The expert panel
- Paul Raftery, Professional Researcher, Center for the Built Environment, University of California, Berkeley
- Kevin Brown, President, KB Squared; Regional Manager, HBS Solutions
- Shane Davis, President, Sustainable Turnkey Solutions
- David Walsh, Co‑CEO and Founder, CIM
- Hosted by Jim McClleland, Journalist
Summary of transcript
Benefits of building analytics
Kevin Brown: Ongoing commissioning and better data are lifting the ceiling on what consultants can deliver. Expect more impact from advanced sensors and IoT, plus a need for teams with both breadth and depth of skills. With higher bars from frameworks like LEED v5, owners are asking for leadership, not just checkbox compliance.
Shane Davis: Expectations are shifting beyond “code‑compliant” to “prove it works.” Owners want measurable reductions in energy and carbon and continuous improvement across the life of the asset, not one‑off projects.
David Walsh: AI needs to be trusted and verifiable. At CIM, the approach is to embed AI where it can be validated by data and field outcomes, focusing on demonstrable value rather than bolt‑on features.
Challenges in operationalising analytics
David Walsh: Communicating what’s genuinely different about AI‑enabled operations is a real hurdle amid market hype. Success hinges on clarity about outcomes and where AI is reliable today.
Paul Raftery: After the quick wins, governance keeps performance from drifting. Normalize and tag data early, establish ownership, and treat data quality like an ongoing commissioning task.
Kevin Brown: Change management is as important as tech. The wins right now are often utility‑driven programs and simple control strategy changes that finance can verify quickly.
David Walsh: Predictive optimization and maintenance are near‑term opportunities where machine learning can help, provided measurement and verification are in place.
Paul Raftery: Tactical examples matter, e.g. , strategy tweaks to outside‑air or supply‑air set points that avoid comfort penalties but cut load. Pair analytics with a clear playbook so actions stick.
Shane Davis: Anchor the program in a practical sequence: start with low‑disruption ECMs, build trust with the site team, and maintain momentum with transparent dashboards and weekly planning.
Audience Q&A
Paul Raftery: On balancing near‑term ROI with long‑term carbon goals, align measures to the organization’s objectives, but document baselines carefully (weather and hours) so finance accepts the savings.
Shane Davis: Sequence interventions for quick, low‑disruption wins first, then layer in deeper retrofits once the team has confidence in the data.
Kevin Brown: Keep M&V simple and transparent. The easier it is to verify results, the faster stakeholders will back scaling across the portfolio.
Shane Davis: Work backwards from value and integrate with the BAS thoughtfully, read‑only to start, validate findings with field teams, then time control changes with maintenance windows.
Final takeaways
Start small and prove value quickly. Build an internal coalition around real data and stories from your buildings. Don’t let early wins stall; put in place ongoing data QA and ownership so improvements persist. Think about analytics as a platform for continuous improvement, not a one‑off project. And be ambitious with AI: look for outcomes you couldn’t deliver manually, not just incremental tweaks.
