The use of big data to improve built asset performance CE asset management task group, April 2017

Transcription

1 The use of big data to improve built asset performance CE asset management task group, April @UK_CCG

2 Introductions John O Brien Group chair LCMB Colm Quinn Group secretary @UK_CCG

3 Meeting objectives Share leading thinking and insights Share CE's members lessons learnt Update group on WLP+ project progress Capture key insights for wider @UK_CCG

4 The CE vision Improving industry performance to produce a better built @UK_CCG

5 Built assets and value Construction Design 100K Operation and Maintenance 1M 5M Business Costs 200M Outcomes M? Process Push User @UK_CCG

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7 Agenda for pm 25 th January 2017 How process can improve operational performance Examining the use of BIM, soft landings etc. to improve the operational performance of built assets 1.30pm 26 th April pm 12 th July pm 20 th September pm 24 th January 2018 The use of big data to improve built asset performance Integrating data systems Making existing built asset work Asset management summit Unlocking and using big data to improve built asset performance How to improve the performance of built assets by joining up data systems How to improve the performance of existing built assets Joining up guidance and insights for CE members to help differentiate their @UK_CCG

8 Agenda Innovative ways to use new technologies and analytics Dr. Pierre-Andre Maugis, UCL Centre for Science The Big Landscape by Paulina Zakrzewska, UCLH IOT: Digital Disruption in FM Jack Clough, Spica Tech The use of big data and data analytics to improve performance Milesh Patel, Iconics WLP+ update, summarise, next meeting John O Brien, @UK_CCG

9 + The UCL Big Institute Innovative ways to use new technologies and analytics 01/02/2017 Pierre-André Maugis

10 + One common problem What can we do with our data, - For academic research? - For scientific publishing? - For online programs? - For epidemic prevention?

11 + A translation of problems What makes a node in a network special? Business objective: Target users by their role in the network. Research objective: Study local properties of random graphs.

12 + Many dialogues Partnerships between academics and professionals, - On medium to long term time scales - Through knowledge exchange - Through concrete data examples - With strong ethical awareness

13 URL: ucl.ac.uk/big-data/ 01/02/2017 Pierre-André Maugis

14 The Big Landscape by 2045 what will it look like by the time I retire Paulina Zakrzewska, UCLH

15 UCLH 2010

16 UCLH 2017

17 UCLH 2017

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21 2017

22 2045

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24 Digital solutions People mindset Visualisation Open Sharable Transparent Verified Validated Visualised Automation Efficiencies Intelligent Buildings Flexible Designs $$$ Validated Information Shorter Programmes CYBER SECURITY Legacy built environment data

25 Thank you for listening

26 Whole Life Performance Plus (WLP+) John O Brien LCMB john@lcmb.co.uk

27 Project aim Develop a software model and commercial service for optimising internal building conditions to improve productivity by at least 10%, reduce energy use by 30%, and improve occupant comfort and wellbeing. Objectives are to: Empirically validate the link between IEQ and staff productivity Test the solution in a number of trial commercial buildings Develop a software-based supervisory control and reporting solution operating in a cloud environment

28 Project Partners

29 Examples of findings from existing research

30 Progress Summary Feb 2016 Project started Feb Aug 2016 Research IEQ and productivity Aug Sept 2016 Identification of case study buildings Oct Dec 2016 Preliminary investigations of case study buildings Jan 2017 IEQ monitoring commenced at King s College London Feb 2017 IEQ monitoring commenced at NATS March 2017 Survey work started at King s April 2017 Survey work started at NATS

31 Capture in Action

32 LCMB Workplace Optimisation People Productivity Well-being Absenteeism Strategic asset plan Place Technical Space Systems Performance Benchmarking Projects and interventions Performance Operational cost Risk Energy Validation and measurement

33 Lessons Learnt

34 Lessons Learnt BMS too inflexible and costly for IEQ monitoring IEQ monitoring presents practical challenges that can impact on data quality What appears to be easy to measure is more difficult in practice Communication with all stakeholders is key, and challenging in large organisations

35 Further Details

36 Agenda Innovative ways to use new technologies and analytics Dr. Pierre-Andre Maugis, UCL Centre for Science The Big Landscape by Paulina Zakrzewska, UCLH IOT: Digital Disruption in FM Jack Clough, Spica Tech The use of big data and data analytics to improve performance Milesh Patel, Iconics WLP+ update, summarise, next meeting John O Brien, @UK_CCG

37 Dates for your diary 1.30pm 25 th January 2017 How process can improve operational performance Examining the use of BIM, soft landings etc. to improve the operational performance of built assets 1.30pm 26 th April pm 12 th July pm 20 th September pm 24 th January 2018 The use of big data to improve built asset performance Integrating data systems Making existing built asset work Asset management summit Unlocking and using big data to improve built asset performance How to improve the performance of built assets by joining up data systems How to improve the performance of existing built assets Joining up guidance and insights for CE members to help differentiate their @UK_CCG