The Four Cornerstones of a Sound Data Foundation

Guest blog by Patrick MacDonald, Group Manager – Real Estate & Security at Microsoft

For a large organization with a diverse global facilities portfolio, real estate data can hold insightful answers to the biggest questions about their assets. Who wouldn’t love a daily dashboard or weekly report that reveals exactly how a property’s amenities are being used, whether its space utilization aligns with corporate strategy, or exactly where every person sits in every building?

Unfortunately, many corporate real estate (CRE) data systems seem designed to actively block this objective. Extracting and collating relevant data can take weeks of trawling through multiple, often disconnected, databases that each have only a piece of the story. Ad hoc linkages made by users seeking their own answers, and content copied to local drives for manipulation, often lead to data that is duplicative, conflicting, missing, inconsistent, and outdated—and thereby unreliable. Without a strategic data plan and foundation that ensures their data and sources are accurate, timely, and trustworthy, many companies miss out on the best potential of their CRE metrics.

The real estate group at Microsoft had faced similar database dilemmas for years, so we took a hard look at data warehousing, data mining, and analytics to help us find the answers. We moved beyond just “making easy-to-use reports” and focused on establishing a sound CRE data foundation that stands on four cornerstones—standardization, a single source of truth, self-service business intelligence, and a data-fluent culture. The result has been a highly accurate, trustworthy data system that empowers our CRE teams to make well-informed decisions every day.

The first cornerstone, standardization, yields “clean” data and sources that reflect your master data strategy. You make critical decisions such as which data to retain and how it looks; which data must map between interdependent systems such as HR and real estate; which source takes precedence as the “real truth” for each data point; and which business rules and roles govern the data’s authenticity, accuracy, and potential issues.

Standardization of data and its rules ensures that everyone is working from the same set of clean, consistent, and accurate content, increasing the reliability of analysis results.

The second cornerstone, a single source of truth, means having a consolidated data warehouse that contains one copy of all the data from which all users and systems draw. Certain groups “own” their part of the data warehouse (e.g., at Microsoft, HR owns all people data, CRE owns building data, accounting owns financial data), and they are solely responsible for that data.

A single source of truth gives people one source of data instead of many. Users can trust what the truths are—and where they come from—as they share, search for, and analyze the same data. People no longer need to copy a database locally, and they are prevented from creating ad hoc mappings between databases, both of which contribute to data consistency.

The third cornerstone, self-service business intelligence, involves understanding who uses the real estate data and why, then empowering them with direct access to the data they need to do their jobs, in ways that suit their workstyle.

Our portfolio managers, for instance, receive an automated report that refreshes every day from the same data source, so they can track status and trends. Filters, levers, and switches enable them to tweak the information for custom analysis. For those who prefer to dig into data themselves, we provide a tool that pulls data into Excel and lets them do pivot tables.

The final cornerstone, a data-fluent culture, is about finding ways to get people to engage with the new data warehouse, the self-service model, and the value-add that working with data can bring.

Centralized communications vehicles are useful for disseminating such information, and at Microsoft we got creative with open Q&A forums and entertaining newsletters that invited people to “think outside the box” when interacting with actual real estate data. (Think playing “Where’s Waldo?” using a database.)

Most critically, we built connections between those who gather the data and produce the self-service reports and those who need the data to run the business. These employees now work together to develop the value-add of the data itself—such as deciding what other information to include in reports and exploring new ways to view information for insights.

At its core, achieving actionable business insights from CRE metrics is less about how a final report looks and more about the hard work of building a sound foundation for gathering, cleansing, and reporting all your organizational data. Regardless of which tools and technologies you use, investing in the four cornerstones described here can position your enterprise to extract the full potential of its CRE metrics.

Patrick MacDonald is Group Manager – Real Estate & Security at Microsoft