When asked what skills are needed to create a successful People Analytics team, many HR professionals might list statistical analysis, data visualization, or experience using statistical software packages. In reality, the most important skill for a successful People Analytics team isn’t analytical ability. As Stacia Garr and the team at RedThread Research point out in this terrific piece, the most influential People Analytics teams prioritize other skills, such as understanding business context, partnering with business leaders, and delivering products that provide not just insight but direct the business toward solutions. Of course analytics capability is important, but true success in influencing the business requires those of us in People Analytics to demonstrate the business value of our work to solve critical problems.
Imagine this scene:
Business Leader: “Hmmm. This data is interesting.”
People Analytics Leader: “Yes! It really is! We were excited to find it!”
[Silence]
Business Leader, to themselves: What in the world do I do with this? This isn’t going to help me with any of the issues on my plate today.
This is the moment no people analytics leader wants to experience. As one of our interviewees put it,
“Providing interesting data is the fastest way a people analytics team goes out of business. You have to provide insights that support decisions on critical business questions.” -- Marilyn Becker, Senior Director, People Analytics and HR Technology Strategy at Western Digital
In the last few months of the COVID-19 pandemic, the importance of people analytics providing critical decision support has become more apparent than ever. In many organizations, people analytics teams have played a starring role as organizations grappled with moving people to work-from-home environments and are now wrestling with the question of how – or even if – to bring employees back into office environments. In these organizations, people analytics will continue to guide critical strategic decisions.
But then there are the other organizations – the majority of organizations: the 82% of organizations where people analytics teams are primarily providing lists of employee data to decision makers or describing how COVID-19 is impacting the business but not explaining how or what to do about it.i Those that have people analytics or employee engagement teams, but where those teams are not brought into critical conversations about how COVID-19 is affecting the workforce. Those organizations where people analytics is not providing significant business value.
There is a yawning gap between those organizations. But it is not impossible to bridge. And, given everything that is happening today, it is more important than ever to cross it.
We wanted to understand how to bridge the gap. We reviewed numerous articles and webinars as well as interviewed close to 20 people analytics leaders to understand how people analytics teams can provide significant business value to their companies – and the journeys those teams went on to get to where they are today. As luck(?!) would have it, we started the interviews before the COVID-19 pandemic began and continued them well into the crisis. This article reflects what we learned.
In the course of our research, we determined that the people analytics teams that are today providing strategic, critical value started on the other side of the bridge – where they were seen as providing comparatively little value. Those teams have inched their way to where they are today, conversation by conversation, day by day, year by year.
To cross the gap, they built a bridge using five pillars – pillars they continue to rely on especially during the COVID-19 crisis. This article tells the story of those pillars and provides examples of how they are being used to provide more business-aligned people analytics insights broadly as well as in the context of the current pandemic.
There are five main pillars people analytics leaders rely on to deliver strategic, business-focused value (See Figure 1):
Figure 1: The Five Pillars of Business-Value People Analytics
Source: RedThread Research, 2020.
One of the questions we asked people analytics leaders was, “Who is your primary customer?” Dutifully, many of our interviewees answered our question, with a roughly 50/50 split answering it was either HR or business leaders. But we realized, at one point, that this was the wrong question. Why?
First, there is no customer. If you have a customer, it implies that at some point, the customer is always right. However, always providing exactly what the customer wants is a sure way, to borrow Henry Ford’s language, to only create a faster horse, not a car. Second, a customer implies that there is a need to serve that may be something other than providing business value, like a narrow HR need or a specific business leader’s need. This is muddy thinking.
People analytics exists to provide value to the overall business, and individual customers and non-scalable projects can detract from that big-picture focus.
Figure 2: Pillar 1 – Be a Business Partner
By contrast, the most thoughtful people analytics leaders indicated that they are business partners with other business leaders in the organization and that their priority is providing meaningful business value. This means that they:
These people analytics leaders come to the table with ideas and insights that are at similar levels of influence and creativity as their business and HR colleagues. They take action items necessary to achieve the bigger objectives – but they are not handed tasks and assignments like a vendor fulfilling a customer’s needs. They own a part of the solution to making the business more successful. They are on the team, not just supporting it.
A critical aspect of this approach is focusing on the business problem, not the specific tools or capabilities the people analytics team has at its disposal. Several of the people we interviewed alluded to the well-known phrase:
One of the ways people analytics leader Annemieke Nennie, formerly the lead of people analytics and insights at Rabobank, provided business value was by coaching her colleagues to lift-up from the day-to-day challenges and think more holistically about business problems. For example, while absenteeism or rewards might be presented as a business challenge, the real and bigger issue causing these challenges might be a lack of employee empowerment. By designing processes and systems that address these bigger challenges, people analytics will be able to solve more effectively for the smaller everyday concerns which arise out of them.
