Governance within People (HR) Analytics: insourcing or outsourcing
By Alex Hellemons
To successfully implement HR Analytics or People Analytics, governance is crucial, and you need experts in various roles within the data domain. But what are those roles exactly, and is it more practical to have them in-house (insourcing) or to outsource them to an external party (outsourcing)?
Highberg has gained a lot of experience with governance models for HR Analytics. Therefore, in this article, we will delve deeper into the various possibilities.
Collaboration with other domains within the organization
When looking for experts to handle analytical tasks, it's wise to explore other departments within your own organization. Often, there are already existing domains that work with data, such as Marketing, Finance, Sales, or Facility Management. Examine how these established domains are organized, so that your HR department can align with them now or in the future. Collaboration in this area can yield valuable synergies.
Or will your start on your own?
Connecting with existing structures can be rewarding but challenging. For instance, it can be difficult to secure time and capacity from professionals who are often already fully occupied. Therefore, it may be a choice to organize the governance of HR Analytics separately to generate more speed in the short term. The downside is that it may lead to 'reinventing the wheel'.
Is a middle ground possible?
A great option is a middle ground, where the HR department sets up its own data governance in a decentralized manner, within centrally established frameworks that apply to all domains. Think of frameworks such as which technology is used (Azure, SAP, Amazon, etc.), how data is collected, processed, and stored, and so on.
This way, each domain can develop and undertake at its own pace on topics that are opportune for them, while retaining the possibility to centralize data initiatives across different domains. This prevents more mature domains having to stand still due to domains starting with data, such as HR. Or, on the contrary, that HR remains underexposed because continuous priority is given, for example, to Finance & Sales.
Roles within an HR Data Team
Before determining which roles to fill through insourcing and which through outsourcing, we list the various roles within the HR data domain.
- HR Analytics Translator/Consultant:
- Acts as a bridge between HR, IT, and Analytics, ensuring that data-driven insights are translated into actionable HR strategies and policies. Learn more about the role of an HR translator.
- Employee Experience Specialist:
- Collects and analyzes data on employee-related topics, utilizing methods such as surveys or interviews.
- Data Scientist:
- Uses mathematical, statistical, and programming skills to explore and analyze large datasets, creating predictive models to reveal trends and patterns that can lead to business insights.
- Data Engineer:
- Responsible for designing, building, and maintaining the systems and architectures needed to collect, store, process, and analyze large amounts of data.
- BI Developer:
- Designs and implements BI software and systems, including data modeling and database structures, to transform business data into actionable insights.
- Software/System Engineer:
- Designs, develops, tests, and implements software applications and systems necessary for conducting business operations, including tools used for data analysis and processing.
The collaboration between the different roles
The image below explains the coherence and collaboration between the different roles.
Insourcing or Outsourcing? The Pros and Cons
Insourcing is when a company chooses to perform certain tasks or activities internally, within the organization. Outsourcing is when a company chooses to delegate certain tasks or activities to external parties. Both solutions have advantages and disadvantages.
Regardless of whether a decentralized or centralized data governance is chosen, insourcing these HR data analytics roles has several pros and cons:
- As an organization, you have everything in-house.
- The whole setup can be tailored to your own preferences.
- The people filling the roles are part of the internal organization and culture.
- Knowledge needs to be built entirely, which takes time and money.
- Many FTEs are required to fill all data roles, making it costly.
- There is a higher risk of setbacks.
- There is a low level of flexibility and scalability.
Outsourcing has different pros and cons:
- You purchase knowledge, which is immediately available.
- You buy hours for data roles, not FTEs.
- Limited risk of setbacks.
- More flexibility, better scalability.
- The partner must adapt to the client's structure and vice versa.
- Hired individuals are somewhat more distant from the organization because they are not part of the internal organization/culture.
Is it Outsourcing or Insourcing?
We have listed the pros and cons and now need to make the decision: are we going to outsource or insource? HR wants to demonstrate the added value of a data-driven approach quickly. Therefore, it is essential to achieve results promptly. This can be a reason to initially fill multiple roles, especially the most strategic role (Translator), externally. The purpose of this person is to identify opportunities in the short term based on input provided by, among others, the HR management team, HR colleagues, or the organization. The knowledge this person brings can expedite this process.
The Translator brings HR context, which needs to be conveyed to the Data Science team. These roles can be quite generic and, depending on the organization's (future) needs, can be filled internally or externally. The aforementioned pros and cons must be considered in this decision.
An exception is the role of Employee Experience Specialist. Unless there is someone within the company with a lot of experience in this field, it is preferable to hire an expert for this role. Asking critical questions that can lead to actionable insights is indeed a specialized skill.