This article was first published on LinkedIn on October 12, 2023
In this Q&A style memo, I reflect upon my Hacking HR Panel discussion around People Analytics, Change Management and Business Agility at this year’s Hacking HR People Analytics Summit, hosted virtually. Unfortunately I wasn’t able to join the live panel because of technical issues 🙁
Many thanks to my co-panellists Eli Hernandez, SHRM-SCP, CDP, Heather McBride-Morse, HEATHER HOLLAND, SPHR and our moderator Minola Jac –and of course El Capitan Enrique Rubio (he/him) for his awesome support and for all the hard work put in.
I’d encourage you to join the Hacking HR community – a brilliant space that champions open sharing, inclusiveness, empathy and all the good things we need in the People function today.
I’d like to begin this memo with some general observations that I see among HR practitioners today and the use of data analytics in the people function.
One prevalent thing that I see in people analytics today is that people analytics has focused mostly on employee attribute data, such as the traits of individuals like their ethnicity, gender, and work history and what is known as “state data”, such as age, education level, company tenure, value of bonuses, commute distance, days absent.
Recently though, through accessible platforms such as Microsoft Viva insights, we are starting to see more relational data which examines how people interact, identify the ones who are influential within the organisation and through such data points, I do see an uptake of employers who are starting to profile their employees using relational data – identifying who are the social butterflies, who are the lone wolves, so on and so forth. This is a very interesting development.
There’s no clear or singular answer to the question of how to measure productivity. Fundamentally, companies need to ask themselves: do outputs or inputs matter more? I believe there’s only one answer that will come from business leaders.
In my experience working with clients and also in-house, I realised that within people analytics, there is often very little focus on what we call “relational analytics” and how these are presented back to the business. Often, relational data are treated in the same way as attribute data, which I disagree with.
We report in the number of hours people work, and how many hours they spend in meetings and all that. Sometimes we succumb to blanket statements, for example, “too many meetings” break an organisation’s productivity.
I think this is a huge missed opportunity to create a meaningful data picture of the organisation comprising of the nuances. I once worked with a HR business partner who didn’t understand that in an advertising agency setting, what looks like “too many meetings” are actually brainstorming touchpoints for ideas to spark. Therefore the wrong thinking was applied to create productivity analytics that wrong-footed the organisation and set back its culture greatly.
Instead of a simple “input-output” spectrum (time and investment to complete tasks vs. value of task), we should also be measuring work satisfaction vs. customer satisfaction. This would add a completely new dimension to how we think about productivity, real world business impact and workforce planning.
During COVID-19, there was a huge focus on productivity analytics, especially time to productivity and team productivity. For too long, managers in organisations, especially in the Asia-Pacific region where I’m based, have used face time as a measure of organisational effectiveness and productivity. We operated under the notion that “as long as my worker is at work, my worker is working”.
We know that’s a fallacy. The body may be present, but the mind really doesn’t have to be. But somehow, companies are still pulling people back to the office, and many of them want us in five days a week.
The pandemic brought us the work-from-home paradigm, which companies struggled with. The key difficulty that I hear a lot from the industry, and as a people manager, is this: “How would you measure productivity when I can’t see my employees at work?”
The remote-working paradigm has come and gone, but companies continue to struggle on this front.
There’s no clear or singular answer to the question of how to measure productivity. Fundamentally, companies need to ask themselves: do outputs or inputs matter more? Given a choice, what would you prefer? I believe there’s only one answer that will come from business leaders.
This is why HR needs to bring value to the table in terms of measuring productivity. This shouldn’t just be the job of an economist or the finance team, yet the reality is that finance is often the one putting together these metrics.
Instead of a simple “input-output” spectrum (time and investment to complete tasks vs. value of task), we should also be measuring work satisfaction vs. customer satisfaction. This would add a completely new dimension to how we think about productivity, real world business impact and workforce planning.
This topic is an extremely interesting one and I might share my thoughts in detail about this in a follow up post sometime about how this could translate across to real-world measurement.
