The Future of Work is Not About Where You Work; It is About How You Work and Measure Success
Much of the conversation about the future of work is focused on where work gets done. On one side, you have Airbnb CEO Brian Chesky declaring that “the office as we know it is over”, while at the other end of the scale, the notorious publicity-shy Elon Musk has told Tesla employees to return to the office or ‘pretend to work’ elsewhere. Most companies, however, seem to have decided to opt for a hybrid mix, such as Spotify, with its well-publicised ‘Work from Anywhere’ approach.
While the office vs remote vs hybrid debate provokes strong opinions, we must be careful about obsessing solely about where work gets done. This is not a binary conversation. The people analytics teams we work with at Insight222 are also analysing data and informing decisions about when work gets done (with employees having more flexibility on work hours hence the rise of the ‘Triple Peak’ day, and employers increasingly experimenting with four-day weeks), and how work gets done with the evolution of workplace design.
Measuring the effectiveness of where, when and how work gets done and its impact on employees, teams and organisations, as well as topics such as productivity, innovation, well-being, inclusion and customers, is incredibly complex.
As such, I was pleased to catch up recently with Phil Arkcoll, CEO and co-founder of Worklytics – an analytics platform that supports chief people officers and people analytics leaders by helping teams continuously improve their work and collaboration.
1. Can you please provide readers with a brief introduction to your background and responsibilities at Worklytics?
Thanks for inviting us to this interview. As you mentioned, at Worklytics, we help teams analyse anonymous collaboration data across common tools like Office 365, Google Calendar, Drive, Slack, Zoom, GitHub, JIRA, and the like. Our insights help them drive engagement and team effectiveness by improving how they spend time, coordinate and balance individual-focused work with collaboration. For example, we’re helping several teams devise strategies to avoid countless coordination meetings, freeing up people’s time to focus on deeper work and problem-solving.
We’ve been in this space for the last eight years and have lived through the before and after of the changes brought about by the pandemic. Our focus of late has been on helping teams navigate the transition to remote and hybrid work. In particular, adapting to the changing demands faced by remote and hybrid teams, such as worsening work-life balance, increasing risk of burnout, and over-collaboration.
We leverage techniques and tools like organisational network analysis (ONA) and predictive analytics to gain insight into how teams collaborate. A key component of this is ensuring we have the trust of the teams we work with while also protecting employee privacy. Protecting employee privacy is at the core of everything we do. We also offer a number of advanced tools to cryptographically anonymise all data, only analysing the flow of communication and never the content.
2. With the pandemic rapidly changing the way we work, and forcing this shift towards a hybrid way of working, what has been the impact of virtual and hybrid working on innovation?
The pandemic led to the largest change in ways of working since the introduction of the personal computer to the office. I don’t think teams can go through such a significant change without an impact on how they innovate.
To fully understand the impact, we need to consider the conditions that allow for innovative teams: trust and psychological safety, easy communication of ideas to understand the customer and stakeholder needs, cross-functional connections, and the ability to rapidly iterate and test ideas.
While some of these things are easier to do with remote work/hybrid technology, many are now more challenging. Building trust in teams and efficient communication, for example, requires strong bonds across an organisation. We have seen these bonds decline in the post-pandemic world, where connections and networks take longer to build and are narrower, leading to more silos within companies. On the flip side, many people find it easier to concentrate on individual-focused work and deeper problem-solving when they are remote and less likely to be interrupted. Innovating has essentially become easier in some ways and harder in others. This is why data analytics in this space has been particularly helpful since it allows us to isolate those areas in need of help and course-correct where appropriate.
3. How has the notion of work culture, interpersonal skills, and cohesive team collaboration been affected by hybrid working?
I think one of the key differences in hybrid or remote work is how people have to be far more intentional and proactive about maintaining culture and connections. We took for granted how much company culture and relationship-building emerged organically when we were all in the office together. This connectedness doesn’t just happen in a hybrid world–it must be engineered.
A great example of this is how much the new hire onboarding experience has changed. It used to be that in your first few weeks, you would get invited to lunch, walk around the office, and be introduced to other teams and key connectors. This mostly organic interaction would fast-track your ramp-up and integration into a team. In a hybrid/remote environment, things are very different. You’re often starting your first week from home. If managers and other team members don’t proactively reach out to you, you’re going to struggle to make those connections. It’s easy to be out of sight and out of mind, and many new hires are struggling as a result.
Data can be critical in mitigating the impacts in this key area. Organisational network analysis can help us understand the development of these relationship networks and implement interventions to spur their growth. In the remote onboarding case, this involves understanding where you’re struggling to integrate new hires and helping you implement strategies like a new hire buddy system to get things back on track.
