2. What we learn here…
• Instances of Decision making in Business
• Scenarios of Decision making: Uncertainty, Risk and probability
• Schools of Thoughts on Uncertainty
• Assessment of Risk
• Probability and Decision Making
• Application of Probability theory in Business and Research
• Examples
3. Instances of Decision Making in Business..
• How do I recruit the one who will generate the best future sales?
• Should I expand my business by adding Plant B? Does it give me positive
returns?
• What are the chances of success or failure for Product C if it is launched in
the market now?
• Should I take up investment A or investment B? What are my risks and
returns?
• What are the outcomes if I implement the cost-cutting strategy? How does it
affect my ‘bottom line’ ?
• Will the market crash or will it perform normally? Should I invest now or
not? …… many more
4. Decision Making
Choosing the best course of action
under given conditions
Scenarios of Decisions making
Outcomes are certain ….?
Outcomes are known but little
(probability)
Outcomes are not known at all
(uncertainty)
Outcomes are expected (risky)
5. ………“As long as Ford produces cars, it will be T-
model and the colour is Black”
This guy WAS CERTAIN!
7. Two Schools of Thoughts on Uncertainty
Hillson & Murray-Webster (2007)1
• Uncertain - Universe by nature is mysterious and prediction is a futile exercise.
• Predictable - Advancement in technology and knowledge enables one to predict
future more accurately thereby removing uncertainty.
Hillson & Murray-Webster (2007) suggest that uncertainty is due to two things:
1) Variability: a situation where the outcome of a measured factor can be within a
given range. It can also be referred as objective uncertainty as suggested by
theory of individual choice under uncertainty (Machina, 2004)2.
2) Ambiguity: a situation where the outcome can either happen or not or
something totally different may happen in future. As per the theory of individual
choice under uncertainty, this is also known as subjective uncertainty
(Machina, 2004)
1. Hillson D., & Murray – Webster, R., 2007, Understanding and Managing Risk Attitude (2nd edtition), Burlington: Gower Publishing Company.
2. Machina M.J., 2004, Almost – Objective Uncertainty, Economic Theory 24, 1-54.
8. • The Royal Society of Britain stated risk “as the probability that a particular adverse
event occurs during a stated period of time, or results from a particular challenge”
(Adams, 1995)3.
• Risk is adverse or undesirable outcome of an event.
• Risk is associated with uncertainty and it comes with consequences (Hillson & Murray-
Webster, 2007).
• Paul (Hopkin, 2002)4 - risk is a “circumstance, action, situation or event (CASE)”
which has the capability to impact on key factors acting as dependencies of core
processes of the organisation.
• Risk is product of probability or likelihood and potential impact.
• Risk is “an uncertainty that could affect one or more objectives” or “uncertainty that
matters” (Hillson & Murray-Webster, 2007)
What risk is…..risky to define in certainty!
3. Adams J., 1995, Risk, London : UCL Press Limited; 4. Hopkin P., 2002, Holistic Risk Management in Practice, London : Witherby & Co. Ltd.,
9. A Law suit from a client…
• A motorcycle company (say …..) gives a news paper advertisement that a
particular model (say….) gives an average mileage of 70 Kmpl
• Mr …. buys that vehicle believing it to be true!
• After using it for 1 week, the client files a law suit on the company ….. For
compensation!
• The court gives judgement in company’s favour [no compensation]
Why…..? What are the risks here for the company and the client?
A Small Challenge to you!
10. There is risk everywhere..
• Agriculturist – Risk of Monsoon failure and crop loss
• Business – Cost/Price risk (inflation), credit risk (default), competition, economic
cycle (business risk), interest rate risk
• Banks – credit risk, interest rate risk
• Stock markets – market risk, interest rate risk
• Insurance (is it because there is risk or uncertainty??)
….. Etc.
11. Risk assessment….how serious is a risk?
Source: https://www.jisc.ac.uk/full-guide/risk-management
Riskiness depends on two parameters—
Probability – the likelihood of risk occurring
Impact – the consequences if the risk does occur. Impact can be accessed
in terms of effect of risk on – time, cost and quality
The third parameter— Risk Proximity. When will the risk occur?
12. Suppose a risk has a 50% likelihood of occurring and may cost you INR 20/unit…
Suppose a risk has 40% probability of occurring and may cost you INR 10/ unit…
Promote/
Demote Risk
Red risks = unacceptable.
Green risks = acceptable.
Risk assessment…..
Source: https://www.jisc.ac.uk/full-guide/risk-management
13. What is probability?
The classical approach to using probability depends on several future events that are
equally likely to happen.
Probability1: Likelihood of an event occurring. It is measured by the ratio of the number
of favourable outcomes divided by the total number of possible outcomes.
Source: 1. http://smallbusiness.chron.com/importance-probability-rules-business-31263.html; 2. http://smallbusiness.chron.com/role-probability-distribution-business-management-26268.html
Probability distribution2: A probability distribution is a statistical model that
shows the possible outcomes of a particular event or course of action as
well as the statistical likelihood of each event. For example, a company
might have a probability distribution for the change in sales given a
particular marketing campaign. The values on the "tails" or the left and
right end of the distribution are much less likely to occur than those in the
middle of the curve.
14. Types of probability..
Theoretical probability – it is all about the occurrence of an event based on all possible
outcomes that are already known. It is defined as the ratio of ‘number of outcomes in the
event set’ to the ‘number of possible outcomes in the sample space’ or simply put P (E) = n
(E) / n(S). Example: tossing of a coin. We know that the result would be either head or tail,
which are equally likely. By means of theoretical probability, P(E) = ½ with E being the
event of the coin landing heads up. we know that the likelihood of a head or tail coming on
top is same i.e. ½ or 0.5.
