Big Data and Big Promise: How Not to Lose Sight of What Matters

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Chair Of The Month

Tracy Brower, PhD, MM, MCRw
Tracy Brower, PhD, MM, MCRw
Tracy Brower, PhD, MM, MCRw Dr. Brower is a work environment sociologist and a Principal with the Applied Research + Consulting group at Steelcase. She is the author of The Secrets to Happiness at Work and also, Bring Work to Life by Bringing Life to Work: A Guide for Leaders and Organizations, which focuses on work-life fulfillment. Tracy is a contributor for and Fast Company as well as an executive adviser for Coda Societies and for the MSU Professional Mathematics Program. Over her career, Tracy has had the opportunity to engage with a wide range of organizations including many of the Fortune 500. She is a three-time recipient of the CoreNet Luminary Award for speaking and a recipient of the University of Houston Alexander Real Estate Innovative Practices Award. Tracy has also taught university courses in management and organizational effectiveness. Tracy holds a PhD in the sociology of work as well as a Master of Management (MM) in organizational effectiveness and a Masters of Corporate Real Estate with workplace specialization (MCR.w). Tracy’s work has been featured in TEDx, The Wall Street Journal, Work-Life Balance in the 21st Century (book), Globe and Mail (Canada), InsideHR (Australia), HR Director (UK), T3N (Germany), Inc. Magazine, Real Estate Review Journal,, Inc. Magazine, and more. You can follow her on twitter @tracybrower108, on LinkedIn at Tracy Brower, PhD or at

Steelcase’s Tracy Brower explains why we need both big and thick data to make good decisions when it comes to workplace design.

Image courtesy of Steelcase

Big data holds big promise to change the way we work and live. But it holds risks as well. Because it is so voluminous, complex and available, it can overwhelm what really matters: the experience we create for people.

True story: Year after year a friend of mine and senior professional, Annie, produced a data-rich report. Every month, she would include a sentence that read something like, “If you’ve read this sentence, contact me and I’ll give you $5.” In all her years of producing the monthly report, she only had to pay out once. It was a report for the sake of reporting. No one was reading it, but even more importantly, no one was using the data to make decisions or inform improvements for the employee experience.

The risk of big data is the same – that data for its own sake is prioritized above the decisions it informs.

Image courtesy of Steelcase

Companies are under more pressure than ever to compete and win. This landscape, along with the availability of unprecedented amounts of data results in leaders seeking increasing amounts of information at their fingertips. The ambiguity and complexity of our world make us want more certainty in our decision making and data is a way to reduce the risk of important decisions. Of course, opportunities are greatest at the point of the most ambiguity and risk. As clarity rises, opportunity falls since the greatest opportunities are ahead of the curve. The conjunction of big and thick data are a way to reduce this risk.

One of the investments for which we want to increase certainty is the workplace. The risks of getting it wrong are high: negative impacts to engagement, productivity, or retention. As a result, we seek more certainty – and often more data to help inform the ways we design and decide about workplace solutions.

Image courtesy of Steelcase

Data leveraged effectively contributes to an evidence-based culture rather than a HPPO culture – one in which the Highest Placed (or Paid) Person gets the majority of decision-making power and influence. A data-driven, evidence-based culture fosters more egalitarian decision making and a more comprehensive approach to decision making – all of which are important to the best decisions in the best interest of the culture and the company.

To make good decisions, we need both big and thick data. Big data is defined by its complexity, its volume, and its quantitative nature. Thick data is defined by its focus on context and qualitative nature. Often big data answers the ‘what’ – what is going on, what is happening, what are the patterns. Thick data is contextual and typically qualitative. It is more effective at answering the ‘why’ and providing the texture and nuance surrounding the ‘what’ of big data. Better together, the combination of big and thick data provide for the most complete picture of what’s going on in a given situation, and, in turn, what to do about it.

Even with this new horizon of data however, the data is still only the data. The more important aspect of data is its interpretation and its synthesis. Data itself is at the bottom of the hierarchy. It is only when we add meaning that we get to information and when we add interpretation and application that it becomes insight. Insight is significantly more valuable because it is actionable and applied.

