Workforce analytics, like ChatGPT, is an AI application that is changing organizations everywhere. Workforce analytics are used to provide managers with HR-based knowledge in ways that people are not able to do. But getting started with workforce analytics is a bit complicated in itself.
What Are Workforce Analytics?
“Workforce analytics” (WA) is also known as HR analytics, talent analytics, and people analytics. They are a combination of technology and processes that enable the collection and understanding of HR-related data so that managers can build strategies of a kind not possible through a manual approach.
Why Are Workforce Analytics Important?
Like many new technologies, applications for WA are constantly being discovered. There are four stages of WA sophistication (see below), and at the highest level – which is currently rare to find in organizations – the benefits can be revolutionary.
But even at its basic levels, WA holds a lot of promise. Due to the Great Resignation, engagement and retention are two very important topics at the moment. Companies that successfully use WA technologies will gain yet another tool to optimize engagement and retention levels.
Organizations that get started with WA today will develop expertise over time, while those that are slow to adopt the technology might struggle to catch up when WA becomes mainstream. In this sense, WA could be a competitive advantage in the future.
For reasons such as these, organizations that leverage WA are, when compared to non-users:
- More capable of rendering and integrating HR-related data
- Three times more likely to have HR staff that understands business objectives
- Ten times more likely to provide valuable advice to top management
Workforce Analytics Tools
The technologies behind WA consist of analytical software packages. Some of the more well-known vendors are Papaya Global, Tableau, and Visier People. Organizations that are shopping for WA platforms should be aware that different vendors specialize in certain areas, such as a comprehensive dashboard, widespread integrations, or ease of use.
Workforce Analytics Certifications
To operate WA tools, HR employees need considerable expertise. To this end, there are numerous certifications that can be obtained. Examples include The People Analytics Certificate Program by AIHR Academy, People Analytics by the Josh Bersin Academy, and People Analytics by Google.
Obtaining certification in WA is possible through university courses, but these examples are programs that are often self-paced, and which might be best for busy HR people.
The Importance of Data Collection
WA relies on large amounts of data to perform a thorough analysis. But it’s up to the organization to collect that information. This adds another set of tasks to the workload of managers, HR staff, and often employees as well. For this reason, setting out and following up on consistent and simple data collection procedures is vital for success with a WA program.
Examples of Workforce Analytics
There are seven areas that experts have defined where WA can be applied. Known as the Pillars of People Analytics, they include:
Workforce planning; talent sourcing and acquisition; onboarding, culture and engagement; performance management; retention; and wellness and health.
There are numerous uses for WA across these areas. For instance:
- In sourcing functions, the technology can sift through resumes, perform background checks, and create lists of top candidates.
- For retention efforts, WA can look for employees whose performance does not match their compensation rates, identify outstanding efforts, and recognize when a worker is at high risk for quitting.
- In workforce planning, AI can track how long it takes for skills to be acquired as well as which are used most in the organization, and then recommend L&D programs in advance of any skill gaps being formed.
The 4 Levels of Workforce Analytics
Being a relatively recent technology, WA occurs at different levels of implementation throughout its user base. But, as time goes on, more companies will reach higher levels of usage ability. It should be noted that the greatest benefits of WA occur at the top level, and that a company needs to progress through one level at a time.
Most organizations involved in WA work at this level. It is called “descriptive” because it has to do with displays of information that describe a situation, and not high-level analysis. Most of the value at this stage is delivered by a dashboard display of WA data, which makes large amounts of information easier to understand.
The diagnostic application of WA is meant to clarify cause and effect. For example, if a sales team has had a great month, diagnostic WA will identify the most important contributing factors. To get to that point, HR or management needs to decide on a KPI to analyze so that performance can be measured according to a standard.
Instead of matching cause and effect, predictive WA examines what effects will occur according to a variety of causes. So, for example, if the organization hires 20 engineers, predictive WA might calculate the resulting increase in productivity.
This is the ultimate stage of WA. The idea here is to decide on a goal and let WA tell you what needs to happen to get there. If you want to cut onboarding times without losing quality, WA can list the activities that will result in this outcome.
GrowthSpace for Workforce Analytics Support
Learning and development are a central aspect of workforce analytics because they enable workers to build the skills that are behind productivity. But if companies are looking for better performance from their entire HR function, shouldn’t they demand the same from their talent development platform?GrowthSpace is the ideal complement to a workforce analytics system. Its personalized learning technology allows organizations to make the most of AI-based recommendations through training that fulfills precise organizational goals at scale. If workplace analytics is the HR tool for the 21st century, then GrowthSpace is its L&D partner.