Demand forecasting done RIGHT

Obtain 10% better demand forecasts over lead-time!

With product lifecycles shrinking and increasing competition, technology enterprises are relying on Supply Chain functions to become more intelligent, agile and transparent, while keeping the costs under control. The ability to forecast demand accurately and plan inventory holds the key to revenue growth and providing a superior customer experience.

BRIDGEi2i’s Demand and Inventory Watch Tower leverages ML frameworks to forecast demand and calibrate inventory. The solution complements your Demand Planning Systems with best-in-class algorithms to predict demand over lead-time.

Features & Benefits
Features
Benefits
A System Built for Better Forecasting

Makes cutting-edge methods and frameworks for demand prediction available to planners

Better Demand Forecast Accuracy

At least 10% higher accuracy of predicting demand over lead-time

Address Demand and Inventory simultaneously

Encourages Planners to take Buffers out of their Demand Signals and manage Inventory across the value chain more optimally

Lower Inventory

A commensurate and sustained reduction in inventory of 10-12% because of well-calibrated buffers and ROP

Perfect Solution for IBP

An interactive simulation environment allows Distribution Planning, Order Fulfillment teams, and Supply Planning teams to work on the same platform

Lead-time Attainment

3% higher DtFC and Service Levels because of nuanced appreciation for actual lead-times

How does it work?
Profiling & Segmentation

Dynamically segments your SKU-Location portfolio into a large number of micro-segments – each having homogeneous behavior in terms of service levels, volumes, and demand volatility

Causal Data

Consumes leading indicators of demand such as promotions, events and macro-economic factors to help machine intelligence learn causality

Baseline Performance Models

12 conventional statistical models develop an accuracy and bias baseline for more advanced models to beat

Machine Learning Engine

4 families of ML Models predict demand based on meaningful and interpretable causal effects. An Ensemble Model then weighs each ML Model on accuracy and builds the final forecast

Visualization

Planners can visualize forecast accuracy metrics and the value-add over baseline models along with a custom list of metrics and charts. Planners can also simulate various demand scenarios and study the effect on Inventory Levels and Buffers

The Demand & Inventory Watch Tower has demonstrated 10% higher forecast accuracy leading to 12% lower inventory in the supply chain

Why partner with BRIDGEi2i?

Our obsession with “value to customer” and “time to value” has shaped our engagement philosophy and we partner with our clients to make the journey from Information to Insight to Impact easier, faster, and sustainable. We leverage our proven problem-solving frameworks, extensive domain expertise, data science capabilities and proprietary AI accelerators to help companies accelerate their transformation journeys and build digital enterprises of the future.

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