People analytics is evolving – and gaining momentum. As recognition of its potential power, it is finding its way into general HR-speak and, importantly, capturing the attention of the boardroom. This isn’t driven by a shift in the analytical techniques, but rather the immense proliferation of data about ‘how work happens’.
We’re witnessing an explosion in the volume of data available. Our workplaces now use more digital tools than ever to support our work, which means we are constantly generating data about how we work.
Such data is passive data – and it’s changing our understanding of organisational dynamics and paving the way for more informed decision making.
At its core, people analytics is about leveraging data sources to gain a holistic perspective on how work happens, and how it relates to business outcomes. It’s about data collection on a very large scale and it offers a unique perspective that even the most astute individual or team cannot achieve alone.
Take a company with 10,000 employees: how can any single person accurately gauge what is happening across that organisation, identify relevant trends, or determine what truly impacts performance? The sheer scale makes it impossible.
This is where people analytics comes into its own, providing quantitative insights into what is happening, and showing the relationships between data points. It means that people across the company can make informed decisions around the likely impact of any change they might make.
HR professionals are familiar with the traditional data they can access readily from within their HR systems. They can quickly find out who is located where, who is a member of which team, the length of tenure, their working hours, and all the other demographic data collected. The game-changer is the passive, behavioural data; information collected automatically through digital interactions, requiring no active input from employees: sources such as email usage patterns, chat meetings and other digital footprints left during everyday working activities.
While all data might be useful – and its invaluable to have access to multiple data sources – it’s crucial to ensure that the information collected is both robust and reliable.
The beauty and value of passive data lies in its ability to offer insights into, for example, collaboration patterns, time allocation and other aspects of work life.
And then there is survey data: active data obtained from people taking an action, be it giving a response or an opinion, or sharing a perception. Some may be quantitative, others qualitative.
While all data might be useful – and its invaluable to have access to multiple data sources – it’s crucial to ensure that the information collected is both robust and reliable. More importantly, this wealth of data only becomes truly meaningful when combined with the thorough contextual knowledge of the organisation and what it is trying to achieve.
Regardless of the amount of information collected or the sophistication of the analytical algorithms employed, without proper context, the data remains abstract and ineffective. It is the combination of contextual understanding and comprehensive data that tells us how work happens.
While the use of passive data is becoming more widely used and accepted, there is a health warning running alongside.
We also need to ask the right questions and focus on the right area – and this requires skill and expertise. Decisions based on poor metrics or an incorrect focus may mean that an intervention is less effective.
Without the experience of analysing this kind of data, the sheer volume can be overwhelming and it can be difficult to discern its meaning, utility or validity. There can be a lack of sophistication and understanding around how best to interrogate data sources and, while simple methods can be acceptable in the case of certain analysis, we need the understanding and confidence to know when a more sophisticated analysis is required.
There is also the fundamental challenge of where, within an organisation, this analysis sits, and how those responsible interact with the rest of the business.
We also need to ask the right questions and focus on the right area – and this requires skill and expertise. Decisions based on poor metrics or an incorrect focus may mean that an intervention is less effective. Take the example of a team whose members seem to be overburdened with communication. A training programme might help them better manage their time. But what if the bigger problem is not about communication but about working within silos? What's the opportunity cost of an intervention that doesn’t tackle the real issue?
It is not enough to ask a question – however robust – to measure something and to obtain a score. You need to understand the result and know that the analysis is appropriate and valid. And, if you don’t have the knowledge, there’s a need to learn more – and partner with those who do have the experience in data analysis.
Understanding the power of data and recognising the value of people analytics, typically requires a culture shift.
It requires the board and senior team to develop their own deep understanding of what the technology can do and to build these analytics into their thinking and planning.
They need to start to ask the questions. While the analytics can be useful in measuring the impact of a decision already made, it is far more valuable to access and combine the data to properly plan or to test out options in order to really improve the performance of the business.
While there might be some geographical differences in the embracing of data and people analytics, the real difference can be seen between industry or in-house department or function rather than region. That is, companies in the finance sector in the US are more similar in their use of analytics to a finance company in Japan than to a manufacturing company in the US.
This is no doubt because some industries – and departments/functions within an organisation – have access to more quantitative data or set short-term KPIs (and that makes it easier to do more advanced and faster analysis). As an example, it is relatively easy to relate behavioural data to sales figures for salespeople with high volume sales. It is easy to see how a change in one area impacts another. Similarly, for departments such as marketing which has embraced data analytics for many years, a high volume of data is available and a higher level of data maturity and acceptance is evident. Other professions including many of those within HR might not yet be fully confident at their own use of analytics.
Data use tends to examine data from the short-term. But when managing a firm, the timescale is far longer. And that's where things tend to get stuck: not everything is tightly coupled as cause and effect.
In our experience, while there might be more data available and faster analysis speeds, no one sector, department/function or named organisation could be classified as ‘advanced’ in people analytics.
One industry, though, does stand out as truly embracing the power of data. The nature of baseball is such that its data can be decomposed down to single individuals. Once the behaviours of an individual are quantified, the player can join any team, and their performance can be accurately predicted.
Basketball is not like that; it is a team sport. While much individual behaviour can be quantifiable, the exact effect of one player on the game will depend on the other team players: it's not just about an individual. It's a very fluid team sport.
People analytics will move into the area of investor insight. Boards of directors and investors are already starting to use people analytics to evaluate the future prospects of firms.
We already know that increased diversity leads to a workforce performing better. What of key talent, flight risk, or weak succession plans? For investors, this should be a critical question to ask – and to have answered reliably.
These are knowable things.
Such questions will be the impetus of driving much faster change and a more robust uptake of people analytics within organisations. It will no longer be ‘nice to have’ to improve performance, but an imperative, with the CEO needing to be able to calculate the metrics that the board asks of them.
All else being equal, if there are two companies with the same profit margin and same amount of profit, and one of them cannot provide information on how the company is being managed, it raises real concerns about the future prospect of the business.
That's what people analytics does. And businesses should probably be prepared for that.
The surge in passive data is changing people analytics. Those organisations that get onboard with people analytics will reap the rewards. However, organisations and HR leaders need to educate themselves on what is possible and what to be aware of. They can look to academia and seek out research, learn more about the technology: what is possible and how to rigorously vet the tools you use. They can audit the data already available – and be prepared find out that it is more than they thought possible. They can start to have meaningful conversations in-house about the possibilities offered and introduce smaller projects to build organisational muscle in using the data.
Let’s move to a place in which we start to use analytics not only to measure the impact of a decision already made, but to influence plans and strategies.