The Importance of Data Privacy: Managing Private Information with Integrity
This article is part of our ongoing series discussing Our response to the Gartner HR Toolkit. Scroll to the bottom of the page to find links to previous articles and the downloadable eBook.
As Gartner notes, there is an intersection between employee well-being and the explosion of HR Tech post-Covid. Tech is connecting the organisation with remote employees. This also creates a lot of data and privacy concerns.?
There are two key issues here that are important to explore.
There should be transparency over the data collected. Furthermore, a clear boundary should be established between what is acceptable to collect and store and what is not. In short, a company needs to give a statement of integrity. Within this statement, it should be stated what is collected and why and what won’t be collected and why.?
Some uniquely human data points can be gathered on a person’s character. The opportunities offered by this data include essential concepts such as personalisation and equity.
Observing the complexities of a person enables us to offer educational and career advancement opportunities. This gives us a better comprehension of the person's abilities.
This data presents a threat. It could be manipulated or used for unintended purposes. This could have serious consequences.?
Using data more anonymously can help achieve desired results. This gives the learner control over which personal insights are shared. Here is how we achieve that at Entelechy .
Firstly, in creating data points in Entelechy's tech solution, the employee inputs quantitative and qualitative data. The data offered in the numbers allow for a high-level employee profile that can prompt a tremendous one-to-one conversation with individuals. The quantitative data also enables an organisation to create heat maps of talent and deploy L&D strategies and succession plans effectively. We publish materials highlighting how the numbers can be used in organisational storytelling to aid transparency.??
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Secondly, we understand the potential for misuse of the qualitative data inputted needs to be lowered. Encouraging learners to reflect freely and to input honest assessments of themselves is crucial to the success of our methodology.
So, we set a boundary here. We have stated that qualitative data inputted to our technology will not be shared with the enterprise. Unless the individual decides to share it, the data will remain confidential.
The process for sharing any qualitative data is an active choice at the point of sharing. We cannot share whatever we like without a specific agreement statement. In other words, there is no generic agreement that allows us to do so.
If there is an option to share these small moments of personal reflection, the learner actively makes it at the relevant point.?
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The integrity of any organisation is founded on how they treat the people within its ecosystem. We uphold our integrity by being transparent about the design of the data tool available to the enterprise. We make sure to communicate this to all stakeholders.
Our integrity limits the data we can share. Express permission must be granted each time.?
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A world that prioritises a human workforce and uses tech tools to increase a sense of belonging and connection is good – if this integrity is always front of mind.?
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Key points:?
Download our ebook?to find more about the 9 components of an HR toolkit.
Find here the previous parts of this article series:
Author:?Racheal Smith FLPI FRSA?- Head of Learning at Entelechy Academy