Shared thinking accelerates everything

The Workplace Imperative
Workplace Strategy: Aligning real estate with business objectives

Learn from peers how portfolio and workplace strategy decisions deliver against talent, productivity and organisational business objectives. What are the unresolved trade-offs?

5 posts
Workplace Design: Where spatial intelligence meets organisational psychology

Learn from peers how workplace design directly shapes cognitive performance, cultural cohesion and talent retention. Are you design briefs built around heads / hierarchy or behavioural outcomes?

5 posts
Inclusive Design: Designing for Accessibility and Diverse Minds

Learn from peers exploring design gap between inclusion policy and built reality. One in five of your employees experiences the workplace differently. What does your neuroinclusive audit reveal?

1 post
- Design is not neutral. For one in five people, it is a daily barrier.
  
  Suzy
  
  April 30Apr 30
  
  0 comments
Hybrid Working: Engineering Culture Across Distance

Learn from peers examining how leading organisations are engineering cultural gravity, embedding collaboration rituals and sustaining connection at scale across distributed work environments. Where has your hybrid model fallen short and how have you responded?

5 posts
Workplace Experience: Designing destinations worth the Commute

Learn from peers examining psychology of belonging and the challenge of articulating emotional resonant in terms needed to get EX onto the CFO's scorecard. Which design interventions tangible improve how employees experience the workplace?

4 posts
Workplace Analytics: From Badge Swipes to Business Outcomes

Learn from peers testing metrics and approaches to assess the value of workplace and corporate real estate. While finance leaders prioritise return on investment, employees emphasise purpose, connection and autonomy. Which measures most effectively capture the true return on workplace investment?

4 posts
Forces Reshaping Real Estate
Future of Work: Signals, Shifts and Strategic Bets

Learn from peers exploring the structural forces reshaping the rules of work, and the challenge of translating signal into real estate strategy. Which future-of-work trends are you preparing for ?

6 posts
PropTech Adoption: What's Working, What Isn't.

Learn from peers exploring the measurable value of emerging PropTech in day-to-day operations. What commercial solutions have you deployed, what have delivered the clearest ROI and which, in hindsight, have fallen short?

4 posts
Net Zero Reality: Navigating the Gap Between Commitment and Delivery

Learn from peers exploring what credible decarbonisation looks like in practice and the gap between stated sustainability commitments and current trajectories. What's is impeding your carbon management plan?

7 posts
Managing Complexity at Scale
Portfolio Strategy and Execution: Accountability across Markets

Learn from peers exploring the realities of managing large occupier estates and maintaining alignment with organisations in constant flux. From portfolio strategy to transactions and financial accountability. How can decision-making improve when data is incomplete?

3 posts
Capital Projects: Turning Brief into Built Reality

Learn from peers exploring what works in practice, from programming and procurement to negotiation, governance and delivery, as well as the lessons drawn when execution falters. Does your project delivery process align with the RIBA Plan of Work?

2 posts
- Realistic cost estimates at pre-construction stage: is what we present to the board defensible?
  
  Anthony
  
  Wednesday at 13:094 days
  
  0 comments
- The client-side Lean Construction (LC) challenge nobody talks about
  
  Anthony
  
  May 15May 15
  
  0 comments
FM Leadership: Running the Estate for Everyone

Learn from peers exploring the realities of managing internal and outsourced teams, overseeing contract performance and sustaining service quality within finite budgets. Are service-level agreements and KPIs delivering operational excellence?

3 posts

DISCUSSION GUIDELINES

Total Topics 49
Total Posts 56

The AI-Native CRE System: What Exists, What's Being Built and How to get ready for it?

