Why more analysis doesn’t break a vicious cycle in decision-making

Each had:

• two viable directions
• enough knowledge and data to make a decision

And still - neither option was a clear winner.

Intel

In the 1980s, Intel was deciding which business to focus on:

• memory chips - their original core business
• microprocessors - a newer, growing segment

Both could be justified.

Memory was established and still profitable.
Microprocessors were gaining traction but less certain.

“We have two strong businesses - and both still make sense.
Every time we revisit it, we can justify staying where we are - and justify moving into the other one.”

They compared:

• performance
• market position
• growth potential

The more they analysed, the more both directions continued to make sense - and the discussion kept going in circles.

Cavalry vs machine guns

At the start of World War I, both Britain and Germany were facing a shift in warfare.

Machine guns were already known.
Their impact had been observed.

The question was how to adapt:

• continue to rely on mobility and cavalry
• or reorganise around firepower

“We know what these weapons can do - but do we really change how we fight because of it?
Or do we stay with what has always worked?”

They compared:

• speed and manoeuvre
• offensive capability
• firepower and defence

The comparison didn’t settle the issue - it strengthened both sides.

IBM PC

In the early 1980s, IBM was building its personal computer.

They had two options:

• build everything internally, as they traditionally had
• or use external components to move faster

Both made sense.

Internal build meant control.
External components meant speed.

“We can build it ourselves - or we can move faster by using what’s already available.
Both paths get us there. Which one actually matters?”

They compared:

• time to market
• cost
• feasibility

The trade-offs were clear.

But neither option clearly outweighed the other - and the comparison kept circling around the same points.

What happens in these situations

When two options are this close:

• more analysis doesn’t break the tie
• it strengthens both sides

You go deeper.
Compare more.
Revisit the same arguments.

👉 Each round of analysis feeds the next step in the vicious cycle.

More data and more analysis didn’t resolve it - something else had to change.

What actually decided it

Intel

👉 “If we got fired and replaced, what would new management do?” — Andy Grove, Intel CEO

That reframed the decision.

The focus shifted to one factor:

→ Where can Intel actually win long-term?

They exited memory and focused on microprocessors.

That’s where they built their advantage - and became a dominant global company.

Cavalry vs machine guns

Both Britain and Germany had the same information.

The difference was what each treated as decisive.

Germany made the decision to organise around firepower and built its approach accordingly.

Britain continued to prioritise mobility for longer.

That difference shaped the outcome.

Firepower defined the battlefield.

And everyone else had to adapt.

IBM PC

IBM chose to move faster and used external components.

That decision worked in the short term.

In doing so, they didn’t treat control over the ecosystem as the deciding factor.

The PC market grew rapidly - and as it did, they lost control over that ecosystem.

⚡ The factor wasn’t missing. It just wasn’t treated as the one that decides the outcome.

When no option clearly stands out, the problem often is how they are being compared.

More analysis doesn’t get you out of the vicious circle.

👉 Is there something we’re not seeing as the factor that actually decides this?

Until that’s clear, the cycle continues.

🚀 What to do next

If this feels familiar, start here:

👉 Run the Second Look Decision Diagnostic to see what’s missing before you decide
👉See why this happens

 👉 📖 Read more on Second Look blog

You can continue with making the decision afterwwards.