The Domino Effect

Welcome Back to XcessAI

For most CEOs, automation feels like an overwhelming battlefield.
Everyone is talking about AI, productivity, workflow-bots, co-pilots, robotic automation, digital twins.
Vendors show up promising “end-to-end transformation.”
Board members ask why the company isn’t already doing more.

And amidst all this noise, one question actually matters:

What should you automate first — operations or corporate functions?

Get this wrong, and nothing else works.
Get it right, and every other automation becomes easier, cheaper, and far more impactful.

This is the first domino.
Push the right one, and the whole chain moves.
Push the wrong one, and the company stays exactly where it is — just more confused and more expensive.

Let’s break it down properly.

The CEO Dilemma: Two Fronts, One Shot

When I discuss AI automation with industrial operators, they almost always look at automation through one of two lenses, and both feel urgent.

A. Operations — the battlefield everyone can see

Factories, production lines, logistics routes, maintenance cycles, delivery performance.
These are the places where you feel pressure every day.

When you walk the shop floor, the problems are physical:
stoppages, delays, waste, overtime, backlog, downtime.

Automating operations feels like attacking the fire.

B. Corporate Functions — the more obscure battlefield

Finance, HR, planning, procurement, reporting, compliance.
These areas are quieter. But they are often where the real blockages live.

You can’t see bad data, poor costing, or forecasting errors — until they explode into a cash issue or a margin collapse.

And that’s the dilemma.
Do you tackle the visible or the invisible?

The Core Principle

Automation is only as good as the data, visibility, and constraints underneath it.

Automation does not fix dysfunction.
It scales it.

• Bad costing → automated pricing becomes dangerous

• Slow close → automated planning becomes fiction

• Poor unit economics → automated decisions misfire

• No single source of truth → workflows contradict each other

• Spreadsheets everywhere → nothing integrates properly

You cannot automate judgement.
You can only automate what already exists — good or bad.

This is why the “Where do we start?” question matters more than which tools you buy.

You can’t automate what you don’t fully understand.
And you can’t optimise what you can’t measure.

This leads to the real insight.

The First Domino: Automate Corporate Functions First

This is counter-intuitive for many CEOs.
But it is what actually works.

Corporate functions define the rules of the game before operations can play it.

Finance, in particular, is the backbone of everything:

A. Finance is the single source of truth

Margins, costs, cash burn, pricing logic, procurement data, working capital realities.
You cannot automate operations blindly without these fundamentals.

B. Finance defines operational boundaries

You cannot optimise operations without knowing:

• how much to produce

• what inventory to carry

• who to hire

• which contracts are profitable

• what capital is available

Automation needs constraints.
Finance creates them.

C. Finance produces the visibility layer

Dashboards, forecasts, cash positions, rolling KPIs — this is the intelligence layer automation relies on.

Without financial visibility, operational automation becomes guesswork.

D. Corporate automation is fast, cheap, and de-risked

You get early wins.
You build internal confidence.
You avoid expensive factory-floor mistakes.
You establish a foundation for operational automation to actually work.

This is the first domino.
And everything else depends on it.

When Operations Should Come First

There are exceptions. You’re not dogmatic, you’re strategic.

There are cases where the operations layer is so clearly the bottleneck that it needs to be addressed first.

Operations-first makes sense when:

• The financial systems are already robust

• Unit economics are clear

• Monthly close is tight

• Operational volatility is extreme

• Downtime costs are catastrophic

• You’re in asset-intensive industries (smelters, refiners, mills)

• Sensors already feed rich data streams

• Operations is the only real choke point

Even then:
If finance doesn’t measure and integrate the gains, they evaporate.

Even in ops-first environments, finance must follow quickly, or you lose the value.

The Two-Stage Automation Pathway

There are two stages, and the order is most frequently:

Stage 1 — Build the Financial Engine (Corporate Automation)

This is the part that transforms the business from reactive to intelligent.

What gets automated:

• Cash flow

• Unit economics

• Forecasting

• Close process

• Budget cycles

• KPIs

• Variance analysis

• Procurement logic

• Pricing inputs

• Board reporting

• Scenario modelling

Outcome:

You create an always-on financial nervous system.

At this point, the company can finally see itself.
Automation becomes grounded in reality.
Operations become predictable.
Strategy becomes anchored in numbers, not assumptions.

Stage 2 — Build the Operational Engine (Execution Automation)

Once the intelligence layer is solid, you move into the heavy machinery.

What gets automated:

• Scheduling

• Maintenance

• Throughput optimisation

• Quality monitoring

• Logistics routing

• Inventory management

• Demand forecasting

• Workflow orchestration

Here, automation becomes force multiplication.

The factory becomes self-regulating.
Supply chain becomes anticipatory.
Workflows stop fighting each other.
Every decision aligns with financial truth.

This is where efficiency gains stack on top of each other.
This is where material EBITDA shows up.

What CEOs Experience After the First Domino Falls

This is the real, observable impact:

After finance automation:

• No more firefighting

• Fewer meetings

• Faster decisions

• Predictable cash

• Transparent margins

• Accurate pricing

• Real-time reporting

• Fewer surprises

• Higher trust across the business

After operations automation:

• Stable throughput

• Less downtime

• Lower carrying costs

• Fewer stockouts

• Better customer fulfilment

• More resilient supply chain

• Lower manual workload across teams

The transformation becomes systemic.

The Mistakes That Kill Automation Projects

Companies generally make 3 of these before they learn the hard way:

• Running automation before fixing data

• Automating operations when finance is still weak

• Starting 10 projects at once

• Buying tools without redesigning workflows

• Expecting automation to fix structural issues

• Ignoring the cash cycle impact

• Using automation as a headcount reduction tool

• Treating automation as an IT project instead of a strategic one

These mistakes destroy ROI, internal trust, and momentum.

The Executive Cheat Sheet: How to Choose Your First Domino

A simple, CEO-level diagnostic:

1. Is your monthly close accurate and timely?

2. Do you know true unit economics across products/contracts?

3. Is your cash forecast reliable?

4. Are your systems integrated, or still on spreadsheets?

5. Do you have operational volatility that exceeds financial visibility?

If Questions 1–3 are weak → automate corporate functions first.
If they’re strong but operations are chaotic → start with operations.

Simple and practical.

Closing: Sequence is Strategy

Automation is not a shopping list.
It’s not a tech stack.
It’s not a digital transformation fad.

Automation is sequence.

Get the sequence right, and automation compounds.
Get the sequence wrong, and automation collapses under its own weight.

The companies that win aren’t the ones who automate the most.
They’re the ones who automate in the right order.

Until next time,
Stay adaptive. Stay strategic.
And keep exploring the frontier of AI.

Fabio Lopes
XcessAI

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