The COVID-19 pandemic has forced human resources to demonstrate more emotional intelligence while leveraging technology to meet fast-changing government requirements as well as to engage a hybrid workforce that is critical to business success.
In a 2022 survey, Robert Half research indicated roughly 50% of workers would rather quit than return to the office on a fulltime basis. According to a PwC pulse survey conducted in 2021, 65% of employees are looking for new jobs and 88% of employers revealed they were seeing higher turnover than normal. These surveys indicate that HR must start thinking about revamping strategic planning while being people-centric. Data can be a valuable tool for HR as it starts to transform itself by adopting the organizational principles and key performance indicators of core business functions.
Data Quality is Key
When I talk to HR leaders, they all agree that data is a key resource for improving business performance, but not many have utilized data when making decisions. Most HR organizations today have the data in their enterprise resource planning (ERP) systems, but they don’t know how to channelize the data and use it effectively for enhanced insights, operations, and compliance. So, what can HR do to gain insights? HR can start by asking the right questions. For example: Why analytics? What is the business need or goal? What data is currently available to us?
And, does the available data help us understand the issue? If it does, then you must understand the story the data is telling you and get insights. Then, make a business decision to increase efficiency.
It’s always important to align the goals to the overall business objective. When HR maps goals to questions and to key performance indicators (KPIs), HR can form precise and holistic representation of the organization’s business environment and needs. It is important to remember that data quality cannot be compromised, otherwise intuition will prevail over data in decision making.
Data can quickly morph from an asset to liability if data quality is poor. Data quality is important as it is intricately linked with business operations, and it is this data that is used in data analytics to drive business decisions. Therefore, to have a successful data analytics initiative, HR must implement a playbook that includes strategy as well as tactical elements to deliver greatest value to the business.
According to a Bersin by Deloitte study, data-driven HR teams are four times as likely to be respected by their business counterparts, which can result in more input in strategic decision making. Aggregating data from different systems into a business intelligence system is very beneficial, as it enables leaders/users to look at data holistically from many different perspectives. Below are some examples of how data can be utilized to drive business behavior, results, and organizational culture.
How are Data Insights Generated?
Data-driven recruiting can optimize recruitment cost by identifying the most effective source or channel for quality candidates. Data-driven insights can allow recruiters to be strategic, thus creating an optimized journey for candidates. A better user experience can be created by constantly monitoring the application process and keeping track of metrics such as:
1) How many candidates have opened an application?
2) What steps did they complete?
3) What percentage of candidates finished the application?
4) What is the percentage of drop-off candidates?
5) Is there a trend in the point of the application process at which most candidates are dropping off? If so, which step?
Internal Mobility and Turnover
When evaluating employee mobility in and out of jobs, a deep dive into aggregated data would provide much-needed clarity. Most organizations’ greatest source of talent is already within their organization. Organizations can leverage internal mobility programs to fill cross-functional opportunities and not just to fill vacancies.
Workforce analytics can be used to dig deep to understand the cause of employees leaving, and a retention plan can be based on the information directly obtained from the data. Some possible questions that can be asked when looking at turnover data include:
1) Is this a voluntary or involuntary separation?
2) Which department has the most separations?
3) Are separations higher for a particular job classification?
4) Are separations higher in a particular division?
5) Are separations higher under a certain manager?
6) Is turnover rate higher for a particular race, age or gender?
Using multiple metrics such as compensation ratio, pay increases, tenure, performance and training opportunities, we can identify correlations and reasons for resignations. By comparing how resignation rates vary across departments/divisions, gender, age, tenure, diversity groups and performance level, for example, organizations can gain insight and develop retention programs strategically.
Data can answer a lot of questions by taking intuition out of the equation. It is therefore important to invest in a robust people analytics software solution that allows decision makers to take evidence-based corrective action to address critical issues that are affecting human resources today. According to an article by Deloitte about people analytics, “The real value is in turning these insights into change that delivers business value. The hardest part of people analytics is implementing the changes recommended by the models, which call for people analytics to be accompanied by sound change management practices.”
Therefore, good change management is required so that insights are consumed by business stakeholders. By adopting the right change strategy, organizations can turn analytics initiatives into engagement and business results.
01 December 2022
Category
HR News Article