All language subtitles for KU PMGT 823 Session 4 (Part A)- Qualitative

Hello everyone and welcome to session 4
of PMGTH 23, Project Risk Management.

In this session, we will explore both
qualitative and quantitative risk

techniques. There are two important
tools for understanding and prioritizing

risks in your project.

This is part A of the session where we
will mainly focus on qualitative risk

analysis. Let's get started together.

In this part of module, we will focus on
qualitative risk analysis, a technique

that helps us evaluate and prioritize
risk based on their likelihood and

potential impact.

It is not about exact numbers just yet,
but more about understanding which risks

deserve more attention first.

Let's explore how this process works and
why it is a key part of risk management

planning.

Okay, let's quickly review the seven key
processes in project risk management

again. As you can see, we have already
covered steps like planning for risk

management and identifying risk.

Now we are moving to step three, which
is performing qualitative risk analysis,

where the goal is to assess and
prioritize risk based on their

potential impact.

This step helps us decide which risks
need a deeper look or a faster response.

Okay, let me start this section by
asking a question.

Why should we use qualitative risk
assessment?

Well, the answer is that not all risks
are created equal.

Some are more urgent or dangerous than
the others. For example, risks that

impact health and safety or those that
give early warning signs often need more

immediate attention.

But what happens if we skip this step?

If we skip this step, teams may fall
into two traps.

either ignoring important risks
altogether or wasting resources by

every minor issue.

This is why making clear distinction
between risks is not just helpful, it is

essential.

Let's take a moment to understand what
we mean by qualitative data in the

context of risk analysis.

Qualitative risk analysis is all about
using non -numerical data to evaluate

risks. Things like interview insights,
direct observations, or even written

reports. Unlike quantitative data, which
is counted or measured, qualitative

data describes risk in more subjective
terms, like frequent, severe, or hard to

detect. For example, if I say I drink
coffee every day, it is qualitative.

While if I say I drink 4 cups or 80
grams, it is quantitative.

So what is the key benefit here?

This process, I mean the qualitative
process, it helps us focus on high

risks early without wasting time and
effort across the project.

So far, we have learned that the goal of
qualitative risk analysis isn't to

calculate exact numbers. Instead, it
helps us understand risk through human

judgment.

First, we subjectively evaluate the
likelihood and impact of each risk based

experience and perception of the project
team or the stakeholders of the

project. Then we create a shorter list
of key risks so we can make sure that we

don't waste time dealing with things
that aren't truly critical.

And finally, in some cases, this process
even helps us decide whether to move

forward with the project or not. What we
call a go -no -go decision.

The keyword here is subjective.

And yes, that means emotions, intuition,
and experience play a key role.

Here is a structured view of qualitative
risk analysis process, straight from

the PMBOK guide. On the left, we see the
inputs.

These include documents like the risk
register, assumption log, and

register. These give us the raw material
for our analysis.

In the middle, we can see tools and
techniques that we can use to assess

These range from expert judgment and
interviews to data analysis,

and visual tools like the probability
and impact metrics.

And finally, on the right, we have the
outputs, updated project documents such

as the risk register and risk report,
which reflect our analysis results.

Remember, the goal of this process is
not just to record risks, but to

understand them well enough to act
wisely.

Let's take a closer look at the inputs
we need for performing qualitative risk

analysis.

Usually, we begin with the project
management plan, especially the risk

management component.

The information like rules, categories,
thresholds, and matrices are here.

Then we have assumption log, which helps
us track assumptions and constraints

that can affect how we prioritize risk.

The risk register is our master list of
all identified risks.

And the stakeholder register tells us
who might be impacted and who might help

us respond.

We also consider enterprise
environmental factors, such as industry

expert reports.

Finally, organizational process assets
can give us access to the lessons

and historical data from previous
projects.

Altogether, this information can provide
what we need to evaluate risks

effectively.

Now let's walk through the tools and
techniques used in qualitative risk

analysis.

Usually we start with the expert
judgment, which means using the

people who have seen similar risks
before, perhaps in the previous

Just remember, different experts might
have different backgrounds, so you

always prepare yourself to receive
different ideas.

Then we have data gathering, like
interviews to explore how likely a risk

how serious it might be.

In data analysis, we look at the quality
of our data, estimate probability and

impact, and consider other factors like
urgency or how easy the risk is to

control.

Interpersonal and team skills like
facilitation help reduce bias and keep

discussion productive.

We also group risks through the risk
categorization and visualize them using

tools like the probability and impact
metrics and bubble charts.

We will discuss about them later.

And finally, risk workshops and team
meetings are great for prioritizing and

assigning owners to each risk.

