{"id":2056,"date":"2025-06-12T17:28:59","date_gmt":"2025-06-12T17:28:59","guid":{"rendered":"https:\/\/footanalytics.com\/?p=2056"},"modified":"2025-06-12T17:40:23","modified_gmt":"2025-06-12T17:40:23","slug":"2056","status":"publish","type":"post","link":"https:\/\/footanalytics.com\/en\/2056\/","title":{"rendered":""},"content":{"rendered":"
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In new work models, flexibility has become the central axis<\/strong>. The office is no longer a place of mandatory presence, but a dynamic environment that must adapt to new expectations and ways of working. Presence is flexible<\/strong> (with a balance between individual freedom and defined attendance patterns), desks are shared<\/strong> (the number of workstations per person varies based on actual usage habits), collaborative spaces are growing<\/strong> (the office is being redefined as a place for meeting, exchange, and co-creation), and there is an elastic demand for resources<\/strong> (desks, meeting rooms, meals, etc.) that varies depending on multiple factors such as the day, the team, or specific events.<\/p>\n

In this context of constant transformation, the concept of the liquid office<\/strong> emerges: an adaptable, agile, and people-centered work environment that continuously responds to the changing needs of employees.<\/p>\n

In a liquid office:<\/h3>\n
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    There are no fixed workstations: spaces are reorganized based on actual use.<\/p>\n<\/li>\n

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    Space is conceived as a living resource<\/strong>, constantly evolving with team activity.<\/p>\n<\/li>\n

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    The employee experience is prioritized<\/strong>, combining areas for collaboration, focus, and social interaction.<\/p>\n<\/li>\n

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    Technology plays a key role<\/strong>, enabling the measurement, analysis, and optimization of every square meter.<\/p>\n<\/li>\n

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    It is not about static design, but ongoing management based on intelligent data and real behavioral observation<\/strong>.<\/p>\n<\/li>\n<\/ul>\n

    The liquid office is not a trend<\/strong>: it is the structural response to a work environment that demands adaptability, efficiency, and human connection<\/strong>.<\/p>\n

    In this context, traditional estimation methods \u2014 based on static ratios or calendars \u2014 are insufficient to capture the elastic and fragmented nature<\/strong> of space usage. To truly understand and anticipate demand, we must adopt more dynamic approaches<\/strong>, integrating real-time data and enabling segmentation by behavior patterns.<\/p>\n

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    The Challenge of Measuring Occupancy: A Practical Example<\/h2>\n

    Let\u2019s imagine a floor with:<\/p>\n

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      48 desks<\/p>\n<\/li>\n

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      4 meeting rooms<\/p>\n<\/li>\n

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      3 collaborative tables<\/p>\n<\/li>\n

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      3 informal spaces<\/p>\n<\/li>\n<\/ul>\n

      We want to know how many people use these spaces and how they use them<\/strong>. There are several ways to measure occupancy:<\/p>\n

      1. Optical Counting<\/h3>\n

      We use direct observation (people counting manually) or optical technology (sensors). This gives us a snapshot<\/strong> of space usage at specific moments. If there are 46 people on the floor and we count 48 desks, we might say occupancy is 96%.<\/p>\n

      But this measurement has limitations: we\u2019re counting people, not behaviors<\/strong>.
      How many are actually working there?
      How many are just passing through?<\/p>\n

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      2. Measurement via Devices Connected to WiFi<\/strong><\/h3>\n

      The WiFi network can detect connected devices and estimate occupancy 24\/7, without the need for sensors or additional investment. It is agile and scalable, but has some caveats: it may count multiple devices belonging to the same person (e.g., phone, laptop) and often includes people from other floors whose signal reaches the area.<\/p>\n

      In our example, the WiFi network detects 53 devices. It seems like occupancy is at 110%, when in reality, there may be fewer actual people working in that space.<\/p>\n

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      3. Foot Analytics: From Counting People to Understanding Behaviors<\/strong><\/h3>\n

      This is where Foot Analytics’ unique value comes into play. Our platform not only detects how many people are present, but also who they are, why they are there, and how they use the space<\/strong>.<\/p>\n

      In the same example: 33 people are actually working on that floor<\/strong>, 6 have come from other floors, 3 are visitors, and 3 are external personnel. The real desk demand is 33<\/strong>, not 46 or 53. That means actual occupancy is 75%<\/strong>, with 15 desks available<\/strong>.<\/p>\n

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      The Value of Data<\/strong><\/h2>\n

      Having access to data is essential for making decisions that lead to cost efficiency<\/strong> while also ensuring a satisfying experience<\/strong>. With the observed headcount<\/strong>, the space appeared to be properly sized. The raw WiFi controller data<\/strong> suggested that the floor needed five more desks to avoid saturation. But with segmented and interpreted data<\/strong>, we know that there are actually 15 surplus desks even during peak times<\/strong>, and that there are specific moments when collaborative spaces are unavailable<\/strong>. The office manager now knows they can assign 25% more users to this floor<\/strong> without causing overcrowding.<\/p>\n

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      Turning Data into Intelligence for Smarter Management<\/strong><\/h3>\n

      In a hybrid work environment, the office manager needs more than just raw occupancy data (i.e., how many people are present). They need to:<\/p>\n

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        Understand usage patterns<\/strong> to plan space availability.<\/p>\n<\/li>\n

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        Properly size and configure<\/strong> the number, type, and dimensions of desks, meeting rooms, phone booths, etc.<\/p>\n<\/li>\n

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        Provide a rich and productive office experience<\/strong> that justifies employees\u2019 decision to come in.<\/p>\n<\/li>\n<\/ul>\n

        By combining technologies (such as the WiFi network) with Foot Analytics\u2019 data intelligence<\/strong>, it\u2019s possible to measure accurately<\/strong>, segment by behavior<\/strong>, and optimize the space<\/strong>. Because it\u2019s not just about counting people \u2014 it\u2019s about understanding real demand to make better decisions<\/strong>.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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        In new work models, flexibility has become the central axis. The office is no longer a place of mandatory presence, but a dynamic environment that must adapt to new expectations and ways of working. Presence is flexible (with a balance between individual freedom and defined attendance patterns), desks are shared (the number of workstations per […]<\/p>\n","protected":false},"author":5,"featured_media":2054,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[20],"tags":[],"class_list":["post-2056","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-utilities"],"acf":[],"yoast_head":"\n- Foot Analytics<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/footanalytics.com\/en\/2056\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"- Foot Analytics\" \/>\n<meta property=\"og:description\" content=\"In new work models, flexibility has become the central axis. 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