PropTech venture investment reached $16.7 billion in 2025, a 67.9% year-on-year increase that surpassed pre-pandemic levels, with AI-centred PropTech companies growing investment at 42% annualised, nearly double the rate for non-AI PropTech.
Several workplace technologies have already surpassed 80% adoption rates for operational functions; predictive maintenance, data warehousing, energy and emissions management, demonstrating that the infrastructure layer is maturing. The strategic intelligence layer is what remains underdeveloped. And the organisations that are closest to having it are not necessarily those that spent the most on technology, they are those that made deliberate decisions about data ownership, integration architecture and operating model design before they bought anything. JLL
Which brings me to the question I want this community to answer from lived experience - How should your PropTech capability be structured for tomorrow's AI-native system — in-house, outsourced, or hybrid?
Specifically:
— If you outsource your CPIP/IWMS to an IFM provider or managed service, do you retain meaningful control of the data model and integration architecture — or does the AI-native capability you'll need in five years effectively belong to your supplier?
— If you are building in-house, where have you drawn the line between what you own and what you buy — and how are you keeping pace with a vendor market moving faster than any internal team can match?
— Has anyone in this community piloted a genuinely agentic AI workflow across the portfolio-to-projects pipeline — not a chatbot on top of a legacy system, but something that reasons across connected datasets and surfaces decisions? What does that actually look like in practice?
— And for those mid-transition: what would you tell your past self about the sequencing? Data first, then platform, then AI — or did you find a different order that worked?
The blueprint for the AI-native CRE system is being written right now, partly by vendors, partly by the occupier organisations willing to architect it themselves. Interested to understand where peers in this community are in that journey and whether anyone is further along than the rest of us suspect.

By Anthony · Wednesday at 14:284 days
PropTech and the target operating model: has technology changed how you structure your CRE function?

Research in the Corporate Real Estate Journal (Vol. 14, 2024–25) draws a sharp distinction between organisations that have deployed PropTech tactically i.e. a new IWMS here, a sensor layer there, and those that have used it to fundamentally redesign their target operating model (TOM). The latter group report materially better cost transparency and decision speed.
The honest version of this conversation in most organisations is: we bought the technology, but we didn't change the org chart, the governance or the data ownership — and so it hasn't changed much at all.
In summary, most organisations appear to have gone down the tactical deployment route, buying technology without redesigning the operating model, the data governance, the team structure or the decision-making culture around it resulting in over promises and underperformance. Whereas, the organisations achieving genuine value from their technology investment are those that have treated it as an organisational transformation programme with a technology dimension, not a technology procurement exercise with occasional change management attached.
Where has technology genuinely shifted how your CRE team is structured or makes decisions? And where has it underdelivered against the promise?
Expect an import lesson here for those hoping to unlock the AI advantage.

By Anthony · Wednesday at 13:444 days
Realistic cost estimates at pre-construction stage: is what we present to the board defensible?

Research in the International / Journal of Construction Engineering and Management identifies a consistent pattern of optimism bias in pre-construction cost estimates, particularly in occupier-led projects where the design is still evolving and market benchmarks are applied without adequate project-specific adjustment.
The result is a board approval at RIBA Stage 2 based on a number that bears limited resemblance to the out-turn cost. By the time the real figure surfaces, commitment is too deep to reverse and the conversation becomes about finding savings rather than making a genuine decision.
How do you build genuine contingency and risk allowance into a business case without the number being rejected by Finance as too conservative? What's your methodology for getting to a defensible estimate early?

Couple of links below for those who want to read more on topic. Spoiler alert, out of the six categories of factors that determine whether a conceptual cost estimate is reliable before a spade hits the ground, Bozorgmehr Nia, Taheri and Jamalpour 2023 study's most striking finding: time allocated to the estimate is rated by practitioners as the single most influential factor of all twenty categories assessed.
(50) Achieving Realistic Cost Estimates in Building Construction Projects: A Reliability Assessment of Pre-Construction Stage Cost Estimates
Impact of Optimism Bias Regarding Organizational Dynamics on Project Planning and Control | Journal of Construction Engineering and Management | Vol 137, No 2

By Anthony · Wednesday at 13:094 days
AI and data readiness in FM: How mature is your FM data infrastructure?

IFMA's 2026 Global FM Trends research (2026 Global Facility Management Trends & Insights | IFMA) highlights circularity and data-driven decision-making as the defining themes of the next era for FM. The common themes is this: organisations embedding AI in FM are seeing real gains ... but only those that have first addressed data quality, legacy system integration and governance frameworks.
The risk is deploying AI on top of poor data. A predictive maintenance algorithm trained on incomplete asset records, or an energy optimisation tool fed by uncalibrated sensor data, can create false confidence and worse outcomes than manual management.
How mature is your FM data infrastructure? What has been the biggest barrier to AI readiness — asset data quality, system integration, team capability or governance? And what would you prioritise if you were starting the journey again?

