Data analytics has been a key part of businesses for years now. But with the rise of multiple tools for tracking and measuring various activities, the quantum of data to pore over is only expanding.
HR has traditionally been a slower adopter of analytics due to the amount of human intervention that is required in most HR tasks. Now more HR leaders are answering the calls for the adoption of people analytics and automation in this space.
In this blog, we’ll take you through what employee data is, how it is collected efficiently and how it can be put to use even by small companies.
What is Employee Data?
Employee data is all the personnel information provided to the company throughout an employee’s lifecycle. This ranges from just their name to even their reason for leaving the company.
Employee data can reveal work-life imbalances, management issues and even training opportunities to create high performing teams.
There are three main types of employee data:
Regular Employee Data
This data is limited to things like name, reporting manager, department, office location, compensation and other attributes that are used in the day-to-day functioning of personnel planning.
Employee Data Collected for Analysis
This type of employee data collection is done for the express purpose of understanding why something is happening. For example, after introducing a new HR initiative pulse surveys are conducted to judge their adoption rate. The purpose of any data collected is to figure out how the initiative was received and how it’s performing.
Employee Data Collection without HR intervention
After the pandemic, companies are using even more applications and tools for the operations side of the business. They can range from communication apps like Gmail and Slack to process-related apps like MailChimp and HubSpot. Companies take subscriptions and employees are granted access.
This gives companies access to vast volumes of information that may or may not be useful in people analytics. This category of employee data is where big data analytics can be put to good use.
Are Workforce Analytics Feasible for Smaller Companies?
Employee analytics to resolve issues isn’t new by any means. But with the rise of remote workplaces, it is gaining more attention than ever before.
Every single technology in the market promises to offer insight into the end-users behaviour and HR applications are no different. With the pressure for HR to contribute more to strategic business planning, it’s becoming more important to decipher these volumes of data into actionable insights.
Although there is value in analysing data from HRIS, often smaller companies may have just piecemeal solutions for them.
For example, IBM is obviously on a kickass full-service HRIS but a smaller SaaS company with 150 employees may just make do with a few HR specialists and Excel sheets. To take it a step further, they could have an attendance and time tracking solution along with a payroll provider. In that case, is there any value in looking at predictive workforce analytics?
Check out the new AttendanceBot integration with Gusto Payroll Software.
Supporters may say that doing so can help HR predict future staffing needs and even shore up employee retention. But skeptics may say that this is just too little data to be making business decisions upon.
But we are of the belief that irrespective of the volume of data, data is valuable. All business decisions, including those made in HR, will only improve if they’re data-driven. It doesn’t matter if you’re just tracking 2-3 HR metrics using your currently available tools, but start small and build those up over time.
What are the Types of Employee Data Collection Small Companies Should Prioritize?
Basic HR Data through an Employee Self Service Portal
Data entry by HR professionals takes up a lot of time and can be susceptible to human error. The basic HR data beyond name, designation and reporting manager can be filled by employees themselves. Fields can include gender, emergency contact, blood group, allergies, preferred pronouns and others. Employees can use an Employee Self Service portal for editing many fields.
Attendance Data
What is the first HR process to be standardized in any company? Attendance, without fail, is always the first.
It is integral to track how many employees are coming in for work each day and how many are taking time off. It is often tracked first through Excel or Google Sheets and then done using a dedicated attendance tracking system.
But irrespective of the way it is tracked, attendance data can help companies learn about their workforce, employee satisfaction and even future attrition.
Time Tracking Data
Time tracking data is important to figure out when employees punch in and out. This is certainly useful for calculating payroll but can be closely interlinked with productivity metrics too.
Employee Engagement Data
When a company is smaller, the cost of attrition feels a lot worse than that in a larger company. That’s when HR begins to look at ways to engage employees and build relationships that tie the employee to the company. The initiatives may range from pulse surveys to eNPS and they’re important to improve retention in the company.
Employee engagement can be improved using this survey data to create policies.
Digital Exhaust
The Harvard Business Review coined the term “digital exhaust”, for all the everyday digital activity done by employees. They believe that every email, message, posts on in-formal threads and project assignments should be tracked. Using these touchpoints of employee data, informal organizational networks and relationships can be tracked.
Although this does walk into the murky territory of big data, HR can do exploratory data dives into data from small teams to build these organizational charts.
