Big Data, Facility Planning and Quantum Mechanics

What could these three things possibly have to do with each other?
A fundamental concept of quantum mechanics is that the position of sub-atomic particles like electrons orbiting the nucleus of an atom is defined as a probability function… and when we started thinking about how to measure people moving through a building, the models became eerily similar.

Designers, architects and facilities teams are always striving to create spaces that align to the activity of the occupants.  Over the years, we’ve built models based on surveys, counting people, and time studies, but all of these models tend to fall apart because:

• What people need today isn’t what people will need tomorrow
• Work styles change due to technology like laptop computers and Wi-Fi, as well as new practices like AGILE
• How people use space is influenced by the space itself

So a building that lasts for decades is designed and constructed based on data from a snapshot in time that’s probably out of date before the doors open.

Enter IoT, Big Data, and Cisco’s Connected Mobile Experience (CMX).  By using the Wi-Fi signals from the cell phones, laptops, and tablets of the occupants of the building, combined with other data sources such as security system badge-in data, Outlook Meeting data, and other facilities information, we can create a model of building utilization over time – a quantum mechanics probability function that tells us how many people are in a space at any given time.  This model is more accurate than any one of these individual data sources, and the error continues to decrease as we gather more data over time.  All of this data for over 40 buildings and almost 7 million square feet of Cisco’s global facility portfolio is being collected and analyzed in Optimo, a Software-as-as-Service (SaaS) tool from Cisco Solution Partner Rifiniti.  This solution provides facilities teams the ability to quickly visualize the data on demand as needed during building designs, people movement discussions, and conversations with business leaders.

The output of the model is a building heat map that shows how individual work spaces are used.  This heat map can then be used to answer these long unanswered questions, and lead to action plans to improve utilization by:

• Moving people based on actual availability of space
• Changing space configurations – from furniture to hard walls
• Bringing teams who collaborate extensively into the same physical space

For example, if we construct a meeting room with an occupancy of 12 people, but the average utilization of that room is only 4 people and the peak is 6 people, then we can propose splitting the room into two rooms.  These two new rooms will end up with higher utilization and provide the occupants a new collaboration space.

The key success factor – and the difference from prior measurement solutions – is the ability to leverage CMX.  By using the Wi-Fi network, there is no need to install additional sensors or to upgrade the building automation or lighting systems (although we can and plan to integrate those data streams as well!).  There is also no addition of stand-alone sensors which often require batteries that need to be monitored and replaced.

So what’s next?  We continue to add buildings to the system as well as looking for other existing data streams which will enable us to collect occupancy and activity data at little to no cost.  An example is leveraging video endpoints and security camera analytics to provide people counts. And as we add these data streams, we continue to deliver more accurate and timely information for our facilities management processes

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