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Succession Planning analytics and Hr Dashboard in Tableau

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A few years ago Interworks were engaged to work with a human resource analyst ‘Adrian abarca’ on a visual analytics project. At that time he was working for a global insurance provider with over 60,000 employees. Adrian’s job was to provide human resource analytics. He had just discovered tableau and wanted to use it to develop presentation materials for a meeting, but he perceived that he didn’t know much about it and it is definitely a difficult task to finish the work without any expert help. Interworks had played the role of expert and hence provided him the required support.

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A framework for spurring effective conversation and action

Adrian’s mission was to provide fact-driven research that supports workforce analysis to facilitate strategic workforce planning. The insight gleaned from this work helped human resource professionals at the company to assist with operating managers in generating fact-based decisions. He also wanted to provide proactive information that would give managers insight which would aid to strategic planning rather than just giving manager’s historical views.

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Succession Planning Dashboard

Providing progressive information for succession planning

Succession planning data is crucial to an organization’s talent development strategy. Normally, this information is not structured in a way through which leaders can easily identify potential pitfalls in the leadership pipeline, but it is conferred in a way that helps people diagnosed future issues before they arise so that plans can be laid to prepare for smooth transitions. The dashboard in figure 12.11  was used to facilitate conversation between leadership and their human resource support partner.
Source: Case study and figure is contributed by Adrian abarca company. The name is withheld upon request.

Succession planning dashboard

                                  Figure12.11: succession planning dashboard

This dashboard assists in identifying successors’ needs using two ambiguous dimensions: the employee’s tenure with the organization and age. By using these parameters, the users can change the view to fit specific organizational requirements. For example, if the expected retirement age for a company is 55 and tenure is 15 years, the reference lines can be changed to express those facts via the reference lines in the scatter plot.

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Selecting one or more marks (individuals) in the scatter plot, allows users to filter the crosstab and also to display pertinent information related to those selections. The scatter plot is also broken into four quadrants that help the user identify where the urgent needs for successors exist. This data alone is not enough to fully understand the critical skills of the dashboard as it requires deeper analysis and understanding of the specific skills and talents needed-providing a means for identifying talent gaps in prospective replacements for each position. For confidentiality, this information has been removed from figure12.11.

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Human capital is every entity’s most valuable asset. By expressing appropriate facts and dimensions visually, it becomes easier to see outliers that require attention. But, progressive dashboards like the one presented here offer more than typical historical headcount reports-as they provide a means for progressive plans.

In mid-2013, tableau software started trading publically on the New York stock exchange. Considering that the company has been in existence for a mere 10 years, it is exciting to imagine what the next 10 years will bring.

Our ability to capture, use, and analyze data has improved considerably since the 1970s when database tools started to become commercially available. In the early 1980s, the spreadsheet became the “ killer application” on early personal computers because it provided a quantum leap in our ability to model different scenarios. Tableau provides yet another breakthrough in the ability to understand large and diverse data sets by making data easier to visualize and easier to grasp.

The ultimate goal of storing data is to turn it into information that can be further used to make better decisions. We are here with a belief that this post will help you reach your goals with tableau even faster.

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Last updated: 04 August 2023
About Author
Remy Sharp

As a Senior Writer for Mindmajix, Saikumar has a great understanding of today’s data-driven environment, which includes key aspects such as Business Intelligence and data management. He manages the task of creating great content in the areas of Programming, Microsoft Power BI, Tableau, Oracle BI, Cognos, and Alteryx. Connect with him on LinkedIn and Twitter.

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