{"id":1108,"date":"2019-02-15T10:31:58","date_gmt":"2019-02-15T10:31:58","guid":{"rendered":"http:\/\/kusuaks7\/?p=713"},"modified":"2023-07-28T13:54:11","modified_gmt":"2023-07-28T13:54:11","slug":"bringing-hr-analytics-to-life-unleashing-the-power-of-your-organization","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/bigdata-cloud\/bringing-hr-analytics-to-life-unleashing-the-power-of-your-organization\/","title":{"rendered":"Bringing HR Analytics to Life – Unleashing the Power of Your Organization"},"content":{"rendered":"

Introduction<\/strong><\/h3>\n

A lot has been recently said and written about HR (or people) analytics, but it is still a nebulous concept to most. This article is a guide that will lead you through all the necessary steps to successfully introduce and execute HR analytics, making a fundamental impact on the culture of your organization. The intended audience includes executives as well as HR and analytics professionals.<\/p>\n

We introduce the key concepts behind people analytics, and how it can be made an indispensable tool in your organization. The key take-away is that HR analytics is not just an implementation of technical concepts: it requires an organizational commitment to defining a data-driven strategy and adopting a data-driven culture, and it is critically dependent on having the right leadership, facilitation skills, and resources in place.<\/p>\n

Impact of HR Analytics on Organizational Culture<\/strong><\/h3>\n

Every organization has a distinct set of people challenges that it wants to address. People analytics means translating these challenges into a properly articulated set of objectives and\/or metrics that can then be\u00a0mapped into what the organization knows about its employees and what it would like to know.<\/p>\n

This exposes the need to have an HR executive (a Chief Human Resources Officer (CHRO)) in the inner circle of top executive management (with the CEO and CFO) (a\u00a0suggestion\u00a0highlighted in a recent HBR article<\/a>)<\/em>, who understands both the organizational needs at their most strategic level and the employee data landscape. If you can articulate how the two connect, your organization is ready for people analytics and the HR function has likely\u00a0achieved the holy grail of strategic partnership.<\/p>\n

Putting HR analytics in place will not be an easy journey, as it requires getting leadership commitment; educating management on the power of analytics; learning about and evaluating tools, technologies, and techniques; making this capability fit seamlessly with your existing processes; identifying new HR roles and skills; and training your staff on applying and using it most effectively. In the absence of a one-size-fits-all solution, it also requires careful consideration of build vs. buy factors and a roadmap for rolling out analytics capabilities in stages.<\/p>\n

Another important consideration is cost versus benefit. Having an HR analytics capability is costly.\u00a0 It requires considerable people and monetary investment during all phases from conception to deployment, and this continues through ongoing training and operations. However, against this cost picture is a very compelling value proposition: consider, for example, the cost associated with a bad hire. Recruiting and training costs alone can add up to a very substantial amount. Add to that the opportunity cost associated with not having the right person in that role (e.g. sales), and the cost will easily reach\u00a0hundreds of thousands of dollars. A good HR analytics implementation will pay for itself many times over.<\/p>\n

This article will help you decide the best approach for driving cultural change in your organization through HR analytics, as well as identifying expectations of\u00a0the HR and organization development and of the analytics experts whom\u00a0you will consult.<\/p>\n

HR\u00a0Analytics Framework<\/strong><\/h3>\n

We describe a framework that connects data inputs (i.e., what we know, or don\u2019t know but would ideally like to know) about the employee and his or her role in the organization to a set of outcomes or metrics that the organization is interested in.<\/p>\n

In the middle is a complex model that analyzes the input data and predicts outcomes and generates metrics.\u00a0 In essence, the model represents (predictive) analytics capabilities that can technically be implemented in a variety of ways, such as through the use of advanced statistics, data mining, and machine learning techniques.<\/p>\n

This picture shows the components of the HR analytics\u00a0framework and the roles of the various participants.<\/p>\n

 <\/p>\n

This article will not go too deep into the underlying techniques or mathematics, but is intended to show what is feasible, and, most importantly, highlight the fact that it is possible to educate and train executive management and HR professionals in the key concepts as well as on how to successfully apply them in their organization.<\/p>\n

A New Role in HR<\/strong><\/h3>\n

As the practice of HR analytics evolves, so must the roles within HR. We argue for the creation of a new role within the HR function that combines HR and analytics skills, bridging the\u00a0current HR staff and the analytics staff.<\/p>\n

The right person for the role is\u00a0someone who is able to bring all the data (known\/unknown, accessible\/hidden) together in new ways and\u00a0translate the CHRO’s vision into action, thereby converting the\u00a0HR analytics environment into a\u00a0true catalyst for cultural change.\u00a0 The role also requires a strong partnership with HR and organization development professionals to understand the dynamics of the organization and the people behind the data\u00a0and its impact on the culture.<\/p>\n

We believe that this\u00a0role belongs in HR, even though some of responsibilities may belong on the operational side (a point made by Josh Bersin in a recent LinkedIn article<\/a>).<\/em><\/p>\n

Desired Outcomes<\/strong><\/h3>\n

What are some desired outcomes and how can they be measured, classified, and\/or predicted?<\/p>\n