that the forecasts have a high level of accuracy. This accuracy in projecting prescription unit demand increases inventory agility and enables precise operations planning, ensuring the right staffing levels at the right time to effectively serve customers at the lowest cost.

According to Sachin Pahuja, senior manager of S&OP and Labor Planning at Amazon Pharmacy, "AWS Supply Chain has enabled us to easily integrate our forecasting processes and reduce time-consuming manual tasks, resulting in substantial time savings of approximately 5 hours per week. We now have better identification of correlations, seasonality, and trends, which has significantly improved our forecasting accuracy."

By eliminating repetitive manual tasks, AWS Supply Chain delivers substantial time savings and enhances data reliability. The streamlined process decreases the need for corrective actions, allowing more time for value-added analytics. Amazon Pharmacy has reduced manual adjustments to the forecast models due to increased trust in data accuracy, further reducing effort and manual time.

Outcome | Driving Future Innovation with Automated Forecasting

With the foundation laid by AWS Supply Chain, Amazon Pharmacy is poised for continued innovation, scalability, and growth. The improved forecast accuracy and time savings from reduced manual efforts allow the planning team to shift focus toward higher-value activities. These include analyzing demand drivers, simulating scenarios, and exploring advanced forecasting techniques like ML.

The scalability enabled by AWS Supply Chain positions Amazon Pharmacy to seamlessly handle increasing prescription volumes as the business expands. The centralized, automated platform can readily accommodate new product lines, customer segments, and geographic regions without arduous implementation efforts.

Looking ahead, Amazon Pharmacy plans to further enhance its forecasting capabilities on AWS. Potential areas of focus include incorporating external data sources such as weather and events, as well as leveraging future generative AI and ML services to uncover deeper demand insights. Using AWS Supply Chain as a catalyst, Amazon Pharmacy is primed to continue optimizing inventory levels, streamlining operations, and delivering an exceptional customer experience through accurate and agile supply planning.

About Amazon Pharmacy

Amazon Pharmacy is a full-service pharmacy available on Amazon.com and the Amazon app. Customers can use Amazon Pharmacy to conveniently buy medications prescribed by their doctor, and have them delivered free to their door. Amazon Pharmacy offers upfront pricing, a wide selection, and 24/7 access to pharmacists.

AWS Services Used

AWS Supply Chain

AWS Supply Chain is a cloud-based application that unifies data and provides ML-powered actionable insights, built-in contextual collaboration, and demand planning.

Learn more »

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