Image courtesy of Steelcase

Insight is about the ‘so what’ of the data for example, it can help us take action to improve the workplace and work experience. Sensing data can tell us which areas of a floor plate are most utilized. People vote with their feet. But beyond the sensing, it’s the sense-making that matters most – making sense of the data in relationship to what people want in their ideal work environment and how the workplace must change to align with culture and align with the changing nature of work.

More data isn’t necessarily better, but in general, more data from more sources is better. Mixed methodologies are key. From a variety of big and thick data sources – both qualitative and quantitative – we can more effectively draw conclusions and predict what people want in their workplace and the work experience of the future.

Without interpretation, meaning and context, too much data can be a significant burden. As we’re looking for needles, more data just makes the haystack bigger. It creates more noise when we’re really looking and listening for the signal. So how to find the signal within all the noise?

  • How frequent is the effect? How often and how consistently is the effect showing up?
  • How significant is the effect?
  • To what extent is the pattern correlated with other data sources versus an anomaly?
  • What are the patterns that are developing?
Image courtesy of Steelcase

We worked with a client who was experiencing record-positive survey results. Unfortunately, this didn’t match with the feedback we were hearing in interviews and focus groups. The discrepancy was key. With investigation, we learned work team leaders were incenting their teams to provide positive survey feedback. The survey feedback was prioritized above the experience that the leaders were seeking to create for employees. The patterns of data were important and the lack of alignment between the quantitative data and the qualitative data pointed to insights that were critical to improving the design of the employee experience.

When determining what big and thick data to collect, consider the following:

  • What is the vision for the future and which data can help inform it? Always start with the desired outcome and work backward in order to determine what and how to measure.
  • What is the story we want to tell from the data? Stories are more persuasive than any level of raw data, so consider which data will contribute to the most powerful anecdotes and the stories that point to the desired outcomes.
  • Which are the best listening posts to utilize? Consider where and how often data should be collected?
  • What is the minimum necessary data? The Goldilocks Rule works best here: when designing for a data collection strategy include as much as necessary and as little as possible toward the simplicity on the other side of complexity.
Image courtesy of Steelcase

In the end, big data and thick data will change the way we make sense of the world and make decisions for the future, but the data is still only the data. The real focus needs to stay on people, their experience, and the decisions that will most effectively contribute to a powerfully positive work experience.

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  1. Tracy, I agree, big data holds big promise! We definitely are seeing an increase in activity with companies responding to the impact big data has made on their business. For companies of any size, getting meaningful insights from data analytics is an important priority. HPCC Systems ( is one of the open source big data platforms with built-in analytics libraries for Machine Learning to help extract useful insights from data. Designed by data scientists, HPCC Systems represents more than a decade of internal research and development in the big data analytics field. For a compelling case study on Marketing big data, visit

  2. Thanks for your comment. Yes, big data and thick data are full of potential as long as insights are generated (versus the data being a significant burden). Our lens for interpretation is important as well. I saw an interesting article recently that talked about ‘fat data’ and ‘data spills’ ( — which are interesting concepts. As data proliferates, we have a lot to figure out in terms of its collection, interpretation, use.

  3. By now, every marketing organization, agency, and administration has heralded a “Big Data” Initiative. While these algorithms generally provide marketers a mass volume, variety, and velocity of real-time data to improve customer experience and drive marketing impact.Today’s technology is more complex than the tools of the past, but the guiding principles for your data remain the same.

  4. I agree, Addy. Volume, variety, and velocity have increased so much — and all of that is just additionally burdensome unless we can interpret and derive people-focused insights from the data — which is so much more important than just more, more, more data!

  5. Big Data is trending nowadays. IoT is also on the way to create a hype for big data.9 different physical settings of IoT will generate a huge amount of data.AI is going to handle the processing of data. This is time to take initial steps for creating more value by utilizing these technologies.

  6. I agree, John, on all counts. IoT is reinventing the way we understand the workplace and its effects on people. We have a huge opportunity to create experiences that in turn create value!


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