You are not short of data.
You have already bought the sensors, the booking system, the badge readers, and the dashboard sitting on top of them. What you are short of is anyone who can tell you which of those numbers to believe.
Most of the data that matters was never collected for real estate. Badge logs exist for security. Calendar data exists for scheduling. HR systems exist for payroll. The signal is in there. Getting it out is most of what I do.
Independence
No transaction. No design fee. No sensor to sell.
Most of this analysis sits inside a larger transaction, design, or technology engagement. It is one input to another deliverable, and it goes only as deep as that deliverable needs.
Here it is the entire business. I spent thirteen years building these methods at Gensler. I left to do only this.
I work with whatever data you already have, on whatever platform it already lives. Nothing I conclude changes what I sell you next, which means I am indifferent to what you conclude.
Typical Engagements
Organizations usually call me when:
Different datasets point to different conclusions.
Leadership is about to commit capital based on uncertain assumptions.
Existing dashboards explain what happened but not why.
AI-generated summaries need to be validated before decisions are made.
Planning teams need behavioral frameworks, personas, forecasts, or scenarios rather than another report.
AI and Analytical Judgment
Your AI will summarize a biased number with total confidence. It cannot tell you the number is biased.
I gave two frontier models a workplace study I had already finished, with an answer I knew cold. Briefed carefully, they rebuilt much of the structure. Prompted casually, the way a busy person actually asks, one told me the building was damaging how people connect and recommended a program to fix it. Confident. Well argued. Wrong. I only knew because I had done the work.
The model did not fail at the math. It failed at knowing what the number could not see. That is the layer I work in, and it is the layer that decides whether the summary above it is worth anything.
The model is good at answering what to do. The question that still needs someone who did the work is why the last thing did not. I do that part.
Testimonials
"Jerde Analytics possesses a unique understanding of both the physical design of space and the underlaying workplace data sets. This enables complex analysis of space utilization, ideal space definition and correlation of the physical environment and productivity. Chris has a "beautiful workplace mind" and I look forward to working with him again. "
RIKU PENTIKÄINEN
Executive Director, Corporate Real Estate and Services
Nomura
__________
“Chris is a trusted advisor who I've worked with closely for the past five years. His analyses of diverse datasets have helped me navigate the complexities of hybrid employee behavior, providing valuable insights that advance our workplace strategies. Chris' approach combines deep workplace knowledge with superior analytics to produce tailored and relevant insights for CRE professionals. I most value Chris' ability to listen to and understand my priorities and my role, and then tailor his services from there to help me succeed.”
JOHN SCHERER
Global Workplace Strategist
Microsoft
___________
“The value that Jerde Analytics brings to any portfolio, no matter the size or headcount, is their ability to apply an in-disciplinary approach to workplace planning. Their approach goes beyond the “butts in seats” mentality - They bring predictive analytics, experience, and intuition to provide solutions that impact the business at scale. Their services are an asset to any real estate and workplace portfolio.”
ALBERT DE PLAZAOLA
Senior Principal, Strategy
Unispace
