Employee Engagement has been one of the biggest challenges faced by organizations worldwide for quite a long time. Year after year, major organizational surveys show a very reluctant employee engagement arrow that is so stubborn to move above the 15% mark. That means around 85% of workers across the globe are disengaged and would like to look for better options if they can. Do you think that your employees also fall into this category?
Are you not seeing results even after spending thousands of dollars on annual employee surveys, performance appraisals, rewards programs, manager trainings, and other engagement initiatives? It then boils down to a question of whether you are spending time and money on the right thing, for the right people at the right time. And the simple answer to it is, “Dig your data”.I know that you may be tired of everybody asking you to use data and analytics. You Google it and are bombarded with articles on how predictive analytics and big data have been saviors for many organizational issues including sales, market research, and customer experience management for many years and now human capital management too.
While it’s unquestionable that data can be one of the most important drivers of your engagement strategy, like any other HR issue, there is no single strategy that fits all. It’s more or less like picking up the estranged pieces of a jigsaw puzzle and connecting them together to give a complete picture of the past, current, and future state of how well your employees are committed to the organization and its success.
Traditionally, engagement initiatives have been based on an annual engagement survey and its findings or in some cases merely on the judgments of those in the HR department.
Having a data-driven engagement strategy is much more than having that one annual survey. It needs a well-defined end-to-end game plan, with a clear-cut goal, action items, a team, definition of success, and of course budget.
While most organizations start right on these, they stumble upon two daunting problems:
How to Measure the Data That Matters
The success of the entire strategy depends on the quality and relevance of the data collected. The traditional engagement surveys also have been collecting data, but it happens once a year and that leads to a lot of biases and inaccuracies.
For example, it’s impossible for the employees to respond to a survey keeping in mind the facts of an entire year. The responses will be based on recent events, and since it’s taken only once, it is a representation of what the employee feels at that very particular moment. Basically, it’s just a snapshot. Most importantly employees, as well as managers, don’t seem to have much faith in these surveys and their outcomes (if at all any!). A recent survey by Achievement Group/HRmarketer revealed
58 percent of respondents believed that the survey results did not help managers gain a better understanding of what behaviors or practices they could change to improve.
So what would be a better approach to solve this?
Collect data as frequently as possible without tiring the employees of the survey: Organizations have started using pulsed surveys which are shorter in length, with just 3-5 questions on a daily, weekly, or monthly basis, ditching the mammoth annual survey. There are multitudes of software products and apps that help organizations capture employee sentiments on a real-time basis. Invest in one that suits your needs. Also, make use of pre-boarding, onboarding, and exit surveys.
Ask the right questions: Design your survey with simple straightforward questions that can have a definite answer. Questions asked may be as simple as if they would recommend the organization to their friends, what is one thing that should be changed in their team, what is that they dislike/like most about working in the organization, etc.
Go Mobile: For obvious reasons. Have all your surveys, tools, apps and intracompany social networks available on mobile devices. Convenience and accessibility are big factors in helping employees answer.
Get data from multiple sources: Why do we always have to ask the employees about their engagement levels? They may end up telling us what we want to hear rather than the truth. Observe and capture other data points also; like team interactions, the quantity and quality of the organizational networks within and beyond the team, usage of collaboration tools like SharePoint, Yammer, Slack etc. and internal social networks and the information obtained from these sources.
There are many organizations that take the help of machine learning and AI to gauge employee sentiments, similar to how customer experiences are captured. This even includes analyzing employees’ faces when they enter and leave the office, scanning the office emails and chats, etc. The most important thing to remember here is to draw clear boundaries and not to invade employee privacy. Otherwise, this can backfire and turn into a costly legal affair.
Make use of the data that you already have: HR departments carry a whole lot of employee data pertaining to their demographics, salary, experience levels, skill sets, performance reviews, leave patterns, rewards, and so on. Put them to use along with other data collected to draw conclusions for specific employees or a particular group etc.
What to Do With the Measured Data?
Once you have gathered enough data, it's important to practice what is known as Data Governance Strategy to ensure quality throughout the entire lifecycle of your data. According to Wult.io,
Data governance is a comprehensive system that can securely control data collection, usage, and understand the quality of different data types against others.
Once you ensure the quality of your data, the next order of business is "How do you interpret the data and use it as the baseline for engagement initiatives?".
HR departments have always struggled with this part, even with the data collected through annual surveys. When we are talking about big data, which is actually massive amounts of data, collected from multiple sources, this part becomes even trickier and you need to use advanced analytics to draw conclusions.
First and foremost, analyze the data, segment it, and categorize it as much as possible to find patterns. Connect the patterns back to individuals or groups. A very high-level example of this can be to find insights about employees belonging to a certain age, salary range, experience level, education, etc. You may be able to find out if there is a particular no. of years after which employees leave the organization, or if more people at a certain salary level are leaving.
This will help you to understand who is engaged and who isn’t and decide where to use your engagement budgets. For example, Genpact uses this kind of predictive analytics to predict employees who are at the highest risk of voluntary attrition within the next 6 months and design interventions to re-engage them.
Plan tailor-made initiatives based on the refined data. Let employees know that actions are being taken based on their inputs and that their time and opinions are highly valued. If employees don’t see actions out of the surveys, over a period of time, the surveys will lose credibility.
Decide on how much data to be made transparent to the employees. This is a very significant new trend among a large number of Silicon Valley companies. Almost all organizational data is made available to all the employees and a collaborative approach is followed by decision making, breaking down the silos.
Many organizations keep the performance data accessible to employees on a real-time basis so that they have a picture of how they are performing and the ownership of their performance is transferred to them, rather than to the manager.
Most importantly, find the link between the engagement levels and the critical business outcomes. This is very very important as this part is where the entire program becomes strategic and adds value to the organizational goals. For one of their major retail clients, IBM Watson was actually able to show a direct correlation between employee engagement, customer satisfaction, and the actual sales in the retail stores. Such an understanding is extremely important from a management perspective to invest in engagement initiatives.
The advancement in big data and analytics practices and the easy access to technology that supports the same are a big advantage and opportunity to the HR function, especially at a time when its relevance itself is highly questioned. Now we can have data that can back up every decision and show results quantitatively.
People analytics have and will continue to transform the way employee engagement is managed by organizations and hopefully, we may soon be able to witness significant changes in engagement levels worldwide.
Krishnapriya Nair,PHR : A very passionate and thorough HR/OD professional with global experience in various fields including Learning & Development, Process Improvements, HR consulting, Business Analytics, Compensation & Benefits, Reward Operations, Talent Development, and Succession Planning. She is an alumnus of the prestigious Indian Institute of Technology, Kharagpur, India, and is the author of the blog The ArdentHR. In 2016, she was chosen as one among the Top 100 #PowerWomanAtWork by People Matters magazine and she is currently based out of Minneapolis, MN.