Another people analytics leader, Blair Hopkins at EY in the United Kingdom, shared how his team prioritizes business value above everything else in their strategy. They see themselves in the unique role of packaging analytics in a way that makes sense to the business leaders, so they can consume them instead of being confused by them. The EY analytics team is focused on helping the organization understand the big and macro external drivers that impact the business, their evolving market, and new services. The team is not as invested in explaining the technical details of their findings or the “how” of the analyses as they are on explaining the “so what” to the business leaders. By being able to frame the findings in such a manner, the team is not only able to grab the attention of business leaders but also work along with them and be seen as an equal player.
This laser-focus on the business was echoed by RJ Milnor from Uber who believes the success of the function isn’t solely based on the knowledge of the people analytics industry or capabilities. Instead, it is dependent on their ability to navigate problems, understand Uber at its core and the unique aspects of the specific business they are serving, and their ability to communicate business needs and impact in business vernacular. Some of the ways they are able to achieve this at Uber are by working across functions, maintaining regular check-ins, rigorously prioritizing projects by impact and effort, and designing work for cross-team collaboration instead of working in silos.
When we asked our interviewees on how they stay up to date on the business priorities, one response captured what we heard from many:
“If you don’t know what the business strategy is, then you must ask. The people analytics teams must know the people priorities for the year, how they connect to the business strategy and if they don’t know, then they should reach out to the head of HR and attend leadership meetings to get clarity, instead of working in a vacuum.” -- Dawn Klinghoffer, people analytics lead at Microsoft
As The Economist rightly pointed out, COVID-19 is the head of HR’s crisis (versus 2008 being that of the CFO). However, what it didn’t mention is how critical people analytics is to helping business leaders make much better decisions about pressing, immediate people needs.
For example, Tanuj Kapilashrami, Global Head of HR at Standard Chartered Bank, shared that her team sees their main role during the crisis as getting management and senior leadership to make decisions that are supported by the data. In the first few weeks of the COVID-19 crisis, some senior leaders and managers were making decisions based on the last story they heard instead of data. To combat this situation, the team quickly launched daily pulse surveys of employees to better understand what employees were struggling with most and the types of solutions they could provide. In addition, the bank rolled out a COVID-related survey to capture data and listen to their employees on a continuous basis. By doing this, they were able to identify areas they needed to understand more deeply and not get carried away by what the leadership thought the employees were thinking or needed to manage the crisis.
“This is a big humanitarian crisis and our role in HR in this is key. There is so much emotion but one of my big jobs with my management team and senior leaders is to get them to take as many decisions as they can on the back of data”. - Tanuj Kapilashrami, Group Head of HR at Standard Chartered Bank
Another example of acting as a thoughtful business leader during the COVID-19 crisis came from Kraft Heinz. The company’s leadership team wanted an analytics solution that would allow them to overlay the John Hopkins COVID-19 data on their employee footprint. When they reached out to the people analytics team for help, the first thing the team did was to put on their “consultant hat” and work with leadership to identify the specific business problem they were trying to solve, who was going to consume the data, and what were they going to do with the information once they had it. The aim was to clearly understand what data they needed in order to answer the most pressing questions for the business and provide maximum value.
With this information, the team started collecting external data and employee footprint data, and tracking internal data on employees in different locations so they could do real-time risk assessments and identify potential issues with supply chains. This also allowed them to more deeply understand employee needs, which allowed them to shift as a business and continue producing their products to meet market demands.
“To maximize the value that we create for the business, people analytics leaders must avoid starting with data and instead start with the problem. Otherwise we will be constrained by what we have, instead of what we need.” -- Serena Huang, Global Head of People Analytics at Kraft Heinziv
While it is one thing to see oneself as a business owner, it is another to be invited to the meetings where you can act like one. We have heard this question for years:
How do I gain credibility to work on the big strategic questions?
Figure 3: Pillar 2 – Think Like a Sales Representative
The best practical advice we heard was that people analytics leaders – especially in their first year – need to think like a sales representative opening up a new market. Leaders need to determine:
Then it is the people analytics leader’s job to figure out how to help those people solve their most pressing issues.
A few of the leaders literally mapped out on a whiteboard the “market” of people they could help in their organization, identifying those who were the most influential. They then reviewed those individuals’ needs in the context of the people analytics teams’ capabilities, identifying those where there was a high degree of overlap. With this information, they created a prioritized list of people they needed to “bump into” or “grab for coffee” and began to develop those relationships. They kept at this approach for months, regularly updating their board and list. While this represents an extreme case of “thinking like a sales rep,” we heard of plenty of others who did this mapping in less explicit ways.
