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ICAEW Management Information > 6. Budgeting > Flashcards

6. Budgeting Flashcards

1
Q

What is budgeting?

A

Budgeting involves looking ahead to a future period and estimating an organisation’s use of resources, profits, cashflows and financial position.

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2
Q

Why do businesses prepare budgets? (8)

A
  • Budgeting forces management to look ahead and plan how to achieve targets.
  • Budgeting necessitates the communication of ideas and plans to staff.
  • Budgeting necessitates coordination and cooperation among teams (e.g. procurement and production teams).
  • Budgeting forces management to determine how much resource is needed for the coming period (cash, staff etc.) and to consider the best way to allocate their resources ahead of time and to (reducing the chance of unforeseen resource shortages).
  • Budgeting necessitates some delegation of authority (e.g. to incur expenditure) to staff at lower levels, which should both motivate employees and enable more efficient operation of the business.
  • Budgeting provides a framework for responsibility accounting (making staff responsible for specific budget targets).
  • Budgeting facilitates a system of control, with teams and employee performance vs. targets analysed via variance analysis
  • The act of setting targets and monitoring performance vs. targets can be motivational for employees (as long as those targets are achievable and within the control of the staff).
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3
Q

What is a budget?

A

A quantified plan of what the organisation intends should happen in the future

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4
Q

What is a budget committee?

A

The budget committee is the coordinating body in the preparation and administration of budgets. The budget committee is usually headed up by the managing director (as chairman) who is assisted by a budget officer.

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5
Q

What is a budget period?

A

The budget period is the period covered by the budget, which is usually one year (divided into months or quarters). However, budgets can be prepared and used for longer periods, for example capital expenditure budgets.

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6
Q

What is a budget manual?

A

The budget manual is a collection of instructions governing the responsibilities of persons and the objectives and rules relating to the preparation and use of budgetary data.

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7
Q

What is the principal budget factor (PBF)?

A

The principal budget factor is that factor which limits an organisation’s activities - e.g. sale volume, resource procurement

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8
Q

For most businesses what is the principal budget factor?

A

Sales demand - the volume of goods the business can sell is the limiting factor

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9
Q

What are the key types of budget we will look at?

A
  • Sales budget
  • Production budget
  • Raw materials usage & purchases budgets
  • Labour budget
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10
Q

What is a sales budget?

A

A budget that derives the budgeted sales revenue from the budgeted sales volumes (often forecast using e.g. time series analysis) and expected sales price per unit

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11
Q

Outline the pro-forma for producing a sales budget

A
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12
Q

What is a production budget? When can this be produced?

A

A budget that derives the expected number of units of product the organisation will need to produce to satisfy sales demand.

Hence, this can only be prepared once the sales and closing inventory budgets have been produced.

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13
Q

Outline the pro-forma for producing a production budget

A
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14
Q

Outline how to calculate expected number units wasted to be used in a production budget given a % for wastage

A

1) Determine the budgeted production of completed units (unit)
2) Divide this by the % wastage to give the ‘total units to produce’
3) Substract the ‘budgeted production of completed units’ from the ‘total units to produce’ to give the number of unit expected to be wasted

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15
Q

What are raw materials usage & purchases budgets? When can this be produced?

A

A budget that derives the expected quantity and cost of raw materials to be purchased.

Hence, this can only be prepared once the production budget and standard quantities of materials per unit have been set.

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16
Q

Outline the pro-forma for producing a raw materials usage budget

A
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17
Q

Outline the pro-forma for producing a raw materials purchase budget

A
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18
Q

What is a labour budgets? When can this be produced?

A

A budget that derives the expected number of labour hours and labour costs to be incurred.

Hence, this can only be prepared once the production budget have been set.

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19
Q

Outline the order of budgets that need to be prepared if sales demand is the PBF. How would this change if raw materials was the PBF

A

If raw materials is the PBF: Raw materials budget would be prepared first then sales then production, etc

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20
Q

What is a master budget?

A

The master budget provides a consolidation of all the subsidiary budgets and normally comprises a budgeted income statement, a budgeted balance sheet and a cash budget

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21
Q

Outline a pro-forma for a master budget showing the budgeted income statement and balance sheet

A
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22
Q

Outline the pro-forma for producing a labour budget

A
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23
Q

What is a forecast?

A

A prediction of what is likely to happen in the future, given a certain set of circumstances

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24
Q

What methods can we use to use past data to forecast sales volumes or costs for future periods?