Q: What are some challenges that organisations face when using data and people analytics for change management and business agility?
A: The biggest challenge comes from within. Analytics are always a double-edged sword. We often hear “What gets measured, gets managed.” I’m not sure if many of us would prefer to be measured by a manager – or encouraged by a leader. Being measured denotes scrutiny, and the expediency which data provides creates tension. It’s uncomfortable. And of course, we all know how data can sometimes be posited to withhold even well-deserving promotions.
I also think that generally, the People function often do not “trust their data”. We hear the phrase “Single Source of Truth” being tossed around a lot, but often it is thought of as an ideal state. My view is that in the People function, we are often overly sceptical or suspicious about what we don’t grasp or understand. This is different from being discerning.
Apart from a lack of trust in data, HR systems aren’t always connected across processes. While some of this may be systemic and limitations of the technology, often it is about whether we have the right People Analysts with the right domain expertise. Many tools today such as Workday are Platforms-As-A-Service and require configurators with deep HR domain knowledge, and not simply technical developers or non-HR business analysts.
You can’t just toss the problem to the IT department to figure out. If they don’t have the right HRIS specialists, we won’t even move past the needs analysis stage. We need to ensure that we have the right workforce to operate the tools, or risk getting stuck.
Q: How can data and people analytics be used to develop and implement effective change management strategies?
A: Fundamentally, we need to acknowledge that bringing the people along is tougher than plotting the journey itself – which can be the theoretical component of the change. Change is uncomfortable, plain and simple, even to those who claim to embrace constant flux. Success means putting the user at the center of the change and adopting a design thinking approach. This necessitates data!
Data and people analytics help us to identify pain points in the journey of change, to help build personas of the talent we want to engage with and nurture. One example that I’ve seen is the use of the Employer Value Proposition (EVP) as a North Star for change.
An EVP can be subjectively interpreted by different personalities within the organisation. Building and mapping talent personas helps us to understand the profiles of employees: to understand what truly drives and motivates them.
Once we’ve built this data picture, we can use this to posit different dimensions of the EVP as a driving force for change. We’d be looking into talent attraction drivers, leadership capability gaps in order to determine the right value behaviours that can help drive the change needed to transform an organisation.
Q: How have organisations successfully used data and people analytics for change management and business agility? And what are some lessons learned from these examples?
A: I once worked with a large, century-old financial firm that was cognisant of fintech gaining a foothold in their industry. They decided to move and disrupt first, or risk getting disrupted. They wanted to do this intentionally while they were still in a position of strength both financially and organisationally.
One really interesting thing about the change they wanted to bring about was that they recognised that culture was the linchpin of the organisational change they were trying to bring about. It wasn’t just about developing new products, services, or new ways of working. They knew that it was essential to bring their people on the transformational journey and to provide a north star for their people to be guided by during the massive change that was about to be experienced by their workforce.
To do this, they turned to the Barrett Values Centre, which provides a measure of cultural entropy through the level of alignment between the organisation’s stated values and the actual behaviours as reported by employees.
This was a 15,000-man-hour project that was spearheaded by the culture and OD lead. A new values framework emerged from the outputs of this project, which set the stage for a data-driven employer value proposition. This proposition was then used to guide the workforce through various activation touchpoints to get them on the journey.
That employer value proposition was called “Create Something New,” and it was pillared on four distinct values, as uncovered through the Barrett Values Centre. Dendrogram analysis was used to create personas of employees and match them against the profiles of talent that the organisation wanted to attract and nurture.
Years on, I am still in contact with the senior management of the company, and I have witnessed the organisation move from phase to phase: from the values-led transformation, to going through the chaos of change relatively quickly, to maturing past the transformative phase and stabilising the change.
I think they got the part about culture eating strategy for breakfast right.
Thank you for reading this far. I’d encourage you to join the Hacking HR community and to learn from more like-hearted thought leaders – and I am always up for a cuppa to discuss! – AL