How a Financial Services Company Used Data to Rightsize their Workplace

Summary

The workplace team at a major financial services company partnered with HubStar to ensure data-informed decision making. The team started work with HubStar in 2021 to capture data to inform their future workplace design, following the uncertainty that came with the COVID-19 pandemic. As a result, the workplace team has been able to determine office occupancy and utilization, dwell time of spaces, and the differences between employee intentions and employee behaviors.

The Challenge

With multiple offices in the UK and no objective property data available, COVID-19 spun this workplace team into a whirlwind looking for answers about what was coming next. Pre-pandemic, employees were working in a traditional workspace environment with assigned seating, private meeting spaces, and minimal collaboration zones. The workplace team had a good idea of how space was and wasn’t being used, thanks to data previously collected via manual studies, access control systems, and occupancy sensors. However, that data wasn’t granular enough, and wasn’t presented in a way that allowed them to discover important insights. They were missing the ability to view full data stories, in order to inform new ways of working and the future workplace design.

The team identified key areas to a successful transformation journey:

• Collect unbiased occupancy and utilization data on how various workspaces in its offices were used, while also respecting individual team member privacy.

• Extract key insights to engage in meaningful conversations with business unit leaders.

• Understand how the employees’ intended behaviors compared to their actual behavior through comparisons between the desk booking data and sensor data.

• With the spotlight on return to office and new ways of working, the team had a need to collate data to drive decision making in relation to sharing ratios, neighborhood sizes, the types and numbers of spaces as well as number and size of meeting rooms.

The Solution

The workplace team partnered with HubStar for its data analytics and insights platform, recognizing that while some sensor technology on the market is similar, it’s the analytics which are crucial. HubStar successfully deployed over 700 state-of-the-art proprietary desk sensors to measure occupancy, utilization, and dwell time of seats, alongside a desk booking integration and dashboard to capture employee intent vs employee behavior.

Within hours of installing the sensors, the organization was able to begin accessing the data it needed.

The team chose to measure three main metrics that were most relevant and actionable:

• Occupancy (whether or not there was presence at a seat)

• Utilization (how long the seat was continually in use)

• and finally, through a desk booking integration, data insights were captured regarding employee intent vs employee behavior.

The data collection is ongoing, and to date has enabled key learnings and decision making. Through segmentation, the data collected assisted in space planning and the design of department neighborhood zones. The team was able to observe and segment occupancy and utilization data by floor and business unit, providing the level of detail necessary to facilitate discussions with each business unit owner about how their space was being used and the safety protocols in relation to return to office.

The ‘Spaces’ data visualizations informed the workplace team of the peak and average utilization and occupancy, highlighting that Wednesday at 11am was the peak for utilization (381 desks), and each desk used had a dwell time of 18 minutes. This data helped to build psychological safety for employees that there were enough desks available for them to remain physically distanced where they chose, as well as the sanitization of spaces in line with average dwell times being shown within the data.

Data filtering allowed the workplace team to dive into granular data and inform the sizes of the neighborhood zones for each department. As an example, the team itself utilizes 8 seats on average, with a peak of 12 seats taking place on a Friday at 9am.

With ‘Live’, the workplace team can view office occupancy in real time, which was operationally helpful during the pandemic when the team were not always in the office themselves due to the restrictions in place. On the following page there is an example of the live view highlighting the spaces which are available

The desk booking technology adoption was initially low, due to a lack of demand on the spaces. As space utilization increased, employees began to adopt the technology to drive their experience. Below is an example data set comparing employee intent (desk booking) vs employee behavior (sensor data).

The example data set highlights an occupancy of 34%, but only 20% of spaces were booked, meaning 19% of spaces (121) were subject to squatting. From the spaces booked, on average 5% (29 spaces) were booked but not occupied (no-shows). This data is reviewed on an ongoing basis as the supply and demand of space balances out which will then drive the requirements to book spaces or not.

Key Outcomes

• Learned about the peak and average utilization and occupancy rates in their workplace

• Drilled into granular data by department thanks to data filtering

• Monitored office occupancy remotely using Live, during the height of the pandemic

• Determined no-show rate of meetings booked (about 5%)

The Result

The workplace team was able to learn utilization and occupancy rates, drill into granular data, monitor office occupancy remotely and decrease the rate of no-show meetings.

The data insights have:

• Driven space planning, sharing ratios and neighborhood sizes.

• Informed workplace design.

• Provided data to aid return to office