Improving Team Productivity with ONA
We’re often asked about using data from collaborative tools to measure the productivity of individuals. My response to this question is that it is ultimately far more interesting and valuable to look at whether people are working in productive teams. Does the environment and structure at the team level support high productivity? After all, you can hire the best talent available but if you place people in a chaotic and unfocused environment, they are likely to be unproductive.
After all, you can hire the best talent available but if you place people in a chaotic and unfocused environment, they are likely to be unproductive.
We recently collaborated with a marketing company that was struggling with productivity issues. Some of their project teams were consistently delivering late or poor quality work and they had a sense that this may be down to individual productivity. We used organizational network analysis to take a closer look at how their teams were working together, with the goal of providing insight into the issue.
Internal vs External Focus
Productive project teams tend to be autonomous and focused. Having multiple external stakeholders or shared resources can create bottlenecks and slow decisions.
We performed an analysis of external vs internal (E/I Analysis) collaboration in project teams, using data from email, calendar, document repositories, and project management tools. E/I Analysis compares the percentage of time team members spend collaborating with each other, against the time they spend collaborating with individuals outside of their team. This data is used as a proxy for how focused and autonomous a project team is.
A highly focused team should invest a significant portion of its time in internal collaboration. This of course differs from team to team but in our analysis of over 100 organizations, we’ve found that a ratio of around 60/40 (internal/external) is about average for teams of knowledge workers. Below are the results of our analysis for one of the project teams.
Diagram comparing time spent on collaboration between team members inside a team with collaboration between the team and other parts of an organization.
They appeared to be spending all of their time sending email, in meetings, chatting, writing documentation and working on tickets with other teams and departments.
In this case, our analysis showed that a few of the project teams were spending upwards of 75% of their time on external collaboration. In other words, their project teams appeared highly dependent on external resources or stakeholders. They appeared to be spending all of their time sending email, in meetings, chatting, writing documentation and working on tickets with other teams and departments. Far from what we would expect of a focus and autonomous project team.
We also looked into which departments the external interactions were with. Interestingly we found that the majority were with only two other departments: Customer Service and Sales. These two customer-focused teams accounted for over 65% of the interaction with the underperforming project teams.
Impact of Externally Focus Teams
To highlight the impact of these external interactions, we performed an Activity Analysis using data from calendar, email and messaging platforms within the organization. The Activity Analysis is designed to give a sense of the typical day-to-day life of team members and the impact that external interruptions have on this.
Research indicates that knowledge workers require significant periods of uninterrupted time to focus and problem solve. Before and after every interruption there is a ramp up and ramp down period, while people get back into the problems they were working on. This is best illustrated by the image below:
The impact of a small meeting on the schedule of a knowledge worker - source
Our analysis highlighted that several individuals within the underperforming project teams had highly disrupted schedules, with multiple meetings and other interruptions per day.
Our analysis highlighted that several individuals within the underperforming project teams had highly disrupted schedules, with multiple meetings and other interruptions per day. This indicated that people had limited time available to focus on important tasks and deliverables. The diagram below illustrates a typical day in the life of a team member and highlights estimated impact on productivity.
Diagram highlighting the impact of interruptions on the productivity of a team member. Even though they are in the office for 8 hours a day, they only have around 2 hours to really focus on the work that matters.
Taking Action
Our results indicated that the environment and work habits at the team level were likely a significant driver of productivity issues. Consistent interruptions and collaborative overload appeared to be making it hard to get work done. Direct feedback from the team members confirmed these findings. People had previously complained about the environment being disruptive but without the data not much was done about it.
We provided managers with a series of recommendations to help them build more focused team environments. This included actions such as providing single points of contact between Customer Service and project teams. We have also worked to provide “Focused Time” as a core metric for success on teams and as a way to ensure that similar issues are rapidly identified in future.
Interesting analysis. I would love to see research like this supplemented with inquiry into the human experience of these people working in this environment, what they saw as drivers, enablers, obstacles or diversions. What they thought about the ONA data, how they responded to it, what solutions they co-created and how they felt this related to the leadership climate and behaviours they saw. Other research into productive self-managing teams looks at 'heedful interrelating' where productivity takes place across co-ordinated but not simultaneous individual efforts. I wonder if tactics to improve heedful interrelating could have also been useful for these teams? e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4796034/ And like Michael Merritt above, it would be great to hear about the follow-up and evaluation. Thanks for sharing!
People Analytics at Citi
7 年Very interesting. I'm also just getting my feet wet with ONA (with the possibility of a small scale experiment in the near future). Would be interested to know: did you conduct a follow up post-treatment/recommendations to managers to measure the efficacy of this effort?
Ph.D. in Organization Theory, x-Faculty @MIT & Carnegie Mellon | Current: Guest Lecturer @ London Business School and Associate Professor of Management @ New Uzbekistan University
7 年Michael Gralla
More signal, less noise, with Recruiting Brainfood
7 年Fantastic post. ONA is something (to my shame) I have only just come across. I - we - need to do more in this area. Thanks Philip Arkcoll for giving this overview