Data Governance: A Critical Component of Good Workplace Management

By Kane Hochster
Chief Sales Officer

Every business collects data of some kind. Small companies may keep customer records in spreadsheets while global organizations use multiple systems to manage everything from HR data, sales, assets and workplace management. 

But having data doesn’t automatically mean the reports gleaned from that information are accurate and actionable. You know the saying, “Garbage in, garbage out”? Businesses may be great at collecting data, but is it the right data? Is it being used to meet objectives? 

“Inaccurate data means you’re basing decisions on bad information, which may mean building a workplace that doesn’t meet employees’ needs or drains facility management budgets,” said Kimberly Castle, account director with Buildingi, an IWMS/BIM consulting firm said. “You may also be leasing too much space because bad data shows that 15% of your workforce doesn’t work in the physical office anymore – when the true figure is much higher.”  

Many businesses are learning a hard lesson as they navigate their ongoing responses to COVID-19. The constant flux of COVID safety mandates puts greater emphasis on the need for real-time data to create processes to meet those standards. Companies must rely on accurate reports to make decisions on everything from maximum allowable occupancy for conference rooms to workstation spacing to where to position contactless circulation pathways. As work from home policies persist, most firms will seek to adjust their portfolios and add flexibility to promote workplace choice. That’s where a robust data governance system comes in. 

For clarity, data governance is not the same as data management. CIO Magazine defines data governance as: A system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.” Data management is the logistics of collecting and storing information – a must for data governance to work. 

Bob Sits Where? 

Fellow Buildingi account director Amber Miller once helped a client combine an integrated workplace management system (IWMS) with an HR system. This common integration is designed to make it easier for users to update where they sat, so the HR platform was populated with a list of room numbers. 

“But then we started noticing anomalies, like people being assigned to a bathroom or hallway. We had to go back and have the client apply data governance rules to limit which types of seats and rooms were approved for the data feed,” she said. 

Then there’s the issue of corporate tech systems not speaking the same language. Castle was helping a large life insurance company integrate data from multiple systems. 

“There were all these terms that had a different meaning in every system. For example, the definition of ‘full-time employee’ or ‘headcount’ wasn’t the same across the board,” she said. “And that was a problem because data reports would get sent to the CEO with glaring discrepancies.” 

 Think of it this way: One person may collect and store information (data management), but a large number may access it, run reports, and use those details to make strategic decisions. If one person alters or uploads inaccurate data, the change effects everyone downstream. That can cause big problems if your job is reporting compliance levels to regulatory agencies or preparing a company’s tax returns. 

“It’s one thing to collect and track data, but if there’s no data integrity, you’ll simply get ‘garbage-in and garbage-out,’” Castle said. “Technology allows us to automatically flag where things don’t match; a tight and consistent data governance program is key to getting everyone on the same page.”  

Data Governance and COVID-19 

The ups and downs of COVID-19 is creating a new urgency for companies to collect data on and analyze employee movement in the workplace. Data on occupancy, furniture arrangements, and desk reservations is a starting point for health and safety measure implementation. But without rigorous data governance, employee movement and contact tracing information are unreliable.    

“Before COVID, the industry focused on ‘butts in seats,’ or how many people are assigned to a building. But the challenge during the pandemic is that’s no longer an accurate way to measure occupancy,” Miller said. “For example, an employee can be assigned to a desk, but they aren’t coming into the office every day. We’re now looking at utilization in terms of users in building vs. users assigned to seats.” 

Floor-to-ceiling elevation is one metric that’s been impacted by COVID because it impacts air quality and flow, Miller said. Before the coronavirus forced everyone to think about ventilation in new ways, space planners didn’t have cause to look across a floor layout. Now, data that was once used almost exclusively by facilities is being analyzed and acted upon by executive management, HR, and other departments. 

COVID-19 has put greater emphasis on why data governance is the foundation for quality workplace data management. Companies are asking questions of data sets that weren’t in the original parameters, searching for answers that will ultimately keep businesses open and employees safe. As organizations look beyond the pandemic, better data governance is critical for making confident and productive strategic decisions about workplace management now and into the future.  


