A light hearted look at why unusual data stories still point to a serious business challenge.
I have been away for a few days, which always gives you a bit of space to think.
Not necessarily deep, philosophical thinking. More the kind of thinking that happens when you finally step away from back to back meetings, look at the weather, check the news, and realise the world has become slightly absurd.
This time, one thing really stood out. The data has been weird.
The UK has been recording temperatures that feel more like the south of France than the north of England. Food prices have made the humble barbecue feel like it needs a budget holder. And somewhere in the world of data visualisation, someone has apparently decided that what analytics really needed was a Croissant Chart.
Which, to be fair, sounds delicious.
But it also got me thinking. Behind all these slightly funny, slightly ridiculous data stories is a serious point.
Data is everywhere. It is constantly telling us things. Sometimes it confirms what we already suspected. Sometimes it warns us that something is changing. Sometimes it gives us the evidence we need to act before the issue becomes obvious to everyone else.
The challenge is not whether the data exists. The challenge is whether we can see it, understand it, trust it and act on it quickly enough.
When May starts behaving like August. There are certain things we expect from May in the UK.
Bank holiday traffic. Someone optimistically buying garden furniture. A colleague declaring that “we should really do more walking meetings”. A national debate about whether it is too early to put the barbecue on (which incidentally for me is year round).
What we do not usually expect is the UK casually reaching 35.1°C in May.
Yet here we are. The Met Office reported that the UK’s May and spring temperature record was provisionally broken for the second day in a row, with 35.1°C recorded at Kew Gardens on 26 May 2026. The previous May record had been 32.8°C, set in 1922 and 1944. Heathrow also reached 35.0°C on the same day.
In other words, the weather did not just go off script. It rewrote the whole dashboard.
Weather data is easy to understand because most of us can feel when something is unusual. But the data tells us how unusual it is, whether it forms part of a wider pattern, who may be affected and what action may be needed.
A hot day is a talking point. A heat trend is a planning issue. A record breaking temperature is a signal.
And signals matter.
The barbecue now needs a budget holder , Then there is food price data.
We all know the weekly shop has felt more expensive. That is not exactly breaking news. But when you see the numbers, it gives shape to the feeling.
The Food Foundation’s May 2026 Food Prices Tracker reported that food and non alcoholic beverage inflation was 3.0% in the 12 months to April 2026. It also found that the cost of its weekly basic basket had risen significantly since April 2022, with the woman’s basket up 30.6% and the male basket up 38.4%.
So while the sun may be out, the barbecue is not exactly a casual affair anymore.
The sausages need a forecast. The salad needs a margin review. The potato salad may require board approval.
And if someone suggests “just doing a few bits for the grill”, it may be worth checking whether they have carried out a full procurement assessment first.
Joking aside, this is another example of data making the invisible visible.
A price increase is not always obvious in isolation. One item goes up a little. Then another. Then another. Before long, the basket looks very different, but the individual changes may have felt small at the time.
Businesses experience this all the time. Costs creep. Customer behaviour shifts. Operational delays increase. Manual processes quietly absorb more time. A report that used to take two hours starts taking two days. A support issue that looked isolated becomes a trend.
The individual data point may not seem dramatic. But the pattern matters. Without visibility, those patterns are easy to miss.
And then there are Croissant Charts
Of all the data stories I came across, this was probably my favourite. Croissant Charts. Yes, they are real.
A 2026 research paper introduced Croissant Charts as a way of helping people compare normal distribution visualisations more effectively. The study explored how design choices can influence how people interpret data and make comparisons.
Which is a very academic way of saying that sometimes the shape of the chart really does matter.
Although, admittedly, naming it after pastry does improve the experience.
It is also a useful reminder that data visualisation is not just about making things look attractive. Good visualisation helps people understand information more quickly and with less effort. Poor visualisation can create confusion, hide meaning or lead people to the wrong conclusion.
That matters because dashboards are not just pictures. They are decision tools.
A good dashboard should make the important things easier to see. It should help people focus on what has changed, what needs attention and what action may be required. It should reduce noise, not add to it.
We have all seen dashboards that look impressive but do not actually help anyone make a decision. Lots of colours. Lots of charts. Lots of numbers. Very little clarity.
