ACCA Applied Knowledge · Management Accounting

Sources of data: formula sheet

Full chapter guide

Key formulas

Data to information: Data + processing/context → Information; Data is raw and unprocessed. Information is processed and meaningful to the user.
ACCURATE mnemonic: Accurate, Complete, Cost-beneficial, User-targeted, Relevant, Authoritative, Timely, Easy to use; Eight qualities. Some books use slightly different wording, so focus on the meaning of each.
Cost-benefit rule: Produce information only if its benefit > its cost; Benefit is hard to measure. It is usually judged by how much it improves decisions.
Primary data: Primary data = collected first-hand, for the specific purpose in hand; Examples: surveys, interviews, observation, experiments, focus groups.
Secondary data: Secondary data = already collected by someone else, for another purpose; Examples: government statistics, published accounts, industry reports, trade journals.
Classification test: Ask: who collected it, and was it collected for this purpose?; If you collected it for this purpose, it is primary. Otherwise it is secondary.
Selection trade-off: Choose on cost, time, relevance, accuracy and control; Primary usually scores higher on relevance and control. Secondary usually scores higher on cost and speed.
Systematic sampling interval: k = population size ÷ sample size; Round sensibly. Choose a random starting point between 1 and k, then select every kth item.
Proportionate stratified sample: Sample from a stratum = (stratum size ÷ population size) × total sample size; Use this when the strata should be represented in proportion to their size. Round to whole items.
Random vs non-random rule: Random = each item has a known, non-zero chance of selection; Quota, convenience and judgemental methods fail this test, so they are non-random.
Cost-benefit rule for information: Net benefit of information = Expected benefit − Cost of obtaining it; Collect or buy the information only if the net benefit is positive.
Value of information (expected value): Value of information = Expected value with the information − Expected value without it; Compare this value with the cost. If cost is lower, the information is worth buying.
Response rate: Response rate = Responses received ÷ Questionnaires sent × 100%; A low rate raises the risk of non-response bias.
Cost per response: Cost per response = Total collection cost ÷ Responses received; Useful for comparing methods such as postal questionnaires and interviews.

Quick revision

Data is raw facts; information is processed data that is useful for a decision.
Good information is relevant, accurate, complete, timely, understandable, and worth more than it costs.
Primary data is collected first-hand for a specific purpose.
Secondary data already exists and was collected for another purpose.
Internal sources come from inside the organisation, such as accounting records.
External sources come from outside, such as government statistics or trade publications.
Sampling studies part of a population to draw conclusions about the whole.
Random sampling gives every item a known chance of selection; non-random methods rely on judgement or convenience.
Surveys, interviews and observation are common ways to collect primary data.
Information is worth collecting only if its benefit exceeds its cost.
Secondary data is usually cheaper and faster but may be out of date or not fit the purpose.

Common mistakes

Saying data is always less useful or lower value than information regardless of context. Fix: Remember that data is unprocessed and has no context for the user. Information is processed and meaningful. The output of one process can be data for the next.
Confusing relevant with user-targeted. Fix: Relevant means it relates to the decision. User-targeted means it fits the person's level, role and detail needs.
Classing a company's own old records as primary data. Fix: Primary means collected for the current purpose. Old records gathered for another purpose are secondary, even though they are internal.
Treating primary data as always more reliable. Fix: Primary data can suffer from bias, a poor sample or badly worded questions. Say that quality depends on how well it is collected.
Classifying data as internal because the company holds a copy. Fix: Judge by origin. A competitor's report on your file is still external data.
Assuming external data is always more reliable because it is official. Fix: State that reliability varies. Check the date, the method and the purpose of the source, especially for internet data.
Treating quota sampling as random Fix: Ask who picks the individual items. If the interviewer chooses, it is quota and non-random.
Confusing stratified with cluster sampling Fix: Stratified takes some items from every group. Cluster takes all items from some groups.
Saying questionnaires give detailed, in-depth answers. Fix: Remember that questionnaires are cheap and wide but shallow. Interviews are deep but costly and slow.
Accepting a leading question as good design. Fix: Ask whether the wording suggests a preferred answer. If it does, it is leading and poor.

Exam tips

Learn all eight ACCURATE words and what each means. Questions describe a symptom, not the label.
Separate the look-alike pairs: relevant vs user-targeted, and complete vs relevant.
Remember trade-offs. Better accuracy can cost more and delay delivery, which affects cost-beneficial and timely.
In multiple response items, select exactly the number asked. Do not add an extra option you are unsure about.
Link good information to its purpose: planning, control and decision-making.
Always decide first who collected the data and why. That one check answers most classification questions.
Do not mix up primary and secondary with internal and external. Examiners use both pairs, sometimes in the same question.
In scenario questions, tie your choice to the facts given, such as budget, time or need for accuracy.