2.4.1-2.4.2 Business calculations and performance
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27 Terms
Total revenue
Selling price × quantity sold
Total costs
Fixed costs + variable costs
Profit
Total revenue − total costs
Sales revenue (from statement)
Total income from sales
Cost of sales
variable costs of producing goods
Gross profit
Sales revenue − cost of sales
Expenses/overheads
Fixed costs (e.g. rent, wages)
Net profit
Gross profit − fixed costs
Gross profit margin (%)
(Gross profit ÷ Sales revenue) × 100
Gross profit margin meaning
Shows how well a business controls cost of sales (variable costs)
High gross profit margin
Better profitability / efficient production
Low gross profit margin
Poor control of cost of sales
Net profit margin (%)
(Net profit ÷ Sales revenue) × 100
Net profit margin meaning
Shows overall profitability after all costs
High net profit margin
Good control of total costs (fixed + variable)
Low net profit margin
High expenses or poor cost control
Why margins are useful
Compare performance over time or with other firms
Limitation of margins
Need more than one year of data for trends
Another limitation
Must compare with similar businesses for meaning
average rates of return
(average annual profit ÷ cost of investment) x 100
average annual profit
total profit ÷ number of years
Types of business data (quantitative, financial, market, marketing)
Quantitative data = numerical data used to measure performance which includes:
financial data → revenue, costs, profit
marketing data → sales trends, customer numbers
market data → market size, competitors
Using data to assess business performance
Data is used to measure performance
identify trends over time
compare with competitors
make decisions e.g. pricing, investment
set targets
Graphs, charts and trends
Data is shown using graphs/charts to identify patterns
trend is the general direction of change (e.g. rising sales or falling profit)
Benefits of using financial information
Helps measure success
supports decision making
identifies problems (e.g. rising costs)
allows target setting
Limitations of financial information
Data is historical (may not predict future)
ignores qualitative factors (e.g. customer satisfaction)
may be inaccurate
lacks context