Written and published by Peter Romero, People Analytics Lead at University of Cambridge, Psychometrics Centre on April 22, 2021
From Peter Romero and Andreas Kyprianou
Making predictions is very often a fool’s errand. FE Smith, one of the most outspoken British politicians of the Churchill government in the 1930’s wrote a book about what the world would look like by 2030. Some of his most ‘interesting’ predictions included a canal cut from the Mediterranean to Sahara, as well as the continuation of the British Empire with the capital moving from London to Canada or Australia!
However, not all predictions need to be as obscure as this. Based on the trends we’ve been observing in the People Analytics world, we feel quite confident when saying that the future of People Analytics is not as part of Human Resources (HR), but instead will become a critical part of overall organisational analytics. Let us make our case.
Talent Acquisition paradigm
What do we know already? With the advent of the fourth industrial revolution, AI will replace more and more jobs that are still qualitative in nature. Replacing or automating positions or entire functions that are off-product is a number one priority to increase margins for revenue and cost-conscious corporations. Classical HR in its ‘wrapper role’ for administrative and operational tasks, compensation and benefits, or employee relations is clearly a perfect target for this. On the other hand, strategic HR components like corporate culture, leadership development and People Analytics should be able to avoid this fate, by thriving outside the HR bubble.
In fact, before talking about People Analytics, it may be useful to view another strategic HR function as a paradigm – Talent Acquisition. Given Talent Acquisition’s key strategic position within the organization, its early embrace of analytics and technology and its proactive, rather external than the traditional internal focus of HR, there’s been a growing tension between Talent Acquisition and traditional HR. Some thought leaders (e.g., Sullivan, 2019) have been calling to transition Talent Acquisition from an overhead role into a business function with more direct accountability- serving a business purpose by hiring exceptional performers who will immediately boost the business results of the teams that they join.
It has been clear for a while that HR and Talent Acquisition have not been walking the same path on strategic, tactical, and talent-related issues. The overall maturity of HR functions did not, and could not, evolve at the same pace as that of Talent Acquisition. For example, modern recruiting practices require a very agile approach that accounts for a constant shift in talent supply, economic changes, and internal shift of priorities. And, it needs to work incredibly fast to avoid losing great candidates to an array of competitors. This goes against the traditional HR model and mind-set, which is based on consistency and structured regular engagement surveys and performance reviews. Unlike HR, Talent Acquisition is a field that can demonstrate a clear business impact of each successful and unsuccessful hire to the top management teams. Hence, the modern Talent Acquisition function resembles more of a powerful hybrid of the best of Marketing (company brand), Sales (candidate sourcing) and Finance (workforce planning), than HR.
People Analytics paradigm
Applying the insights from this paradigm to People Analytics, the resemblances are striking. Good People Analytics functions are forward looking, pacy and innovative, bring something that is more ‘sexy’ to the organisation, produce insights that are highly important to the top management team, and very often, are staffed with quantitative experts from analytical departments. We predict that in the short term, a comparable tension will arise similar to the Talent Acquisition one detailed above, leading to an eventual split from central HR.
However, there is a key difference. Unlike Talent Acquisition, which is pretty unique in what it does, most corporations already have analytics or Business Intelligence (BI) departments, which are in their set-up and mission very close to People Analytics, and their areas of expertise overlap in many cases. Hence, there is a clear case for predicting that in many cases, BI departments will merge with People Analytics departments, or rather swallow those and create a range of experts in quantitative organisational analytics. This makes a lot of sense on a number of levels:
- On a strategic level, all corporate analytics must be geared towards informing strategic decision making and align fully to business vision and mission. Achieving this is much easier from a centralised analytics team, rather than from functional stand-alone teams. People Analytics can often be guilty to take on a one-sided, HR-centric perspective- turnover analytics, or engagement survey design and analysis may be important in their own right but if these don’t help the business solve their big challenges, they end up being HR-centric and mostly useless.
