Demand Sensing & Forecasting

Be it a rainy day or a holiday, always know your demand.

High-Precision Accuracy

Nothing stands between you and better demand accuracy

The precision of AI-led demand sensing, establishes your exact demand to the last unit at any given time; embracing demand drivers such as promotions, holidays, weather, and waste.

Self-Learning Algorithms

The market evolves in the blink of an eye, so do our algorithms

Our self-learning AI engine constantly cycles through and picks changes in your demand using tailored algorithms for every SKU, channel, store, or warehouse within your distribution.

New Product Introduction

Got a new entrant planned? Kronoscope has you covered

By analyzing look-alikes and substitute products, our demand sensing engine - Kronoscope plans your new product launch factoring in cannibalization, pricing and placement.

Reduced Inventory

Sell more with 20% - 30% reduced stockouts

Don’t be thrown off by up or downticks. Our automated outlier detection corrects anomalies to give you optimal inventory recommendations.

Moving the needle towards a stronger top and bottom line with

up to

30%

lift in forecast accuracy

up to

75%

reduction in stockouts

between

15% - 25%

improvement in promotion linked predictions

Get unmatched demand-prediction accuracy with our demand sensing engine

Book a Demo

Get accurate demand forecasts with highly granular near-term market insights with our AI-led Demand Sensing. Leverage advanced AI & ML with the best demand planning software to process large volumes from various sources, both internal and external, to allow for data-driven inventory decisions for every node in the supply chain. Unlike traditional demand forecasting which leverages only historical data to predict future demand, demand sensing enables you to respond to changing customer demand, market changes and optimize your supply chain pipeline and production in real-time. We help you include the impact of factors that impact demand like price, promotions, seasonality, events & holidays etc with the assistance of our demand forecasting software.

We have a bottom up approach to demand sensing where the forecasts are made based on the data collected at most granular SKU/store/channel levels. Demand is predicted at such granularity and is then aggregated up for overall demand forecasts. In this approach, demand is predicted as close to the customer as possible and then rolled up to the top for more accurate demand prediction numbers. A bottom-up approach is a more pragmatic approach with lesser chances of human bias or error.

With automated demand forecasting solutions like Kronoscope, you can predict demand accurately by layering your historical sales data with various other factors that impact demand accuracy. The factors such as seasonality, pricing, promotions, weather, events, etc. have a significant impact on the daily demand trends. This helps you respond rapidly to any changes in your supply chain.

Demand Sensing also introduces automation in data collection and analysis through a demand forecasting tool that leaves very little room for manual error and biases and thus resulting in higher prediction accuracy. An accurate demand forecast helps in projecting optimum inventory levels and safety stocks leading to increased revenue, profitability, and working capital. Demand Sensing can help decipher customer sentiment and preferences at a granular level helping improve product mix and overall customer satisfaction levels.

Resources

Transforming Inventory Efficiency for workplace food solution company: 35% Reduction in Cost of Wastage with AI



Overcoming Supply Chain Challenges Across Diverse industries



Mastering Demand Forecasting: 5 Crucial Lessons for Inventory-Led Businesses



The FAQs

What is demand sensing?

Demand Sensing is the new-age method of utilizing AI/ML, IoT, and other advanced technologies to provide more accurate, real-time demand predictions.

It is the real-time analysis of customer demand signals collected from various sources like POS, social media, and market research to capture short-term fluctuations and trends.

Read more about our demand sensing here

How is demand sensing different from demand forecasting?

Demand Forecasting is a theoretical and statistical way of predicting consumer demand based on historical sales data. Typically, forecasts are done over 18-24 month cycles but may vary based on product category and industry.

Demand Sensing takes Demand forecasting to the next level by considering short-term trends, incorporating baseline data adjusted for external and internal factors to create an ever-evolving real-time demand forecast. Demand Sensing provides higher accuracy in demand predictions, day-by-day sensing by leveraging a high level of data granularity to analyze daily demand information as close as possible to the end customer and immediately detect changes in demand behavior.

What are the factors we consider in our demand sensing engine?

We follow a bottom-up approach to sense demand changes at the most granular (SKU) level. The Baseline predictions deal with SKU, Channel, Store level demand predictions which takes into account Historical sales trends, Seasonal effects, Cyclicity, Outlier Corrections.

In the next stage, the Factor adjusted demand predictions are made by including factors like Changes in pricing, Marketing/Promotional Campaigns, Holiday & Weather. The system analyzes the impact of these factors on demand and adjusts the baseline predictions accordingly.

Know more

What kind of models do you use for your demand sensing engine?

We use an assembly of machine learning models and statistical modeling - whichever helps us minimize the error in our prediction. There’s an ensemble of models - every combination gets a custom model.

We check historical sales data to determine how we want to segregate the data, and we can have separate models for each channel, our sub brands or categories and the model tuning depends on the data.

‍

How do you predict demand for newly launched products?

Predicting demand accurately and planning inventory for new products or stores can get tricky as there’s no historical data available. Our solution simplifies this by intelligently associating new products or new stores with existing ones that have similar attributes. Eventually, the system learns continuously and trains itself to predict demand and plan inventory for new products/stores independently.

Learn ways to achieve

We are excited to explore how we can add value to your demand sensing and inventory planning approach

Subscribe to our Newsletter