A
  • The high-low method
  • Linear regression
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25
Q

Briefly describe the high-low method used to forecast cost. What is its main assumption?

A

The high-low method is a technique for analysing the fixed and variable cost elements of a semi-variable cost and thus predicting the cost to be incurred at any activity level within the relevant range, utilising only the data points with the highest and lowest activities.

It assumes that the total cost and activity level (e.g. units produced) have a linear relationship

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26
Q

Outline the linear equation assumed in the high-low method

A
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27
Q

Outline the equation for variable cost per unit used in the high-low method

A
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28
Q

Outline the method for forecasting cost or activity using the the high-low method

A
  1. Determine the data points with the highest and lowest activity and their corresponding costs - put them in the matric like this
  2. Find the difference between the costs and activity levels
  3. Divide the difference in cost by the difference in activity level - this will give the value of V (the variable cost per unit)
  4. We can then find the fixed cost F by substituting the value for V into the linear equation formula for either the high point or the low point
  5. We can then forecast the total cost at any other activity level(or vice versa) using the linear equation formula through substitution
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29
Q

What are the disadvantages of the high-low method?

A
  • It assumes a linear relationship between total cost and activity level.
  • It ignores all data points other than the highest and the lowest activity levels (which may not be representative of the population as a whole).
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30
Q

Briefly outline what we need to know about the linear regression method for this module. What is its main advantages over the high-low method?

A

Linear regression analysis is another statistical technique for establishing a straight-line equation to link a dependent and independent variable.

However, linear regression analysis is superior to the high-low method because it determines the straight-line relationship that best fits all sets of recorded data, rather than only those at the highest and lowest activity levels.

31
Q

What is correlation?

A

Correlation is the degree to which one variable is related to another, i.e. the degree of interdependence between the variables.

32
Q

What descriptors can be used to describe two variables with regards to correlation? (2-4)

A

Correlation can either be described as:
* positive (as one variable increases the other increases)
* negative (as one variable increases the other decreases)

Further terminology can then be used to describe the degree of correlation between two variables:
1. perfectly correlated
2. partly correlated
3. uncorrelated
4. subject to nonlinear correlation

33
Q

Define the coefficient of correlation (r) and what its value tell us

A

The degree of correlation between two variables is measured using the coefficient of correlation r.

r has a value between:
* –1 (perfect negative correlation) and
* +1 (perfect positive correlation)
* If r = 0 then the variables are uncorrelated.

34
Q

Define the coefficient of determination (r²) and what its value tell us

A

The coefficient of determination, r², is a measure of the proportion of the change in one variable that can be explained by variations in the value of the other variable

r² has a value between 0 and +1
* A value of 1.0 indicates a 100% variable correlation and is a reliable model for future forecasts.
* A value of 0.0 suggests that the model shows that prices aren’t a function and therefore an unreliable model for future forecasts

35
Q

What is important to remember regarding correlation and causation?

A

It is important to remember that correlation does not necessarily mean that a cause-and -effect relationship exists

Two variables may look to have a causal relationship but a third variable, a confounding variable, is influencing both both variables making it look like one is causing the other.

36
Q

What is a time series?

A

A time series (TS) is simply a set of data observed over a period of time, e.g. sales patterns by month over several years.

37
Q

What is time series analysis?

A

Time series analysis is a statistical method that analyzes data points collected at regular intervals over time to identify patterns and trends and produce forecasts

38
Q

What key components are required to be identified for a time series forecast? Define each (4)

A
39
Q

What method can we use to determine long-term trend (line) of a time series?

A

Moving averages

40
Q

Outline the method for determining the trend in a time series using moving averages

A

METHOD

41
Q

What two models are used to determine the forecast time series given the trend and seasonal variations?

A
  • The additive model
  • The multiplicative (or proportional) model
42
Q

Briefly describe the additive model, including the equation and when it should be used

A

A model that assumes that the seasonal variations are independent of the long-term trend and therefore will be constant, thus we can just add an adjustment for seasonal variation to the long-term trend value

The additive model should be used if the seasonal variations are independent of the trend

43
Q

Briefly describe the multiplicative (or proportional) model, including the equation and when it should be used

A

A model that assumes that the seasonal variations are dependent on the long-term trend and therefore will vary with the trend, thus we make a multiplicative adjustment for seasonal variation to the long-term trend value

The multiplicative (or proportional) model should be used if the seasonal variations are dependent of the trend

44
Q

Outline the advantages (2) and disadvantages (3) of time series analysis

A
45
Q

What are the different approaches to setting budgets that we will discuss?