9 Powerful Ways HR can use Employee Data
#1 Use Case for Employee Data: Blinded ATSs to Recruit Diverse Talent
We’ve spoken about this in a previous article about innovation opportunities in legacy HR processes. An HR tool that can help rid the screening process of implicit biases is blind recruitment technology.
These solutions redact age, gender, race, ethnicity, education and other factors in the resume screening and interviewing process. It shifts the focus from implicit biases and recruiter “gut feels” to focus only on data-based recruitment. There is an expansion of the hiring pool due to the focus on skills and job experience.
Using blind recruitment technology to strip resumes to data points has been called taking the “human” out of human resources. But if it helps build more diverse teams, we believe that it’s a risk worth taking.
#2 Use Case for Employee Data: Effective Onboarding with Basic Employee Data
A number of studies by Deloitte and the Harvard Business Review have made a connection between onboarding and workforce productivity and engagement. Clearly, it is a very important aspect of the new hire process that can directly impact the bottom line of the company.
So how can we make onboarding data-driven?
To begin with, every single new hire has jumped through the hoops of documentation and access on the first day in every organization. HR can personalize the onboarding process in many ways using just basic employee data:
- Interest-Based Buddy System: During the hiring process, the employee may have filled in details regarding their interest and hobbies. HR can assign a buddy with similar interests so that the current employee is able to build a relationship with the new hire quickly.
- Skill Mapping: By mapping the skills of the new hire to the job description, HR can zero on the areas where they may need additional training. During the onboarding process itself, they can lay out and begin training to equip the employee with all relevant resources for success.
- 1:1 Meetings: It is regular for new hires to have 1:1 meetings with reporting managers and even team members. But using data available to them HR can also set up 1:1s with other key stakeholders whom the new hire may need to coordinate with.
These are just some of the ways that onboarding can be personalized for new hires. Let us know if you have any other ideas.
#3 Use Case for Employee Data: Understanding what Benefits/Incentives can Attract High Performers
Recruitment data can be mined in a number of ways, but with such huge volumes of data, small companies should prioritize and create a plan of action before diving in.
Some ways recruitment data can be used is to figure out how to attract and retain talent are the following:
- Out of the employees who left the organization, zero in on why they left. Exit interviews may not always paint a complete picture. You can do this by analysing their compensation, incentive structure, where they’ve joined next using LinkedIn and a small survey to team members. Often, the cause of attrition can be better compensation and perks offered by competitors. If that is the case, try and research how compensation packages can be improved. This will have a direct impact on attrition rates.
- For the employees who have been at the company for more than a year or two, conduct stay interviews. Analyze how their experience was different from that of those who left and double down on that. Additionally, also ask them how the company can incentivize them to do better and try to build out incentive structures for all roles.
#4 Use Case for Employee Data: Track Failed Starters in the Company
Failed starters are employees who leave the organization in less than 12 months. They are a huge drain on resources and are unlikely to be ambassadors for the organization.
By tracking which teams had more of these failed starters and breaking down attrition rates to team-wise figures HR can zero in on the teams that need help. They can then figure out why the new hires left, the best recruitment channels with the lowest rate of failed starters and training opportunities for managers for improved retention.
Although this may seem very simple, the fact remains that high attrition rates are one of the scariest metrics for any HR. More so, for one from a small company who can’t afford to hire over and over again.
#5 Use Case for Employee Data: Time Off Data to Predict Staffing Needs
Time off is an integral component of any benefits package that a company can offer employees. But the utilization can indicate a lot about how employees may be faring and it is the job of HR to interpret vacation data correctly.
For example, a disengaged employee looking for a job switch may be over-utilizing leaves. In that case, HR should begin looking for replacements or try and improve employee engagement.
On the other hand, under-utilization could indicate that the employee is inching closer to burnout. It may be due to factors like excessive work pressure, an implied understanding that taking leaves is frowned upon and many others.
Using a tool like AttendanceBot for vacation tracking allows HR to view these reports visually and get actionable insights easily.
#6 Use Case for Employee Data: Attendance Data for Predicting Employee Performance
Although unlimited leave policies exist, every company pays attention to attendance data. Simply because it isn’t possible for employees to work at their full potential with excessive absenteeism.
