Free resource · A Naked Finance session
Analytical thinking,data bias anddecision-making.
Turning complexity into decisions worth defending. Six ideas from the session, one thread running through them: judgement. With five of the live experiments to try for yourself.
MELISSA WHIPP · NAKED FINANCE · LIVE SESSION, JUNE 2026
00 · Agenda
Six ideas, one thread: judgement.
Financial modelling
What a model really is, and how it drives strategy.
Data-driven thinking
How businesses turn raw data into decisions.
Forecasting
Using analytics to build a view with history, and without it.
Benchmarks and scenarios
Reading uncertainty through multiple futures.
Analytical thinking
Descriptive, diagnostic, predictive, prescriptive.
Critical thinking
Bias, scepticism and better judgement.
Ten years turning numbers into decisions, from accounting and BAE Systems through start-ups, KPMG, NEOM and Head of FP&A roles to Naked Finance. The lesson that outlasted every job: data makes the work smarter, but only if you learn to think critically with it.
01 · Modelling
A model is an argument about the future.
Storytelling with numbers, built to be questioned, not admired. Every robust model is made of four parts, and each one is a place to be challenged.
Assumptions
The foundational beliefs about how the business operates.
Drivers
The key variables that move outcomes and performance.
Scenarios
Alternative futures under different conditions.
Outputs
Statements, metrics and decision-ready insight.
Models don't predict the future. They prepare you for it.
Try it · One number, a hundred assumptions
A discounted cash flow values an investment by its future cash flows, discounted to today. Net present value is what is left after the outlay. Every confident figure rests on assumptions you can move.
WORKED EXAMPLE · DISCOUNT RATE 8.0%
| YEAR | CASH FLOW | PV @ 8.0% |
|---|---|---|
| 1 | £100.0 | £92.6 |
| 2 | £110.0 | £94.3 |
| 3 | £120.0 | £95.3 |
| Σ PV | £282.2 | |
| Less outlay | (£250.0) | |
| NPV | +£32.2 |
VALUE CREATED
At 8.0% the same three cash flows are worth £282.2 today, £32.2 more than they cost. The number was never the fact; the assumption was.
02 · Data into decisions
Data tells stories your eyes can't see.
Read it well, it guides you. Read it badly, it misleads. Every number you trust has been through the same five steps. Four of them are preparation.
WHERE THE TIME ACTUALLY GOES
01 · COLLECT
Pull the raw data from every system: transactions, exports, logs.
02 · CLEAN
Reconcile, de-dupe and fix. The unglamorous majority of the work.
03 · ANALYSE
Find the pattern, test it, try to prove yourself wrong.
04 · VISUALISE
Make the insight legible to someone who is not you.
05 · DECIDE
5% of the effort. 100% of the value.
Roughly four-fifths of the job is preparation. Skip it, and the decision is built on sand.
Try it · Same data, two stories
Visualisation is removing everything between reader and point. The smallest choice changes everything: a default -1240.00 is easy to miss; a formatted (1,240) reads as a loss in an instant. And the axis is the biggest choice of all.
HONEST
Axis starts at zero. Steady growth of about 7% across the year, exactly what the numbers say.
REAL GROWTH Q1→Q4
6.9%
HOW IT LOOKS
7%
"How it looks" is the growth in bar height, which is what the eye reads. The data is identical at every position of the slider.
What is FP&A?
The cockpit of the business.
Financial Planning & Analysis is where data becomes decisions: the link between the numbers and the room they are decided in.
Forecasting
Projecting performance from trends, drivers and strategy.
Challenging assumptions
Stress-testing the business case with hard questions.
Finding risk and upside
Spotting what could go wrong, and where value hides.
Numbers into decisions
Translating complex data into clear recommendations.
The loop
How businesses think with data.
A continuous loop, not a one-off report. Good organisations cycle through five stages, each one feeding the next.
- 01StrategyDefine objectives and direction.
- 02DataCollect what is relevant.
- 03InsightFind the pattern and meaning.
- 04DecisionTake informed action.
- 05RefinementLearn and adjust.
03 · Forecasting
History doesn't repeat. But it rhymes.
Forecasting is imagination plus logic: creative thinking, held to a rigorous frame.
When history helps
Where there is a track record, the past gives you reference points worth trusting.
Valuations
Comparable companies and precedent deals rely on historical multiples.
Cashflow optimisation
Working-capital and seasonal patterns reveal liquidity headroom.
Synergy analysis
Past acquisitions inform realistic synergies and timelines.
Macro stress-testing
Combine entities and run scenarios at micro and macro level.
When there's no history
New product, new market, blank page. With no track record, you build the future from four sources.