A
  • Incremental budgets
  • Rolling budgets
  • Zero-based budgets
46
Q

Describe incremental budgets and give its pros (3) and cons (4)

A

Previous budget plus an uplift

47
Q

Describe rolling budgets and give its pros (3) and cons (3)

A

Continuous budget - always having a 12-month budget

48
Q

Describe zero-based budgets and give its pros (2) and cons (3)

A

Starting from scratch

49
Q

What are the two main approaches to setting budgets with regards to the responsible parties?

A
  • Bottom-up budgeting (participative)
  • Top-down budgeting (imposed)
50
Q

Describe bottom-up budgeting (participative) and give its pros (4) and cons (5)

A

The budget is produced by starting with the individual personal and departmental objectives set by the local management and then working up through the different levels of the organisation, setting appropriate targets to ensure the lower-level objectives are achieved.

Pros:
* Budgets are set by those closer to the detail so should be more informed and realistic
* Greater staff participation leads to greater commitment and motivation
* Takes up less senior management time
* Encourages communication between departments

Cons:
* More scope for non-goal-congruent behaviour, budgets fitting local objectives rather than corporate goals (i.e. dysfunctional)
* Lack of overall coherence
* More time consuming and costly
* Budgetary slack may be built in
* Budgets may be inaccurate if less experienced managers are in place

51
Q

Describe top-down budgeting (imposed) and give its pros (5) and cons (4)

A

The budget is set by starting with the overall corporate objectives set by the senior management and then working down through the different levels of the organisation, setting appropriate targets to ensure the higher objectives are achieved.

Pros:
* Less scope for non-goal-congruent behaviour, budgets fitting local objectives rather than corporate goals (i.e. dysfunctional)
* More overall coherence
* Less time consuming and costly
* Less budgetary slack built in
* Less affected by inexperienced managers

Cons:
* Budgets are set by those further from the detail so would be less informed and realistic
* Less staff participation leads to lower commitment and motivation
* Takes up more senior management time
* Discourages communication between departments

52
Q

What is beyond budgeting?

A

The idea hat the traditional ways that businesses prepare budgets should be abandoned and that budgets should be more adaptive and agile and that this can be achieved using its 12 Beyond Budgeting principles:

53
Q

Outline and define the 12 beyond budgeting principles

A
54
Q

Define big data

A

Large datasets (often relating to customers) collectable / accessible by organisations,
whose analysis could provide key business insights

55
Q

Define data analytics

A

Collecting, organising and analysing these large datasets to discover patterns and aid
business decision-making

56
Q

Define data mining

A

The act of sorting through data to identify patterns and relationships (turning raw data
into information)

57
Q

What are the main characteristics of big data?

A

The 4 Vs

  • Volume
  • Velocity
  • Variety
  • Veracity
58
Q

What are the main benefits of big data? Briefly explain each (2)

A
  • **Forecasting demand: ** big data from sources such as website traffic, online trends, customer feedback, promotions and microeconomic factors specific to the business’s industry can be processed and an accurate model of future demand can be generated. allowing businesses to predict
    customer demand responses to new products and marketing campaigns and this information
    can be fed into the sales forecast.
  • Identifying customer preferences: the ability to understand the preferences and desires of each customer. This saves the customer time in finding what they want (because the website knows the products they are interested in) and more relevant promotions can be created
59
Q

What are the main problems with big data? Briefly explain each (2)

A
  • Lack of forecasting tools: The sheer volume, complexity and speed of Big Data means that traditional forecasting tools cannot cope
  • Privacy: The link between online and offline identity and who should control our data is a key question. Concerns about whether or not governments are also gathering Big Data about individuals, including their own citizens, raises questions about the balance between the benefits and the infringement of rights.
  • Security: Companies using Big Data should ensure that they are not infringing the security of other organisations and their customers.
  • Incorrect data: If the data is incorrect then it is worthless and potentially harmful if incorrect conclusions are reached as a result.
  • Lack of skilled data analysts: Big Data requires data analysts and therefore a business needs to be able to recruit suitable
    employees to make full use of the data
60
Q

Define artificial intelligence (AI)

A

Technology that enables computers and machines to perform tasks
traditionally requiring human intelligence such as learning, reasoning and problem solving.

