Proprietary Machine Learning Algorithm Achieves Dramatic Accuracy Improvements at Enterprise Scale
San Diego, CA. January 24, 2018. (PRWEB) Halo announced today the worldwide release of HaloBoost©, Halo’s proprietary demand forecasting engine that leverages proven Machine Learning algorithms. HaloBoost© combines Machine Learning methods to improve forecast accuracy over time, a high-speed modeling workflow to improve analyst productivity and knowledge discovery, and a simple, scalable method to introduce external factors like pricing, promotion, social media, and weather predictors.
“Manufacturers, Distributors, and Retailers have been seeking tools that can provide simplification in the forecasting process to improve accuracy and throughput, and we’ve responded by introducing our most powerful modeling engine, HaloBoost©. Traditional approaches are limited in their ability to maximize forecast accuracy without significant analyst effort across broad and sparse data dimensions such as regions, points-of-sale, and SKU-level granular forecasts. Our proprietary modeling workflow effectively uses the computer to simulate a large team of forecast experts, working in real-time, to find the best result across a broad range of forecast scenarios,” said Bill Panak, Ph.D. Vice President of Data Sciences, Halo. “Our Data Science Advisory Services group was tasked with finding bold innovative approaches from other industries to create transformative solutions for the supply chain space. The results to date have far surpassed our customers’ expectations with regard to accuracy, transparency, and ease of implementation.”
Whether it’s forecasting demand, warehouse stock levels and depletions, spend by product and by cost center, or cash flows, busy managers want analytical tools that can be set up quickly and deliver results with a high degree of confidence. HaloBoost© raises the bar for forecasting technology. For the first time ever, analysts can watch HaloBoost© work through multiple layers of data and many generations of modeling results until the most practical model is selected. “The HaloBoost© engine features a powerful statistical and mathematical approach that delivers functionality that has been in use in world-class prediction engines used by the financial services and insurance industries,” said Dr. Panak. “Halo’s adaptation of Machine Learning for demand planning is perfect for improving the quality, performance, and utility of forecast results.”
Finding the Right Price Points
HaloBoost© was designed for deployment in the Halo v17.2 analytics platform for organizations seeking an automated, but flexible forecasting system. HaloBoost© is offered as a separately licensed module in either the SaaS or On-Premise versions of the Halo solution. After an initial setup, users can adjust HaloBoost© by including new predictors specific to their business needs. Common additional predictors added to HaloBoost© are price, discounts, promotions, new product introductions, shipping expenses, renewals, and fees.
HaloBoost© delivers a new way to approach statistical forecasting and simulation analysis allowing for more information to be incorporated, higher accuracy and deeper insight into the organization’s forecast and overall performance
Halo is an advanced analytics software and advisory services provider that offers customers an innovative blend of technology to drive better supply chain performance. Halo’s advanced information hub is a first-of-its-kind solution to help companies leverage all their corporate data to generate new insight for competitive advantage. Halo is headquartered in San Diego, California, and can be reached via the web (halobi.com), Twitter (@Halo_BI) or email at info(at)halobi(dot)com.