Two Powerful Lessons PRESSURE (the movie) Can Teach Analysts
When I first saw the movie trailer for Pressure, it immediately went on my personal watchlist. I had studied about the D-Day and Eisenhower back in college while taking U.S. History, so the moment I heard about this movie, I knew I wasn’t going to miss it.
Also, I figured it wasn't going to be the usual gory war movie, which I generally avoid.
So, when I finally got to watch it, not only did I savour the intensity of the story, but very surprisingly, I found myself relating to it in a way I never ever expected -
DATA!!!
Seriously, who knew a World War II movie would make you think about analytics?
Quick Overview
Okay, just so you can relate to my article, here’s a quick overview of what the movie is about.
The entire movie focuses on the days leading up to D-Day and the enormous pressure surrounding just one critical question: Is the weather safe enough for the allied invasion to go ahead?
Three characters sit at the centre of this decision.
1️⃣Dwight D. Eisenhower
He’s the Supreme Allied Commander and ultimately, the decision-maker.
His question is simple, but the consequences are enormous:
Can they proceed with D-Day on June 5, or do they have to postpone the invasion?
2️⃣James Stagg
Stagg is the lead meteorological advisor responsible for bringing together the available weather intelligence and advising Eisenhower.
According to Stagg’s assessment, a storm is approaching, and an invasion on June 5 could be extremely dangerous. Not what the military leadership wants to hear!!!
3️⃣ Irving P. Krick
Krick is the American meteorologist, and he has a very different view. He expects calm weather conditions for June 5, and strongly believes the invasion on June 5 can go ahead.
Here’s a short clip from the movie featuring one of the key discussions, where Stagg desperately tries to make his case. Enjoy the scene, along with a bonus movie trailer at the end. Hopefully, it’ll pique your interest enough to give the movie a watch!
Now that you know about the three main characters of the movie, let me share with you the two big “analytics” lessons, which I think you can learn from this movie:
LESSON - 1
Don’t use historical data only to confirm the outcome you want
One of the biggest lessons this movie highlights is the danger of relying too heavily on favourable historical patterns.
In the movie Krick relies heavily on historical weather patterns that resemble “current weather conditions” and he uses those patterns to predict what is likely to happen next.
Based on that historical evidence, his forecast looks convincing, and he gives a go ahead for June 5th!
His thinking is something like : if today looks like this past situation, tomorrow may develop in a similar way.
But James Stagg takes a slightly different approach.
Rather than simply looking at past patterns, he also looks at what is happening in the atmosphere right now, how is the weather developing, plus all other previous situations where the weather was bad, and ultimately considers the possibility of an unfavourable outcome as well.
In other words, he doesn’t just look for the pattern that supports the forecast. He also looks for the pattern that could break it.
Based on his analysis, he strongly believes there's a storm brewing and it could potentially make the invasion disastrous.
Now Krick has a pretty good history with successful weather predictions, but Stagg insists that in this situation, Krick is not considering all possibilities. After a lot of deliberation, Eisenhower finally decides to listen to Stagg and postpone the invasion.
And guess what?
The weather deteriorates exactly as Stagg had warned!
There is a brief window on June 6 during which the weather conditions become better, allowing D-Day to proceed on that day instead of the 5th.
Seriously, this entire drama & conundrum reminded me of something we often do in business forecasting. We look at historical data, find a pattern, build our forecast and then unintentionally search for evidence that supports the outcome we already want.
But historical data should not only tell us what is likely to happen. It should also help us understand what could go wrong.
If I’m forecasting demand, revenue, staffing or any other business outcome, I don’t just want to know what happened under average or favourable scenarios.
I want to know:
What happened when things went badly?
What were the outliers?
What external factors affected the outcome?
What assumptions didn't work?
What happened during the worst periods?
If we deliberately leave the unfavourable scenarios out of our analysis simply because they make the forecast less attractive, we’re not really helping the business, are we ?
We’re simply helping management avoid an uncomfortable conversation.
And there is a big difference.
A forecast that gives everyone a comfortable answer today but leaves the business unprepared for tomorrow is not good analytics by any means.
Giving good news might feel very easy, but as analysts you should also be able to raise any red flags and give early warnings to management/ leadership teams so they can think about mitigation, recovery or contingency plans.
LESSON - 2
Being right doesn’t always mean being heard
Now this one felt a little more personal.
Throughout the movie, Stagg continues to argue his position even when the people around him don’t necessarily want to hear it.
He is the person bringing the uncomfortable forecast into the room, and despite having strong evidence to support his own argument, he doesn’t have the same level of influence as the other people who are within the decision-making circle.
This really reminded me of my own experience.
Back in corporate, I’ve always been pretty upfront with management when it comes to forecasting and analysis. When I used to prepare forecasts, I used to factor in external variables into the analysis rather than simply extrapolating historical trends in an excel sheet and calling it a day. That approach generally resulted in a very high degree of forecasting accuracy.
Management trusted my forecasts because I consistently tried to account for the things that could potentially throw them off.
And it was during all this success that I happened to learn an important lesson about influence in organizations:
Influence comes in different forms.
✨There’s influence you earn through expertise, credibility, hard work and consistently delivering strong analysis - which I had.
✨ And then there is the influence that comes from simply being very well connected to the people making the decisions.
I’ve been in situations where I was asked to conduct a major analysis, including a critical forecast. I did the work, presented the findings, made the recommendation, and then somehow, someone else would magically show up with their own version of the forecast, built using a completely different approach.
And sometimes, their recommendation would get approved. Not because their analysis was necessarily stronger, mostly because they simply had stronger relationships with the executive team.
At the time, even though it felt very frustrating, the experience definitely taught me an important lesson:
Being influential because of your expertise is not the same as being influential because of your relationships.
You can earn credibility through years of doing good work, and build a reputation for being well-researched or accurate; none of it automatically guarantees that people will listen.
Sometimes, people with weaker analysis will have a louder voice simply because they’re better connected to the decision-makers.
So, if you’re an analyst who wants to progress, you need to develop both.
▪️You need the credibility that comes from doing excellent analytical work.
▪️And you need the relationships and communication skills that allow that work to actually influence decisions.
Final Takeaway
Pressure was a surprisingly good reminder for me.
I don’t have to deal with the corporate bureaucracy and politics anymore, thankfully, but the movie reminded me just how emotionally demanding an analyst’s role can sometimes be.
I do recommend you watch the movie so you can enjoy the intense discussions, keep up with history, and along the way take home two big lessons of surviving the analyst role:
1️⃣ Have the courage to tell people what they need to hear, even if it's uncomfortable.
2️⃣ Credibility alone won't cut it. Also build strong relationships to make sure they actually listen.
Trust me, whether you like it or not, in a data role, being right with accurate insights is only half the job.
The other half is making sure you have enough influence to actually change the decision.
RECOMMENDED READING
Want to learn more about James Stagg’s remarkable heroism? I highly recommend giving this piece from The National Archives a read.
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