Contact
Free trial
Data Management |

7 MIN

What is Data Management? Your Guide to Excel in the Future of HR

What is Data Management? Your Guide to Excel in the Future of HR
Alexandre Diard
What is Data Management? Your Guide to Excel in the Future of HR

Do you want to master data management? Then you’ve come to the right place.

Data management refers to the practices that manage data, including data processing, storage, and organization. As an HR manager, employee data management is a part of your tasks. It is essential to have efficient practices in place to ensure high data quality. With help of data management tools, administrating your HR data can be made simple.

Related articles:

- 6 Reasons to Leverage Data Integration in HR
- An Effective HR Database: A Must-Have for Enterprise HR Teams

 

Book Demo

 

Why Should You Focus on Data Management?

In a data-driven business world, data management is necessary. Your information management practices depend on your data elements, such as data model, data source, data warehousing, data architecture, and more. For example, do you have structured data or unstructured data? Your data management will depend on if you store your records in a data lake or data warehouse. No matter what, we all want to avoid disparate data as more organizations are facing bigger challenges regarding insights and data analytics. According to PwC HR Tech Survey, 39 percent of organizations reported that their biggest obstacles in relation to human capital were HR insights and data analytics.

Disparate data can pile up quickly and does often not show up until the issue is uncontrollable. This can lead to serious dysfunction within the organization, such as managers wasting time on interpreting and analyzing unclear datasets, or in some cases, drawing the wrong conclusion and making inaccurate business decisions.

To avoid the consequences of disparate data, HR management departments need to establish a functional data management system across the organization. Data integration in HR prevents disparate business data and ensures a centralized system that consolidates all your data-sets in one spot, which streamlines data discovery and management. Data integration tools bring business value in many ways:

  • Allows for the creation of data visualization and reports of all types of data

  • Increases speed and cost-savings

  • Provides truthful data

  • Improves employee experience

  • Controls data access

  • Boosts communication efforts

 

Start by Identifying the Problem: Where is Disparate Data Coming From?

Is the management software you are relying on not returning detailed reports enough for you to draw a complete conclusion? Is your learning and development tool failing to plug business-critical skills disparities? Are you wasting time on identifying inconsistencies and moving information from one application to another? If this is your situation, you are probably having a case of disparate data. HR professionals should especially look out for inconsistent data in these areas:

  • Payroll and accruals

  • Learning and development

  • Performance management

  • Attrition and retention

  • Compliance

  • Diversity, equity, and inclusion

Book Demo

 

How to Clean HR Data

Do you want to achieve data-driven HR? Start by making sure that you are meeting conditions such as proper data governance, organized data, and incorporated data into company culture and decision-making. If you are already meeting these conditions but something is missing, analyze your data. Chances are that you need to clean your data. To do so, follow these steps:

 

Identify All Your Data Sources

Start with identifying all data sources. Where is the inconsistent data coming from? Do you have a single source of truth for all your employee data or is it spread out across multiple systems? Once identified, rank your data sources based on the importance of data, which will serve as a foundation for your data strategy.

 

Know What Information You Want from Each One

If you are working with multiple data management solutions, you need to identify what information you want to get from the different data sources. For example, a payroll solution should provide you with different data than a performance management solution. Once you have established what information you want to retrieve from each system, integrate your employee data into a digital employee fileEmployee files integrate all employee data in one place, which serves as a strategic tool for HR managers and improves internal communication. With digital employee files, you can expect to enhance:

  • Employee data management efficiency

  • Access to employee data

  • Accuracy of information

 

Filter Data Outliers/Irrelevant Data

When analyzing data, it is important to filter outliers or any irrelevant data that will skew your results. The outliers or irrelevant data can affect the reports enough that you will draw inaccurate conclusions.

 

Take Care of Missing Data

Identify if you have any missing values. If you are cleaning your data in Excel, removing missing data is simply done by following these steps:

  1. Under the ‘Go to’ dialogue bow, use CTRL + G

  2. Select the ‘Special’ option, and select ‘Blanks’

  3. Click OK, and on the keyboard, press F2

If you followed these steps, you have been enabled to fill in the blanks with which value you desire by highlighting the cells with the formatter. If you want to fill in the blank cells with the same value, use CTRL + Enter.

Book Demo

 

How to Decrease Future Data Clutter

To https://blog.peoplespheres.com/en-us/create-single-source-of-truth-hr-data-3-steps once and for all, cloud-based unified management systems are recommended. Many organizations are facing challenges regarding modernizing their systems to agile and modern systems, however, it is crucial as disparate data increases the risk of misinterpreted data and inadequate business decisions. Having unified data models brings numerous values and can give you a competitive advantage through its scalability, agility, accessibility, and intuition. Having centralized data management software also allows you to simplify and automate repetitive tasks and perform advanced analytics.

To create a single source of truth for your data management platform, follow these three steps:

  1. Identify all HR data sources across the employee lifecycle

  2. Integrate HR data into an aggregated data system

  3. Set up workflows to ensure your HR data is up to date

 

Questions to Choose the Best Management System

Choosing between data management software can be complicated. There is numerous HR software on the market, and you might be wondering about the quality of each tool. How do you know which data management tool will bring you the best quality of data? The answer is that each system will bring your business a different value depending on your business needs. Analyze your HR processes to find out what type of management system you are in the need of. When trying to pick between the different systems, ask yourself these questions:

  1. Is it adaptable and customizable?

  2. Does it provide a centralized interface?

  3. Do I care if it utilizes a single system of record?

  4. Is it easily integrated?

  5. How important is data security for my organization?

  6. How customizable do I want the software to be for each employee?

  7. Is it necessary that my software can standardize business processes and build workflows?

 

PeopleSpheres: Consolidation of All Your HR Data

Are you modernizing your HR data management strategy? Are you looking for consolidated data systems for your employees? PeopleSpheres consolidate all your HR data on a unified dashboard, providing single-point access with trusted data for your employees. By providing a merged HR database, PeopleSpheres allows you to synchronize and perform data analysis of your employee information in one place. The software is integrating any quality tools that you choose, allowing for customizability and flexibility for business users. Optimize your data management process by removing tasks such as multiple data entries and complicated data sharing.

Book Demo