The Importance of Data Integrity in Corporate Real Estate (CRE)

As a corporate real estate leader, you need accurate, precise data—often in real-time—in order to make critical short- and long-term business decisions. Whether you’re trying to boost productivity by co-locating business groups or negotiate for better lease options, it is imperative to have data you can trust.

Data integrity refers to the quality and reliability of the data: in a nutshell, is the data extracted and communicated in a consistent and rigorous format? Understanding the importance of data integrity, and how to maintain it, is especially crucial when you’re using a tool like Serraview, which takes in data from multiple outside sources, such as your IWMS, entry sensors and other IoT devices.

If data integrity isn’t maintained, you won’t be able to make evidence-based business decisions. Either you won’t get data at all because of an issue with the systems sending and receiving data, or the data you do get won’t be accurate or valid.

The Three Pillars of Space Planning Software

Before we examine how to verify data integrity, let’s review the “three pillars” of space planning:

1. Gathering Data

In today’s workplace, data comes in a variety of forms: space management information, space utilization data, cloud and network usage, building systems and utilities, employee productivity and engagement, and more. You need a robust tool (or tools) to collect and aggregate this mountain of data.

2. Analyzing Data

A tool like Serraview is able to conduct the important first level of analysis on this aggregated data, allowing you to see accurate, real-time reporting about space usage and more. Other effective tools employ data science and machine learning to identify patterns and compare real-time with historical data to better inform your decisions.

3. Taking Action

Armed with this analysis, from a CRE perspective, your next step is to look at it critically and ask questions. For example: Do your group allocations make sense, or are people randomly split up from their team? What’s causing the conference room shortages that seem to happen every Thursday?

Once you go after these next-level insights, you’re able to make evidence-based decisions to improve your workplace.

A Data Contract

When one system takes in data and then sends it to another system for aggregation and analysis, there needs to be a shared understanding of the content and formatting of that data.

Serraview creates a “data contract” that documents what kind of data the system will receive and from where. The system checks all the data it receives to ensure it conforms to this expectation. If the data Serraview gets is inconsistent in some way, it will either request to resend the data or alert the user that there is an issue.

Ensuring Data Integrity

Serraview, and the systems it receives data from, typically uses a checksum hash function on all data to ensure this data contract is being upheld. The sending system takes its large file of complex information, runs it through the checksum hash function, and gets a simple label (like “12345”). It sends the data file and label to Serraview, which runs its own checksum hash function. If Serraview gets the same “12345” label, it will accept the data. If not, it will reject it and either request it be resent or alert the user.

The Right Amount of Flexibility

When there are issues with data integrity, you generally have two options. First, you can go back to the sending system and correct the data it collected. For example, if your IWMS collects HR data on new hires and sends it to Serraview as part of the space utilization analysis process, and you discover the manual data entry was done incorrectly. The data can simply be re-entered and re-sent to Serraview.

Second, Serraview’s settings can accommodate a certain level of variation in the data it receives. You might be switching to new entry sensors, and the old devices send whole numbers (10) while the news ones are slightly more precise (10.0). Without some degree of artificial intelligence and flexibility, Serraview would unnecessarily reject the data it’s receiving from the new sensors.

Good Business Decisions Reinforce the Importance of Data Integrity

Maintaining data integrity is a cornerstone of Serraview’s development. Without a system that rigorously maintains high standards for your data, you can’t obtain any meaningful analysis to make strong decisions.

But technology can’t do all the work—the individuals using the data to make decisions need to have some knowledge about the context. If the reports and analysis you get seem off, you must determine:

  • Is the data received from an input system corrupt?
  • Is the system rejecting accurate data because it’s not being flexible enough?
  • Is the system being too flexible and accepting bad data?

The human side of maintaining data quality involves thinking critically and asking questions. To make sure your technology and systems are conforming to your expectations and standards, you should run periodic checks and audits to verify and validate the data you’re getting. If you are working with bad data, these will help pinpoint the source so you can correct the issue.

