7.2 Sensitivity analysis and stress testing budgets | Budget data

Question 1

Sensitivity analysis involves

Answer 1

• Revising the budget on the basis of a series of varied assumptions
• One assumption can be changed at a time to determine the impact on the budget overall
• Spreadsheets can be used to change more than one variable at a time to present alternative versions of the future

Question 2

Stress testing a budget involves

Answer 2

• Examining how a budget would perform or function under severe or unexpected pressure
• The stresses can come from internal or external events
• Org should be constantly assess these stresses and test their budgets to evaluate their ability to cope with any or all of these at any point in time
• It will also identify correlations between events

Question 3

Risks and events must be evaluated for

Answer 3

• Plausibility before stress testing process is initiated
• Because it is a complicated, time consuming and expensive excercise

Question 4

Sources of business stress include:

Answer 4

• Sudden changes in economy (ie recession)
• Cybersecurity attacks
• The loss of a major customer
• Foreign exchange rate risk
• Advancements in technology, rendering products obsolete or uncompetitive
• Changes in customer tastes
• A workforce strike / industrial action

Question 5

Budget data (sources of info that can be used as basis for budgeting):

Answer 5

• General economic data - info on changes to the economy such as expected growth in the economy or changes in consumer spending is regularly published
• Public announcements - competitors and customers may publicly announce their plans for the future which may impact on sales and pricing expectations
• Historic sales trends - these can be examined to identify patterns and changes in existing buyer habits and tastes
• Market research - all of the above can be verified through independent market research
• Business unit consultation - for org where budgets are set centrally, regular communication with managers of individual bus unit managers may provide better insights into local conditions and expectations

Question 6

Big data is

Answer 6

• Large volumes of data, both structured and unstructured, beyond the normal processing, storage and analysis capacity of typical database application tools
• It is often in digital form and created outside the org and available to everyone
• It can be analysed in order to provide insights that lead to better decisions based on more informed knowledge

Question 7

Big data analytics is the

Answer 7

• Gathering, analysing and using of massive amounts of digital info to improve bus operations
• It enables org to make decisions based on data instead of bus instinct

Question 8

Main benefit of big data analytics for budgeting is to reduce the problems of

Answer 8

• The principal budget factor is often the sales forecast but this can be very subjective and due to a high degree of uncertainty
• There will also be uncertainty when estimating costs and other assumptions
• Some data may not be included because it is considered unquantifiable

Question 9

Further benefits of using big data include

Answer 9

• Gaining competitive advantage - Better tracking of consumer trends from more up to date info means org can react more quickly than rivals
• Driving innovation - Customers needs are more readily identified meaning that new product ideas can be more easily formulated and market tested
• Improved productivity - Bus operations can be examined and analysed in order to find areas for streamlining and simplification resulting in cost reductions and efficiencies and non value adding activities or failures in systems can be identified and removed

Question 10

Big data analytics can play a key role in stress testing in the following ways:

Answer 10

• Identify stress events
• Help quantify the effects of stress events
• Help test the validity of assumptions in measures to deal with stress
• identify correlations for stress events
• Create and identify warning signs / triggers for stress events

Question 11

Big data and AI

Answer 11

• Big data captures info about consumer habits that wasn’t previously available
• This info together with use of AI and complex algorithms can be used to help org answer what were previously thought to be unanswerable questions
• Eg: What will rivals do next? How will consumers tastes change? Why are customers switching to substitute products?

Question 12

Big data analytics must overcome a number of problems explained by characteristics of big data (4V’s)

Answer 12

• Volume - there is often too much data to analyse
• Variety - the data comes in various forms
• Velocity - it is created and changed at great speed
• Veracity - concerns about the truthfulness of the data collected

Question 13

There may be other problems in performing big data analytics such as

Answer 13

• Because the data is often freely available it can be used and analysed by rivals so that any competitive advantage gained may be very short lived
• It requires a significant investment in IT in order to store, organise and manage the data (plus specialist staff and software which can be costly)
• The data can be distorted by data outliers (this is data that does not appear to fit in with other data that has been gathered)