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Analyzing the HR Criteria of a Company and how they promote their Employees and keep Balance between them using Data Analytics, Data Visualizations, and Machine Learning Models for Classification Purposes.

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Analyzing the HR Criteria of a Company and how they promote their Employees and keep Balance between them using Data Analytics, Data Visualizations, and Machine Learning Models for Classification Purposes.

HR leaders must align HR data and initiatives to the organization’s strategic goals. For example, a tech company may want to improve collaboration across departments to increase the number of innovative ideas built into their software. HR initiatives like shared workspaces, company events, collaborative tools, and employee challenges can be implemented to achieve this goal. To determine how successful initiatives are, HR analytics can be utilized to examine correlations between initiatives and strategic goals.

Once data is gathered, HR analysts feed workforce data into sophisticated data models, algorithms, and tools to gain actionable insights. These tools provide insights in the form of dashboards, visualizations, and reports. An ongoing process should be put in place to ensure continued improvement:

Benchmark analysis Data-gathering Data-cleansing Analysis Evaluate goals and KPIs Create action plan based on analysis (continuously test new ideas) Execute on plan Streamline process

Retention

The cost to replace an employee could be over 200% of their annual salary, according to AmericanProgress.org. The true cost might even be higher due to training/onboarding, lost productivity, recruitment, and decreased morale among other employees. Losing an employee that’s in the top 1% of performers could mean the difference between growth and decline. For this reason, decreased attrition and improved employee engagement are often top priorities for HR departments. HR analytics can help improve retention through a churn analysis that looks at data points like:

Current churn rate Attrition by department Attrition by estimated commute time Similar attributes of employees with longer tenure Similar attributes of employees who leave within 1 year Onboarding experience Survey data Qualitative data such as employee interviews Employee performance data to forecast future attrition

Through this data-driven approach, HR analytics can illuminate the major causes of attrition, and new policies, along with training programs, can be put in place to help mitigate the problem. For example, data might show that high-aspiration employees are not challenged or employees are frustrated with a certain management style. Human resources analysis will reveal these issues, and then it will be up to leadership to act.

It’s also possible to spot an at-risk employee before they leave so preemptive actions can be taken to resolve issues. For example, a once high-performer may not be as productive because he feels he or she is underpaid. An analysis of productivity alongside a comparison of market-value salaries can help spot this.

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Analyzing the HR Criteria of a Company and how they promote their Employees and keep Balance between them using Data Analytics, Data Visualizations, and Machine Learning Models for Classification Purposes.

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