How To Use HR Data Visualization To Tell an Impactful Story

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How To Use HR Data Visualization To Tell an Impactful Story

Data visualization for Human Resources offers an impactful way to present and communicate information to stakeholders. In today’s world, businesses can no longer succeed without the use of data. 

HR, in particular, uses analytics to help to guide talent, leadership, and hiring decisions for companies. A well-designed visualization of your key HR data brings life and meaning to insights that exceed what can be achieved with bulleted or numbered points on a presentation.  

What is HR data visualization? 
Why is data visualization essential for HR?
The history of data visualization
How to use HR data visualization
What makes for good data visualization
Types of data visualization techniques
HR dashboards 

What is HR data visualization? 

Our world is increasingly data-driven, and in order to remain competitive in the business landscape, it is more important than ever to be able to view and understand data. HR data visualization is especially important when making HR decisions because we can no longer be guided by instinct or intuition. 

Data visualization can be defined as the representation of information and data presented in a graphical form. In order to view data in a manner that is easy to understand, the use of charts, maps, and graphs are utilized to understand patterns, trends, and outliers in your data. 

Not only are you able to make data-informed decisions through the insights gathered, but it also provides a way to present data to non-technical people who need clarification. 

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Why is data visualization essential for HR?

HR specialists sometimes lack data visualization skills (skills gap). However, data visualization offers HR professionals a considerable opportunity to provide meaningful insights into the organization’s talent. HR can strengthen this valuable skill through the AIHR data visualization course.  

Human Resources also works with enormous amounts of data. Daily, you collect data on payroll and benefits information, employee engagement scores, feedback, and performance reviews. Additionally, you are collecting core employee data such as employee name, address, phone number, assigned department, vacation days, sick leave, special skills, and qualifications, among many other data points. And the larger the organization, the more data there is to collect. 

Visualizing is the key to conveying your message when there is a large amount of data. In fact, the brain processes visuals 60,000 times faster than text. By using data visualization, you can increase HR’s impact on the business. 

There are additional reasons why HR data visualization is important:

  • Data visualization for HR provides more significant insights and analysis into the recruitment and talent management processes. HR can better understand elements like productivity, compensation, and company culture to improve employee engagement.
  • Data visualization taps into an individual’s visual processing skills to visually explain convoluted and large volumes of data. This leads to more clarity around how to interpret the data you are seeing. 
  • Data enables HR to move away from qualitative or ‘gut’ decision-making to more data-driven insights. As new data is explored, more data owners within the business are included in the analysis of the data. Data visualization enables HR and the various business divisions to further explore and identify meaning in the data.
  • Data visualization improves transparency across datasets.
  • You can easily share the insights you find from data with decision-makers who may not have the time or understanding of how to read unrefined data sets. 

The history of data visualization

Data visualization has been spoken about more frequently these days. However, visualizing data has been used as a tool to communicate insights and information for 100s of years, albeit without the use of modern technology. 

Before the 17th century, data visualization existed predominantly as maps in the shape of markers such as cities, roads, land markers, and natural resources. However, better visualization was needed as the demand for more accurate mapping, and physical measurement rose. William Playfair and Charles Joseph Minard are two historical figures that stand out in this period due to their contribution to data visualization.

William Playfair, a British engineer and political economist, is widely credited as the founder of some of the most famous graphs we use today, such as pie, line, and bar charts in the late 1700s early 1800s. He first used visual charts to explain the English economy in The Commercial and Political Atlas, which he published in 1786. 

Visualized by Charles Minard, this chart shows Napoleon’s disastrous march to Moscow.

Another important figure in the history of data visualization is French civil engineer Charles Joseph Minard, who is credited with creating flow maps. His most famous work was the visualization of what had occurred in Napoleon’s Russian campaign in 1812.

There were others that influenced the creation of more accurate data visualization during this time, which led us to where we are today. 

