Automating Forecasting for GoApptiv: Empowering Supply Chain with Precision and Saving 4 Man-Days Monthly

Background

GoApptiv, a trailblazer in India's healthcare distribution landscape, leverages its phygital business model and proprietary technology platforms to drive growth for over 700 brands. By bridging healthcare providers and markets, GoApptiv empowers stakeholders with agile market access and optimized operations. However, managing supply chain forecasts at an SKU (Stock Keeping Unit) and SD (Super Distributor) level posed significant challenges, requiring an innovative solution to streamline this complex process.

The Problem

GoApptiv’s supply chain faced significant hurdles in creating reliable, SD-specific forecasts:

Complex Baseline Forecasting: Generating SKU-wise forecasts across multiple SDs required integrating historical sales trends and diverse data sources.
Dynamic Sales Manager Input: Sales managers with varied responsibilities across regions and clients needed to validate forecasts, but inconsistent SD-client mappings added complexity.
Frequent Changes: New client additions and updates to SD assignments disrupted consistency in the forecasting process.
Management Review: A centralized monthly review of forecast accuracy and inventory planning required a more structured and scalable approach.

Solution Offered

Easemylife (EML) developed an automated, end-to-end forecasting system to address these challenges:

Baseline Forecast Automation:
- Sales data was extracted from ERP systems, processed monthly, and integrated into historical sales trends.
- SKU-level forecasts for the next 21 months were generated using this trend data.
SD-Level Customization:
- Forecasts were broken down to SD levels based on the SKU’s sales history over the last six months.
- Masters were created to manage active/inactive SKUs and SD-client mappings, ensuring accurate forecasting alignment.
Collaboration Templates:
- Excel templates, preloaded with SKU-SD level forecasts, were distributed to sales managers for field-level review and validation.
Centralized Review:
- Sales manager inputs were collated and reviewed centrally by top management for final sign-off.

Implementation Process

The implementation of the automated forecasting system followed a collaborative and iterative approach:

Interactive Template Development: Forecasting templates were co-created with feedback from sales and supply chain teams to ensure usability.
Master Data Management: Dedicated masters for SKU-SD mapping and SD-client responsibilities were created for flexibility and accuracy.
Automated Data Integration: Monthly sales trends were seamlessly updated, enabling system-generated forecasts with minimal manual intervention.
Field-Level Adoption: Sales managers were empowered with automated templates, reducing their workload while maintaining high accuracy.
Continuous Refinement: The forecasting process was fine-tuned based on initial feedback, ensuring its robustness and reliability.

Results and Benefits

The automated forecasting system delivered transformative outcomes for GoApptiv’s supply chain:

Efficiency Gains: Automation saved approximately 4 man-days each month, allowing teams to focus on strategic priorities.
Accurate and Reliable Forecasts: Sales managers relied on the system-generated baseline, significantly reducing their manual effort.
Enhanced Inventory Control: Regular reviews at the management level ensured inventory days remained optimized, supporting smoother operations.
Robust Supply Chain Planning: The automated forecast formed a solid foundation for SKU supply planning and stock distribution to SDs.

By automating and refining its forecasting process, GoApptiv not only achieved operational efficiency but also laid the groundwork for a more agile and scalable supply chain. EML’s solution empowered GoApptiv to better serve its stakeholders, aligning with its mission to revolutionize healthcare distribution.