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In this time in our history, the struggle is not a lack of data but the opposite. We find ourselves with massive volumes of data at hand and the challenge of making sense of all of it. We sat down with ‘data whisperer’ Christina Stathopoulos to learn more about data visualization and storytelling, particularly for the field of human resources and human capital management.
What is data visualization?
Data visualization is a powerful tool to help us make sense of large amounts of data. It's a way to take complex data sets and turn them into visuals that are easy to understand and interpret. This can range from simple charts and graphs to complex interactive dashboards.
Data visualization is an important skill for everyone these days, and it's becoming increasingly important in many fields. For example, it can be used in business to help make better decisions, in healthcare to track the effectiveness of treatments, and in education to track student performance. We are seeing an increase in people analyst roles in Human Resources and People Operations, a sign that people data and analytics are increasingly important to organizations.
“Large amounts of data can be easily digestible when it is presented visually in a graph or a picture instead of a table of numbers.” - Analytics Specialist Christina Stathopoulos, MSc
Why is data visualization important?
Whether you're a data scientist, a marketer, a student, or a HR professional, data visualization can be a powerful tool. With the right data visualization techniques, you can unlock the full potential of your data and make better decisions.
Data Visualization Statistics
- 90% of information transmitted to our brains is visual
- People remember 80% of what they see but only 20% of what they hear
- We absorb imagery 60,000 faster than words
Presenting data visually, through images, not only allows us to understand data quicker but also helps us remember key points.
“We cannot assume this is a natural ability. But with proper training, really anyone and everyone in a team can be empowered to get most out of data.”
What are the 3 main goals of data visualization?
1. Communicate information clearly and effectively.
Data visualization is a way to present data in a way that is easy for people to understand and interpret. By using visual elements like charts, graphs, and maps, data visualization makes it possible to quickly convey complex information and highlight important trends or patterns.
2. Discover insights and patterns.
Data visualization is a powerful tool for uncovering insights and patterns in data that might not be immediately obvious. By using different visualization techniques and exploring the data from different angles, it is possible to gain new perspectives and uncover hidden trends and relationships.
3. Facilitate decision making.
Data visualization is often used to support decision making by making it easy to compare different options and evaluate the potential outcomes. By presenting data in a clear and concise way, data visualization can help people make more informed decisions based on the available information.
Examples of good Data Visualization
Good data visualization is found at the intersection of three different domains or skill blocks.
Data
You need good quality data to begin with. But once you have it, you want it to be insightful and purposeful, so that you can influence your stakeholders and your audience. In order to do that, you need to transform data into clear messages.
Function
How can we give purpose to the data? We need to find the hidden core message. What point are you trying to get across? What emotion do you want to evoke in your audience? Function involves finding the right angle to present the data.
Design
How can you turn the above into an impactful visualization?
“You want to keep all three factors balanced when you are building your data visualizations: You want to stay true to your data. You want to give it a valid function or a clear message, and you want to comply with good design principles.”
Watch Christina discuss how to separate the wheat from the chaff to find relevant data here.
Data Visualization, Data Science, and People Analytics
We are starting to see how data is becoming more and more relevant across all departments within organizations. Companies are hiring data analysts within their HR department or creating people analytics departments, indicating that data is becoming the lifeblood of human capital management. With high volumes of data at hand, HR needs to mine and shape the insights. Equally important is presenting the key findings in a more intuitive, meaningful, and convincing manner to leaders in the organization.
Find relevant data for clear data visualization.
First, ask yourself what data sources can be used in order to make data-informed HR decisions. Christina classifies the data into two categories: external and internal. External data comes from the financial and economic landscape your company operates in, and it is data that comes from different relevant factors as shown. Internal data, on the other hand, has to do with people data that HR departments should have access to.
Christina understands the responsibility that comes with the decision to choose which data is to be used, and which should be discarded, which is why she always recommends that you keep your audience in mind, and remember that it is them and the objective you want to achieve that should guide your decision.
Focus on your objective and message.
It is important to focus on your objectives and a clear message in data visualization because this helps to ensure that the visualization is effective at communicating the information you want to convey. By having a clear understanding of your goals and what you want to communicate, you can design a visualization that effectively presents the data in a way that is easy for people to understand and interpret.
This can help to ensure that your visualization is successful at achieving its intended purpose, whether that is to highlight a particular trend or pattern, support decision making, or simply to provide an overview of the data. A clear message and focused objectives can also help to keep the visualization simple and avoid including unnecessary or distracting elements that might confuse or mislead the audience.
Partner with data scientists and analysts.
Once you’ve clarified the objective and have the relevant data to support your key message, it’s always good to partner with and get feedback from others. If there are data analysts in your company or a data science team, they can help bring your data to life through proper data visualization.
Christina also recommends training and upskilling members of departments that work with data, like HR, to understand how to use and present data properly and with confidence. “We cannot assume this is a natural ability, but with proper training, really anyone and everyone in a team can be empowered to get most out of data”, says Christina.
5 ways data visualization helps HR
Do you want to motivate team leaders? Inform the decisions of C-levels? Address concerns of employees? Data visualization can help! Make sure to find the right data that meets the objective and the message you want to get across to your audience, and be clear on how you present the data and insights.
1. Make better people decisions.
Faster and more objective decisions such as headcount planning, data-informed recruitment of new team members.
2. Improve collaboration with other departments.
To create more efficient HR resources, Christina recommends implementing HR training and development programs for all employees. "The goal is to better understand your employees' needs so that you can provide them with the appropriate training and resources," she says. By providing employees with the skills and knowledge they need to succeed, these programs can help to improve overall HR efficiency and support the overall success of the organization.
3. Better understand your employees.
You can use data to spot risks as well as opportunities within your workforce.
4. Predict workforce needs.
By gaining a deep understanding of your employees through unbiased (preferably anonymous) data, you will be better equipped to respond to your employees' needs and anticipate potential challenges, such as employee turnover. This agility and preparedness to adapt to daily workforce insights can help to improve HR efficiency and support the success of the organization.
5. Win leadership buy-in.
Data visualization can be a powerful tool for influencing and convincing c-level executives because it provides a clear and concise way to present complex information in a way that is easy for people to understand and interpret. It can make it easier to convince c-level executives of the value and importance of your recommendations, and help them to see the potential benefits and opportunities that the data presents. Additionally, because data visualization is objective and based on facts, it can provide a strong foundation for your arguments and can be difficult for leaders to refute.
Keep this in mind for data analysis and visualization
In order to fully leverage the benefits of data visualization, we must also consider its potential risks and limitations. Christina notes that a lack of data literacy within teams can lead to incorrect interpretation of the data and false assumptions. Another risk is bias, as the designer or presenter may unintentionally show one-sided information leading to incomplete or misleading conclusions. Therefore, it is important to ensure that teams have the necessary data literacy skills and to carefully consider potential sources of bias when creating data-based visuals. This will help to avoid presenting incorrect or incomplete information to the audience.
Bias can also even affect the sources of our data. Learn about the limitations of employee surveys here.
Always follow the Cooperative Principle.
Christina concluded with a word of advice: Follow the cooperative principle.
The cooperative principle is a concept in linguistics and communication theory that describes the way people communicate and collaborate with one another. The principle is based on the idea that people generally try to be cooperative and helpful when interacting with others, and that they assume that others are also trying to be cooperative. This means that people will typically provide just enough information to be understood, and will expect others to do the same in return. The cooperative principle is often broken down into four sub-principles: the principle of quantity, the principle of quality, the principle of relevance, and the principle of manner.
“The way I think of it: Be brief, be true, be relevant, and be clear."
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