How to use HR data visualization  

There are many ways HR can use data visualization; let’s explore a few:

  • Using data visualization with recruiting: Visualization is easy to interpret and allows your team to make data-informed decisions. For example, you can find which job board brings you the most qualified candidates or the cost-per-hire. Many Applicant Tracking Systems (ATS) already come with a reporting function, but not all reporting tools have the same functionality, and many ATSs provide the only basics. Look at our article on Recruitment Analytics to learn more about which metrics to track.
  • Using data visualization for turnover: To understand employee turnover, track the number of employees leaving a company during a specific period, commonly one year. This number includes voluntary resignations and dismissals. By implementing data visualization, you can see trends to predict when you’ll need to hire to backfill roles or if there are any outliers, such as a considerable amount of staff leaving a specific department.
  • Using data visualization with retention: Similarly to turnover, you can visualize retention data to see why employees want to stay in your organization and what motivates them across different countries, departments, or even teams. Use this data to retain talent in your organization.  
  • Using data visualization with productivity: There are many ways you can utilize data visualization to increase productivity. For example, have your team use flowcharts to visualize processes or mind maps when brainstorming. By implementing these graphical images into your process, your team can save time and focus on the real challenges at hand. 
  • Using data visualization to visualize future trends: The best way to understand future trends is to analyze past data you’ve collected. Predictive analytics is the use of data analytics to make future predictions. If you track the relevant data points, you’ll be able to analyze areas such as hiring success or even revenue through employee engagement, which are closely linked. 
  • Using data visualization in workforce planning: Workforce planning is the process of analyzing your organization’s current employees and expected business growth or changes in order to determine the steps your team must take to meet current and future hiring needs. It also looks at the most efficient and cost-effective methods to recruit and retain talent.

Additionally, HR can provide meaningful insights into the business too and display connections or relationships between variables such as work satisfaction, employee commitment, engagement, motivation, and performance. Employees who are satisfied with their work are more likely to have higher performance than those who are not happy and vice versa. Using these metrics can help you understand retention efforts and your bottom line.

Telling a narrative/ storytelling is an essential element of data visualization. Studies show that humans are wired to remember stories much more than data, facts, or even figures. When using storytelling, data comes alive. You have a better chance to explain why your data is essential, especially to leaders and decision-makers in your organization. 

There are many hr data visualization tools, both free and paid, that you can use. A great tool to start using if you have a few data points to track is excel or google sheets. However, excel and google sheets can be somewhat manual. So, if you are dealing with many data points, it is best to invest in data visualization tools such as Tableau or Power BI.

What makes for good data visualization

A good data visualization tells a story while removing unimportant information from data and highlighting helpful details. However, it’s more complex than adding all data points into a graph and calling it good. 

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Let’s discuss the steps you need to take to get relevant information to make data-informed decisions: 

  1. Defining the purpose: In order to get the most relevant information out of your data, understand what question you should ask. By defining a goal for your data visualization, you’ll remove all the noise in your data. For example, the goal of your visualization could be to showcase the financial impact of employee turnover on your bottom line
  2. Understanding the audience: To whom will you present your data? C-Level Executives? Or your team? Understanding your audience will allow you to create a more tailored visualization and will elicit quicker time to insight and action. For instance, when demonstrating the impact of employee turnover on the business to the C-suite, you could visualize the cost increase if the turnover continues to rise.
  3. Identifying what data makes for the best kind of visualization:
    1. High-volume data: Not only is high-volume data more suitable for data visualization than low-volume data, but the more data you have on the defined purpose, the more accurate it will be.
    2. Multivariate data: You can define Multivariate data as the analysis that involves more than two dependent variables that result in a single outcome. A real-world example of this is determining the value of a house. In order to know the selling price, the real estate agent will consider variables such as the size of the home, the number of bedrooms and bathrooms, and the location. In HR, you can use multivariate data in many ways. In HR, as an example, you could predict an employee’s performance ratings and pay. Knowing what impacts your outcome is essential as it is not always the same in each company.
  4. Content: Deploy different methods depending on what you want to visualize. For example, if you want to compare values, you can use a Pie Chart or a Mekko Chart. On the other hand, a Line graph or Double Axes Line Chart is better to use for analyzing trends. 
  5. Color: Choosing the right colors to represent and differentiate information is critical. A recent study by Salesforce found that color impacts how quickly and accurately users make decisions. For example, muted palettes made the charts more challenging to analyze.  
  6. Dynamics: Dynamic data visualization brings movement, or animation, to show aspects of your data that would be hard to illustrate in a static graph. This kind of visualization is beneficial when representing data such as workforce growth over time. 

