Using Data and Technology Forecasting

Name: Using Data and Technology Forecasting
Author: Michael D. Ford

Technology hasn't managed time travel yet, but there's plenty it can tell us about how the future will look

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Course: On-Demand

(uplifting music) Analyzing data requires recognition of demand patterns, which can be stable or dynamic, have upward or downward trends, and have seasonality. Demand can also be cyclical. This is similar to seasonality, but refers to a cycle that doesn't fit within a calendar year. There are cycles that are longer than a year and cannot be predicted using trend models, or the seasonality index. For example, the housing market used to have a 10 to 15 year cycle between boom and bust. The electronics industry used to have a seven to 10 year cycle. These cycles were severely disrupted by the great recession of 2007. And we have yet to establish what the new norms are. All demand patterns will include randomness, and some may include trend, seasonality or cyclical variation. Some may include all four elements. Tables are good for representing the actual numbers and data sets, while graphs are best for helping us identify demand patterns. It is much easier to visualize trends, cycles, and variations by looking at a plot of the demand data. It is important to recognize that how we break down or aggregate data will affect what we see. For example, if you look at only a total sales of vehicles in North America, you may miss the fact that standard passenger car sales are down, while SUVs and crossovers are up. This also applies to the time periods we are analyzing. If we observe mayonnaise sales over the course of a year, we will find the peak in the summer months. This is when lots of mayonnaise is used in sandwiches and salads for picnics and cookouts. There is also a mini peak late in the year, corresponding to the Thanksgiving and winter holiday season. This is important information for the food processing facility manufacturing the mayonnaise. When you break down grocery sales data into months and weeks, you will find there is a peak at the start of the month for persons who are paid on a monthly basis, such as persons collecting a pension and some school district employees. There are also peaks on weekends for those who are paid weekly. This information is important to grocery wholesalers who supply retail outlets. Breaking sales down further in to days or even hours, we find that sales increase during the lunch hour or after work. This is important for retail stores in terms of staffing cashiers and stock clerks.

Advanced Provider : Michael D. Ford 4 Lessons · 8m in Arabic, German, English, Spanish, French, Portuguese, Chinese

Course Description

Forecasting is a method used by business leaders to anticipate the needs of their customers in order to ensure they can meet future demand. Forecasting incorporates many differrent methodologies depending on the type of organization, what you're trying to predict and how far ahead you're looking. This course offers a deep-dive into different types of forecasting and how each type can offer you a different glimpse into the future of your business. In addition, you’ll learn about the technology and software available to enhance and refine forecasting, as well as how to analyze collected data to gain meaningful insights.

What You'll Learn

Analyze collected data to identify demand patterns
Use a forecast to project demand
Choose the best forecasting approach based on your needs
Apply technology and software that aid business leaders in developing forecasts
Compare different types of forecasting and what each reveals about your business

Key Takeaways

Forecasting is a method business leaders use to anticipate customer needs and ensure they can meet future demand.
Forecasting incorporates many different methodologies depending on the type of organization, what you are trying to predict, and how far ahead you are looking.
Different types of forecasting each offer a different glimpse into the future of your business.
Technology and software are available to enhance and refine forecasting.
Analyzing collected data helps you gain meaningful insights and identify demand patterns.

Frequently Asked Questions

What will I learn in this course?

You'll learn how to analyze collected data to identify demand patterns, use a forecast to project demand, choose the best forecasting approach based on your needs, and discover technology that helps business leaders develop forecasts.

Who is this course for?

It is aimed at business leaders who use forecasting to anticipate the needs of their customers and ensure they can meet future demand.

What topics does the course cover?

The course covers analyzing data, choosing the best forecasting approach, using the implemented forecast, and technology and forecasting.

What skills does this course help build?

It builds skills in forecasting, corporate forecasting, economic forecasting, financial forecasting, forecasting management, and technology forecasting.

Does the course cover forecasting technology?

Yes. It covers the technology and software available to enhance and refine forecasting and how it aids business leaders in developing forecasts.