Poor data management and inconsistent data leads to false conclusions, hampers compliance and demotivates employees. This is just the tip of the iceberg for HR teams dealing with data-management wanting data quality and structured data to not waste time to make this raw data actionable.
Did your new learning and development tool your company invested in, failed to plug business-critical skills gaps? The holistic performance management software you were relying on to standardize performance reviews did not return the in-depth promotability insights you were hoping for? Or maybe you’re just fed up with performing spreadsheet gymnastics as you move information from one application to another?
Beware. You could have a case of disparate data.
Disparate data — data that is inaccurate, incomplete or inconsistent across systems — hampers HR teams in the extreme. In fact, it can be difficult to wrap your head around its impact:
Worldwide, companies feel that 26% of their data is unstructured.
Subpar data costs the US economy a staggering $3 trillion annually; at the company level, it costs any given business 12-15 percent of its annual revenues
Just 4% of HR professionals have complete faith in the accuracy of their people dataset to make decisions.
Intuitively, good HR tech systems should mitigate these issues of having a rational-database. Yet, the rise in HR tech spending has actually had the opposite effect – leaving teams with a multitude of new data from various sources and systems that don’t talk to each other. When related data is entered into separate silos, there’s a very real risk your non-matching systems will misrepresent reality with false forecasting. This sets off the types of data across your processes, reducing your impact and sapping your productivity.
In this article, we look at six areas where inconsistent data-sets can cause a real headache for HR professionals, and the simple step you can take to clean and unify your data to finally have control of your data flow. This will not only increase the quality of data but will automate most actions in your workflows.
#1. Payroll and Accruals
Payroll is one of those functions that no one ever comments on when things are going right. However, Imagine the frustration and financial difficulty an employee suffers if they fail to get their due compensation. Imagine also if an employee needs access to vacation and other accrued benefits, and then is denied just because of a lack of control in business data.
If you can’t get payroll right, nothing else matters. Mistakes erode the trust employees have in your organization to such an extent that, after one payroll error, one-fourth (24%) of your people will look for another job. After two payroll errors, almost half your employers could be sending out their resumes. Then, when pay issues get out on social media and show up on your Glassdoor ratings, the reputational damage can be devastating as everyone would have accessed all the mistakes and taking them into consideration towards their job requirements.
From a bigger-picture perspective, data errors such as misclassifying employees, misstating leave categories, miscalculating overtime and mis-logging hours will bleed your company resources and throw your budgets out of focus. This is no minor issue, since it gives senior leaders an incomplete picture of operational performance.
This is where cloud data comes into play. As-a-service platforms can get rid of the redundant data and lets you focus to retrieve the advanced data that actually helps your company make rapid decisions. Through this database-management you can retrieve all your information from one platform. This is not only to retrieve information fast but this comes to help into:
1. Expanding internationally
2. Mergers & Acquisition
3. Legacy Modernization
#2: Learning and Development
In the race to stand out as a preferred employer, a high-level commitment to learning and development is key. Quality L&D programs not only fill the skill gaps relevant to your business objectives, they allow individual employees to grow and excel in their position. This can help to create a people-centric working culture to attract and keep the best talent.
Virtualization is also something companies are now implementing to facilitate the learning process and be able to master data to have a better access to the employees weaknesses and strengths. This will subsequently affect the performance management as well.
However, without consistent data, HR teams can struggle to measure the impact of their L&D programs. This makes it much harder to prove the return on investment and secure buy-in for future initiatives. It also risks turning L&D into a bureaucratic, box-checking exercise where effectiveness is measured by attendance rather than the value it delivers.
More effective ways to inform L&D can include looking at:
Productivity metrics: has productivity gone up after an L&D intervention?
Before-and-after assessment scores: How did employees perform on a test or task before the training and after it? Are there still areas to focus on?
Observation data: has there been a noticeable shift in behavior amongst employees after completing training?
Retention: Are employees sticking with the learning programs and coming back to learn more?
The reality is that attendance numbers and feedback forms – so-called ‘happy sheets’ – can only tell you so much. You need joined up and consistent data to help measure the effects of business decisions and take only the relevant, trusted data into consideration.
