With global data volumes rising rapidly, organizations are now poised to extract hidden insights about their workforce and generate value. However, the continued reliance on data scientists is a big challenge for most companies. Not all companies (especially small and medium-sized businesses) have the resources and skill set to realize the full potential of data.
Human Capital Management (HCM) Suites for High-growth Enterprises: The Ultimate Guide [Buyers Guide]
Your HCM System controls the trinity of talent acquisition, management and optimization – and ultimately, multiple mission-critical performance outcomes. Choosing the right solution for your organization….
That’s where augmented analytics comes in. It democratizes data-to-insight conversion, allowing virtually any stakeholder to access insights in a comprehensible format. This has significant implications for HR – let’s look at them in greater detail.
Learn More: 5 Ways Predictive Analytics will Transform HR
What Is Augmented Analytics in HR?
Augmented analytics can be defined as a branch of data science that aims to automate the insight generation process. It achieves this by using cognitive technologies, enabling machines to view and represent data from the same perspective as humans. The following components power augmented analytics:
Machine learning (ML)
ML lets technology systems intuitively learn, without the intervention of human coders. They can automatically adapt to different scenarios independent of rule-based programming. Powered by ML, augmented HR analytics can get incrementally better at providing the right insights with every data processing cycle.
Natural language processing (NLP)
NLP is particularly relevant to HR. Thanks to NLP, HR professionals do not need years of data science experience. Instead, the augmented HR analytics interface can deliver insights in a human-readable format. This is a four-step process:
Data in natural language such as English is processed via NLP and converted into a machine-readable format.
The machine data is then fed into analytics models to detect patterns, trends, and anomalies.
A predictive engine performs a root cause analysis to identify the most probable factors causing the trend.
The insight is finally converted back into a natural language, to be actioned by any lay user.
As per traditional analytics models, data scientists spend 19% of their time on collecting data, and another 60% on cleaning and organizing it. These processes can be completely taken over by the insight automation capability of augmented analytics. Instead, data scientists (or, augmented analytics solution providers) can focus on building more effective training sets and refining analytics algorithms. HR only needs to feed the correct data into the interface and access the most relevant insights.
Together, these elements make HR analytics much easier to use. Let us now look at the different applications of augmented analytics in HR and its key benefits.
HR Augmented Analytics Use Cases and Three Benefits You Can Expect
Interestingly, augmented analytics isn’t limited to a single HR function or area. Much like the internet, data and analytics have the potential to transform processes across all facets of the enterprise completely.
A promising use case to consider is aligning hiring efficiency to employee quality. In a competitive labor market, HR risks compromising quality due to a disproportionate focus on quantity. There are deadlines to meet, time-to-hire goals to achieve, and recruitment campaigns to be kept under budget. In the middle of these KRAs, quality of hire can often be undermined. HR augmented analytics lets you feed recruitment data into the software and assess where you stand on the quality spectrum.
Another use case for HR augmented analytics is controlling voluntary attrition. Attrition in any enterprise is a complex issue. Not all of it is voluntary, and not every case of voluntary attrition is regrettable. Augmented analytics lets you deep dive into all of these characteristics, sifting through employee lifecycle information and pinpointing the cause and nature of attrition. The resulting insights can help you refine the employee management mechanism for optimal attrition rates, targeted towards your most high-performing and ROI-friendly employees.
These uses the only scratch the surface. You can apply augmented analytics to virtually any HR use case, such as employee engagement, onboarding pain points, or benefits administration. And this will help you achieve several advantages over traditional analytics:
1. Incorporating the power of AI into analytics systems
Enterprises are now eager to adopt AI technology but aren’t always sure of the right utilization. Augmented analytics takes a solution-oriented approach to AI adoption, identifying a measurable HR challenge and using data to solve it. As a result, you can obtain tangible returns from your investment in AI.
2. Dramatically reducing your time to value
Augmented analytics has a clear leg up on manually driven analytics systems. Data scientists can take weeks or even months to collect and cleanse the data, not to mention the time spent on building analytics models. Augmented HR analytics automates the first half of this activity, significantly accelerating insight generation. It is even faster than regular analytics because you don’t have to spend time converting these insights into action points. The predictive capabilities of augmented analytics will indicate a clear course of action.
3. Democratizing business intelligence and reducing cost
Augmented analytics opens up advanced business intelligence to the broadest group of stakeholders. From your IT team to the payroll division, from C-level leaders to third-party employee engagement consultants, virtually anyone can leverage augmented HR analytics to improve processes. This, in turn, eliminates the need to hire experienced data scientists, dramatically reducing the cost component of your analytics function.
The Future is Now: Strides in HR Augmented Analytics
Augmented analytics is an exciting area of innovation and research. Its global market is expected to cross $22 billion in the next six years, growing at a staggering pace of 25.2% every year. In fact, augmented analytics was named among our top five disruptive HR technology trends to track in 2019.
So, is this only a futuristic technology currently being hyped? The answer is a resounding no.
Technology giants across the world are already looking at implementing augmented HR analytics as part of their larger business intelligence services. One year ago, HR tech giant Workday announced a new version of people analytics that would leverage AI and ML for automated insight generation. Solutions like this help to reduce information load by a factor of 1000 or more, significantly reducing data clutter so that you can view only the most critical insights.
As HR looks at propelling a brand new growth curve for companies, fueled by fast and effective decision-making, augmented analytics will be indispensable to the HR toolkit of the future.
Source : https://www.hrtechnologist.com/articles/hr-analytics/what-is-augmented-analytics-in-hr/