We have more data than ever before coming at us from many sources – both in our personal lives as well as business. Data is everywhere: from the production flow of a manufacturing floor to the sales results in a grocery store to the number of shares a page gets on Facebook. How do you sort it all out in a way that makes sense? Which data should you worry about and which should you ignore?
Whether you work in engineering, R&D, or a science lab, understanding the basics of experimental design can help you achieve more statistically optimal results from your experiments or improve your output quality.
“The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.” — Bill Gates
Producing and distributing raw materials and foodstuffs with a low profit margin is a challenging business. One major supplier has made significant gains through applying multivariate data analysis (MVDA) to their manufacturing processes and logistics.