4. What hybrid or remote workforce trends have you begun to see in this new post-pandemic world of work?
One key trend we’re focused on is the fact that a number of remote/hybrid organisations are really struggling with over-collaboration. The sudden shift to remote during the pandemic left many teams scrambling to implement tools and processes to help them coordinate and manage priorities while apart. In many organisations, this led to an explosion in collaboration, most often in the form of large numbers of recurring meetings. We also saw many organisations rush to implement tools like Microsoft Teams or Slack, which, when adopted poorly, can lead to a further explosion in collaboration. The net result is that many knowledge workers who require uninterrupted periods of time to think and problem-solve are struggling to focus.
The teams that are adapting well to this change have managed to balance their mix of asynchronous (e.g., a shared priority list or ticket system) with synchronous (e.g., meetings or real-time chat) coordination. They avoid overloading people with meetings and email but also use face time to maintain connection when it matters. Managing this aspect of work has been absolutely critical to ensuring the shift to hybrid/remote is a success.
Another key trend we are seeing is that the role of the office is changing drastically.
Before the pandemic, the office was largely seen as the place that people travel to in order to actually get work done. Everything from office building design to the furniture and tools in the office was built with this goal in mind. Offices are now seen, however, as the place that teams come to in order to strengthen relationships and collaborate. The on-site days in a hybrid work environment are prescribed for days when teams have to collaborate closely, while WFH days are seen as the days when deep work is expected to be done.
5. We’ve seen an increase in interest in Organisational Network Analysis (ONA) and how organisations can use network analysis to assess how this shift to hybrid working is impacting productivity and collaboration. Can you share some insights into how your clients have benefitted from leveraging ONA?
Absolutely. Relationships are unconditionally critical to how effective teams operate. How we form and maintain these work relationships has fundamentally changed since the start of the pandemic. With far less face time, we now rely heavily on digital platforms like Zoom and Slack to build and maintain networks. Understanding how these networks are evolving is key to making the changes required to ensure the transition to remote and hybrid is a success.
This is where ONA comes in. ONA had been slowly growing in prominence for years, but the last couple of years have led to an explosion in interest. Many organisations are concerned about whether their teams are becoming more isolated and siloed and if this negatively impacts employee experience, team effectiveness, and innovation. ONA can be incredibly helpful in quantifying this problem and point to where teams can work to proactively rebuild connections and bust silos. We’re also seeing ONA be very helpful in understanding whether remote team members are being excluded as a result of being out of sight / out of mind. This form of isolation is one of the key drivers of increased burnout many are experiencing over the past year.
Another common application is in answering how the networks of managers/leaders have evolved in the hybrid environment. ONA can help to ensure that leaders are adapting to the change and proactively maintaining relationship networks needed to nurture company culture.
Without tools like ONA, understanding these changes is a somewhat intractable problem. Tools like surveys can provide some clues on network health, but without being able to pinpoint and quantify bottlenecks and deficiencies, it’s hard to take action to improve outcomes.
6. How can people analytics play a greater role in preventing employee burnout?
This is an area where people analytics is already doing a lot to help. Burnout is a complex process driven by many factors, but data can help to pinpoint specific actions teams can take to tackle the problem.
One example here is the over-collaboration that I mentioned earlier. For many knowledge workers, spending time on deep problem-solving is key to making work meaningful. The recent explosion in collaboration that is driven by remote work has meant that a far greater amount of time is spent on coordination across meetings, email, and chat. This is a major hidden source of frustration and an underlying driver of the increased burnout seen among knowledge workers over the past 18 months. Data can help us quantify and pinpoint where this problem is most severe so that teams can take action to buy their teams the time they need for focused individual work and healthy collaboration.
Another good example of an underlying cause leading to burnout is the blurring of the line between personal time and work time for at-home employees. We all know that extended work periods with excessively long days tend to cause people to burn out. Anonymous data on workday span has shown that with the move to remote, the typical person’s workday increased by at least one hour. As we can see, data and analytics are crucial here to help quantify and highlight this problem so that organisations can take action to prevent it from further spiralling out of control.
7. As we continue to head toward a global economic recession, how can predictive analytics be used to better support workforce strategies?
As an economic downturn looms, we’re seeing more companies rely on data and analytics to ensure their decisions are promoting a stable work environment in this uncertain time. The key metrics we’re seeing companies use continue to focus on employee well-being and effective collaboration. Economic downturns often mean that teams have to do more with less. This requires creating strong relationships, having effective communication and for teams to use their limited time as efficiently as possible. Without these practices, the additional pressure of an uncertain economic environment is likely to worsen ongoing trends in employee burnout and attrition.
