It’s Always the Process, Stupid!
Why AI Won’t Save Your Broken Workflow
- AI does not inherently make an organization smarter; it only makes processes faster.
- Implementing AI on a flawed business process will only accelerate the generation of poor outcomes.
- Enterprises often treat AI as a 'magic wand,' expecting it to solve structural inefficiencies without addressing the underlying processes.
- AI's unique capability lies in handling unstructured data, which often exposes unstructured business processes.
- Processes relying on unstructured data are typically undocumented and intuitive, residing in human knowledge rather than formal procedures.
- To effectively use AI for unstructured data, the workflow itself must first be structured and designed.
- Key questions for process design include identifying the trigger, defining the transformation, and specifying the structured output.
- AI excels at acceleration by pattern matching, while true intelligence requires human wisdom, context, and governance.
- The core recommendation is to map, streamline, and optimize business processes before applying AI to enhance speed.
- AI 구세주를 찾는 대신, 화이트보드로 돌아가 가치사슬을 재점검해야 함
- 특히 비정형 데이터가 얽힌 인간 중심의 복잡한 영역을 시각화하고 병목과 낭비를 찾아야 함
- 프로세스가 단순하고 논리적이며 견고해진 뒤에야 AI를 가속 장치로 활용 가능
- 기술은 변하지만, 비즈니스 효율의 원칙은 변하지 않음
- 결국 핵심은 언제나 프로세스임
There is no such thing as an AI strategy. There is only Business Process Optimization (BPO).
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One of my favorite stories about processes and documentation:
- Work at a hedge fund
- Every evening, the whole firm "cycles" to start the next trading day
- Step 7 of 18 fails
- I document Step 7 and then show it to a bunch of folks
- I end up having a meeting where I say: "Two things are true: 1. You all agree that Step 7 is incorrectly documented. 2. You all DISAGREE on what Step 7 should be doing"
I love this story as it highlights that JUST WRITING DOWN what's happening can be a giant leap forward in terms of getting people to agree on what the process actually IS. If you don't write it down, everyone may go on basing decisions on an incorrect understanding of the system.
A related story:
"As I was writing the documentation on our market data system, multiple people told me 'You don't need to do that, it's not that complicated'. Then they read the final document and said 'Oh, I guess it is pretty complicated' "
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hammock 2 days ago | unvote | parent | context | favorite | on: It's Always the Process, Stupid
Your story and the article’s thesis that AI is for acceleration and automation (not other things like design/intelligence) remind me of one particular CEO’s five step product process:
- design smart(er) requirements- I.e beat up the ask and rewrite the problem statement correctly. 1B is every requirement has a persons name attached who is traceable/responsible for its inclusion- not a department.
- delete features you don’t need or which are hedges (if you aren’t adding back 10% of the time, then you aren’t deleting enough)
- simplify or optimize. This step must come after 1 and 2 so you aren’t wasting effort optimizing the wrong thing
- accelerate
- automate
This way is very clear where AI plugs in- and more importantly, WHEN it plugs in.
Also, plenty of times people try to run this process backwards, with poor outcomes.
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Feynman's Algorithm:
Write down the problem. Think very hard. Write down the solution.
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A similar observation commonly comes up related to software development - "it's not tech debt, it's org debt" (or to put a different way, "trying to use a technical solution to solve a social problem").