So what exactly do we mean by
qualitative analysis of a risk?

Well, we are trying to understand the
quality of the risk, that is, how it

affect the project's schedule, cost, and
performance.

We start by estimating two key
dimensions.

probability that is how likely is it to
happen and impact that is how serious

would it be if it did then we multiply
these two values to get what we call a

risk factor that helps us to build a
probability impact matrix later the

this number the more attention that we
need and remember risks with a higher

score often become candidates for
quantitative analysis later on, where we

deeper using numbers and models.

This table shows how we can
differentiate between major and minor

combination of probability and impact.

Along the top, we have different levels
of impact, from insignificant to

catastrophic. And along the left side,
we see probability levels, from rare to

almost certain.

Each cell shows resulting severity
rating like high, moderate, or extreme.

For example, even a moderate impact can
become serious concern if the

probability is high and vice versa.

This matrix helps us visualize which
risks require urgent attention and which

ones can be monitored more likely.

Here is an example that brings
qualitative risk analysis to life.

Imagine you are managing the
construction of a five -story office

Kansas, and the team has identified
several potential risks during early

planning.

Let's look at three of them.

First, there is a likely delay in
obtaining municipal permits.

This could significantly affect the
schedule, so it is rated extreme.

Second, there is a chance of equipment
breakdown.

It is less likely, but still
destructive.

So that one gets a high risk rating.

And finally, a nearby resident may file
a noise complaint during construction.

This has low probability and minor
impact, so we classify it as a moderate

Here is a detailed view of how we can
apply the probability and impact matrix

specific project objectives.

Along the top, you will see probability
levels that are low, medium, and high,

and are measured numerically.

Along the left, we evaluate impact
across four dimensions, scope, time,

and quality.

For example, if there is a high chance
of a time delay and the impact is 16 %

more, then that is a major concern.

Or if there is even a moderate chance of
the quality of sleep age that would

make the product useless, then we need
to act fast.

This table helps teams move from vague
risk descriptions to specific measurable

definitions, so everyone can make sure
that they are on the same page when they

are prioritizing risks.

Let's apply what we have learned to a
real -world example using the

and impact matrix.

In this table, each risk has been
evaluated based on its impact and

and we have calculated a significance
score by multiplying them.

Take the first risk, that is, team not
staffed in time.

With an impact score of 4 and a
probability of 5, its significance is

You can see it mapped in the top right
red zone, meaning that this is a

risk that requires immediate action.

Next are language misunderstandings and
team not experienced.

Both score 15.

These are also high priority and sit
close to the red boundary, meaning that

they still need careful planning.

Risks like available resources or
testers not available with scores of 4

into the green or yellow zone, meaning
they are less severe and might just need

monitoring.

And the matrix on the right visualizes
this beautifully.

Larger red color bubbles mean higher
risk exposure.

Another helpful tool in qualitative risk
analysis is the Fishbone Diagram, also

known as the Cause and Effect Diagram.

It helps us visually explore the root
causes of a risk.

In this example, the risk is late
delivery placed at the head of the fish.

Then, each major bone represents a
category, like people, machines,

materials, and we ask why repeatedly to
dig deeper.

For instance, under people, the team may
be untrained, over -allocated, or

juggling too many tasks.

Under machines, issues like equipment
not working or not being available can

show up.

This diagram encourages critical
thinking and teamwork because it's often

combination of small causes across
different categories that lead to big

So when your team says, let's figure out
why this risk might happen, this is a

great place to start.

After we complete qualitative risk
analysis, it's time to make sure that

results are captured and acted upon.

First, we prioritize the risks.

As I mentioned before, not all risks are
equally important, and this step helps

us focus on what matters most.

Next, we assign a risk owner for each
high -priority risk. That makes it clear

who is responsible for monitoring or
responding the risk if it happens.

And finally, we update our project
documents, especially the risk register,

report, issue log, and assumption log.

These updates not only keep the team
informed, but they also lay the

for quantitative risk analysis if that's
the next step.

So please don't skip this part.

Documenting what you have learned is
essential to making risk management

To wrap up this part of the session,
here is the key takeaway.

If your team already has a good
understanding of the key risks from

analysis, you may not need to go
further.

You can jump straight into planning risk
responses and assign owners.

But if there is still uncertainties or
disagreements about certain high

risks, that's when we use quantitative
techniques to dig deeper.

So qualitative risk analysis doesn't
always lead to numbers, but it always

to clarity.

And that brings us to the end of part A
of our session on qualitative risk

analysis. If you have any questions,
feel free to reach out.

Thanks for your attention. And when
you're ready, I'll see you in the next