To ensure the data being entered into Serraview is valid and accurate, there’s a built-in CRM system that allows individual business units to review and validate their allocations, saving the CRE team from doing manual walk-throughs. Companies can create their own processes to ensure data gets reviewed and validated on a regular basis, and the system can also provide reports on whether or not that happens, so the CRE team is informed and can follow up directly with department heads when needed.

Interested in collecting more, and better, data so you can make strong, informed business decisions about your workforce and workplace? Download our guide to workplace utilization data and discover how IoT and other technologies provide insights.


How Big Data Is Changing Corporate Real Estate

How’s this for some almost incomprehensible numbers: It’s been reported that 90% of the data in the world has been generated in just the last two years. We are currently creating 2.5 quintillion bytes of data daily—and that rate is accelerating. (1 quintillion has 12 zeros, in case you were wondering.)

Big Data has infiltrated every industry and every organizational group. Big Data in real estate is no exception. It’s reaching our personal lives in ways many of us don’t even realize yet. And it’s not groundbreaking to predict that this trend will only continue.

Because of the rate at which Big Data is growing and the incredible number of ways it can (and will) be used, it’s important to take a step back and seek a greater understanding of what types of data are being collected, how it’s gathered and analyzed, and how it can best be used by organizations. All those quintillions of data points mean nothing without the ability to capture, review, and analyze them effectively and, ultimately, use them to make informed business decisions.

The Limits of Big Data for Real Estate

For the past several years, Big Data has been touted as the solution to every business problem. If it’s not solving your problems yet, it will soon—or so we’ve been told. And so, many corporate real estate leaders have focused primarily on capturing and gathering as much data as possible, through IoT sensors, building management systems, and employee management systems.

What IoT integrations provide the most value for space planning?

Now, however, companies have huge amounts of data without the means of effectively analyzing it. Raw data, without analysis and context, isn’t useful when making business decisions. Companies may try to build an in-house team to get a handle on the data coming in, but without training in how to work with Big Data, most of what those teams do amounts to guesswork and science experiments. This is why working with a vendor or platform that specializes in data collection and analysis, like Serraview, is so crucial.

Part of the problem companies face is that we are still figuring out which data is the most valuable for corporate real estate. We know that looking at desk assignments and space usage in real-time can provide actionable insights, but when we started to combine that data with, say, information on air quality from building systems, we found patterns we didn’t expect. In other cases, we found solid evidence to back what we’ve suspected for years—that air quality can impact the health, happiness, and productivity of employees. With this knowledge, you can work with your building maintenance team to optimize your building’s environment.

Know What You’re Looking For

With Big Data, it’s really easy to get caught up in the latest shiny object. A new sensor or beacon comes out that measures X and you become obsessed with measuring X without first questioning why you want to measure it or what insights it will provide. When it comes to Big Data in real estate, you need to stay focused on the questions you’re asking—otherwise you end up wasting time and money. After all, if you’re making an apple pie, you’d be wasting your time trying to harvest all the raspberries you can find.

Why is space planning so important for corporate real estate?

Some questions you may consider include:

  • How do people in my organization work together or collaborate?
  • How are they using the space?
  • What does a day in the life look like for different people or teams in my organization?
  • What tools are they using and how?
  • How is technological collaboration happening?

Staying clear and focused on these questions will help you seek out the data that will be the most valuable and provide the best insights.

Using Big Data Strategically

The strength of a tool like Serraview is to take all that data you’re collecting—from sensors and beacons, other software platforms, and systems—and make it useful and actionable. You still need to ask the right questions and think critically about the analysis Serraview provides, but it makes the process more efficient.

Want to learn more about how Serraview helps corporate real estate leaders make evidence-based business decisions? Request a free demo today.


How Data Visualization Can Help You Save on Real Estate Costs

Doesn’t everyone love good data visualization? Cool infographics and colorful charts look great on slide decks or websites, but once you have that pretty visual aid, what do you do with it?

Here’s how real estate data visualization tools like Serraview help you take huge amounts of data and actually use it to make business decisions.

