In part 1 of this 2-part series, we broke the word sustainability down into its parts. The word ‘sustain’ is a verb meaning to support, hold, or bear up from below. This is something we actively do - not something we are or something we have. When we shift that word to a noun - sustainability - it takes on a whole different meaning and carries a political vibe. Foundational and supportive transforms from functional and necessary to polarizing and subjective. That’s the crossroads that needs exploration.

What if we were in business to be pro-planet? Imagine if we used ‘sustainable’ as a baseline rather than a goal. What if we applied this approach to agriculture, land management, and urban planning - where the focus shifts from minimizing harm to actively enhancing the capacity of the land to sustain us? What if the bottom line was breakeven - and the top line was better AND profitable?

Boy, it’s exhausting in AI….and the vocabulary continues to deepen. Despite what you’re seeing on LinkedIn live feeds, CRE might not be the best place to seek SMEs on AI - especially ML/LLM’s/Tokenomics. Like pollen in the Spring, CRE is allergic to DeFi. Vector databases are the antihistamines and prescription strength is only available after seeing the data doctor. Sadly, data doctors don’t traditionally work in CRE. Maybe they’re in the basement with their dev teams, crushing Celsius and jamming to metal in their PJ’s? They certainly aren’t concerned about RTO’s and mandates.

Those who choose to practice technology and innovation see it. Advancements in chipsets and compute power will jettison us to next-level processing. The shift from central, to graphical has moved to neural. It feels fast because it is fast. We’ve never had more ability to ‘do’ than now. This is when we, as humans, give that speed the direction it needs. This is where speed turns into velocity - and we influence the intended outcome. This is a phase change.

Do you remember where you were? I do. I had just gotten off the phone with a friend of mine who works for the CDC in Washington, DC. It was a Friday afternoon, after lunch. The exact time escapes me, yet I remember there were buds on the trees, the grass was starting to grow and the hope of Spring was eternal.

For organizations that can move to digital transformation, radical transparency will be among the first of the benefits. Things we couldn’t see or didn’t know will become evident. Most of this transformation will happen through open-source data that has been validated by multiple, impartial parties. Chainlink’s Cross Chain Interoperability Protocol (CCIP) calls them Decentralized Oracle Networks, or DON’s.

When we think about professions where individuals ‘practice’ their work, it generally refers to fields where continuous improvement, updating of skills, and adherence to evolving standards or knowledge are crucial. Medicine, Law, Education, Music, and Sports come to mind. The terminology around “practice” relates to fields where there’s a direct, personalized service component, involving ongoing learning, ethical considerations, and a body of professional standards or regulations.

I want to riff off a post that a colleague, Phil Kirschner, made this week on LinkedIn about org health. The post came from the viewpoint of an org’s sustainable competitive advantage based on their perspective and support of fully remote teams. He references a refreshed version of McKinsey’s Organizational Health Index (OHI) which I will link at the bottom of the article. More specifically, he cites GitLab as a glowing example.

Misinformation is false or inaccurate information - getting the facts wrong. Provided the data collection process is engineered with proper intent, a statement like ‘data doesn’t lie’ is misinformation. If the entire data collection process is designed deliberately to mislead - intentionally misstating the facts, that’s disinformation. Our modern world is full of both - let’s dive in.