Maybe you’ve encountered this scenario before in the business world. You head to an important meeting to discuss financials. Someone pulls out a time-based chart in front of the group to communicate the latest data collected.
After a few seconds of review, someone stands up and heads to the graph. He points to two or three points of data in a row and proclaims, “Revenues are on their way up!” Everyone nods eagerly in agreement. After all, a trend has been identified, and everyone is eager to share the news.
But there’s something missing from this picture. Can you guess what it is?
The Risky Business of Unchecked Proclamations
If you guessed historical context, you’re right on the money. Finding trends in data takes more than a cursory glance and comparison of a few points on a chart. Sure, proclaiming “Expenses are down” or “Profits are ticking upwards” is a surefire way to generate some buzz. But unfortunately, it’s also a quick way to circumvent any risks associated with such predictions, and it fails to answer a key question: “Is this common cause variation or special cause variation?”
Time-based charts of all kinds, no matter their simplicity, should demonstrate as much historical data as possible and should also include control limits. These two elements make the difference between poor interpretations and good decision making based on a solid understanding of data and trends.
Build on your statistical knowledge, interpretation, and decision making through SS502 Introduction to Statistical Methods and SS503 Statistical Process Control. Fall course dates have just been announced: SS502 will run October 5-6, 2017 and SS503 will run October 18-19, 2017. Learn more at CEPE.
Why Trend Charts and Variance Matters
Decisions are made too often based on the results of small data samples. Unfortunately, the trends displayed by these samples may be inaccurate or present a skewed version of reality. For better, more effective decision making, factor in variables and performance with larger data samples.
Within the Six Sigma methodology, you’ll find the ideal tool for this type of decision making: the trend chart. The trend chart factors in the past, present, and future as they highlight data over time periods in great detail. Trend charts require you to focus on data for the long-haul as they depict the pattern of change indicated by data over time. That means making a buzz worthy proclamation based on a few data points just won’t cut it.
Why is it important to analyze data over time? Realize that variance is always a factor with processes. A limited capture of data can lead viewers astray and often fails to display the “big picture.” By looking at data over a longer period of time, you can understand how the process truly functions. Real analysis requires a complete picture and deep understanding of common cause and special cause variation.
Ready to master common cause variation, special cause variation, and everything in between? Check out NWCPE’s Six Sigma courses today.