“Figures don’t lie, but liars do figure.”
“Lies, damned lies and statistics.”
Although the definitive source for the first quote is uncertain it has been attributed to several individuals including Carroll D. Wright and Mark Twain. Mark Twain popularized the second quote in the U.S. Anyone who has worked with data knows firsthand how you can come up with a different conclusion depending upon how the data is presented, understanding the first phrase very well. However, numbers and data have a very persuasive power and thus the relevance of the second quote.
Managing a feed or grain business takes lots of different skills: people and delegation management skills; customer relations skills; financial management skills; time management skills; and a myriad of others. One area that all managers deal with is utilizing data to make management decisions. It has been said that “what gets measured gets done,” and this is perhaps the key factor in why data analytics leads to a higher performance level by those organizations who religiously implement it. In this column, we will examine data from all angles and look at a number of the “hows and whys” of management using facts and figures.
What is data?
Data is (or “are” if you actually want to be grammatically correct — as the word data is the plural of datum) typically the results of measurements and can often be visualized using graphs or images. In fact, preparing a graph from many of the types of data we will discuss below is a great way to look at and visualize progress or to measure performance against a goal. There can be errors in data (we are all human) and anomalies in the tables/graphs can lead you to those errors, allowing you to get them corrected. In addition, presenting data in graphical form is a good way to share thoughts with your employees.
Data is necessary in making effective decisions and solving problems specifically because it has no “personal” agenda. Data is neutral — or as our quote at the beginning of this column suggests, “figures don’t lie.” However, remember the second phrase. As humans, we are the ones who hold differing opinions that often shape decisions which lead to differing results. Thus it is critical that all of the members of your feed and grain firm’s management team be able to read and correctly interpret the data you are using. This means familiarizing yourself with a few basic data terms and concepts such as mean (average), standard deviation, counts and benchmarking. This will ensure that your team members do not “find” something in the data that is not valid but simply supports their own personal views.
Let’s define these terms briefly (several are from the area of statistics — did you know that 2013 is the International Year of Statistics?):
Mean (average): for a sample or population, the mean is the arithmetic average of all values; calculated as — adding up (summing) all the numbers you have and then dividing by how many numbers you have. Formula:
Where: X = mean of all values in the data set x = sum of all data valuesN = number of data items in sample
Example: data set of observations = 56, 62, 53, 55, 59, 57
n = 6; X = (56+62+53+55+59+57)/6 = 342/6 = 57
Standard deviation: shows how much variation or dispersion exists from the mean (how spread out the numbers are). A low standard deviation indicates that your data points tend to be very close to the mean; high standard deviation indicates that your data points are spread out over a large range of values. Formula:
Where: = standard deviation
= sum of
X = each value in the data set
X = mean of all values in the data set
N = number of values in the data set
Example: Using the data from our average example above
This is interpreted as follows: a bit more than 68% of our data falls within one standard deviation above and below our mean. (In a statistical sense, 1 standard deviation either side of a mean encompasses 68% of your values.) Three quick graphs illustrate our point: