Big Data Meets Employee Engagement: Top 3 Ways in Which Data Analytics Can Boost Employee Engagement

Today, businesses in India are searching for any competitive edge they can get in the fiercely dynamic economy. To improve operations, many companies are buying into data analytics and Big Data.

Big Data, however, is more than just a tool for commercial applications and decision-making for businesses. It can aid in boosting employee engagement, which is advantageous to employees, their supervisors, as well as the company.

Having said that, companies could be reluctant in using big data to evaluate employee engagement. After all, client retention and other similar objectives frequently make use of big data analytics for business. 

In this context, one would wonder why data is necessary to measure employee engagement.

At first glance, it might appear like data analytics isn’t even remotely related to employee engagement — they are polar opposites (because engagement is difficult to track and measure).

But even if they may seem at odds, the need has never been greater because engagement today is crucial to a company’s growth. This fact is made ever more clear by studies and reports that suggest that, today, only 1 in 6 employees are actively involved in their jobs.

It only means that most employees either despise their work or perform the absolute minimum. Simply put, they are not emotionally invested in their jobs. So, if you want to prevent this at your company, utilising data analytics could be a feasible solution. 

How exactly is big data improving engagement? Let’s take a look.

#1 Employee Performance, Data Analytics, and Enterprise Outcomes

The inferences that can be drawn with big data analytics can enable workers to feel like important contributors to corporate strategies. Analytical reports can help them to comprehend how their daily actions relate to company goals.

The application of technology has provided staff with the knowledge required to determine goals and the drive to pursue them. Additionally, employers can employ the data as a useful tool to pinpoint members of staff who may require upskilling. Supervisors may formulate personalised plans for career advancement for each employee thanks to big data technology. 

Every action performed by an employee for an information-dependent business derives insights that superiors may analyse and correlate with performance expectations. Senior managers can learn more about their staffs’ skills that could assist the company in other areas through big data.

Furthermore, supervisors can utilize the reports and the information to communicate department-wise targets and performance outcomes with workers in order to assist them in comprehending the significance of their own career objectives.

#2 Tracking Professional Growth

Big data can be utilised to track employees’ career progression and record progress every quarter or month, whether they are furthering their professional development through company-sponsored learning and development, or continuing their education to better their skills.

With the help of data analytics and reporting, workers can identify specific areas for professional growth and track their personal metrics and those of their peers. The technology can also provide feedback that can inspire them to improve their productivity.

Tracking employee skill through analytics is something that both businesses and employees can use for their collective benefit. By addressing weaknesses and shortcomings, employees can better themselves, which eventually helps companies make the best use of their staff. 

Similarly, workplace engagement too experiences significant improvement when workers are offered complete autonomy over their professional growth through data analytics and reporting.

#3 Data-Driven Decision-Making

It’s not a secret anymore that companies today have embraced the philosophy of basing their business decisions and choices on factual information produced by data analysis in order to increase employee engagement. 

On that note, supervisors and the leadership should build a corporate culture in which all staff members and their respective managers engage and promote data-driven decision-making. Having said that, organisational leaders and managers must ensure to restrict the queries to defined areas of interest because data takes many forms and originates from multiple sources.

It’s absolutely critical that individual stakeholders communicate the results when the data and analytics team produces the final report. The findings and inferences from the data reports must be shared with as many key parties as possible to optimise the report’s utilisation because the data insights and inferences are valueless if they aren’t shared.

During interaction with customers, top executives must instruct, monitor, and assess staff on how to obtain information effectively. At all stages of client interaction, there need to be restrictions for the collection and storage of information. With such contingencies in place, businesses can explore all avenues for growth as well as provide staff with the capabilities they need to be successful and highly engaging at work.

Conclusion

The objective is to give corporate leaders improved and ongoing insights into the shortcomings and capabilities within the firm by developing a framework that harvests data directly from employees.

Instead of relying just on annual assessments, big data enables businesses to examine data in real-time. In this manner, it is relatively simple to perceive the extent of employees’ happiness and engagement within the company.