#3: Performance Management
Performance management is challenging to get right and very damaging without structured data, correct visualization of the problem and correct data-processing. Employees are smart: they know when managers are making promotion decisions based on their own biased feelings, and they quickly lose faith in performance review systems that claim to be objective when they seem to not be rational or coming from the incorrect data-collection.
What adds the fairness factor to performance management? It’s data – and specifically, current and consistent data that is brought together from all relevant data analysis , such as:
Job scope and specification documents
KPIs and individual performance targets
Actual progress against those goals
Overall performance data for the wider company, department or team
Feedback from various sources and over a period of time
Past appraisal reports
In the best performance management systems, managers will operate from a single source of truth without constant data migration. In this way, digital data will be more accessible to analyze and connect to each individual instantly. That way, all employees understand the company’s overall performance and how they contributed to it with ease. This is critical to showing employees you care about their growth and will act fairly in supporting their performance.
#4: Attrition and Retention
Employee turnover impacts businesses in many ways, most of them negatively. For starters, it adds costs, such as the time and resources required to replace staff members and onboard new employees. It also imposes softer costs, such as reduced morale and a ‘brain drain’ as top performers leave to pursue other opportunities.
As an HR team that is tasked with managing attrition, you need to know who is leaving, when and why, so you can see how your turnover rate compares to industry benchmarks and how it changes over time. Then if the rate is high or climbing, you can identify root causes and intervene.
Quality data is foundational to getting the story behind departures, and you likely will need to combine multiple data sources for better HR analytics. For example:
What’s the average length of employment for departing employees?
What’s the turnover rate by department or manager?
What’s the rate for low performers? For star performers?
What is the new hire retention rate?
As a business, how do you score on employee happiness/ satisfaction?
Because employee turnover is a lagging indicator — that is, you only become aware of the problem after the employee has decided to leave — you need to carefully track the data to identify flight risks. HR professionals who have joined-up data at their fingertips can remain alert to problems and create solutions to retain their most valuable contributors.
Compliance doesn’t just happen in organizations and, as a human resources professional, you likely spend a lot of time ensuring that your hiring and workplace practices comply with laws on pay, benefits, layoffs, discrimination, medical leave, family leave, drug screens, notice periods, immigration, confidentiality, safety, and unionized staff. This can be cluttering and the retrieval of this data can be time consuming. High quality data can be inside this data lake where its business value is hidden to the point where business-intelligence is no longer there.
Too many data sources with too little consistency is a nightmare for compliance. Under the Fair Labor Standards Act, for example, wrongfully classifying an employee as exempt, who is, in fact, nonexempt, can leave the company liable for all unpaid overtime owed to that employee, as well as penalties, interest and audits by the Department of Labor. These issues directly impact the bottom line.
#6: Diversity, Equity and Inclusion
Business and HR leaders alike are being asked by their employees, customers and stakeholders to commit to increasing diversity at all levels. This has led to a noticeable ramping up of DEI resources which can only be a good thing. However, no matter how much you invest in DEI, improvement initiatives will have only minimal impact unless they are backed with enough data to identify problems, kick start solutions and measure progress.
But it’s not just about collecting demographic datasets from your employees. DEI issues are systemic in nature and directly tied to one another. This means you have to track DEI metrics across all your processes – sourcing, hiring, promotion, engagement, leadership, pay equity, participation, work allocation and discrimination complaints.
This is one area where the transparency and integrity of your data is critical. Without the correct identity fields, synced and unified between systems, you are going to have a hard time unlocking insights into possible biases. You essentially will be flying blind, which undermines your good intentions around DEI.
Bringing it all together
For HR teams, data cleaning is a major factor that HR is now a key-value to have to have the best data. But, how do you get the accuracy your team needs for data-driven HR? The easiest solution is to invest in a data unification platform that connects and synchronizes all your HR software into one centralized information system. These solutions eliminate data silos and cleans all your data up by removing errors, inconsistencies, duplication and redundancies. The result is one unified and accurate data source, all in one place.
Long story short: good employee experiences require good data. The best companies are using data unification platforms to bring good data into one central HR dashboard giving HR professionals the real-time insights they need to maximize the potential of their people and create a culture of openness and growth.
Ready to see what unified data can do for you? Book a demo with PeopleSpheres and see what a management platform where you can consolidate your data and have all your software in a single platform.