People Analytics and the Strategic Impact of HR

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October

2021

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By Lennart Dany

HR has long been a function viewed by the rest of the organization, as operational or supportive of the core business. Due to this perspective, HR has never been able to claim their seat at the table. After all, the title CHRO is still rare to see and if so it hardly ever has the same weight as titles like CFO, CEO, or even CTO.

Now the reason for this perspective on HR can, in part, be explained by the history of truly operational work, mainly executed by the HR department. Think of the traditional corporation, using a ticket system for handling all sorts of requests, ranging from office supplies to relocation attempts of staff members. While these types of requests are certainly important to be handled, one may understand the stigma that has become associated with HR over the years.

However, it is now this very stigma, which is holding HR back. Today many HR organizations are already putting much of their efforts into becoming more data-driven. Now, what does becoming data-driven really mean? You can essentially break their journey down into three stages:

Stage 1: Data assembly and cleaning

Stage 2: Operational reporting

Stage 3: Predictive & Prescriptive Anlaytics

Let’s break them all down. In stage one, the HR organization has devised a team or multiple teams to enable data-driven decision-making. While the specific objectives will be different and specific for each organization, the first step to making any decision based on data is gathering it. For many large corporates, this is the easy part. Data has been collected on a least a range of basic metrics for years – e.g. absence rates, attrition, employee turnover, and so on. However, usually, the data is not yet centralized and far from being clean. In other words, central databases have to be created for easy access, while the data entering them must first be check for erroneous entries, outliers, and the like. While this can be quite an effort in itself, it is only in the next stage that the data will be used for anything.

In stage 2, data from what we refer to here as a central database is finally used for reporting. Usually, the goal here is to get some of the most important HR metrics running on any type of automated dashboard that can be checked regularly by senior management. Usually, building such a dashboard will consume the majority of the HR analytic’s teams time. Nonetheless, once in place, the completion of this stage can yield valuable insights for senior management and if implemented correctly and it could already promise a net positive ROI on any prior investment in hardware, software or staff.

Finally, in stage 3 the HR analytics team has persevered to arrive at a point that allows the team to exercise their profession. With time freed up from an automatically updated dashboard, fewer requests are coming in from colleagues in the HR department and if so, they can be easily handled by redirecting HR business partners and managers to the right dashboard. The void of time essentially leaves space for the analytics team to proactively apply advanced analytics to solve important business challenges. The team can build models that will predict future outcomes or prescribe actions based on the results and data fed.

While all this sounds pretty lofty, in reality, the majority of organizations are still struggling anywhere between Stage 1 and stage 2. This is where we touch back on our previous discussion on the stigma of HR. The harsh reality for many HR organizations is not a lack of effort, ambition or willingness to learn and advance. Instead, a lack of corporate sponsorship often derails HR analytics projects already in the early stages. After all, implementing data management systems, allowing data to flow globally, and building accurate dashboards cannot happen without a sound level of financial resources. Moreover, such initiatives often being of a global nature, requires global leadership to create awareness and excitement about the upcoming change. Unfortunately, in the majority, if cases HR is not supported in such a way, and in this blog post I argue that this is due to an old stigma. After all, who wants to devise larger budgets for HR than for the Finance department?


Disclaimer: The careful reader may have noticed a lack of sources in this post. The goal was to share some of my own experience work in the corporate HR landscape as a b2b sales representative for a few years. To add some additional resources, there are a few interesting articles linked below and a list of companies one can look into.


Some companies who are prime examples of doing it right that you can google:
Nestle
General Electric
Credit Suisse
Experian


Some literature:
Short list of case studies: https://www.aihr.com/blog/hr-analytics-case-studies/
What is People Analytics | HR Analytics: https://www.aihr.com/blog/people-analytics/
People Analytics in the Pandemic: https://www.aihr.com/blog/people-analytics-in-the-pandemic/

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Is Matrix Turning to Reality!? 

