Design to Value: the importance of data and analytics in building design and construction

This method proves crucial for clients with national or global projects requiring rapid execution..

There were many reasons for this approach:.Standard solutions allow for a greater level of design and refinement – if a solution is going to be used multiple times then the benefit of good design is multiplied and amplified.

Design to Value: the importance of data and analytics in building design and construction

It afforded us a far greater level of stakeholder engagement and buy-in than we would typically achieve for a one-off design (see below).This resulted in, for example, designs that were highly optimised in terms of layouts, space allocation, adjacencies and functional flows – which could then be deployed across the PETP programme and wider prison estate.It creates further efficiencies.

Design to Value: the importance of data and analytics in building design and construction

For example, the standard building types can be used across a range of sites.For each, the site-specific design activities can be focused on the placement of the buildings relative to each other, arranging orientation to minimise overlooking and overheating (for both the comfort of prisoners and to reduce energy use), maximise views of landscape, and so on.

Design to Value: the importance of data and analytics in building design and construction

It contributes to overall better design and allows designers to focus more of their efforts on solving the specific challenges relating to a particular site and context.

Standardised solutions lend themselves to efficiencies in construction and the application of DfMA.The need to focus on the future function of labs, rather than generic labs was clear..

The group agreed that opportunities to magnify the value output of laboratories lie within the broad spectrum of data, automation/growth in data processing, and smart technology and systems.Artificial Intelligence and Machine Learning offer transformational change in value creation.

Although there are some individual examples of its real-life deployment, we are at the start of an exponential curve.. A thread of discussion around the idea that systems could be self-validating created significant energy in the room, as well as friction between those who understood how transformational such a realised idea could be with those who saw the potential disaster.Regulators are clearly going to be either a key partner/enabler or barrier to smart developments.

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