61
Q

What are the different fields within AI?

A
  • Machine learing: A field within AI whereby computers learn to do things rather than follow pre-programmed rules
  • Computer vision: AI that identifies information from video and images
  • Generative: AI that creates texts and images in response to human prompts eg ChatGPT
  • Natural language processing AI that allows understanding and manipulation of human language eg Amazon’s Alexa
62
Q

Outline how AI can be useful in forecasting and budgeting? (5)

A
  • Cash flow forecasts: i.e. algorithms could be used to predict whether invoice receipts
    will be received on time or before the due date or to analyse overdue invoices and predict late
    receipts
    Budget software population: automatically extracting and categorising data from the
    accounting system and adding it to the budget software
  • Expense tracking and insights
  • Scenario planning: how changes in prices, activity levels, market conditions and so on impact results
  • Identifying seasonal variations
63
Q

What are the problems with AI? Explain each (8)

A
64
Q

Define professional scepticism

A

Assessing information, estimates and explanations critically, with a questioning mind, and being alert to possible misstatements due to error or fraud

65
Q

Define data bias

A

Data is biased when it is not representative of the population. Data may be biased before its analysed just because the method of collecting the data means that some members of the population have a lower (or zero) chance of being included in the sample. People who analyse data and reach conclusions can also introduce bias.

66
Q

What are the different types of bias we will look at in this course?

A
  • Selection bias
  • Self-selection bias
  • Observer bias
  • Omitted variable bias
  • Cognitive bias
  • Confirmation bias
  • Survivorship bias
67
Q

Explain when selection bias arises and give an example of when this might occur

A

This occurs when the data is not selected randomly and leads to a sample that is not representative of the population. In order to be representative, all items in the population should have an equal chance of being selected for the sample.

Example – ease of selection
Selection bias sometimes occurs because it is more convenient to select a certain group, for example, people in a particular geographic area

68
Q

Explain when self-selection bias arises and give an example of when this might occur

A

This occurs when individuals select themselves.

Example – new product survey
When customers choose whether to respond to a survey, those who choose to respond may have a certain characteristic or interest that leads them to respond. This creates a sample that is not representative of the whole population.

69
Q

Explain when self-selection bias arises and give an example of when this might occur

A

This occurs when observing and recording results and relates to interpretation the researcher allows their assumptions (which may be unconscious) to influence their observations.

Example – unconscious bias
Managers may be observing labour processes and draw conclusions based on their unconscious bias towards particular staff members

70
Q

Explain when omitted variable bias arises and give an example of when this might occur

A

Omitted variable bias is when a variable is excluded from the data model and therefore the cause of a change in one variable is incorrectly attributed to another variable in the model.

Example – sales budgeting
Sales of a product may depend on many variables such as advertising, price competition, fashion and cost of living. It would be easy to attribute an increase or decrease in sales volume to the wrong variable

71
Q

Explain when cognitive bias arises and give an example of when this might occur

A

This relates to human perception and includes bias depending on how data is presented (eg, infographics or the order of presentation, known as the ‘framing effect’) and ‘anchoring’ (eg, being influenced by the first piece of information offered
or ‘stuck’ on last year’s numbers).

Example – budgeting
Budgeting based on last year’s figures is very common but may lead to poor decision making and underachievement. Opportunities may be missed. This can be overcome by using zero-based budgeting or by considering what the budget might be if last
year’s figures were unknown, ie, considering market size, growth, competition etc.

72
Q

Explain when confirmation bias arises and give an example of when this might occur

A

This occurs when people see data that confirms their beliefs, and they ignore (consciously or sub-consciously) data that disagrees with their beliefs.

Example – new product/market research
Managers may have an idea for a new product and then ask for market research to confirm the viability of the idea. If market research is being performed to assess the popularity of a new product that the company has spent a lot of time and money developing, there may be pressure on the market research department to conclude that the product is not likely to fail

73
Q

Explain when survivorship bias arises and give an example of when this might occur

A

This is the tendency towards studying successful outcomes while excluding unsuccessful outcomes. Only items that survived some previous event are included in the sample.

Example – performance management
An accounting firm might decide to do a survey to find out how good its programme for trainee accountants is, by surveying a sample of trainees who have worked for the firm for one year. Such a survey would exclude trainees who left the firm before the
end of the first year, who were presumably not very happy with the programme

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