The Impact of Predictive Analytics and CI on Patient Satisfaction
Explore how predictive analytics & continuous improvement tools can improve patient satisfaction with Minitab Statistical Software and Minitab Engage.
The Future is Now: Improving the Supply Chain with Predictive Analytics
See how predictive analytics can be used in the supply chain to optimize inventory, route planning, risk management, customer satisfaction and more.
Improve Delivery Times for a More Streamlined Supply Chain
Learn how Minitab's powerful problem-solving tools and predictive analytics solutions can help improve supply chain delivery times.
Win-Win: Expedite Insurance Claims to Improve Profitability and Customer Satisfaction
Discover how Minitab tools like CART, Workspace and Random Forests can help reduce the time it takes for insurance claims.
CART: Classification and Regression Trees for Sales Recruitment
Learn how to build a data-driven recruiting profile using CART in Minitab Statistical Software. Our solution helps you screen candidates efficiently.
Enhancing and Digitizing the Customer Experience in Financial Services
Explore two examples about automation and harnessing data analysis to enhance and digitize your customers' experience in the financial services sector.
Get a Sneak Peek at CART Tips & Tricks Before You Watch the Webinar!
I'll be sharing tricks for Classification and Regression Tree (CART®) models in Minitab Statistical Software in a webinar. Read on to get a sneak peek.
Understanding Customer Satisfaction to Keep It Soaring
Customer satisfaction is a key metric for any business. Learn how CART in Minitab can help airlines understand how and why their customers are satisfied.
Better, Faster and Easier Analytics + Visualizations, Now From Anywhere
The latest release of Minitab Statistical Software provides better, faster and easier data analysis and valuable visualizations, now from anywhere.
Predictive Analytics and Determining Patient Length of Stay at Time of Admission
Learn how historical data from a hospital can be used to accurately predict how long a patient will stay based on information you know when they arrive.