For those of you for whom “selling” feels uncomfortable, remember that really good salespeople are partners in helping other people get things done when they lack the resources themselves to do them. That is the type of selling we are suggesting -- not the icky used-car salesman type of selling.
One of the ways the people analytics team at Merck Group was able to overcome barriers when they were the new kid on the block was by identifying people for whom they could deliver specific impact through their capabilities. They began by mapping out the organization, understanding the business, and identifying the “hot buttons” where they could add value. They helped the relevant leaders solve their challenges and then leveraged these relationships to make inroads into other parts of the business. By systematically identifying these opportunities, the people analytics function was able to deliver visible impact which led to a rise in momentum.
“It's really about understanding the key satellites and super influencing people and knowing when they can give you the booster to amplify.” – Alexis Saussinan, Global Head of Strategic Workforce Planning and People Analytics, Merck Group
As part of this, people analytics teams must be deft at building and managing many relationships. For example, Nicholas Garbis, VP of People Analytics Strategy at One Model, who led workforce planning at both Allianz and General Electric, emphasized the importance of balancing the “give and take” of relationships with both business leaders and the teams that support people analytics. While the specific partnerships and stakeholders can vary across different organizations, people analytics depends on other teams, such as business unit/functional operations teams, IT, data science, and HR operations, to do its job effectively. It is critical to always understand the balance on the “emotional bank account” with those teams. How much has people analytics withdrawn (asked for time/resources) from those teams? How much has it deposited (provided value or support)? It is critical to never have a negative balance with those stakeholders.
Across the last few months, we’ve seen teams really embracing this “sales rep” mindset by focusing on where they can provide the most value in this challenging time – even if it is by collaborating with a group they do not typically partner.
An example of this was shared by Nokia. As a multinational telecommunications company, Nokia has about 100,000 employees with a presence in around 120 countries. To provide insights on the workforce’s well-being and collaboration levels, the people analytics team collaborated with their Health, Safety, and Security function, the travel team, and their real estate team to overlay employee data with the publicly available COVID-19 data to build a dashboard for the global leadership team. The result was a very critical travel tracker with granular information available at both the country and site level. This helped the organization keep up to date with travel restrictions and to then make critical decisions (See Figure 4)v.
Figure 4: Nokia’s Coronavirus Dashboard
Another example was shared by Merck Group, where the people analytics team built and managed an extensive stakeholder influence network map. The intention was to understand who works on what and plan ways that the people analytics and strategic workforce planning team could deliver critical insights for decisions at different organizational levels such as the Executive Board, Group Crisis Management Teams, and Country teams, at different moments. Due to the early network mapping, the team was prepared to quickly deliver insights on managing flexible working arrangements, the adaptation of work from home, the effect of training their leaders and teams have on virtual collaboration, and shaping the key evolutions of the future ways of working that they want to sustain post-crisis.
One of the things we heard most frequently from leaders is the imperative to think about people analytics work as products, not projects. Practically speaking, this means several things:
Figure 5: Pillar 3 – Deliver Products, not Projects
This pillar focuses on the importance of avoiding one-off projects that require continued, manual interventions, which is relatively low-value work. By contrast, when the team has to plan for more scalable, continued ongoing use, they must take a different approach. The team has to determine user personas and use cases for the technology. As part of that work, teams figure out how end users will leverage the insights to support decision-making – not just providing information that might be useful.
For example, when talking about designing products that have scalability and extensibility, a people analytics leader at a multinational conglomerate company referred to their people analytics team’s approach of first quantifying the business impact and feasibility before taking on new work. The team is extremely particular about being honest about whether an opportunity is good for only one line of business or could have enterprise-wide or broader extensibility. In case it has a wider applicability, the team will quickly work on scaling it, if not, the team moves on to the next opportunity. Not only does this help them stay product-focused and in touch with business priorities, it also helps them frame their work in terms of actual business problems.
Another people analytics leader at a global healthcare company spoke to us about how their company is significantly invested in thinking about people analytics as products, not projects. To implement a completely agile approach to people analytics technology and offerings, the people analytics team recently moved away from reporting to HR and instead now reports to IT. All delivery teams have scrum masters and daily stand-up meetings, and the team only plans in three-month cycles. The team has product management designing business user stories that are then translated into a clear user experience with appropriate features and functionalities. The move to this new approach was driven by a desire to increase transparency and to respond much more quickly to changes in the organization’s needs.