The best dashboards do not simply display data. They guide understanding.
What this looks like inside a business: In a business, the “heatwave” is rarely actual weather.
- It is the support trend nobody spotted until customers started complaining.
- It is the renewal risk that was visible in product usage data, but not surfaced early enough.
- It is the operational bottleneck hidden across three systems.
- It is the board report that still depends on manual exports and spreadsheet stitching.
- It is the customer facing reporting feature that started as “good enough for now” but has become a blocker to growth.
For SaaS vendors, these signals can affect retention, customer experience and product value.
For regulated organisations, they can affect audit readiness, operational control and confidence in reporting.
For leadership teams, they can affect how quickly the business can respond.
That is why analytics cannot sit at the edge of the business. It needs to be embedded into the workflows, products and decisions where people already operate.
The serious side of silly data. It is easy to laugh at unusual data stories. A heatwave in May. A pastry shaped chart. A barbecue that now feels like a capital expenditure request.
But behind each of these examples is a more serious point.
Data is valuable because it helps us notice change.
A sudden temperature spike matters because it affects transport, healthcare, energy usage, retail demand, staffing, supply chains and customer behaviour.
Food price changes matter because they affect household spending, business margins, supplier relationships and purchasing decisions.
Chart design matters because people make better decisions when information is easier to understand.
The number itself is rarely the most important thing. The real value comes from understanding what the number means, who needs to know, and what should happen next.
That is where many organisations still struggle.
They have the data. They have the systems. They have the reports. They may even have several dashboards.
But do they have insight?
Can the right people see the right information at the right time? Can they trust it? Can they act on it?
Or are they still waiting for someone to extract the data, clean it, move it into a spreadsheet, format it, sense check it, send it round by email, then discuss it in a meeting two weeks after the decision should have been made?
That is the difference between reporting and real operational intelligence. Businesses are surrounded by signals
Every organisation has its own version of the heatwave, the Croissant Chart and the barbecue budget.
It might be a sudden increase in support tickets.
- A drop in customer engagement.
- A reporting process that takes too long.
- A team relying on spreadsheets that only one person understands.
- A compliance report that is still being pulled together manually.
- A sales pipeline that looks healthy until you examine conversion quality.
- A customer trend that is visible in the data, but only after someone has had time to go looking for it.
These signals are often already there. The problem is that they are hidden across different systems, teams and processes.
One team has the operational data. Another has the customer data. Finance has the commercial view. Compliance has its own reporting requirements. Leadership wants the board pack. And somewhere in the middle, someone is trying to reconcile five versions of the truth before Friday.
This is where data stops being funny and starts becoming expensive. Because when insight is delayed, decisions are delayed.
- When reporting is manual, people lose time.
- When teams cannot trust the numbers, confidence drops.
- When visibility is limited, opportunities are missed.
And when issues are spotted too late, the cost of fixing them is usually higher.
From “that’s interesting” to “what should we do next?”
At Panintelligence, we believe analytics should do more than show people what happened.
It should help them understand what is happening, why it matters and what they may need to do next.
That means dashboards should not just be decorative. They should be embedded into the places where decisions are made. They should reflect the right permissions, the right context and the right version of the truth.
Most importantly, they should help teams move from reactive reporting to proactive action.
Because whether you are tracking weather records, operational bottlenecks, customer engagement, financial performance or regulatory reporting, the question is the same:
What is the data trying to tell us, and are we able to act quickly enough?
That is the point where analytics becomes genuinely useful.
- Not when it produces another report.
- Not when it adds another chart.
- Not when it creates another spreadsheet tab that someone has named “Final final version 3”.
It becomes useful when it changes what people can see, what they understand and what they do next.
Why context matters?
One of the biggest mistakes organisations make with data is assuming that visibility alone is enough.
It is not.
A number without context can be misleading. A chart without explanation can be ignored. A dashboard without a clear purpose can become just another screen that nobody checks.
Context is what turns data into insight.
- If sales are down, compared to what?
- If support tickets are up, which customers, products or regions are affected?
- If usage has dropped, is it seasonal, behavioural or a sign of churn risk?
- If a compliance report is late, is that a one off delay or a recurring process issue?
