Drowning in Data. The secret to meaningful workplace insights.

Data plays a crucial role in shaping workplace decisions - the kind that carries significant fiscal implications and ripple effects on individuals' emotional, social, and psychological well-being.? Organisations look to data to give insights about how the office should perform, what size it needs to be, what should be in it, whether the right hybrid working policy is in place or whether something needs to change.

Organisations collect a multitude of data that helps understand that, or at least some of it. ?There's space booking data, badge-in data, Wi-Fi analytics, space use sensors, observation data, employee experience apps and space management systems that connect with headcount data, surveys, asset management systems, sensors, software analytics (Zoom, Microsoft Office) and more.

Access to more data, better analytical software, and processing power were meant to make workplace decisions easier. ?But the opposite is happening. Oracle's Decision Dilemma Survey found that data burn-out is real. ?

We can’t avoid data overload, but there are steps we can take to manage it and make better sense of it.

Know what you're solving for

Before you can work out what data you should focus on, you need to understand what you're trying to uncover and why.

Are you trying to discover how to get people to connect more effectively? Do you need to understand what value people place in the office and how it aids their workstyle so you can better design what goes inside? Or do you need to understand your physical office’s capacity?

Whatever it is, remember, the workplace is more than just a physical space—it's a catalyst for performance. ?Workplace measures are not merely about literal occupancy metrics; metrics should help us comprehend how the technology, tools, places, processes, and culture enable people to perform at their best.

Know the limitations of your data

Data isn't foolproof and can be open to interpretation.

Where your data comes from, its context, and completeness all matter. Sometimes data can be incomplete (maybe some info got collected incorrectly), biased (if the sample size is too small), or even misleading (through careless interpretation).

It's crucial to be aware of the assumptions you make when interpreting data and to fact-check them. Geography, demographics, sample size, and context all play a role. ?Be clear about the limitations and identify any gaps so you know where and how to validate certain assumptions.

Focus on the experience, not just occupancy targets

Organisations are increasingly concerned about the productivity implications of hybrid work models and how to incentivise employees to return to the office. ?As a result, building and space occupancy data has become a primary metric in workplace planning. ?

While occupancy metrics are useful for assessing capacity and identifying areas that require further investigation, they fail to provide insights into why people value their time in the office, what makes certain spaces more successful than others, and how well the workplace supports focus, connection, creativity, and collaboration.

• Consider experience and behavioural observations alongside occupancy data to gain a comprehensive understanding. ?
• Focus on measures that explore the connection between work and how the office, tools and culture support it.?
• Leverage experience data from other areas of the business, like engagement surveys, job applicant information and attrition statistics.

By shifting the focus to user experiences and addressing pain points, organisations can gain valuable insights into improving the overall workplace experience.

Use data from multiple sources – most of it is likely to exist already

"Trust but verify", a Russian proverb made famous by Ronald Regan and immortalised in memes, is also commonly applied in data analytics.

This means looking at occupancy data in conjunction with other metrics, such as employee satisfaction surveys, real-time feedback tools, and even financial performance indicators. A lot of this data is likely already easily available in your organisation.? Teams and Zoom analytics are great for understanding key relationships, communication and meeting habits, and coffee or vendor sales can be a useful cross-reference for utilisation, particularly where leaders may be disputing patterns. ?Employee-reported issues through apps or operational teams can help understand people’s struggles.

Using data from multiple sources enables you to cross-reference and evaluate results. It also helps to identify patterns, outliers and gaps that may not have been clear when only using one source of data.

Don't go it alone

Workplace metrics often shed light on technology issues, leadership, culture, and other people-related matters. ?Don't hesitate to involve other functions or leaders to gain a deeper understanding and develop solutions. Collaborating with technology, people and culture, and workplace experience teams can bring about valuable insights and enhance problem-solving effectiveness.

Final thoughts

When workplace metrics are disconnected from how people work, the data collected is less meaningful and creates noise instead of providing insights, which can lead to data distrust and decision paralysis. ?

To solve this, be clear about the problem or experience you're measuring and collect data from accessible sources. ?Keep it simple and be clear about the limitations and context of the data.

As workplaces evolve, we need to adapt our measurements to account for the complexity and diversity of people. ?Gathering data from various sources and analysing them together provides a holistic understanding of the workplace experience.

With strategic measurement and contextual understanding, leadership gets reliable data intelligence to help make informed decisions in uncertain times.

This Newsletter is a summary adapted from our October 2023 WPR Insider edition, Analysis Paralysis, available exclusively to Peer to Peer RoundTable Clients.