Empirical Probability - Most real-life events can be predicted based on their occurrences in
the past by studying the data collected from surveys, trials, opinion polls etc. Such kind of
probability theory is called Empirical Probability and it’s based on observations and
experiences. Example, Suppose from a group of 100 children, 35 chose vanilla, then the
probability that a child will prefer vanilla flavour over others is 35/100 i.e. 0.35.
15. • From weather forecasts, opinion polls to making business decisions, the
concepts of probability come in handy at various aspects of our daily lives.
• Whether you are an economist, a businessman or a manager, you will come
across instances when you have to face uncertainty with respect to the outcomes
of your business decisions.
• For example, when you have to launch a new product into the market, you will
need to weigh in factors like market demand, customer perception and
usefulness of the product in the targeted area. Probability theory helps managers
and businessmen to select the right markets and the best time to launch the
product based on prior surveys and customer information etc.
Need for probability..
16. Use of probability…
Source: Zikmund Babin, & Carr Griffin,, ‘Business Research Methods – eighth edition’ (pdf), page no. 326 -327
17. • Sample selection
• Statistical Inference
• Hypothesis Testing
….. more
Probability in Research..
Probability make it possible for the statistician to generalize
from the known (sample) to the unknown (population) and
to place a high degree of confidence in these
generalizations.
Statistical Inference
18. Application of Probability theory in Business
Scenario Analysis
Probability distributions can be used to create scenario analyses.
A scenario analysis uses probability distributions to create several, theoretically
distinct possibilities for the outcome of a particular course of action or future event.
For example, a business might create three scenarios: worst-case, likely and best-
case.
The worst-case scenario would contain some value from the lower end of the
probability distribution;
the likely scenario would contain a value towards the middle of the
distribution;
the best-case scenario would contain a value in the upper end of the scenario.
Source: http://smallbusiness.chron.com/role-probability-distribution-business-management-26268.html
19. Ex: Expectation of Returns
under given probabilities5
5. http://people.stern.nyu.edu/adamodar/pdfiles/papers/probabilistic.pdf
They can represent a probability-
weighted average of cash flows
under all possible scenarios or
they can be the cash flows under
the most likely scenario.
In scenario analysis, we estimate
expected cash flows and asset
value under various scenarios,
with the intent of getting a better
sense of the effect of risk on value.
Source: http://www.teachmefinance.com/probabilitydistribution.html
20. 1.1 Sales Forecasting –
Helps company frame its possible future values in terms of a likely sales level
under the worst-case and the best-case scenarios. The company may construct its
own probability distribution of scenarios to base its business plans on the likely
scenario but still be aware of the alternative possibilities.
1.2 Risk Evaluation –
Consider a company entering a new business line. If the company needs to
generate $500,000 in revenue in order to break even and their probability
distribution tells them that there is a 10% chance that revenues will be less than
$500,000, the company knows roughly what level of risk it is facing if it decides
to pursue that new business line.
Application of Probability theory in Business
1. Scenario Analysis
21. 2. Decision Tree
Source: https://hbr.org/1964/07/decision-trees-for-decision-making
• It is a chart of possible choices and
results.
• A diagram set out like the branches of a
tree that shows the consequences of a
decision, each decision entailing a
course of action that requires various
other decisions.
22. 3. Monte Carlo Simulation
• It is a problem solving technique that uses the probability of certain
outcomes by running multiple trial runs, called simulation, using random
variables.
• Monte Carlo Simulation generates large number of simulations (various
course of actions), say, 1000 or 10,000, using random experiments. The
results of independent system realizations are assembled into probability
distributions of possible outcomes. Hence, the outputs are probability
distributions
• Wider applications in – Engineering, Project Management, Finance,
Research & Development, Energy, Manufacturing, Insurance, Oil & gas
and the environment.
• Programming, machine learning, Algorithms are used for this purpose.
Monte Carlo is the name
of a Casino.
23. 3. Monte Carlo Simulation – Example of rolling two dice
• The outcomes of rolling a pair of dice can
be manually computed.
• Example: There are six different ways of
getting a sum of seven (see the diagram).
Hence, the probability of rolling seven is
equal to 6/36 = 0.167 or 16.7%
• We could throw the dice a 100 times
(random experiment) and record how many
times each outcome occurs, and construct a
probability distribution.
• Example: if the dice totalled seven 18
times out of 100 rolls, the probability of
rolling seven is approximately 18%
24. 4. Probability in Manufacturing
Manufacturing businesses use probability to determine the cost-benefit ratio
Location or Transfer of a new manufacturing technology based on likelihood
of improved profits.
For financial success of a new product under competition, market demand,
market value and manufacturing costs.
Statistical control, TQM
Determining the likelihood of producing defective products,
Determining regional need (demand) and capacity (supply) for manufacturing.
Application of Probability theory in Business
26. Brain Teaser (Q & A)..
• Do risk and uncertainty mean the same?
• What does zero probability mean?
• When you add all probabilities of an outcome, what is the result?
• Can probability be a negative number?
• How do you find the probability of rolling a ‘six’?
• Generalizing from sample and implying on population is statistical inference. True
or False?
Assignment-01: ‘Relevance of Probability in Business Decision Making’. Justify
your points with examples
