Making Healthcare Organization Decisions Based on Workforce Data and Analytics

April 1, 2021
April 1, 2021

A wide array of organizations, including many in healthcare, are collecting data about employees in ways that have never before been available and using it to make important decisions about hiring, staff management, employee retention, and whatever is necessary to make sure the workforce is operating as efficiently as possible. This emerging focus on people analytics is aimed at improving staff performance.

The Importance of People Data

According to the report, 2018 Deloitte Global Human Capital Trends, three converging forces are driving the growth in importance of workforce data analytics:

  1. The understanding that workplace issues have an important effect on productivity, such as employee engagement, development, gender pay equity, and diversity.
  2. Investment in complex HR systems that are compiling a trove of data that has not been available up to now
  3. Organizational anxiety about data security, especially that of employee data (Agarwal et al, 2018)

When the systems that oversee all human resources functions are able to collect data, it can be used to connect what is going on with employees to business results. Furthermore, when organizational objectives are established or not being met, leaders can go back to the data, make decisions, and take action to change it. Ultimately, the goal of data collection and analysis is to make better people decisions and plans, which in turn will lead to more successful business outcomes.

Five Trends Involving Data and Talent Strategy

A recent Forbes article looks closely at how business and organizations are now “awash in data, and workforce data in particular as organizations have moved to digitize the entire employee lifecycle—from sourcing to offboarding” (Weisback, 2017). Furthermore, the author tells us to think more broadly about all the data that is collected on employees, beyond recruiting, hiring, performance, etc. In turn, this data will interface with artificial intelligence, leading many organizations to completely change how we perceive and make decisions about the workforce. Five trends associated with this transformation include:

  1. Using Internet of Things (IoT) Data to measure how employees and teams work together. Weisback believes that “data gathered from sociometric badges can help businesses support the kinds of informal communication networks that lead to productivity and innovation.”
  2. Identifying specific skills gaps and hiring to fill them. We are likely to move from recruiting based on an open number of roles to engaging candidates based on fit and skill and what top performers are able to achieve.
  3. Determining which jobs will be assumed by robots or automation. It’s likely that data will give a big boost to decision-making about when human labor is “more productive and/or cost-effective than technology.”
  4. Predicting workforce changes more effectively. Weisback insists that “by forecasting when, how many, and which employees are likely to leave, for example, businesses will be better able to plan for hiring.”
  5. Understand learning effectiveness better and make better development decisions. With more complex data and access to learning analytics, “talent development professionals can connect the necessary HR and business systems together to make it faster and easier to analyze learning data” (Weisback, 2017).

Weisback closes by sharing that when it comes to understanding and interacting with information about employees and their contributions to organizational success, “one thing is apparent: when it comes to the data experience, we’ve only seen the tip of the iceberg” (Weisback, 2017).

Understanding the Risks Inherent in Using Workforce Data

The Deloitte report shares how “Some experts worry that algorithms and machine-based decisions could actually perpetuate bias due to flaws in the underlying data or the algorithm itself” (Agarwal et al, 2017). Organizations are reminded of their obligation to prevent any bias from entering into workforce recruiting, hiring, or advancement processes. Even so, “the promise of people analytics remains too valuable for organizations to pass up” (Agarwal et al, 2017). If organizations are going to make decisions based on workforce data and analytics, then it is essential to enact “robust policies, security, transparency, and open communication to address the associated risks” (Agarwal et al, 2017).

Using Workforce Data Analytics to Power Healthcare Organization Decisions

When performance is driven in large part by effective resource management and workforce decisions, how do you keep efficient staffing levels, reduce premium pay, and decide where to cut costs? HealthStream empowers healthcare leaders to make decisions based on data about their workforce and organizational processes. Available tools include:

  • MyTeam Dashboard. With MyTeam, managers have access to critical employee data within the HealthStream platform to inform decision making. MyTeam provides continuous access to the team hierarchy, an employee's profile and activities, and actionable insights on learning and assessment progress.
  • Executive Lens. This visual solution helps acute and post-acute leaders make decisions for their organization by having important key metrics at their fingertips, such as staffing ratios, roles or functions that can be consolidated or outsourced, and contractor staffing.

Many healthcare organizations are trying to achieve as much as possible with their limited financial resources. For them, this means that workforce decisions are integral to organizational success. It is imperative that every decision made should be informed by the best and most complete data available.


Agarwal, D., Bersin, J., et al, “People Data: How Far is Too Far?,” in The rise of the social enterprise: 2018 Deloitte Global Human Capital Trends, Deloitte, 2017.

Weisback, Dave, “Talent Strategy In The Data Age: 5 Trends To Watch In 2018,” Forbes, December 6, 2017, Retrieved at