Lesson 1, Topic 1
In Progress

Utilising Data

Utilising data for manufacture and delivery, and machine-to-machine learning.

BIM brings together all the components that make up a project in the development stage, creating a common language, shared knowledge and increased transparency between all the parties involved, from the main contractor through to sub-contractors, specialists and professionals, it is knowing the need.
Both the receiver and provider may need information. Both require time and knowledge.

Why – Need data for lots of purposes, at all stages of the Asset’s life (Answer questions relating to the asset, location, satisfy legal and H&S responsibilities, does it meet the brief).

When – Once agreed, Receivers and providers must work collaboratively to establish when data needs to be exchanged (fixed date, milestones, frequency or a trigger event like maintenance event).

How – Once the why and when has been established, receivers and providers can then work collaboratively to establish how the data needs to be exchanged (the format, structure and naming, the means by which the data is to be exchanged).

What – Finally the receiver and provider must identify the ‘minimum’ amount of data needed to satisfy each purpose and opportunity, and for reuse in other capacities (What non-graphical, graphical and documents are needed).
BIM supported by Big Data analytics has the potential to revolutionise the way assets are conceived, designed, built and operated.

The success of BIM, however, depends on the effective integration of its three components: people, process and technology

BIM technology is a tool to help make the construction industry more economically and environmentally sustainable, and it plays a massive role in improving energy efficiency in construction. BIM assists contractors in visualizing each stage in the construction process, which streamlines the process and reduces waste. 
BIM uses the predictive technology of big data to help create more sustainable construction. For example, a subcontractor can use data from past construction projects to make a prediction that accurately estimates how much of a specific material is needed for future projects based on a plethora of different variables. This visualization capability reduces the amount of wasted time, labour, and materials on a project.
With the constant influx of data emanating from numerous sources, Big Data analytics provide a promising tool to support critical decision-making within data-rich environments.

Extracting true value from Big Data will require significant investments supported by a changed mindset and required skill sets.

Existing contractual models and the fragmented structure of the industry could hinder data sharing and analytics among different parties. This requires industry and academia to work together to develop and drive a business case for BIM-driven Big Data analytics for the industry.

Big-data analytics – for instance, of people’s behaviour or the infrastructure environment helps to optimize design decisions and enhances a facility’s operational efficiency. The engineering giant Arup, for example, combines various data-collection methods including mobile surveys, security camera footage, and traffic flow reports to inform and refine its design decision making in residential and infrastructure projects.
According to a study by The Boston Consulting Group, digitizing the building sector by using BIM to conduct a building-wide energy analysis can save up to 20% of energy costs. This number increases when looking at renovations of older buildings because of the traditionally energy-inefficient nature of the buildings. Using BIM energy analysis in these situations helps improve energy efficiency and reduce material waste, creating a more sustainable environment and benefitting everyone involved.
Introducing a data management approach that enables collaboration along with the other benefits, leading to cultural change in the mindset, supported by investments in technology infrastructure and skillsets, will act as a motivation to overcome resistance and sensitively handle re-organising working habits and protocols.
Using a Sat-Nav as an example.