Types of data visualization techniques

There are many different ways to visualize your data. Here we’ll explain some of the common types of data visualization techniques: 

  • Charts such as line and bar charts are common techniques to visualize your data. Charts are used to display trends or progress over time. You can also use them to compare many different groups related to each other. For example, the employee turnover rate in different locations. 
  • Scatter plots are helpful in situations where you have so much data that it is hard to see a pattern quickly. They are most valuable when you want to show relationships between two large data sets, such as employee number and manufacturing output. 
  • Pie charts represent numbers in percentages, and the total sum of all parts needs to equal 100%. You can use this system to easily visualize the number of applications you receive for a role and which job boards they come from. 
  • Heat maps show the relationship between two items and provide rating information, such as high to low, with color indication. They are beneficial in spotting patterns and analyzing trends quickly. 
  • Matrix diagrams help HR managers visualize and evaluate complex data relationships to make more informed decisions. You can use these diagrams to identify the source of problems, match requirements with specifications or allocate resources based on need.

Tips when visualizing your data

  1. Decide which chart or graph is the best layout for your data visualization based on the defined purpose and your audience.
  2. Make sure you keep your data organized and easy to read. This will help your user process the data quicker, especially when you have big data sets.
  3. Use the right colors to tell stories quicker by highlighting important information. 
  4. Implement shapes and designs into your visualization to get your point across. 
  5. Add limited text when you need more than just visuals to get your point across. 
  6. Make sure not to misrepresent data intentionally, such as using inconsistent scales on size comparisons or using inappropriate colors.  

HR dashboards 

HR managers need to quickly review and analyze all critical key performance indicators (KPIs) data in one place. This is where HR dashboards come in. An HR dashboard is a tool that organizes HR-related data- e.g., information, reports, and KPIs, into easy-to-understand visualizations. It allows HR experts to track and analyze metrics related to the organization. It also helps with reporting, decision-making, and collecting valuable insights. 

Examples of HR data visualization 

Let’s dive into some real-world examples of how you can visualize HR data:

1. Time-to-start

Your organization needs to hire 150 salespeople in multiple cities to support the holiday season rush. You have data from the previous years, which you can use to calculate the time-to-start: the number of days that a vacancy is open to the date a new hire starts. 

Analyzing this data lets you know how early you should move your recruitment resources to focus on hiring for these roles. For example, if you find it takes 35 days in one location but 52 days in another, it’s best to focus on the longer time-to-start locations first. There are many ways you can visualize this data; however, a bar graph is likely the clearest. 

2. Employee turnover

Your HR department wants to track employee turnover from the last 12 months. While you know the overall number of employee turnover is 15 percent, there will be more effective ways to communicate your point than giving the percentage to your leadership team. It also doesn’t tell a larger story. 

Instead, you can use data visualization to break down employee turnover into tenure, location, department, teams, or even gender. With all of these data points, you may need more than one visualization to get your point across. For example, showing employee turnover by gender might be represented best by a pie chart, while departments a bar graph. 

An Employee Cycle HR Analytics Turnover Dashboard

3. Diversity

Diversity is a fantastic metric to track by visualization. Suppose you are interested to know the age distribution of your workforce or gender percentage by department. In that case, a stacked column chart may be a great way to visualize the data. 

If you invest in an HR dashboard, you may already have these capabilities at the push of a button. Otherwise, Excel has a graph-creating tool where you can manually enter the data you would like to see. 

To sum up

HR teams must be able to visualize data in an easy-to-understand and effective way in today’s data-driven world. Your team should incorporate data visualization to help guide talent, leadership, and hiring decisions for your organization’s overall success. You can do this by defining the purpose of your graphics, understanding your audience, and identifying what data makes for the best visualizations. 

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