By Anthony · Wednesday at 12:354 days
Outsourcing evolution: from service contract to strategic alliance, how has your model changed?

Research in the Corporate Real Estate Journal (https://doi.org/10.69554/XFPQ4569 - summary below)traces EY's outsourcing journey from first-generation (single-service contracts) through to fifth-generation (integrated, collaborative, outcomes-based relationships). The finding is that each evolution required the client organisation to change as much as the provider, governance models, internal capability, data sharing and risk appetite all had to shift.
Many occupiers describe their FM outsourcing as "strategic" while operating it as a cost-reduction exercise with annual benchmarking pressure and no genuine risk-reward sharing. The contract says partnership; the behaviours say transaction.
Where is your FM outsourcing model on that evolution curve? What has genuinely changed in the relationship and what structural or commercial features would you need to move it further?

Summary of Article -
Corporate Real Estate Journal (Vol. 15, Issue 1, 2025): Kate Vitasek presents a case study of how EY piloted the Vested outsourcing methodology in its Nordic region as part of a broader evolution of its facilities management (FM) outsourcing strategy. Drawing on EY's journey from conventional service contracts toward a genuinely collaborative model, the paper documents how EY used a collaborative "Request for Partner" (RFPartner) process to select ISS as its FM partner, before applying the Vested methodology to establish a formal relational contract structured around win-win, outcome-based economics — meaning both parties hold a mutual stake in each other's success. The research traces EY's full outsourcing evolution across multiple generations of contracting, examines the commercial and governance architecture that underpins the EY–ISS relationship, and reports on measurable results achieved under the framework, concluding that the flexible, outcomes-oriented contracting model positions the partnership to continue evolving rather than requiring periodic re-tendering — offering a replicable template for occupier organisations seeking to move FM outsourcing from transactional cost management toward genuine strategic alliance.

By Anthony · Wednesday at 12:214 days
Designing from evidence, not aspiration. Is your workplace a living lab?

Space is always speaking. If nobody has moved the furniture in months, is that a sign of contentment ?
For most of workplace design history, we designed collaboration spaces for one type of interaction: human with human. That is no longer the full picture. Gartner projects that by 2029, half of all knowledge workers will develop new skills to work with, govern, or create AI agents. The implication for space design is profound. We are now designing for three modes simultaneously — human with human, human with agent, team with agent ensemble. Most current briefs address none of these directly and only address aspiration.
The best workplaces are designed from evidence.
How well do you know your organisation's actual behaviours (where people actually go, what they avoid, what they quietly work around) and what these reveal about the gap between intention and experience?
What design research are you undertaking to map how people work, where collaboration breaks down, which office rituals epitomise your firms culture ?
Microsoft's Future of Work research throw up another challenge, AI works well for individuals, but not yet for teams.
Accordingly, AI risks widening the human-to-human collaboration gap if it replaces social engagement rather than augments it.
So the design research questions are not abstract. How well do you actually know your organisation's behaviours? Where does collaboration break down? Which rituals hold your culture together and which environments quietly undermine them?
I believe the organisations getting this right are the ones treating their workplace as a living lab: testing space types, tracking experience quality and iterating on what the evidence reveals.
Interested to discover what design research occupiers are undertaking to challenge existing perspectives, push boundaries of conventional thinking and make better decision-making. Has anyone captured pre and post AI behavioural patterns .. what does the evidence tell you ? ... is it time to start distinguishing between AI-prominent and AI-ambient spaces?

By Anthony · Tuesday at 15:535 days

1. Which IWMS software solution outperforms across all aspects of the end-to-end life cycle ?
- IBM TRIRIGA: 0%
- SAP Real Estate Management: 0%
- Trimble (CenterStone): 0%
- Accruent: 0%
- Planon: 0%
- MRI Manhattan: 0%
- Eptura Workplace (formerly Condeco/iOFFICE): 0%
- Archibus (by Eptura): 0%