Making Financial Decisions
Understanding business performance
Contents
Graphs and charts turn numerical (quantitative) data into a picture so patterns, comparisons and trends are easier to spot. A table keeps similar data in rows and columns, which is better when you need to read exact individual values.
Matching the chart to the job
| Type | Best for | What to check |
|---|---|---|
| Bar chart | Comparing values across categories, such as repairs completed at each workshop | Axis labels and scale |
| Pie chart | Showing how one whole total splits into parts, often as proportions or percentages | The key, and that the segments add up to the whole |
| Line graph | Showing how a value changes, usually over time, and revealing trends | Which line is which data series |
| Table | Reading and comparing exact individual values, like monthly revenue | Column headings and units |
Check these before reading a value
Always check the title (what the data is about), the labels on each axis or segment, the key or legend (which colour or symbol means which data series), the scale (what each step on an axis is worth) and the units (pounds, units sold, percentages).
Worked example: a pie chart shows 400 bike repairs split between three workshops. The key shows the blue segment is Harbourside, at 25%. So Harbourside completed 0.25 × 400 = 100 repairs. Without the key, you could credit the 100 repairs to the wrong workshop.
Comparing performance and avoiding poor conclusions
Charts help you find the highest, lowest or most common category and compare performance, such as which workshop repaired the most bikes in June. But they can be misread: choosing the wrong data series, reading a scale step as 1 when it is 10, or mixing pounds with thousands of pounds gives a false picture. That can lead to a poor conclusion, like assuming one workshop is far busier when you have read last year's line instead of this year's.
Financial data is numerical information about money. It includes profit and loss figures, share price data and sales data, and helps a business judge how it is performing.
Profit and loss: who can see it?
A limited company must file details with Companies House, so its profit and loss figures are publicly available. Anyone can look them up, which helps investors and suppliers check the company's performance. A sole trader instead declares financial details to HMRC for tax, so their accounts are not made public. For example, Brightline Kitchens Ltd must file accounts, while a self-employed joiner running Oak & Plane reports income and expenses to HMRC privately.
Share prices and sales data
For a business with traded shares, share price data can reflect investor confidence. A rising share price can suggest investors expect good performance. A falling share price can make it harder for the business to raise finance and can damage its reputation.
Sales data can include sales growth, revenue (also called sales value), volume and market share. Revenue is the money a business receives from its sales, while volume is the number of items sold. If a bubble tea shop sells 4,000 drinks at £3 each, revenue is £12,000. If it sells 4,400 drinks next month, sales volume has grown by 10%, which is sales growth.
Different stakeholders, different reasons
Stakeholders may want sales data for different reasons. Owners use it to judge whether a product is selling well. Suppliers check it when deciding whether to offer credit. Customers may use it to judge whether a popular product will stay available. Competitors compare it with their own figures to see how their sales and market share are changing.
Marketing data is the information a business gathers about its customers, its competitors and the results of its own promotions. It helps a business understand what customers need and what rivals are offering, so it can make better decisions about product development and how to market products.
Campaign data
Campaign data records the revenue each advertising campaign brings in, together with its conversion rate. A business uses it to judge how efficient each marketing channel is: a channel that brings in more revenue than the campaign cost is worth using again, while one that brings in very little may be dropped.
A conversion rate measures the actual sales that result from advertising, as a percentage of the people who responded. If 500 people respond to an advert and 25 of them buy, the conversion rate is 5%.
| Measure | What it records | What it tells the business |
|---|---|---|
| Conversion rate | Sales as a share of the people who responded | How well an advert turns interest into buying |
| Click-through rate | Clicks as a share of views | How many people are interested enough to click |
| Advertising spend | Money spent on advertising | The cost of the campaign, which its revenue must cover |
Advertising spend
Advertising spend is the amount a business spends on advertising. It varies between years and between industries, since some markets need far more promotion than others to reach customers. Successful advertising can increase market share, but spending more does not automatically mean a campaign will work.
Click-through rate
Click-through rate compares the number of clicks a link receives with the number of times a page, email or advert is seen, so it measures the success of an online campaign. A high click-through rate shows that users are interested, but it does not guarantee that a sale will follow.
