Supply Chain Demand Forecasting Accelerator by Impetus

Reimagining Supply Chain Planning with Conversational GenAI and Predictive Insights

Supply chains are undergoing rapid transformation. Global uncertainties, fluctuating demand patterns, and compressed planning cycles mean enterprises can no longer rely on static reports and manual forecasting. What’s needed is an agile, intelligent system that empowers teams to ask business questions in natural language and get data-driven answers instantly.

Impetus’ Supply Chain Demand Forecasting Accelerator, built on the Databricks Lakehouse Platform, brings this vision to life—combining conversational GenAI, advanced forecasting, and enterprise-scale data governance.

Breaking Down Barriers with Conversational Intelligence

Historically, demand forecasting and supply chain analytics have been the domain of expert analysts—armed with SQL queries, BI dashboards, and spreadsheet models. This creates bottlenecks:

Planners wait for reports
Analysts are overloaded
Business decisions lag behind market changes

Our accelerator removes these barriers by enabling conversational access to supply chain insights. Powered by Databricks Genie and Agent Bricks, users can ask questions like:

“What’s the forecasted demand for SKU A in Q2?”
“Which products risk stockouts next month?”
“How does supplier performance impact delivery times?”

Behind the scenes, natural-language inputs are translated into optimized queries on a unified Delta Lake dataset. High-performance serverless SQL engines deliver results quickly, while GenAI layers provide explainable narratives and context.

Advanced Forecasting Meets Enterprise-Grade Governance

Forecasting is more than predictions—it’s about trust in the data. That’s why the accelerator embeds:

Time-series forecasting models tuned for accuracy
Anomaly detection to flag data irregularities
Governed definitions of KPIs using Unity Catalog
Versioning and lineage for audit-ready insights

Users not only get forecasts but also scenario modeling—for example, understanding the impact of promotional events on inventory or evaluating supplier capacity changes under demand surges.

Delivering Tangible Business Outcomes

The business impact of bringing GenAI to supply chain planning is profound:

30–40% Reduction in Analyst Effort
Routine queries and reporting requests are handled via conversation, freeing analysts for strategic work.
80% Faster Insight Cycles
From question to answer in seconds, not hours or days.
5–10% Lower Inventory Costs
Improved foresight enables optimal stock levels and reduced carrying costs.
Better Operational Agility
Quick scenario analyses support dynamic decision-making in volatile markets.

Teams across planning, procurement, and operations gain a single source of truth, accelerating both tactical and strategic execution.

Why This Matters Now

The pandemic underscored the fragility of global supply chains. Businesses that could adapt with speed and foresight fared better. As complexity grows—driven by customer expectations, geopolitical shifts, and supply disruptions—it’s no longer enough to forecast once a quarter.

With Impetus’ accelerator on Databricks, organizations can embed continuous, conversational forecasting into everyday planning. Decisions become faster, data becomes more accessible, and teams become more confident.

Conclusion

Transformative supply chain planning requires more than analytics—it demands intelligence that is intuitive, explainable, and scalable. With GenAI-powered conversational forecasting, enterprises unlock a future where data empowers every decision, and supply chains become resilient, responsive, and predictive.