During this ‘age’, defined by the COVID-19 pandemic, many articles have referred to the ‘Great Resignation’, a phenomenon where employees have moved across industries and changed ‘professions’. This has particularly been the case for hospitality workers faced with limited furlough incentives and rising living costs, their only option was to abandon their established careers and move to more lucrative revenue streams of employment.
There has been much discussion on how enterprises can do better to attract and retain talent, but the ‘Great Resignation’ had major implications from an operations perspective.
The pandemic’s initial stay-at-home orders gave way to a much larger percentage of the technical population working from home. This has had benefits, both in productivity and work satisfaction.
2020 had HR professionals grappling with new work policy arrangements resulting from COVID restrictions. 2021 saw an exodus of millions of people quitting their jobs, for new endeavours – their COVID incarceration had given them time to rethink future career paths.
A period of extreme transition like this affected HR functionality of all businesses. HR departments became aware of the benefits afforded to hiring processes by relying on insight from data and analytics.
Today, in 2023 there is an increased reliance on technology and AI-powered automation to turn staffing data into insights throughout HR processes. According to ‘Fortune Business Insights’, the global human resource technology market is projected to grow from $24 billion in 2021 to $36 billion in 2028, and companies are now likely to prioritise investments in AI to optimise business processes which include HR, and to reduce operating costs.
Data-powered insight can assist in making efficient HR decisions that consider both employee happiness and business growth. However, much of the data will be unstructured.
Structured data can be easily analysed or calculated. Employee name, age, types and number of skills, gender and race are all categorised as structured data. Unstructured data is stored in its most raw format, it consists of textual documents. For example, employee performance evaluations, mental health surveys, company reviews and social data.
Both data types are equally relevant to HR. HR data is intrinsically sensitive, it must be treated with confidentiality and the highest degree of ethics. Its ability to make decisions on data lies in how the data is sourced and curated. Organisations must be able to distinguish between volunteered information and information collected from resources that employees aren’t aware of.
HR analytics is a formulaic or algorithm-based approach to deciphering everything from resource planning, recruiting and performance management to compensation, succession planning and retention. In the final analysis, HR analytics is a set of tools to empower HR teams in how to use data to strategically map out how it employs, why it employs, and who it employs.
HR teams should benefit from this provided they have a clear understanding of the types of data that deliver insights, how to manage the data and which of it can be effectively analysed with investments in impactful technologies.
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