“We are trying to flip our delivery model around from being a hand-held service to being a digital service.” – Head of People Analytics and Reporting at a healthcare company
In the midst of the current crisis, organizations with the “product” mindset have been able to quickly add features to those existing people analytics products to get the insights they need. For example, the people analytics team at ABN AMRO leveraged their existing employee listening practices when they needed to respond to COVID-19. They added questions to their monthly employee experience survey, asking if people can still perform their work in this specific situation and what is helping or blocking them. They also initiated a survey specifically on remote working. The team is working closely with facility management, IT, and communications to deliver these insights and actions to employees, management teams, and the pandemic crisis team via their existing communication lines.
Another company that has been quick to leverage existing analytics capabilities and products to discover insights they can use during the crisis is the National Australia Bank (NAB). Prior to the pandemic, as part of their broader drive at the bank to “use people analytics for good,” the company had been working with Microsoft Analytics for the past 12 months to use Outlook data to provider leaders with deeper insights on how their teams are working, networking, and collaborating. Once the crisis began, the company began leveraging it to understand which work practices had shifted for staff over the past 8-10 weeks. The leaders are provided weekly reports (see Figure 6) based on data that tracks “time in meetings and emails” and “time in afterhours meetings and emails” to get a sense of how work patterns are changing. They also track “one-on-one time” between employees and leaders and compare all of this data to a pre-COVID-19 baseline of February 2020. By leveraging these new insights, the bank has been able to quickly understand the workload pressures being experienced by their employees.vi
Figure 6: Example of Weekly Collaboration Hours Analysis at National Australia Bank
We are just beginning to tap into the potential for data to give us context-specific insights on our business. As one practitioner mentioned,
“The era of one-size fits all is dead. Data moves us beyond ‘best’ practices to practices that we know, based on scientific evidence, work in our organization in a particular context.” – VP, Talent and Development at a technology company
Figure 7: Pillar 4 – Provide Context-Specific Decision Support
What does this mean in real life? It means gaining a more detailed understanding of what, specifically, is happening within organizations with certain groups of employees – and sometimes with individual employees. At this point, it is common for leaders to look at data by some of the common organizational demographics (e.g., function, geography, business units). However, we all know that these sub-groups of organizations are still incredibly heterogeneous, comprised of many different types of employees who will respond to different practices, policies, and approaches in diverging ways.
Given this, some of the most interesting work happening today is analyzing employees by different characteristics (e.g., level, organizational location, demographic characteristics) in different contexts. This level of granularity can provide decision support for asking much more targeted questions. Instead of asking something like, “How is performance management working for employees?” an organization can ask, “How is performance management working for the different genders of employees? And did that change after we implemented a certain intervention?”
For example, the people analytics team at Capital One has provided context-specific insights through an internal study they conducted on their people managers. The team wanted to unpack the specific behaviors common among their most highly rated managers. They surveyed their associates on thirteen behaviors, conducted specific research, and landed on two key manager behaviors: highly rated people managers support their associates (especially when they need it most) and demonstrate consistency between what they say and do. Additionally, they found that improving the lowest-rated people managers would likely have a high return on investment. The team incorporated these findings into their management trainings and have created a people leadership fundamentals development program for key target populations, including new people managers as well as low- and medium-rated people managers.vii
Another example comes from EY in the UK, where they are rolling out predictive models based on dynamic filtering. The tool, which combines machine learning and predictive modelling, allows leaders and managers to find out the probability of employee segments leaving or staying depending on a certain set or combination of attributes that they might possess. Overall, the tool’s ability to offer insights that are specific to managers’ teams makes it powerful and impactful for the organization. Additionally, the team is also leveraging surveys and visualizations in a sophisticated manner to deliver insights out to a wider user base. And while these techniques are not new or advanced, the team has been able to deliver high-impact value through them by allowing their user base to discover insights specific to them.
We have especially seen the importance of context-specific decision support during the COVID-19 crisis. One organization that has done this especially well is National Australia Bank (NAB). Given that COVID-19 has not just caused a health crisis but also an economic crisis, a higher than average number of customers (individuals, small business owners, and larger businesses) than usual were looking to the bank for assistance. To manage the higher volume of phone calls, emails, and chats, the people analytics team was able to identify individuals who previously had customer-facing experience, which helped the bank redeploy 700 people into customer-facing roles. This was all done within a few days of the need identificationviii.
“The ability to redeploy 700 people within a few days shows the importance of having good HR data in a time of crisis.” – Thomas Rasmussen, Executive General Manager, Employee Experience, Digital & Analytics, National Australia Bankix
Another approach is looking at what different employees need from organizations during the crisis. For example, one organization found that different demographic groups had very different needs, and that if solutions were more targeted, employees would be more satisfied with them. For example, while about 24% of respondents indicated they miss social interactions the most, for 51% of the respondents, it’s not even among their top 10 issues they are currently facing. The organization could then use this information to design targeted interventions and make decisions about investments in programs.