- If operational performance has changed, is it caused by volume, capacity, process, system behaviour or something else entirely?
This is why analytics needs to be connected to the decisions people actually make.
A finance leader needs a different view from a customer success manager. An operations team needs different insight from a board member. A regulated business needs reporting that is not only clear, but governed, repeatable and auditable.
One dashboard does not fit everyone. The value comes from giving each audience the right view of the same trusted data.
Why this matters for SaaS vendors ?
For SaaS vendors, analytics is no longer a nice extra. It is part of the customer experience.
Customers increasingly expect to see their own data inside the products they use. They want reporting that is clear, easy to access and relevant to their role. They do not want to wait for exports, custom reports or manual updates.
When embedded analytics is done well, it can increase product value, support customer retention and reduce the pressure on internal teams to produce one off reports.
When it is done badly, or left too late, it can become a source of frustration. Customers question the value they are receiving. Support teams become reporting teams. Product teams get pulled into requests that could have been handled through governed self service.
That is why the question is not simply “do we have reporting?”
The better question is: “does our reporting help customers make better decisions inside our product?”
Why this matters for regulated organisations?
For regulated organisations, the challenge is slightly different but just as important.
The issue is not only whether people can access data. It is whether the data is trusted, governed, permissioned and repeatable.
Manual reporting may work for a while, but it introduces risk. Spreadsheets get copied. Definitions drift. Version control becomes difficult. Reporting knowledge sits with a small number of people. Evidence becomes harder to trace.
In regulated environments, insight needs to be useful and controlled. People need confidence that the right individuals are seeing the right information, and that reports can be produced consistently when required.
That is where governed dashboards and reporting become more than a productivity improvement. They become part of operational control.
The joy of spotting things early. There is also something very satisfying about spotting a trend before it becomes a problem.
Anyone can report on an issue after it has happened. The real value is seeing the early warning signs.
- A rise in failed processes.
- A slowing customer journey.
- A recurring support theme.
- A change in buying behaviour.
- A shift in usage patterns.
- A small operational delay that is starting to repeat.
These are the business equivalent of seeing the temperature forecast before everyone turns up to the office in wool.
The earlier you see the signal, the more options you have. You can investigate. You can adjust. You can intervene. You can plan.
That is the move from hindsight to foresight. And it is where dashboards, reporting and analytics become part of how a business operates, not just how it reviews performance after the fact.
Serious data does not have to be boring
The lighter side of data gives us a useful reminder.
People engage with information when it feels relevant. They remember it when it has a story. They act on it when it is clear, timely and connected to a decision they actually need to make.
That is why good analytics is not just about more charts.
It is about better understanding.
The best data stories are not always the biggest or most technical. Sometimes they are the ones that make people stop and say, “Hang on, that is interesting.”
- A May heatwave does that.
- A barbecue budget does that.
- A Croissant Chart definitely does that.
But once you have someone’s attention, the next step matters. The real question is not simply whether the data is interesting. It is whether it helps someone make a better decision.
So, what can businesses learn from this?
- First, unusual data points are worth investigating.
- Not every spike is meaningful. Not every trend is permanent. Not every anomaly requires action. But if something looks odd, it is worth understanding why.
- Second, visualisation matters.
- How information is presented affects how quickly people understand it and how confidently they act on it. A dashboard should not make people work hard to find the point.
- Third, context is essential.
- A number on its own rarely tells the full story. The value comes from connecting it to business meaning.
- Fourth, speed matters.
- Insight that arrives too late is often just a historical record. Useful analytics should help people act while there is still time to make a difference.
- Finally, data needs to be trusted.
If people do not trust the number, they will not trust the decision that follows it.
Final thought :
So yes, the UK apparently now needs a May heatwave dashboard. The barbecue may need its own cost centre. And somewhere in the world of data visualisation, a croissant has become academically useful.
But behind the humour is a serious message. Data is only valuable when people can see it, understand it and use it to make better decisions. Preferably before the next record breaking heatwave, board meeting or unexpectedly expensive potato salad. If your business has plenty of data but still struggles to turn it into timely, trusted decisions, it may be time to rethink where analytics sits in your organisation.
Panintelligence helps teams embed governed dashboards and reporting directly into the products, processes and workflows where decisions happen.