Benchmarks
Study analogous companies and markets to set reasonable ranges.
Expert judgement
Use domain knowledge to inform the assumptions you cannot observe.
Scenarios
Build several versions of the future under different conditions.
Sensitivities
Test which assumptions actually move the outcome.
Three tools for uncertainty
Benchmarking
What does good look like?
- Identify comparable situations
- Establish realistic ranges
- Validate against market norms
Scenario planning
What could happen?
- Build base, upside and downside
- Identify the key drivers
- Prepare a response for each path
Sensitivity testing
What matters most?
- Vary one assumption at a time
- Find the inputs that move outcomes
- Focus on the high-impact few
04 · Capability
The different types of analytics.
Analytics maturity, one rung at a time
RUNG 01
Descriptive
What happened?
Reporting, dashboards and KPI tracking.
05 · Judgement
Data shows a version of reality, not reality.
The numbers are an argument. Your job is to test it. Question everything, not with cynicism but with curiosity and rigour. Five questions to ask of any number.
Where did it come from?
Source, method and chain of custody all matter.
What's missing?
The absent data often tells the bigger story.
What's assumed?
Every dataset hides assumptions. Make them explicit.
What bias is present?
Collection, analysis and reading all distort.
Who benefits?
Follow the incentives to the conclusion.
Data bias · When numbers lie
Bias gets in quietly, often invisibly. Naming the source is the first step to managing it.
Collection
How data is gathered shapes what you can ever learn from it.
System
Tools and processes encode and repeat existing patterns.
Human
Cognitive biases colour how we read and present information.
Incentive
People report what benefits them, consciously or not.
Interpretation
The same data supports different stories, depending on framing.
Common biases · Hover to reveal
The greatest hits of flawed thinking.
Seeking data that fits what you already believe.
A non-random sample gives unrepresentative answers.
Looking only at winners ignores the failures.
Over-weighting the first number you saw.
Over-weighting the latest events over the long run.
Judging odds by whatever springs to mind.
Too small or skewed a sample distorts the result.
Mistaking a coincidence for a mechanism.
Try it · The anchoring effect
Spin a random anchor, answer a question, then see the gap a meaningless number just opened up.
YOUR RANDOM ANCHOR
A random number. It has nothing to do with the question.
THE QUESTION
Roughly what percentage of new UK businesses are still trading five years after they start?
How analysts reduce bias
You can't remove it, but you can manage it.
Triangulation
Validate findings with multiple independent sources.
Benchmark externally
Test internal assumptions against market data.
Scenario ranges
Bound uncertainty with optimistic and pessimistic cases.
Peer review
Invite scrutiny from people who see it differently.
External data
Bring in third-party research and validation.
Document assumptions
Make the reasoning transparent and testable.
THE GOLD STANDARD transparent method + multiple checks + documented reasoning = defensible analysis.
Agendas and influence
When data is designed to mislead.
Some of the worst misuse of data was deliberate: research funded to reach a chosen conclusion.
- 1960's
Sugar and heart disease
The sugar industry paid Harvard scientists to shift blame to fat, shaping dietary guidance for decades.
- 2010's
Coca-Cola and obesity
Funded research that stressed exercise over diet, deflecting from sugary drinks.
- DECADES
Tobacco and smoke
Studies built to cast doubt on secondhand smoke, despite internal proof of the risk.
Always ask: who funded it, and what wasn't measured?
Game theory
Strategy when everyone is deciding at once.
When your outcome depends on others' choices, think several moves ahead. Four parts to any game.
Players
The decision-makers: people, companies or nations.
Strategies
Each player's full plan, given what others might do.
Payoffs
The outcome for each player from the chosen strategies.
Equilibrium
Where no one can do better by changing alone.
Play it · The iterated dilemma
Cooperate or defect against a live strategy. Tally the payoffs round by round and see why the short-term edge loses the long game.
PAYOFF MATRIX · POINTS (YOU / THEM)
They play tit-for-tat: cooperate first, then copy whatever you did last round.
ROUND
1 / 10
YOU
0
THEM
0
Ten rounds. Each round, choose. Then see what their strategy does with your choice.
06 · Takeaways
Four habits that outlast any tool.
Think critically
Question sources, assumptions and conclusions.
Challenge assumptions
Make the implicit explicit and test the drivers.
Use data wisely
Recognise bias and respect the limits.
Tell the story
Turn numbers into a narrative that drives action.
Your job isn't to remove uncertainty. It's to make it navigable.
Models that survive the board. Decisions, not decks. Clarity over theatre. If you are making allocation decisions that need to hold up in any room, get in touch.
Stay curious. Keep questioning. · Back to Training and resources