Predictive analytics is a powerful tool for identifying bottlenecks and underlying drivers of critical business outcomes across employee well-being, team effectiveness, and collaboration. For example, when looking at how much time teams allocate for individual-focused work versus collaboration, we see clear patterns that help teams determine how much time to allocate to synchronous vs asynchronous work. For example, we found that teams where individuals had less than three hours of focused time per day for work reported feeling 2x less productive and distracted in pulse surveys.
Using collaboration data to understand these trends helps teams ensure they are creating healthy work environments for their in-office, hybrid, and remote employees.
8. Can you provide an example of a customer that has used the Worklytics platform to improve how their teams work and collaborate?
Absolutely. As I mentioned, over the last couple of years, we’ve helped a number of organisations adapt to remote and hybrid work. One of our key customers, a well-known Silicon Valley-based “unicorn”, recently needed help overcoming significant challenges with how their teams coordinated effectively in a “remote-first” environment. Since their transition to remote, they have been dealing with complaints and low employee sentiment around decision-making and coordination. Employees reported that it had become harder to get things done and that coordination and decision-making had become slow. What was equally alarming to them was that they were starting to see significant attrition among key talent partly as a result of these challenges.
When we analysed their collaboration data, we found several signs that their work and coordination patterns had significantly shifted since their shift to remote first. Meeting volume had drastically increased (more than 60%), and the average team member was now spending over 1.5 days in meetings per week.
We also found that focus time at the company had dropped significantly (by over 40%) across the same period and that the average person was now meeting and communicating closely with a far larger group of peers in order to get things done.
These are key markers for high collaborative overhead, meaning that team members often have to interact with many people across many meetings in order to make decisions and get work done. We ran a driver analysis to show that these patterns of over-collaboration were directly related to some of the negative sentiments picked up in surveys. For instance, one of the strongest predictors of “high stress” in the survey was if someone had over 15 close collaborators in a given week.
By sharing these stories with the broader team, we were able to help them put real numbers to what was previously only a gut feeling about the problem. Once they could quantify and pinpoint the issue, it became easier to take action.
They started out by setting a clear company goal of driving up focus time across the organisation. The focus time metric was regularly communicated in all-hands company meetings to help elevate the issue and show progress. They took various corrective actions, including introducing a new policy to set designated hours in the day for collaboration time, with the rest of the work day set aside for deep work for their teams. This program had a measurable impact on focus time, which increased by about 40% to be back in the normal range.
They also got direct feedback from the employees during their subsequent employee survey, where the teams clarified that the increase in focus time greatly impacted their ability to get work done.
Thank You
Thanks to Phil for his time and for sharing his knowledge on how to measure the effectiveness of hybrid work and some of the extremely exciting work they’re doing at Worklytics to help teams and organisations teams continuously improve how they work and collaborate. If you want to find out more, you can connect with Phil on LinkedIn, follow him on Twitter and visit the Worklytics website.
If you’d like to explore more of Phil’s work and that of his team, do take a look at some of the links below:
https://www.worklytics.co/blog/6-kpis-to-make-hybrid-work-a-success
https://www.worklytics.co/blog/top-6-metrics-to-measure-during-an-economic-downturn
https://www.worklytics.co/blog/top-12-metrics-for-effective-meetings
https://www.worklytics.co/blog/distractions-and-interruptions-impact-focus-time
ABOUT THE AUTHORS
Philip Arkcoll is the founder of Worklytics, a Y-combinator backed data analytics platform that provides metrics and meaningful insights into how remote and hybrid teams collaborate and get work done. Worklytics helps clients such as Uber, Boston Dynamics and Panasonic understand and adapt to the changes brought about by remote and hybrid work to enhance team effectiveness, improve meeting culture, and prevent employee stress and burnout. Philip has an extensive background in data science and technology focused on helping organizations design compelling employee and user experiences. He holds a honors degree in Computer Science and Management from the University of Cape Town, in South Africa.
David Green
David is a globally respected author, speaker, and executive consultant on people analytics, data-driven HR and the future of work. With lead responsibility for Insight222’s brand and market development, David helps chief people officers and people analytics leaders create value with people analytics. David is the co-author of Excellence in People Analytics, host of the Digital HR Leaders podcast, and regularly speaks at industry events such as UNLEASH and People Analytics World. Prior to co-founding Insight222, David worked in the human resources field in multiple major global companies including most recently with IBM.
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