Consumer product manufacturers and distributors are always looking to optimize operations which lower production costs and maximize margins. Whether shipping finished product more efficiently, to decreasing waste on production lines, to managing inventories, or dynamic account manager route forecasting, there are dollars to be saved.
Predictive analytics allow CPG firms to accurately understand, anticipate and make data-driven decisions to positively impact the behavior of mechanical assets, logistics, markets and employees.
Summary Our white paper explores the processes and opportunities presented by NLP for social media in extracting valuable data to drive improved operational and strategic decisions for R&D efforts. Natural language processing (NLP) is one of the most promising social media data processing avenues. It is a scientific challenge to Read more…
Both descriptive analytics and machine learning models can benefit greatly from using geographic data analysis to solve segmentation use cases.
Deep learning, specifically computer vision and natural language processing, can be designed to identify defects during the product packaging process. These deep learning models can verify that a label on a package is present, correct, straight, and readable.
If a decision maker is only relying on their ‘gut’, they are not only behind the times, but at high risk of losing competitive advantage, customers and market share.
Working in conjunction with subject matter experts, data scientists can swiftly apply statistical tools and uncover emerging trends. This is extremely valuable for companies trying to operate in a disruption. Not only will executives have an accurate representation of their present situation, but new products & services can be devised from these insights.
Global external shocks are going to continue to happen, that is a fact of operating a business in today’s environment. As companies embrace data science in their decision-making processes, they are better positioned to deal with these disruptions, allowing them to manage a risk-optimized supply chain.
A leading CPG company wanted to diagnose cannibalization hypotheses using a data-analytics-driven approach.
Data Science, specifically machine learning forecasting techniques, enables decision makers across a spectrum of industries to set more effective sales targets and plan profitable customer routes that boost top and bottom line growth.
We designed and deployed an AI model to predict shipments at risk of late fees for one of the world’s largest CPG businesses.
Our AI consultants designed and deployed a custom tool to forecast store-level demand for a leading food & beverage manufacturer.