By taking frequent leaves, irrespective of their duration, employees risk derailing important projects that can lead to reduced productivity.
That doesn’t mean that employees shouldn’t take time off at all, but if they’re taking multiple weeks off in a year, there may be a problem that HR needs to address.
Of course, this is excluding legitimate FMLA leaves that employees may take.
#7 Use Case for Employee Data: Optimization of HR costs to impact the bottom line
With the business world thrown into the deep end since 2020, it has become important for HR to reiterate its importance. It isn’t enough to just focus on HR metrics like bringing down attrition rates and absenteeism while improving employee engagement.
HR needs to contribute to the company bottom line by impacting performance and financials.
A few ways are:
- Decreasing the benefits cost by analysing recruitment data and seeing that employees may be seeking non-monetary benefits
- Focusing on personalization of training and development to improve employee performance tangibly
- Measuring the effectiveness of HR initiatives versus the cost of deployment
These are just some ways we can think of when we think of how HR costs can be optimized. Do you have any other suggestions?
#8 Use Case for Employee Data: Identifying Influencers by Relationship Mapping
Not going to lie, this one is going to get a little complicated.
Organizational hierarchies function in the way that there are C-Suite executives, managers and then individual contributors. There can be multiple levels of management but that’s how hierarchies look.
But influence doesn’t work in the same way. Research by the Harvard Business Review and many other reputed sources has shown that employees aren’t always swayed by company leadership. Rather, it’s people who they interact with in a more informal setting that may influence their decisions.
Relationship mapping can unearth these “influencers”. HR should bring them on board before announcing any major decisions.
Influencers can be of two kinds here:
- By Popular Vote: Finding these influencers is incredibly simple. All you need to do is ask employees in a survey who they think are the most influential employees in their eyes and why. Aggregating should data create a pretty accurate informal relationship map.
- Personal Influencers: Although the method above is laughably simple, HBR thinks that this isn’t the best way to do influence based relationship mapping. They have proven that employees cited as influential by a large number of colleagues were not always the most influential. Rather, the strongest influencers are those who have very strong connections with others, even if it is only very few people. These strong connections will have strong connections with other people and help ideas spread further.They take into account the quality of influence and you should too while relationship mapping. So asking employees who their confidantes are and then building out relationship maps is probably a more effective way.
#9 Use Case for Employee Data: Succession Planning
Customer-facing companies often throw around a very interesting fact. Acquiring new customers costs at least two times more than retaining existing ones.
The same holds true for employee retention. It is very important to hold on to loyal employees who perform well.
While compensation, incentives and relationship building are all incredibly important we also need to be caring for their career trajectory. That’s where succession planning comes into play.
Once you’ve zeroed in on high performing influencers who want to build a future within the company, you need to create a path to the top.
How you use data to retain and take these employees to the next level is the true test of HR.
What are the best practices for collecting employee data?
The How, What and Why
Employees are willing to share more data with companies to improve the personalization of HR services. But employers need to explain how they’ll be taking the data they need, what they’ll do with it and why they need it.
Make sure that you’re able to convey factual and jargon-free information to employees while also allowing them to review data when they need to.
Lock and Key
If you have data with you, you need to have a plan to protect it. Try to use platforms that keep sensitive information multiple approvals based so that employees are confident that co-workers aren’t able to view their data.
Use Data to Elevate, Not Penalize
Digital determinism is the belief that technology will come to define social structures, culture and experiences. With data-driven HR, employees can be fearful of the elimination of the human aspect of HR. Firing an employee should never be the reasons for data deep dives.
For example, using video footage from the office to improve safety and provide more frequent breaks for employees is in their best interests. But if a company uses this same technology to track who spends the most time in the office and tie appraisals to the data it is being misused.
Data is Dynamic
All data is dynamic and needs to be updated periodically to remain relevant. HR should steer clear of a “one and done” approach to employee data.
Limitations of Rudimentary People Analytics using Employee Data
Although these are all great initiatives to begin a data-driven approach to HR for small companies. There are still chances that bias may creep into the process and make HRs look at the data selectively to come to their own conclusions.
We need to ensure that there are multiple eyes watching data collection and analysis methods to try and eliminate any chance of bias creeping in.
Do let us know how you use employee data for predictive workforce analytics in your organization by reaching out to us @HarmonizeHQ.
