‘The importance of data in HRIT implementation is still too often underestimated’
The success of an HRIT implementation process depends on more than the system and the implementation specialists alone. SuccessDay recommends that you first perform an Organizational Readiness Check, which identifies whether your company already has data and process standards in place. HR data and processes are then standardized in ‘phase 0’. In this blog, Data Lead Laurent Esman explains all about the importance of a good data strategy for HRIT implementation.
According to Laurent, organizing your data management is the most important aspect of HRIT implementation. And yet, the significance of data is still often underestimated in his experience. “Data is often a far-removed entity for many organizations, especially for HR departments. It is often unclear what exactly needs to be done in this field or it is underrated. That is why it is so important to provide organizations with solid support”, explains the data specialist who has worked for SuccessDay since April 2022, based in Antwerp.
First and foremost, before embarking on HRIT implementation, it is important to start by determining the importance of the data strategy. This includes agreeing what is expected of the new system, what needs to be done to progress from the current situation to the desired one, who is responsible for what, and finally, drawing up a timeline. Of course, SuccessDay can advise and provide support by taking on specific roles in this process if there is insufficient internal capacity. A data strategy consists of the following steps:
- Determine the scope
The first step in preparing data for successful HRIT implementation is to determine the scope. This answers questions such as: Which system has been chosen? Which modules will be implemented? Which country-organizations, branches and departments are involved in the project and how many employees in total? And finally: Which data sources are currently being used and is any degree of standardization already in place? - Determine the foundation of your data
The next step is to determine the foundation of your data. This means mapping out which regions and country-organizations are involved worldwide, which branches there are, what the organogram looks like, which departments there are, which job positions are involved, whether these are full-time or part-time positions and whether there is a job catalogue. - Organize your employee data
Step three involves collecting and structuring your employee data. This includes name and address details, identity card numbers, bank account details and salary information. Information on absence and leave, recruitment, talent management and succession can also be added, depending on which modules are introduced.
Continual process
The migration of data from the source systems to a new HRIT system is a continuous process. Laurent: “Exactly which data is included is determined during the design sessions. The client usually gathers this data, but we can of course always provide assistance.” Data that is not relevant is cleaned up. “An organization can choose whether or not to transfer historical data to the new HRIT system. They often choose to start with a clean slate”, is Laurent’s experience.
The data migration takes place in the source system, or in a so-called Data Gathering Workbook (you can see this as an enormous Excel file). Alle data conversions or translations are tracked to support future iterations. The data is loaded into the new system in various cycles. In each cycle, the data is validated and if necessary refined for the next iteration.
The complete data migration is comprised of the following steps:
- Analysing data
This involves examining whether the data is available in the source system. The layout is then checked and compared with the details required in the new system. - Cleaning data
The data must be correct, consistent and usable. Any errors or corruptions are detected before loading. Laurent: “This also includes the removal of obsolete data that the organization no longer needs.” - Extracting data
The data extraction identifies the required personnel and organization details from the source systems and moves this data to a temporary location where the clean-up activities can be carried out. - Transforming data
In this step, the information is converted to the required data format and field values for the target system. The data is then validated. - Loading data
The data is then loaded into the new system using the appropriate mechanisms and tools. - Validating data
Finally, the data is validated in the new system and it is time for functional tests in the system.
Enterprise Interface Builder
A useful data migration tool at Workday is the Enterprise Interface Builder. EIBs allow users to load data and extract it in bulk from the Workday systems in order to transfer it to other places within the organization or beyond. “So, the tool loads data into Workday without you having to write complex programmes, which can be a hassle. It speeds up and facilitates the migration process”, explains Laurent.
EIBs are primarily used in tenants that are already functional, in both live and test environments. “For example, in the case of a general salary increase for a group of employees, with new compensation plans or in the transfer of vacation days from one plan to another.”
Extensive process
As you have read in this blog, transforming data is an extensive process that goes back and forth. “This is a serious business. If there’s a comma or a space in the wrong place, things will go wrong. You must have strong foundations – i.e. sound data – if you want to take full advantage of your HRIT system. Data is the most important element of a tenant. If your data is incorrect, you’ll be starting from the wrong point which makes it impossible to make good analyses or predictions.”
Laurent emphasises that close collaboration with the client and good communication are essential factors in data migrations. “Explaining what you’re doing and especially why you are doing it is key. It is also important to allocate Data Owners within the data team and to make clear agreements about who does what. A governance can help with this. Moreover, it is good to include a good division of roles in your data migration strategy.”
