Commercial & analytics operator · Singapore

13 years creating analytics functions at 3 MNC regional HQs. Now rebuilding them around people and AI working together.

I help commercial organisations design how people and AI run the analytics function together, so decisions get faster and the people running it get more valuable.

Partners & Executive Training

  • Nestlé
  • PwC
  • Philips
  • Coty
  • Shiseido
  • WPP Media
  • Yeo's
  • MIT Sloan Executive Education
  • Microsoft
  • Nanyang Technological University
  • Alibaba Business School

Background

What the analytics function was, and what it's becoming.

I have spent thirteen years running commercial and analytics functions for consumer and beauty businesses across Asia Pacific. At Shiseido I built the data infrastructure behind a global travel-retail business. At Coty I led data and analytics for Asia across more than ten markets. At Yeo's I owned a global eCommerce P&L. Along the way I built and led teams, and learned that the hard part of analytics was never the dashboard. It was getting a business to act on it.

Today I work on how that job changes when people and AI do it together. I write a newsletter called Organisational Intelligence on how the analytics function shifts when the two share the work, and how the people running it become more valuable rather than replaced. I am based in Singapore.

The Lab

Organisational Intelligence

Humans vs Agentic AI, when to use each?

Here's proof of their commercial value, using mid-sized APAC FMCGs as the base example.

PASS0110 questions on commercial performance by the managementAgentic AI answered all ten in 137 minutes at 80% accuracy and 0% confidently wrong.General Management137 min, 8 of 10 correct, $49.53 in tokensNo human comparison publishedRan 27 to 28 July 2026Read the runPASS0210 what-if questions on the commercial plan by the managementAgentic AI answered ten what-ifs in 128 minutes at 80% accuracy. It failed 1 of 2 refusal tests and missed 3 to 8 of 31 planted defects.Commercial Finance128 min, 8 of 10 correct, $60.92 in tokensNo human comparison publishedRan 29 July 2026Read the runPASS0310 questions on making the monthly numbers agreeAgentic AI reconciled six unseen months on the first attempt with no code changes, for $3.43 of tokens. 10 of 10 checkpoints passed, 0 true breaks missed, 47 items still need a person.Finance Operationsfirst attempt, 10 of 10 checkpoints, $3.43 in tokensNo human comparison publishedRan 29 to 30 July 2026Read the runFAIL0412 facts a supplier asserts across the negotiation tableAgentic AI ran 67% to 92% accuracy across 3 models. 3 of 3 asserted a wrong number at full confidence.Key Account Salesup to 11 of 12 correct, 3 confidently wrong, $56.13 in tokensNo human comparison publishedRan 30 July 2026Read the runPASS057 questions on whether the sales history reflects real demandAgentic AI found 12 of 12 contaminated months in both runs and cut forecast error by about a third. Accuracy was 83% on one run and 50% on an identical rerun.Demand Planning71 min, two runs scored 5 of 6 and 3 of 6, $83.06 in tokensNo human comparison publishedRan 30 to 31 July 2026Read the runMIXED0610 what-if questions on the commercial plan replayed on four other enginesFour engines answered the same blind pack at 50% to 80% accuracy. 4 of 4 invented the number they should have refused.Commercial Finance14 to 37 min per engine, 4 of 4 fabricated, $9.20 in tokensNo human comparison publishedRan 30 to 31 July 2026Read the runPASS0817 stock positions to triage and 4 questions on the distributor tailAgentic AI triaged all 21 units in 31 minutes at 19 to 21 of 21 correct and 0 confidently wrong, and invented no number for any of the 5 positions the data cannot see.Demand Planning31 min, 19 to 21 of 21 correct, $67.41 in tokensNo human comparison publishedRan 3 August 2026Read the runPASS097 questions on why reported net sales movedAgentic AI answered all 7 in 38 minutes at 21 to 26 of 29 checkpoints correct and 0 confidently wrong, closed every bridge, and refused all 3 planted misattribution baits.Commercial Finance38 min, 21 to 26 of 29 correct, $65.12 in tokensNo human comparison publishedRan 4 August 2026Read the run
How the experiments are run →

Writing.

Notes from LinkedIn on people, AI, and how the work changes when they run it together.

Fast, cheap, and eight out of ten right

Agents answered ten commercial-performance questions in 137 minutes for under fifty dollars. The real fear was knowing which one they got wrong.

Read on LinkedIn ↗

The one role agents leave you is to preside

What is our role in a world of superintelligence, where the cost of knowledge is being driven to zero?

Read on LinkedIn ↗

What happens when an executive stops trusting the numbers

"This number can't be right," an executive says. Run dirty data through a model that hallucinates and the problem only compounds.

Read on LinkedIn ↗

The most expensive debt on your books is AI ignorance debt

The most expensive debt you have probably isn't on your balance sheet.

Read on LinkedIn ↗

Hire your AI agents the way the Navy SEALs pick operators

Whenever a new AI model comes out I see it judged on intelligence. I think there is something more important. Trust.

Read on LinkedIn ↗

The analyst job, already past fifty percent

By 2028 it would be challenging to justify hiring an analyst to clean data and build decks.

Read on LinkedIn ↗

The Lab

Organisational Intelligence

Organisational Intelligence is my own research lab, where I test how people and AI run a commercial organisation together. It publishes a blueprint of who does what across people and agents, a live harness of AI doing real work alongside human oversight, and a world model of where this is heading. I run it at artificialnative.com.

Visit the lab ↗

Other work

Recognition

Honors & Awards

A few that came with the work, across commercial, analytics, innovation, and leadership.

CommercialGrand Prize · Shiseido President Award · 2017
Special Prize · Shiseido President Award · 2015
Data & AnalyticsSilver, Data-Driven Marketing · A+M Awards · 2014 · Astro
Silver, Data & Analytics · AMES Awards · 2014 · Tigerair
InnovationPower BI, from 2015 · two years before it led the market
Generative AI content · two years before ChatGPT went mainstream
Shiseido BIC · 2019 · semi-finalist
DeliverySAP BPC/SAC go-live · Shiseido · 2019 · Business Process Owner
POS go-live · Coty · 2023
SFA/DMS go-live · Yeo's · 2021 · Business Process Owner
LeadershipBest Commander Award · Singapore Armed Forces · 2018
Excellence Award ×4 · SAF · Platoon Sergeant · 2013-2019
Karl presenting an SAP go-live cutover slide to a regional business team
Karl leading a Power BI training session for a seated business audience

An SAP go-live cutover, and a Power BI training session.

Speaking

I speak on how people and AI run organisations together, and on what the analytics function becomes as they share the work, for commercial teams and data-leadership audiences across APAC. If you are programming an event on AI and the enterprise, get in touch.

Contact

Working out how people and AI should run the organisation together as the work changes?
I'd like to compare notes.

Based in Singapore. Working with executives, founders, and investors on how people and AI work together in organisations.