23

September

2021

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Lennart Dany | 23 Sep. 2020

The core idea here dates back to some of the earliest philosophers, most notably Rene Descartes. Descartes was one of the first to argue that, perhaps, the boundaries between our dreams and reality are much more interwoven than we believe them to be.  After all, it is only based on what we do know that we can judge what is normal and therefore should constitute our reality. The image added to this text is a famous early representation of this notion. There are people living in a cave, some are not the way out and others are already enjoying the sun in the outside world. Those deep down in the cave, however, are tied with rope to the cave wall. They view only the shadows thrown against the wall by some of the gatekeepers.  Descartes’s point is that the men deep down in the case will be content with their situation, not knowing what lies outside. Having only experienced the cave with its shadow all their life, they have no yearning for any other reality than their own.

The popular science-fiction movie Matrix, first released in 1999, rapidly gained a reputation for being one of the most revolutionary works at the time. Not only did the film feature some of the latest filmmaking technology, but it also addressed long-established philosophical questions in a fascinating visual representation. 

The overarching theme? Humans live in a fake reality without knowing about it. They are plugged into a computer program, which makes them believe our old world still exists, all while an alien computer species has already taken over the planet earth. Yet, humans living in these computer-generated realities feel content, do not question their reality, and live what they believe to be a normal life.

 

Okay, from a science-fiction movie to old philosophers. Why all this fuzz about fake realities? While the ideas I aim to address in this blog post are centuries old, they have never become more relevant. Today’s breakthroughs in media marketing, algorithmic computer calculation, and an ever-increasing consumption of social media pose a threat to a usually shared reality between you and the person next to you.

As algorithms become better at understanding individual consumers and computing power increases to make these tasks easier, faster, and exponentially comprehensive, our worldview is threatened to become increasingly limited. To blame is not merely digitization itself. Rather, it is the way in which today’s algorithms are designed. To explain, a short excerpt from an author far better equipped to explain the matter:

“Even though most Americans continue to describe themselves as holding balanced views, we still naturally gravitate toward certain content online. Over time, algorithms turn slight preferences into a polarized environment in which only the loudest voices and most extreme opinions on either side can break through the noise. (…) For the biggest brands in social media—think Facebook, YouTube, and Twitter—success is defined by the hours users spend engaged with the content and measured in advertising dollars our attention generates. Social media companies, therefore, rely on adaptive algorithms to assess our interests and flood us with information that will keep us scrolling. The algorithms ignore the recency and frequency of what our friends are posting and instead focus on what we “like,” “retweet,” and “share” to keep feeding content that is similar to what we’ve indicated makes us comfortable”. (Seneca, 2020)

While the goal is not to paint an evil one-sided picture of social media, perhaps we should practice a little more awareness when we choose to engage with a particular type of content. As we consume the same type of content over and over again, the algorithms become ever more effective in showing us the content we want to see. Perhaps, drawing a connection to the fairy tales of a science-fiction movie seems dramatic. On the other hand, our world has never been more polarised. Political views in the United States, as well as Europe, have been diverging in tandem with increasing online media consumption and conspiracy theories have spread like wildfire.

While this is by no means a scientific evaluation, we should all be wary and protective of our reality. Although according to Descartes, we can never be sure of what constitutes reality, we should at least be protective of a shared perception of the world. Without it, the new age of globalization and digitisation becomes prone to failures we may never anticipate, as we make our first steps into a vastly different world.

To wrap it up, you can find some solutions that have been designed to tackle this issue:

Search Engines: 

https://info.ecosia.org/privacy

https://duckduckgo.com/

https://www.startpage.com/

Video Content:

https://www.dailymotion.com/us

https://vimeo.com/

References
Seneca, C. (2020, August 17). How to Break Out of Your Social Media Echo Chamber. Wired. Retrieved September 23, 2021, from https://www.wired.com/story/facebook-twitter-echo-chamber-confirmation-bias/

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