Supply chain

Accurately forecast customer demand

Enhance your demand planning effectiveness by combining advanced process modeling and predictive analytics capabilities

Analyze the multi-faceted and ever-changing needs of customers in depth, drive more accurate predictions, better govern the forecasting process, and bridge cross-functional disconnects with an Intelligent Planning approach.

Watch demo

Demand Planning Image 1 — A view of your demand plan with insights into the product mix.

Boost your demand planning capabilities

Take advantage of Board’s Intelligent Planning Platform which combines automated data forecasting, machine learning, clustering algorithms, and of a range of mathematical and statistical functions to act as a robust demand planning software solution.

Demand Planning Image 2 — Your demand review comparing the key scenarios

Create consensus-based plans in a collaborative process
Automatically aggregate data coming from all the processes within sales, supply chain, and finance, gaining a complete, single version of the truth
Understand forecast changes and their drivers with built-in analytics
Use predictive analytics functionality which features dedicated algorithms for smooth, discontinued, or intermittent time series for each combination of product/location across the product life cycle
Manage the lifecycle of new products and categories
Easily put in place projections for each combination of product/location, acknowledging new category introductions and product lifecycle evolution
Model the impact of promotions and external events
Enhance your forecasting consistency, taking into consideration the impact of promotions, seasonality, cannibalization, pricing tactics, and external factors (i.e. GDP growth, exchange rate, and interest rate)

Segment products/customers and assess the ability to forecast them through data mining and machine learning
Accomplish segmentation of products and customers, leveraging clustering and data mining to enhance your forecasting capabilities within a machine learning environment
Improve the accuracy of intermittent demand through automated forecasting methods
Take advantage of specific predictive analytics functionalities to improve forecasting accuracy with discontinued or intermittent time series
Integrate your R and Python algorithms
Save time by using Board’s advanced API to integrate and use your existing algorithms
Easily accomplish re-planning cycles
Exploit native collaborative workflow capabilities to guarantee continuous input fed from sales and supply activities, supporting the accomplishment of revised demand planning cycles
Achieve consistent predictions
Leverage a machine learning approach which selects, via competition among a family of models, the algorithm that is the best fit with historical data