It is not just the massive volumes of data- it is the mix of structured and unstructured data that is both a barrier and a potential answer to reduce the costs of remedial work.
Snagging lists lead to remedial work that cascades between main contractors and down layers of subcontractors. Too often, descriptions are misunderstood and the remedial work not completed satisfactorily.
Not even mentioned variations; the agreement to "out-of-scope" additional time and materials are major projects proceed.
Video and photographic data, augmented by free-text commentary- no wonder all parties are forever arguing to whether work id finished and delivered to spec. That in turn leads to the fractious issue of retentions that suck out cash from every business.
Big Data Analytics must be able to ingest and visualise the massive volumes and velocity of data from structured and unstructured data.
And make sure it is not just the Project Management Office that views the 10, 20, 30 KPIs vital to any huge construction undertaking. Make sure all people can view these on whatever device they need:-
- Quantity Surveyors
- Site Foreman
- Board of Directors
- Facilities Managers
- Health & Safety
- Contract administrators
- Site Access Managers
Collaborative Big Data Analytics for everyone involved so it must include self-service analytics on a secure and scalable platform. imagine the outcome if the 35% were reduced by just 5% points?
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The construction industry is responsible for undertaking some of the biggest and most expensive projects on Earth. Huge amounts of resources and work go into construction projects which means that huge volumes of data are generated. Number crunching has always been a big part of construction – a commonly heard phrase is "construction companies are accounting companies which happen to erect buildings" 35% of costs are accounted for by material waste and remedial work. So counting the cost of every screw could be the difference between delivering on budget and bankrupting an organization (or several ) financing a build. Even though analytics has always played a part in the sector is it lagging behind other industries such as retail and financing. More advanced analytics and Big Data are just now finding their ways into the sector.