For example, an online plant shop spends £1,500 on a video advert. It is viewed 30,000 times and clicked 600 times, giving a click-through rate of 2%. Those clicks lead to 36 orders worth £2,160, a conversion rate of 6%. The revenue is higher than the spend, so the business judges this channel to be efficient.
Market data is information about the market a business sells in, rather than about the business itself. Typical market data includes total market volume, market growth, market trends and each business's market share. It helps a business judge the size of a market, how it is changing and whether it is worth competing in.
Total market volume is the total quantity of goods or services sold in a market. For example, it could be the number of escape room visits sold in a city in one year. This shows the market's size in units sold, rather than in money.
Market growth is an increase in the size or value of a market over time. If a city's escape room market was worth £1.2 million last year and £1.5 million this year, it has grown by £0.3 million, or 25%. Growth can make a market look more attractive to a business thinking of entering it.
Market trends are patterns or changes in market behaviour over time. In the escape room example, a trend could be more customers booking weekday evening slots instead of weekends. A trend is a direction that continues over a period, not a single busy night.
Using market data
Market data comes from the whole market, not from one business's own sales or advertising results. It can help a business decide whether to enter or leave a market. Rising volume and strong growth may persuade a business to enter; a trend away from its product may persuade it to leave. Market data can also show when advertising needs to change to increase market share. If an escape room's market share falls while the market is growing, its advertising may not be reaching the right customers, so it could promote weekday evening bookings to match the trend.
Average income data is information about the typical income of people in a group or area. It is often given as a single average figure, such as the average household income in a town, or split into income bands, which are groups of earners such as under £20,000, £20,000 to £40,000 and over £40,000.
Identifying target customers
How much people can afford to spend depends largely on what they earn, so average income data helps a business work out who its target customers are likely to be. A shop selling low-price everyday items looks for areas with plenty of people in the lower bands, while a seller of premium goods looks for the higher bands.
| Area | Average household income | Most common income band |
|---|---|---|
| Northfield | £19,800 | Under £20,000 |
| Millbrook | £27,400 | £20,000–£40,000 |
| Ashcombe | £46,500 | Over £40,000 |
A business selling budget homeware would focus on Northfield and Millbrook, where customers are more price-sensitive. A seller of designer furniture would head for Ashcombe instead.
Market entry and product development
Average income data also supports two other decisions. Before market entry (opening in a new area or selling to a new market), a business checks whether enough local people can afford its product: a gym charging £45 a month needs plenty of customers nearby who still have money left after paying for rent, bills and food. For product development, rising average incomes in an area might justify a premium version with extra features, while falling incomes might justify a cheaper, basic version that still sells in volume.
An average is only one figure for a whole group, so it hides the mix of high and low earners inside it. Two areas with the same average income can contain very different numbers of possible customers, so it pays to read the income bands alongside the average.
Judging how well a business is doing from one figure is risky. Quantitative data — numbers such as revenue, sales volume, market share and campaign conversion rates — gives evidence to support, inform and justify a decision. A single measure, such as rising revenue, does not prove success: you need data from several sources to build a fuller picture.
Financial data must be read in the context of market trends and market conditions. A climbing centre chain whose revenue rises by 8% may look healthy, but if the indoor climbing market grew by 15%, it is losing market share. Marketing data might also show fewer enquiries turning into bookings, while one centre could be busy and another quiet. Data can be contradictory or unclear, and parts of a business can perform well while others struggle.
A business can only make the best decision possible using the data available at the time. Using data reduces the risk of a poor decision, but it does not guarantee success. Financial information has limits: it can quickly become out of date as markets change, or cover a time period that does not suit the decision — three months of figures is a shaky base for a plan covering the next two years. It can also be distorted by seasonal swings, so seasonal adjustment evens out these periodic patterns before comparisons are made. Forecasts are built on past events, so they can be unreliable because the future is uncertain.
Financial data also omits non-financial factors such as customer satisfaction, brand image, employee morale and competitors' actions. It may reflect external factors too: a café's sales could fall because of roadworks outside, not poor management. To judge performance more accurately, compare financial data with marketing data, market data and other relevant information.