Context-based insights have been equally crucial for Standard Chartered Bank as they begin to think about bringing people back to office spaces. The bank’s Global Head of HR, Tanuj Kapilashrami, has been interested in understanding the cultural learnings that are emerging out of this crisis and how they will affect the traditionally hierarchical organization of the bank. To that end, they rolled out a series of polls for all people leaders, around 1,400 of them, to ask them about the support available to lead during this crisis. The poll allowed the leaders and managers to input their own questions and vote on the ones they wanted to know most about. The findings revealed a significant difference in the way people were thinking about going back to work. For example, while people based in the western part of the world were resistant to going back to office spaces and were managing adequately working from home and being productive, those in the east were more open to the idea of going back to the offices due to issues such as a lack of necessary infrastructure and cultural context to allow them to work from home.
One of the most effective ways to drive change is to put important insights into the hands of more people – namely managers and their employees – which is what people analytics teams are doing increasingly. However, to create a meaningful impact, these teams need to do all of the things we’ve already discussed in this article: understand the decisions these individuals and managers need to make, design strong user experiences that fit different users’ needs, provide a continuous and personalized stream of data, communicate the specific insights in an accessible manner, and clarify the appropriate next steps.
Figure 8: Pillar 5 – Democratize Personalized Insights
A technology company we interviewed is an example of a people analytics team focused on delivering products that democratize personalized insights. The team has been working on building a one-stop shop for managers. The dashboard provides insights and data to help managers lead their teams and take action on those insights by having everything they need on their team accessible at one place.
Cisco is another company that has successfully leveraged people analytics to put insights into the hand of employees directly. The company decided to provide employees with insights that would allow them to create personalized work experiences for themselves. The solution created by the company allowed employees to assess their current skills and competencies against roles. Thus, by giving them access to personal insights on their growth and development, the company helped employees determine suitable career paths within Cisco as well as highlight learning opportunities that will help them accomplish their goals. Managers can also assess the skills of their team members and identify development opportunities for individual employees to explore.xi
One of the ways organizations are driving value through democratizing insights is by analyzing passive data to help employees and managers understand – and then improve – their work behaviors since moving to a work-from-home environment. By leveraging email data, companies are able to provide employees with insights on the rate at which they are requesting something (e.g., asking a question or asking for an action) after work hours, the amount of recognition they are providing, and other digital manager behaviors. This information is contrasted with what employees were doing before the COVID-19 pandemic. Employees receive an email every two weeks, so they are able to see how their behaviors are (or are not) changing over time.
Referring to how such insights are helping them, Gary Coover, GM at Samsung NEXT, mentioned, “The insights and supporting data indicating that my behavior has changed, like from the Work From Home report or responsiveness report, gives me the self-awareness as a manager to evaluate and adjust my communication to better support my team, which is even more important now during this new distributed work environment."
As we look forward, both to the next phase of the COVID-19 crisis and more broadly, we see these five pillars continue to serve as the foundations upon which business-aligned people analytics teams will stand. For example, people analytics teams will be – and in some cases already are – integral to designing what the employee experience will look like in “the new normal.”
People analytics teams are helping determine which types of employees will be coming back into a physical workplace – and at what frequency – and which types may transition to full-time work from home. They are helping design strategies for staggered work schedules and the implications for physical office space requirements. And they are helping leaders – at all levels – understand what employees need in order to do their best in the current, challenging situation. These are all essential business activities to create some sort of new status quo so that companies can be responsive to the future needs and challenges in the coming months. And they all leverage each of the pillars above.
The volatility and uncertainty we are currently experiencing is unlikely to abate any time soon. Fortunately, there are better data and insights than ever before to help us navigate these times. By relying on these five pillars, people analytics teams can transition from offering “interesting information” to providing “decision-critical insights.”
To quote our opening interviewee:
“People analytics is a superpower. But we have to use it right.” -- Marilyn Becker, Senior Director, People Analytics and HR Technology Strategy at Western Digital
Go forth and use it to make your businesses – and people – better, as we continue through COVID-19 and well into the future.
The Perceptyx platform gives you the flexibility to adapt your listening strategy to rapidly changing real-time events. Combined with support from our analytics experts, our platform can help you keep your finger on the pulse of your people’s needs, so you can provide the support they need during these uncertain times. Get in touch to see how we can help your organization navigate successfully through the COVID-19 pandemic.