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How to use big data to improve NOI in commercial office buildings

While mining big data in stored information for business intelligence is not a new idea it offers a new way for building owners and portfolio managers to identify trends to maximize profit. ?

The majority of data in the commercial real estate industry is currently being both generated and stored by third-party sources who may provide services such as optimizing building management systems for efficiency.

However, in order to fully harness the potential from data generated in commercial real estate office buildings, owners and portfolio managers are starting to manage their own data.

Why do you need to manage your own data?

Managing your own building?s data empowers owners to make decisions that directly impact their users such as improved tenant experience, enhanced asset utilization and can reveal hidden business opportunities.

While third-party providers may be collecting valuable data they are likely to have a siloed approach and often remain focused on providing analytics and insights directly linked to the service they provide, which may not fully actualize the use of the stored data. ?

Combining data from different sources is one of the most effective ways of identifying trends and finding hidden sources of revenue or improving tenant experience and by managing their own data building owners can better identify profitable trends, ?how to best utilize assets and where to devote resources in the long-term.

Big data analytics add exponential value in procuring tenants

The commercial real estate industry handles a plethora of information that requires efficient management such as market statistics, design specs, client relations and legal documentation. All these are different groups of data that must be organized and tied together.

Marketing commercial properties to potential clients can become an easy and streamlined process through a well-managed data strategy as information generated from tenant leads, client feedback and competition are synchronized and consolidated into one place.

One of the biggest problems in the tenant journey of renting commercial space remains the inability to visit properties or the multitude of properties that one needs to search in order to make a decision. ?

Portfolio managers are using big analytics to provide property availabilities by offering an interactive visualization of the space – this could not be accomplished without having an internal data management system. ?

A well-managed information flow also turns employees into experts in the information they manage. Data analytics provides leasing professionals with accurate information that leads to faster tenant acquisition.

Imagine if legal documents can be made available instantly to leasing professionals enabling them to address concerns from potential tenants in real-time rather than having them wait for answers and postponing a potential transaction.

Unlocking value from unstructured data in commercial office buildings

Unstructured data or data that does not follow a specified format accounts for nearly 80% of the data to available to enterprises and a much smaller amount 20% is available is in a structured form. ?This means that the majority to data collected by commercial smart building applications is in a structured format and a large portion of unstructured data is left uncovered.

Examples of unstructured data include satellite images for weather data from sites like Google Earth, data from photographs and videos of security, surveillance, and traffic patterns or internal texts which include everything from documents, logs, survey results, e-mails text from social media sites and mobile messages and user location information.

Until recently, the technology didn?t support doing much with it except storing it or analyzing it manually. ?However, now through the use of machine learning and artificial intelligence companies are uncovering ways to leverage unstructured data to their advantage. ?

While the uses for unstructured data are exponential let?s take a look at a few examples to understand how building owners can leverage unstructured data to improve tenant outcomes and NOI.

Examples of value derived from unstructured data in commercial office and construction

Monitoring the real-time pedestrian traffic both inside and outside office buildings and vehicle statistics can prove to be a powerful tool for attracting tenants especially when marketing to the retail sector. ?By layering traffic data with internal accounting systems owners can better assess whether and how much to increase lease rents- unlocking a new way of valuing their spaces.

The construction industry is also using unstructured data to make important decisions in construction management.

In the construction process data sets from environmental conditions, social media discussions and stakeholder input are not only used to determine what to build but also where to build. ?

For example, Brown University in Rhode Island used big data analysis to decide where to build its new engineering facility for optimal student and university benefit. ?The university used scientific and systematic data not only in the construction process but to also understand the building?s educational end use to determine the best place to put the building based on information collected from both the university and students.

Big data analytics can enable or offer opportunities to improve virtually any aspect of commercial real estate whether assessing risk levels or future outcomes big data offers insights that traditional systems simply cannot.






 

 

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