Statistical Forecasting with Minitab

Course Overview

Forecasting of raw material demand data, raw material price data and other sequential data is a vital business skill. With good forecasts, companies effectively manage material levels and predict their impact on cash flow. With these goals in mind, this course provides a basic understanding of forecasting methods with a clear focus on immediate application of the methods learned.

Heavy emphasis is placed on data visualization and harnessing the power of Minitab to improve materials management.

The course content is suitable to healthcare, plastics, food processing, machining, aerospace, automotive or any other industry where raw materials are purchased for further processing at a production facility. Also useful for any business interested in demand forecasting for staffing, managing inventory levels (e.g., personal protective equipment for healthcare workers).

Pre-requisites

The course requires a good understanding of Minitab fundamentals including navigation, data integrity, annotations, data visualizations and similar. For those without Minitab experience, please see the Pyzdek Institute’s Introduction to Minitab short course.

Attendees must have a PC, a Minitab license (version 19 or 20) and a 2-way headset. Two monitors are highly recommended.

Designed for:

This course is designed for Supply Chain, Purchasing, Financial, Production Planning, Quality and other professionals that need to create forecasts from past data plus additional input such as upcoming marketing campaigns.

Benefits to attendees

This course provides step-by-step guidance for the choice and use of the methods available in Minitab. Specific topics that will benefit attendees include:

• Improved return on investment in Minitab licenses
• Importing data into Minitab
• Assuring data integrity
• Identification of the best Minitab forecasting method
• Interpreting results
• Visualizing results for better collaboration
• Evaluate forecast accuracy

Course structure

Specific topics covered

• Review of fundamental statistics that are relevant to forecasting
• Data visualizations and interpretation
• How to choose the correct method
• Time series plot
• Trend analysis
• Decomposition
• Single exponential smoothing
• Double exponential smoothing
• Winters’ Method
• Autocorrelation
• Cross-correlation
• ARIMA
• Accuracy Measures (MAPE, MAD, MSD)

Schedule options

• Four 3-hour segments
• Three 4-hour segments (recommended)
• Two 6-hour segments