HR Mavericks

Eddy’s HR Mavericks Encyclopedia

Standard Deviation
During a meeting someone mentions the results of a standard deviation analysis and you don’t feel it applies to you. But actually, standard deviation is a great analysis you need to be familiar with. Read on to discover its impact in human resources.

What Is Standard Deviation?

Standard deviation is measuring the dispersion and variation within your given data set in relation to the mean. We will divide this definition into segments to further understand it and why it is important for HR to utilize.

Data Set

Data sets refer to the collection of data you are trying to analyze. Your organization may have large or small data sets depending on size and how much information you collect. Common HR data sets are number of new hires, number of terminations, compensation ranges for your teams, employee count, benefit use and many more. Data sets are normally discussed in two different ways. First, a population means every data value is being included in the calculation. This is the most useful for statistical analysis; however, sometimes it is not the most practical. The second term is sample size, which is a subselection of your overall population that represents its qualities.

Data Point Relations to the Mean

The standard deviation looks at how a certain data point in a data set relates to the mean or average of all data points you are analyzing. Is it really close or far away from the average of your data points?

Measuring Dispersion or Variation

Standard deviation’s purpose is to measure the difference between all your data points and means. Standard deviation is a commonly understood way to communicate this spread and how significant/insignificant differences are.

Why Is Standard Deviation Important for HR?

Standard deviation is important for HR because it can provide a data-backed perspective on what issues need attention. The goal is to give you another tool to filter the many projects you have.
  • Strategic partner. Including standard deviation and other basic statistical analysis strengthens your business recommendations and value as a strategic partner. Standard deviation is utilized in other aspects of your business and can be a common ground for communication.
  • Data analysis skills. We live in a world that is inundated with various data points. As we progress into the future, all positions will have some form of data analysis, so why not be an early adopter and work the bugs out now?

How to Calculate Standard Deviation

Let’s look at a few basic steps to help you calculate standard deviation.

Step 1: Understand the Why

Standard deviations are not the statistical analysis answer to every question. Take some time to map out what data points you are trying to get. Does it make sense to utilize standard deviation to get that answer? If it is, continue on to the next step.

Step 2: Identify Population or Sample Group

You want to understand if you are working with a population or sample size because the calculation changes based on this factor. It also helps you communicate the data results to ensure they are interpreted correctly.

Step 3: Do a Quality/Clean Check on Your Data

Before running a standard deviation and utilizing it in a business recommendation, it is important to glance through the data to make sure you aren’t missing any information or have faulty data. Nothing will sidetrack your proposal more than incorrect data.

Step 4: Calculate Standard Deviation

There are various ways to calculate the standard deviation. It is possible to do it by hand, but I wouldn’t recommend it. The most accessible way is to input your data into Excel and then create a function.

Actions HR Can Take with Standard Deviation

Now that we know how to calculate standard deviation, let’s look at how this analysis can help move HR initiatives forward.

Hiring, Retention, and Turnover

Three metrics you can easily calculate using data in your Human Resource Information System (HRIS), is time to fill, employee retention, and turnover. To review, time to fill refers to how many business days it takes to fill a position. Employee retention looks at how long your employees stay with you. Turnover refers to why individuals leave. Calculating the standard deviation lets you know where you fall in regards to past annual data, or, if available, other companies within your industry. This can be very useful for helping know where to focus HR efforts. For example, completing the standard deviation may show that you are one standard deviation below your previous year time to fill.

Benefits and Compensation

Standard deviation calculation can show you if your compensation is leading, matching or lagging in the market. If you currently hold a paying job, you have benefited from a standard deviation analysis. Organizations and market studies take the salaries that have been collected and find the average or mean of that job title and salary. Then they create a standard deviation to map out where the salaries are in relation to the average salary. Once the mapping is complete, they can identify if the salary/benefits are above market average, or above the standard deviation or below. For technicalities, there are different common markers explaining if a data point is 1, 2, or 3 standard deviations above the average.
Brent Watson

Brent Watson

Brent Watson enjoys problem solving, analyzing data, team building, and becoming an HR Guru. His work experience comes from the employee experience, recruiting, and training arenas. After attending a local HR conference, Brent knew that he had found his people and the problems he wanted to solve for in the business world.
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Frequently asked questions
Other Related Terms
Aging Survey Data
Bell Curve Performance Management
Cost of Labor
Cost per Hire
Employee Experience Metrics
Employee Lifecycle
Employment Cost Index (ECI)
Hiring Quota
Human Capital Metrics
Labor Cost
Midpoint Progression
Offer Acceptance Rate (OAR)
People Analytics
Recruitment KPIs
Revenue per Employee
Satisfaction Rate
Source of Hire
Time to Fill
Time to Productivity
Training Efficiency
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