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How can data visualization help identify the most common causes of employee turnover?

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Employee turnover is a costly and disruptive problem for many organizations. It can affect productivity, morale, customer satisfaction, and innovation. To reduce turnover and retain talent, managers need to understand why employees leave and what motivates them to stay. Data visualization can help managers identify the most common causes of employee turnover and make better decisions to address them. Here's how.

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1 What is data visualization?

Data visualization is the process of presenting data in a visual form, such as charts, graphs, maps, or dashboards. Data visualization can help managers communicate and understand complex information, identify patterns and trends, and discover insights and solutions. Data visualization can also help managers engage and persuade their audience, whether it's employees, customers, or stakeholders.

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Wabiner Douglas Ferrinho

LinkedIn Top Voice | Marketing | Consumer Behavior | E-commerce | Leadership | Entrepreneurship | Digital Business | Growth Hacking | Product Head | Innovation | Ux Design | ForbesBLK
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Data can provide a highly accurate foundation for some information that may be relevant to managers and, especially, the company's HR team. Utilize data, but also consider qualitative assessments to comprehend and formulate solutions for addressing the issue.

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Pablo Hadrava

Sales Manager | Business Developer Manager | Project Manager
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La visualización de datos es una herramienta fundamental dentro del entorno empresarial. Permite simplificar información compleja, destacar patrones y tendencias, así como contar historias persuasivas. Además, su capacidad de involucrar y persuadir a la audiencia la convierte en un activo valioso dentro de la comunicación con los empleados, clientes y stakeholders. La clave está en combinar datos con contexto y ética para lograr una comunicación efectiva y confiable.

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Michealia Skleres, M.S.

Specialized Program Team Manager for Noom
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To put it simply, data visualization can represent turnover data through charts or graphs, which can make patterns and trends more apparent. Analyzing visualized data can help identify common causes, such as high turnover departments or specific reasons like lack of career growth, enabling targeted interventions for retention to be created.

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2 How to collect and analyze data on employee turnover?

Before creating data visualizations, managers need to collect and analyze data on employee turnover. They can use various sources of data, such as exit interviews, surveys, performance reviews, or HR records. They can also use metrics, such as turnover rate, retention rate, turnover cost, or employee satisfaction. Managers should define the scope and purpose of their analysis, such as the time period, the department, the role, or the reason for leaving. They should also clean and organize their data, and use statistical methods to test hypotheses and find correlations.

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Daniel Lundin

Head of Operations at Ortelius, Transforming Data Complexity into Strategic Insights
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Any data project should always start with a hypothesis. Designing a hypothesis must therefore be the starting point. Always start by asking what to I need to know in order to fulfill the hypothesis, and then identify where (and if) this data exists. Use your organization to source the data needed in a pragmatic way and test your hypothesis early. Does it provide you with the insights you desire or not? If not, close down the hypothesis and formulate a new one.

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Pablo Hadrava

Sales Manager | Business Developer Manager | Project Manager
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Recopilar y analizar datos sobre la rotación de empleados es esencial para tomar medidas efectivas. Utilizar diversas fuentes, como entrevistas de salida y métricas como la tasa de rotación, proporciona una panorama completo. Definir el alcance y propósito del análisis ayuda a enfocarse. Luego, la limpieza y organización de datos son cruciales. Los métodos estadísticos permiten encontrar correlaciones y probar hipótesis. Este proceso es fundamental para comprender y abordar la rotación de empleados de manera efectiva.

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3 How to choose the right data visualization type?

When managers are ready with their data, they need to select the right data visualization type for their analysis. Different types of data visualizations can serve different purposes and offer distinct advantages. For instance, pie charts or donut charts can be used to show the proportion of employees who left for various reasons, such as pay, career, culture, or personal. Bar charts or column charts can be utilized to compare the turnover rate or retention rate across different groups, such as gender, age, tenure, or skill level. Line charts or area charts are suitable for displaying the trend of employee turnover or retention over time, such as monthly, quarterly, or yearly. Scatter plots or bubble charts are useful for exploring the relationship between two or more variables, such as employee satisfaction, performance, engagement, or loyalty. Heat maps or tree maps can be used to demonstrate the distribution of employee turnover or retention across different categories, such as region, location, or department.