What Data Does Serraview Help You Visualize?

A data visualization tool like Serraview makes it easy to see:

  • Visual breakdowns of the number of employees in each department vs. the number of allocated workstations or desks
  • A team’s occupancy with its target ratio
  • Heat map indicating utilization of your space in a specific time frame
  • Which teams have fixed seating, flexible seating, or a combination of both

When viewing the data, every team member is color-coded (so, for example, everyone in the Finance department is orange, everyone in Marketing is green, etc.) and you can easily drag-and-drop different individuals or whole units to help you visualize potential moves. The color-coding also makes it easy to drill into the data for a specific department to get deeper insights.

In Serraview’s Portfolio Manager, get a quick snapshot of allocations by department on each floor, or view each floor’s layout for a detailed look at who sits where.

With Serraview, you can also simulate different scenarios, like setting different target seat ratios or whether fixed or flexible seating may be best for your organization.

One of the biggest strengths of a robust data visualization tool is that you can visualize different data sets instantly, in real time—the software has done all the work of gathering and analyzing the data, and both the data and the analysis is contained within the system. Instead of manually downloading and manipulating Excel spreadsheets, you can skip ahead to the step of using the data to make strong, evidence-based decisions. This reduces the risk of introducing errors in that Excel manipulation and when a piece of data changes, you don’t have to download a new file and start over.

Read more about what kind of business decisions you can make with good data.

What Can You Do with the Data?

Your data visualization tool will help you understand how people use your space and see trends—and once you start doing that, you can find opportunities to optimize your workspace, save money, and even help your employees be more productive. You can start to ask and answer questions like:

Consolidate or Expand?

Are you using your space efficiently? You may look at consolidating teams and/or space and save on real estate costs when your lease is up.

On the other hand, if you are planning to grow and hire 50 more employees in the next 6-12 months, you can start to plan ahead and visualize different floor plans and layouts to make sure everyone will have enough space to work comfortably.

What workplace data can help you use your space more efficiently?

Are There Co-Location Opportunities?

In many companies, it’s common to put certain teams (Sales and Marketing, for example) near each other because people assume these groups have a natural affinity. But the data may reveal that the Marketing team actually spends more time with the Product team—and those groups are about as far away as they can get. Moving them closer together means they spend less time walking to and from meetings and increases opportunities for “water cooler” conversations.

How Many Conference Rooms and What Size?

As we have moved into the knowledge worker’s world, conference rooms and other collaborative spaces have become more important than ever. However, many offices still adhere to traditional (old) industry standards that dictate, for every X employees, you have a set number of small, medium, and large conference rooms. These standards don’t take into account every organization’s different needs—the truth is there’s no “one size fits all.” Your data visualization tool will help you determine the optimum mix of spaces and sizes for the needs of each department.

Serraview’s Heatmap view shows the most and least-used areas of your workplace, allowing you to ask higher-level questions about utilization.

Potential Pitfalls of Data Visualization Tools

Like we said at the beginning, everyone loves cool infographics and colorful charts. But your data visualization tool is just that—a tool that needs to be applied with critical thought. Watch out for these common pitfalls:

Assuming the Data Is Flawless

Imagine you’re looking at a visualization of desk assignments by team. You notice that most of your Accounting team is on the third floor, but one person is assigned to the second floor. Is that person there by mistake, or is your HR data incorrect? Maybe she started in Accounting but recently transferred to Sales. You might be surprised by what your data shows you—but avoid immediately jumping to conclusions or skipping the obvious questions.

Jumping to Action Too Quickly

Once you have the data, the next step is to ask questions. Don’t just start moving people and re-assigning teams based on the visualization alone. Using the example above, your first step shouldn’t be to immediately re-assign that person but to get more information. Is she there by mistake? Is there a reason that she’s separate from the rest of the Accounting team? Keep an critical eye out especially for these oddities—asking the right questions will, in most cases, lead to a deeper understanding of how people use your space and help you improve and optimize it.

Want to see Serraview’s data visualization tools in action? Request a free demo here.