{"id":27055,"date":"2023-01-02T16:02:24","date_gmt":"2023-01-02T16:02:24","guid":{"rendered":"https:\/\/mailinvest.blog\/index.php\/2023\/01\/02\/machine-learning-takes-on-the-all-too-human-discipline-of-space-planning\/"},"modified":"2023-01-02T16:02:24","modified_gmt":"2023-01-02T16:02:24","slug":"machine-learning-takes-on-the-all-too-human-discipline-of-space-planning","status":"publish","type":"post","link":"https:\/\/mailinvest.blog\/index.php\/2023\/01\/02\/machine-learning-takes-on-the-all-too-human-discipline-of-space-planning\/","title":{"rendered":"Machine learning takes on the all-too-human discipline of space planning"},"content":{"rendered":"

<\/a>\n
<\/p>\n

\n

Chris Lord relates the story of a space planner at one higher educational institution who faced a conundrum: Plenty of square footage had been allocated for study space, but students were complaining that there weren\u2019t enough places to sit.<\/p>\n

Both sides were right. The university had equipped the space with large trestle tables that seated six people, but it turned out that if just one person was sitting at a table nobody else would. The solution: Place houseplants in the middle of the table to divide the space and create a perception of privacy.<\/p>\n

In short, the space plan looked good on paper but didn\u2019t account for human behavior. That\u2019s a bug Boston-based Lambent is hoping to fix.<\/p>\n

Thanks to mobile phones, smart cameras and Wi-Fi, it\u2019s now possible for organizations to gather fine-grained anonymous data about how space is used to inform smarter planning decisions.\u00a0Lambent, where Lord is chief technology officer, is out to apply machine learning to the process.<\/p>\n

There\u2019s plenty of room for improvement. A recent survey<\/a> the company conducted found that 75% of space planners believe people ask for more space than they need and 90% of senior leaders say they don\u2019t have the data they need to make smart decisions about space planning.<\/p>\n

\u201cIt\u2019s not about reducing the amount of space that we have,\u201d Lord said. \u201cIt\u2019s about making sure that that space fits what employees or students need from it.\u201d<\/p>\n

COVID-driven shift<\/h3>\n

Lambent, which is the business name of Armored Things Inc., shifted its strategy from public safety<\/a> to data-driven space planning in the wake of the pandemic. Launched in 2017, the company initially set out to apply analytics to crowd control but it discovered that the bigger opportunity was in the more prosaic area of helping businesses create more efficient workplaces.<\/p>\n

\u201cIt\u2019s the same core technology under the covers, but it is now being applied to a very different set of problems,\u201d Lord said. \u201cPeople who manage spaces need more than just an understanding of how many people are in an area. They need to understand how that relates to how that space is used.\u201d<\/p>\n

COVID-19 complicated the picture.\u00a0Businesses and universities have struggled to understand what the long-term impacts of social distancing and remote work will be on the workplace. Lambent\u2019s survey found that 86% of corporate space planners believe managing a return to work has been a challenge.<\/p>\n

Failure to gather data creates inefficiency and waste.\u00a0For example, businesses often allocate ample space for conference rooms but don\u2019t check back late on how that space is used. \u201cThey need to look at how many people are in the conference room relative to capacity,\u201d Lord said. \u201cIf people are popping in just to take a phone call, then that\u2019s an ineffective use of space.\u201d A better solution in that scenario would be to install small phone booth-like spaces where one or two people could take a call.<\/p>\n

Lambent is applying machine learning to analyze data culled from devices that permeate the workplace and passively track the whereabouts of people. \u201cIt\u2019s about taking those small signals sprinkled across the space, fusing them together and turning them into that big-picture understanding of how many people are there,\u201d he said.<\/p>\n

Lambent says one\u00a0university customer used the platform to analyze its use of centrally scheduled instructional computer labs and determined that nine of the labs could be replaced by virtual learning experiences, saving $2 million in rent over the next several years.<\/p>\n

Machine learning can make intelligent predictions about where people are even if their devices aren\u2019t visible. \u201cYou can infer where people are based on where you\u2019ve seen them in the spaces where you have coverage,\u201d he said. \u201cThe data comes from instrumentation that lives in the environment already. We call it \u2018dark data\u2019 and in most cases, nothing is being done with it.\u201d<\/p>\n

Behavior change<\/h3>\n

Analytics can not only improve space efficiency but influence workplace practices. For example, knowing that people are more likely to come into the office for meetings rather than to work at a desk can guide decisions about how to allocate collaboration space. Empty offices on Mondays and Fridays caused by people extending their weekends may prompt a company to offer incentives such as pizza parties on those days.<\/p>\n

\u201cThe more advanced customers care about pulling people into the office, giving them a reason to come in\u201d and not demanding what days they should be there, Lord said.<\/p>\n

Simply observing behavior or scrutinizing conference room reservations can be misleading. \u201cUsing poor signals is going to inform the wrong actions,\u201d he said. \u201cYou know that the conference room was booked, but not if it was booked for the capacity it can handle.\u201d<\/p>\n

Lambent says its platform aggregates data across a portfolio of spaces the organization controls and pulls it into a single view that can be filtered across time periods, space types or tags to make it easier to track the metrics that matter.<\/p>\n

The most advanced companies are rethinking the whole idea of fixed workplace design, Lord said. \u201cThey want to get to a point where spaces are not big capital assets that you invest in once,\u201d he said. \u201cThey are malleable depending on what you need this month or this quarter and what the teams and the projects demand.\u201d<\/p>\n

Photo: Unsplash<\/a><\/h5>\n
\n
\n

Show your support for our mission by joining our Cube Club and Cube Event Community of experts. Join the community that includes Amazon Web Services and Amazon.com CEO Andy Jassy, Dell Technologies founder and CEO Michael Dell, Intel CEO Pat Gelsinger and many more luminaries and experts.<\/span><\/h3>\n<\/div><\/div>\n