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Pablo Hadrava

Sales Manager | Business Developer Manager | Project Manager
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Seleccionar el tipo adecuado de visualización de datos es muy importante para transmitir información de manera efectiva. Cada tipo de gráfico ofrece ventajas únicas. Por ejemplo, los gráficos circulares son ideales para mostrar proporciones de razones de rotación, mientras que los gráficos de barras comparan tasas entre grupos. Los gráficos de líneas revelan tendencias a lo largo del tiempo, y los diagramas de dispersión exploran relaciones entre variables. Los mapas de calor y los mapas de árbol ilustran la distribución geográfica o departamental. La correcta elección de visualización enriquece el análisis y facilita la toma de decisiones.

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4 How to design effective data visualizations?

When designing data visualizations, managers need to be mindful of some best practices in order to convey their message accurately and clearly. For instance, they should use appropriate colors, shapes, and sizes to highlight the most important or relevant data points while avoiding clutter. Additionally, they should use clear labels and titles, as well as consistent legends and axes to explain the data and its units of measurement. Furthermore, it is important to use appropriate scales, intervals, and ranges to show the data accurately and honestly. Finally, annotations, captions, or narratives should be used to provide context and interpretation of the data rather than leaving the audience guessing or confused.

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Pablo Hadrava

Sales Manager | Business Developer Manager | Project Manager
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Cuando se trata de dise?ar visualizaciones de datos, la precisión y la claridad son esenciales. El uso adecuado de colores, formas y tama?os resalta puntos clave y evita el desorden. Etiquetas, títulos y leyendas claras explican datos y unidades de medida. Las escalas adecuadas garantizan precisión y honestidad. Además, las anotaciones y narraciones garantizan contexto, lo que evita confusiones. Siguiendo estas mejores prácticas, los gerentes pueden transmitir información de manera efectiva y asegurarse de que su mensaje se entienda claramente.

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Jennifer J.

Civil Servant; CIC Director; CIO Managing Trustee; Fair Treatment and Inclusion Champion; and Academic Quality Assurance Consultant.
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It is also important to use the right visualisation technique. For example a pie chart is good at showing how much of a whole is represented and bar charts could show growth or decline in a sector. Some charts could measure more than one thing allowing for multiple things to be clearly considered at once. It also allows the audience to see if there is a correlation between things such as increase in hours and staff satisfaction as well as clearly identifying areas where there is minimal downside for the most gain.

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5 How to present and share data visualizations?

Finally, managers need to present and share their data visualizations with their audience, such as employees, senior leaders, or HR professionals. They should structure their data visualizations logically and cohesively, using transitions and connectors to link them together. Moreover, they should use a compelling and engaging story to frame their data visualizations, employing emotions and values to appeal to their audience. Additionally, managers should use simple and concise language to explain their data visualizations, avoiding technical terms or acronyms that their audience may not understand. Furthermore, they should use a suitable and accessible format to share their data visualizations, incorporating interactive features or feedback mechanisms to encourage participation and collaboration. Data visualization can help managers identify the most common causes of employee turnover and make better decisions to address them. With this approach, managers can communicate and understand complex information more effectively, identify patterns and trends, discover insights and solutions, as well as engage and persuade their audience.

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Pablo Hadrava

Sales Manager | Business Developer Manager | Project Manager
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La presentación de visualizaciones de datos es un paso clave en la comunicación efectiva... Estructurarlas de manera lógica y cohesionada con transiciones claras es de gran importancia. Además, contar una historia convincente con emoción y valores atraerá a la audiencia, hará que de una u otra forma se enganchen y logremos obtener su atención. El uso de un lenguaje sencillo y un formato accesible o de fácil visualización facilita la comprensión. Incorporar características interactivas fomenta la participación. La visualización de datos ayuda a identificar causas comunes de rotación de empleados, mejorando la toma de decisiones.

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John A. Porcello

Proud Parent | Expert Voice and C-Suite Senior Consultant at GLG | Fiduciary Securities Adviser
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Presentations can be a scary thing for most people, but conveying information in a way that is comfortable for you starts with how it is comfortable with your audience. If you are looking to relay information in the best way during presentation, connect previously.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can data visualization help identify the most common causes of employee turnover?

1

2

3

4

5

6

1 What is data visualization?

2 How to collect and analyze data on employee turnover?

3 How to choose the right data visualization type?

4 How to design effective data visualizations?

5 How to present and share data visualizations?

6 Here’s what else to consider

Decision-Making

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How can data visualization help identify the most common causes of employee turnover?

1

2

3

4

5

6

1 What is data visualization?

2 How to collect and analyze data on employee turnover?

3 How to choose the right data visualization type?

4 How to design effective data visualizations?

5 How to present and share data visualizations?

6 Here’s what else to consider

Decision-Making

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