I don't remember most of the spreadsheets.
Twenty five years in supply chain and there must have been thousands of them.
Forecasts.
Production plans.
Inventory reports.
Purchase orders.
KPI packs.
I don't remember most of the meetings either.
Probably for the best.
But I remember the decisions.
I remember the supplier call I really didn't want to make.
I remember looking at two completely believable versions of what might happen next.
I remember the moments when everything seemed urgent and somebody had to decide what actually was.
I remember being told, quite emphatically:
Absolutely not.
I remember paying for resilience that looked expensive right up until we needed it.
And I remember decisions that looked perfectly sensible until you followed their consequences a little further down the supply chain.
Those moments stayed with me.
And ten Signals into writing The Demand Signal, I've realised something.
I've been writing about judgement.
That wasn't really the plan.
When I started writing these Signals, I wanted to capture some of the things I'd experienced during my career.
The mistakes.
The decisions.
The moments that taught me something.
I deliberately didn't want to write them chronologically.
Careers aren't remembered like that anyway.
At least mine isn't.
One week I might remember something that happened twenty years ago.
Another might come from something I've seen recently.
Sometimes it's something that went well.
Sometimes it definitely isn't.
But when I look across the first ten Signals, there's a common thread.
Again and again, the interesting moment isn't when the answer is obvious.
It's when it isn't.
Supply chain has become extraordinarily good at giving us information.
We have ERP systems.
Planning systems.
Forecasting tools.
Dashboards.
Analytics.
Algorithms.
And increasingly, AI.
That's a good thing.
I've spent a large part of my career wanting better data, better systems and better visibility.
Give me all of it.
But information and decisions aren't quite the same thing.
A forecast can tell us what might happen.
It can't always tell us how much risk we're prepared to accept if it doesn't.
A dashboard can tell us a KPI is improving.
It doesn't necessarily tell us whether we've moved the problem somewhere else.
A planning system can calculate a requirement.
It doesn't necessarily understand the conversation you've just had with a supplier that changes how you think about it.
A model can identify an efficient option.
It may not understand why Quality is uncomfortable with it.
The information matters.
The theory matters.
The tools matter.
But eventually they meet the real world.
A supplier.
A customer.
A constraint.
A trade-off.
A decision.
And somebody still has to decide:
What do we do?
I've started to think that perhaps this is where much of the real work of supply chain happens.
Not when everything follows the plan.
When it doesn't.
A supplier can't deliver.
Demand moves unexpectedly.
Capacity disappears.
Quality says no.
Two customers need the same stock.
The cheapest option creates another cost somewhere else.
The resilient option looks unnecessarily expensive.
The forecast says one thing and somebody close to the customer says another.
Now what?
There isn't always a formula for that.
Sometimes there isn't even a particularly good option.
There are just different options with different consequences.
And somebody has to choose.
We often call that experience.
I'm not sure that's quite right.
Experience helps.
Of course it does.
If you've seen a situation before, you have something to draw upon.
Patterns become easier to recognise.
You know which questions to ask.
You might even recognise the warning signs a little earlier.
But experience isn't the same thing as judgement.
You can have twenty five years of experience and still be wrong.
You can have two years of experience and ask the question everyone else missed.
Experience isn't judgement.
It's one of the things judgement can draw upon.
Data is another.
So is theory.
Expertise.
Research.
Curiosity.
Listening.
Knowing when to challenge something.
And perhaps most importantly, being prepared to change your mind when the evidence changes.
That last part matters.
Because there is a version of supply chain experience that can become:
I've seen this before.
Sometimes that's incredibly valuable.
Sometimes it's dangerous.
Because perhaps you haven't seen this before.
Perhaps you've seen something that looks remarkably similar.
The supplier is different.
The market is different.
The customer is different.
The risk is different.
The world is different.
Good judgement isn't about reaching into a catalogue of previous answers and finding the one that worked last time.
It's about using what you've learned before, alongside what the evidence is telling you now, to understand the decision you're actually facing.
That's a subtle difference.
But I think it's an important one.
And it makes me particularly interested in what happens next.
Because the tools are getting better.
Fast.
AI can already analyse datasets, identify patterns, interrogate exceptions, build scenarios and suggest actions at a speed that would have seemed ridiculous earlier in my career.
It will get better still.
Some decisions we make manually today will become automated.
Good.
If a machine can make a repetitive decision faster, more consistently and with better evidence than I can, I'm not particularly interested in protecting the task for the sake of it.
But that raises another question.
What happens to the decisions that are left?
Perhaps as technology gets better at dealing with the obvious, humans spend more of their time dealing with the non-obvious.
The exceptions.
The competing objectives.
The trade-offs.
The situations where the data is incomplete.
The moments where several answers are technically correct.
The decisions where somebody has to decide not only what can be done, but what should be done.
Maybe AI doesn't make judgement less important.
Maybe it makes judgement more visible.
That also changes how I think about leadership.
Earlier in my career, I probably associated leadership with knowing the answer.
The further I've gone, the less convinced I am.
Sometimes leadership is knowing the answer.
Sometimes it's knowing who might.
Sometimes it's asking the question nobody else has asked yet.
Sometimes it's slowing everybody down.
Sometimes it's speeding everybody up.
Sometimes it's saying yes.
Sometimes it's saying:
Absolutely not.
And sometimes it's being willing to make a decision when nobody can give you certainty that it's the right one.
That's uncomfortable.
But uncertainty doesn't remove the need to decide.
Quite often it creates it.
I’ve created ten Signals so far, which isn't a huge archive.
We're only getting started.
But it's enough to look backwards and notice the pattern.
A frightening supplier call.
Reporting versus leading.
Two believable futures.
The longest lead time.
The changing role of the planner.
Urgency.
Quality.
Resilience.
Local optimisation.
Different industries.
Different stages of a career.
Different problems.
But underneath them, the same question keeps appearing:
What do you do when the answer isn't obvious?
Maybe that's the territory The Demand Signal is increasingly interested in.
Where theory meets experience.
Where data meets context.
Where technology meets people.
Where what we know meets what we actually have to do.
Because eventually, knowledge has to survive contact with the real world.
And somebody has to decide what happens next.
I still want the spreadsheet.
I want the dashboard.
I want the forecast.
I want the theory.
I want the research.
I want the system.
And I'll absolutely take the AI.
Give me the best information we can possibly produce.
Then show me the trade-offs.
Show me what we don't know.
Show me who else the decision affects.
Show me what happens if we're wrong.
And then?
Make the decision.
Because perhaps the real value of experience isn't that, eventually, you know all the answers.
Maybe it's that you get better at recognising the questions.
Ten Signals in, that's probably the biggest Signal I've found.
Theme
Judgement
Signal
Better information improves the decision. Judgement is deciding what to do with it.
Reflection
Supply chains have more information, more sophisticated systems and increasingly capable technology.
That's progress.
Theory helps us understand the principles. Research gives us evidence. Experience gives us context. Technology gives us capability.
But none of them, on their own, guarantees the right decision.
The decisions that matter most are often the ones where several answers look reasonable, the consequences aren't completely known and somebody still has to decide what happens next.
Perhaps that's where judgement begins.
Question
What decision from your career still influences the way you work today?
The Demand Signal
Lessons from the front line of supply chain.