- On a tactical level, best practices between those functions can be exchanged, and ground-truth from HR can be extracted, which further accelerates the automation of HR processes. It also means that multiple skills from multiple disciplines can be sourced and integrated from, which broadens the talent pool, and provides much needed access to the skills which have traditionally been reticent to gravitate towards HR (e.g. statistical skills).
- Also tactically, the blend of information and data that is so important for successful analytics projects can be achieved much faster in a centralised team, where HR, Finance, Sales, or Marketing professionals can come together in agile teams without the usual barriers that accompany data sharing. True analytics projects must combine multiple fields and perspectives to get to true insights.
- Finally, technological advances have meant that systems that were historically limited to each function with its own reporting department, is being disrupted by cross-functional enterprise systems and powerful data warehouses and data lakes where data can be stored and blended. This has laid the foundations for true multi-disciplinary, end-to-end analytics.
So beyond the stereotypical, and frankly derogatory, ‘learn to code’, what can HR professionals do, to own this unstoppable trend, and use it for their advantage? Easy: learn from their past mistakes, anticipate future trends, and prepare for a future that could either be completely HR-free, or the golden age of HR. HR professionals should embrace these changes and become leaders in Quantitative Organisational Behaviour, who are able to lead and advise dedicated experts in various sub-fields like programming, statistics, data science, and machine learning, across multiple functions. People Analytics professionals should seek their place within central analytics and BI teams as soon as possible, to empower them for this future that is about to come.
Some practical implications for People Analytics professionals may include:
- On a strategic level, you need to work hard to understand the bigger corporate picture in terms of mission and vision, and this must inform your focus in everything you do. But choose your battles wisely, since you want to avoid becoming the reporting function, being placed into the Shared Service Centre, on all costs. This means you have to practice the art of diplomatically refusing projects and requests, and focus on fewer but better projects.
- On a tactical level, you need to start using more than people data now – both by using data from outside the organisation like national labour statistics, to better understand exogenous influences and bigger trends, and by using ‘novel’ data from inside the organisation, for example by learning and interacting with BI. That will also mean to get in deep touch with other Analytics teams and Corporate Strategy, and that you should merge your approach with theirs, giving it an unique spin from Quantitative Organisational Behaviour, allowing for many wow-effects, which will bring you many new friends from all over your corporations.
- Finally, your mind-set needs to be ‘hungry’ and eager to push the status quo. You must never become complacent with where you are, nor with where central BI is, but try to influence analytics projects from the get-go. This also means that talent-wise, you need to go for the best. You have a ‘sexy’ product; People Analytics is a hot field right now, much more interesting for top candidates than Controlling or Marketing (no offence to anyone in those fields!), and its influence inside and outside the organisation can be much bigger, if done right. Seek out only the best, and gear them towards your inevitable journey towards a life in central BI functions.
Short Check-List for you to understand where you are:
- Do you report to the CHRO?
- Do you know about big ongoing company wide projects that could use a People Analytics lens?
- Do you already use external data – from outside the organisation and from other departments?
- Do you have strong ties with central Analytics/ BI and Corporate Strategy?
- Do you understand and can discuss the attractiveness of your function?
- Do you understand the skills needed to staff your People Analytics functions effectively, and where to find those skills?
Short To-Do List for you to understand what to do next:
- Make a stakeholder map of the top management team and all senior deciders; understand their connections and priorities
- Make a list of all ongoing strategic projects and initiatives, and write down how you could help them. Incorporate data and analytical methods in that list.
- List up all external data you use, and what sources it comes from. Find new sources and new techniques that could incorporate those.
- Make new friends with BI and Corporate Strategy. Find commonalities and how you can help each other.
- Write down both an elevator pitch for and a love letter to your function. Make it as positive and emotional as possible. Write down why it is the best function in the world. Then, use this to convey your message. If people are not enchanted, go back to the drawing board.
- Make a list of relevant universities and subjects for your field. That could be econometrics, statistics, maths, engineering, data science, computational social sciences, or psychometrics. Next, find the leading people, read their papers, and find ways to cooperate with them, or get early access to their students to sell the potential people analytics journey.