Challenges
The company had traditionally relied on conventional sales forecasting methods. However, frequent inaccuracies stemming from these approaches led to stock mismatches, missed sales opportunities, and increased inventory costs. In order to transition to a more data-driven approach, the Routine Automation team suggested an expertise solution.
During the Discovery Phase, Routine Automation engineers collaborated with our clients to enhance their forecasting processes. We audited and improved forecasting methods, conducted data cleansing, and optimized Salesforce organizational structures.
For Einstein Analytics, we integrated data from various sources, analyzed historical data, and utilized AI-driven algorithms for predictive forecasting. Our clients accessed interactive dashboards with real-time data and actionable recommendations, revolutionizing their forecasting approach.
Solutions
Results
🚀 Enhanced Forecast Accuracy
Our team’s AI-driven approach improved forecast accuracy by 30% compared to the client’s traditional methods.
🚀 Empowered Decision Making
Our interactive dashboards, customized for our client, provided a clear visual representation of sales data, enabling quicker and more informed decisions.
🚀 Optimized Inventory Levels
Accurate forecasting, driven by our expertise, reduced stockouts by 40% and overstocks by 35%.
🚀Efficient Salesforce Org
Post our team’s optimizations, our client’s Salesforce org operated more efficiently, resulting in quicker data retrievals and streamlined workflows.
