paper 2 - 2022 Flashcards
total revenue
sale price x quantity
total variable costs
variable cost per unit x quantity
total costs
total variable costs + total fixed costs
contribution per unit
sales price - variable cost per unit
breakeven output units
total fixed cost / contribution per unit
total contribution
contribution per unit x quantity
margin of safety
actual output - breakeven output
profit
total revenue - total costs
total contribution - total fixed costs
margin of safety x contribution per unit
variance
actual figure - budgeted figures
favorable or adverse
profit margin
profit/revenue x100
gross profit
revenue - cost of sales
operating profit
revenue - cost of sales - operating expenses
or
gross profit - operating expenses
net profit or profit for year
revenue - cost of sales and operating expenses + net interest
current ratio :1
current asset / current liability :1
1.5:1 = good (however important to compare to industry average)
less 1 means not enough current assets to meet current liabilities
acid ratio test
current assets - inventory/ current liabilities
1:1 = good (compare to industry average)
capacity utilization
actual output / maximum possible output x 100
85% to 90% is ideal
gearing
non-current liabilities/ capital employed x100
high gearing = 50% above
low gearing 50% below
return on capital employed
operating profit / capital employed x100
compare to industry average or back account interest
sale forecasting underpin what forward planning in a business
- HR planning
- cash flow forecast
- profit forecasting and budgets
- production planning
the 3 quantitative sales forecasting techniques
- moving average
- extrapolation
- correlation
define moving average
is a quantitative method used to identify underlying trends in a set of raw data
what is moving averages is used to identify what type of underlying trends
seasonal variation or erratic patterns
how to calculate a 3 period moving average
add 3 month of raw data together
calculate average by dividing by 3
calculate variation
how to calculate an average variation
average variation = actual data - trend data