top of page

Power of Data-Driven Design For Future At Work

At PHI Space, we believe that collecting and analyzing data is key to creating better designs and user experiences.

When tasked to develop a design for a cafeteria space in a commercial office building in Hyderabad, our design approach started with understanding data.

What is typically restricted to occupancy and square footage, was expanded into several unique data points like details on user demographics- like age, gender, background, interests, spending power

  • Various requirements in terms of operators- F&B, Wellness, Lounges etc.

  • Space opportunities- addition of amenities, open areas, access, visibility.

  • Movement within the space- duration of stay, frequency, timings and preferences for seating.

  • Sustainability and smart solution Integration- operational requirements, carbon foot-printing and evaluation of relevant integrated solutions for occupancy sensors, air quality etc.

  • Data points related to costing- long term capital spend versus operational expenses.

The result was the transformation of a 10,000 sq.ft. monotonous cafeteria into a dynamic location- capable of servicing the needs of occupants across a diverse range of spaces. The cafeteria, deli and executive lounge address the F&B requirements as well as provide opportunities for collaboration and cross-pollination, as identified through the analysis of several data points.

A transformation inherently lent a sense of identity to an otherwise characterless cafeteria space. A vibrant and upbeat space incorporating various design elements that create interest and an enhanced experience to the user.

With a focus on biophillia and sustainability, the materials used in the spaces and curated internal landscaping echo the sentiments of occupants around wellness in the workplace.

We believe the success of delivering a powerful spatial experience comes from this deep understanding of what users want and translating it into a floor plan and design- perhaps the most important factor to bring people back to work, over the course of the next few months.

bottom of page