October 23, 2025 • 15 mins
We break down why risk analyses often become checkbox theater and replace them with a simple, practical impact vs likelihood matrix that guides action. From quick wins to high-stakes unknowns, we show how to calibrate effort, buy the right learning, and move with confidence.
Join the Substack for monthly guides, templates, and QA where I help you apply these to your specific projects.
Are your teams struggling with poor communication and rushed timelines? Is your product vision clouded by a lack of clarity? It's time to find your way through the confusion and build products that truly resonate with users.
Introducing "Pierce the Design Fog" by Dianna Deeney, the essential guide to turning abstract ideas into high-quality products. This book offers a proven playbook with practical frameworks and tools to help you foster team synergy, lead with vision, and ma
JOIN ME ON SUBSTACK Subscribe today.
GET THE BOOK Pierce the Design Fog
ABOUT DIANNA
Dianna Deeney is a quality advocate for product development with over 25 years of experience in manufacturing. She is president of Deeney Enterprises, LLC, which helps organizations and people improve engineering design.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
SPEAKER_00 (01:22):
Once you know how to do risk-based thinking, it
really is a game changer.
However, there are somepitfalls.
We talked about some of them inthe last episode, about picking
the wrong tool.
When we're applying risk-basedthinking and we're reaching for
risk analysis tools to help us,if we're focused on the wrong
thing, we can get into risktheater.
(01:43):
Let's talk more about that afterthe brief introduction.
Welcome to Quality DuringDesign, the place to use quality
thinking to create productsothers love, for less time, less
money, and a lot less headache.
I'm your host, Diana Deaney.
I'm a senior quality engineerwith over 20 years in
manufacturing and productdevelopment and author of Pierce
(02:05):
the Design Fog.
I help design engineers applyquality and reliability thinking
throughout product development,from early concepts through
technical execution.
Each episode gives youframeworks and tools you can
use.
Want a little more?
Join the Substack for monthlyguides, templates, and QA where
I help you apply these to yourspecific projects.
(02:27):
Visit qualityderingdesign.com.
Let's dive in.
I've heard of this complaintquite frequently that people are
doing FMEAs and they're a littlebit confused about what's going
on and how to use it, or they'regetting results that don't line
up with the decisions thatthey've already made, and now
(02:49):
you have a conflict.
And it can feel frustratingbecause you're doing these risk
analyses that are supposed tohelp you implement risk-based
thinking, but all they're reallydoing is being a checkbox,
something that you have to dobefore you can move on to the
next stage of your development.
And it's not helping you makedecisions or drive changes.
(03:10):
It's just something that youneed to get done and put on
file.
And then when you do put it infile, you never really look at
it again.
That's what I call the risktheater.
You're going through themotions, but we're not really
using the information to be ableto make decisions.
In the last episode, we talkedabout how to know when to reach
for what tool.
And this episode, I want to talkmore about making the risk-based
(03:34):
decision.
So not necessarily looking forpotential risks, but you know
what the risk is, or that youknow that you have a problem,
you have a risk, and you need toassess it to be able to help you
make a decision.
What I want to introduce you totoday is an impact versus
likelihood matrix.
So it's a two by two matrix.
(03:56):
On the x-axis is the impact ifwe're wrong, if we make the
wrong decision.
Y-axis is our likelihood orconfidence in making this
decision.
Generally, a high likelihoodmeans that we're confident that
our current design or belief iscorrect.
We have some initial evidence ora strong past precedent.
(04:20):
A low likelihood means we're notconfident in the current belief
or design decision.
We have conflicting data, nodata, or a high degree of
technical uncertainty.
So you're mapping out how riskyis it and how confident am I in
the decision that I'm making.
And why do this?
Because wherever you land onthis matrix gives you more of a
(04:44):
clue towards next steps.
And even before that, just beingable to name the problem and the
impacts to your project withyour team, because they have a
different viewpoint andunderstanding of the problem
too.
So work with your team andreally define the impact that
this decision is going to haveon your project.
And then you're naming out loud,you're putting a pin in how
(05:09):
confident you are heading intothis decision.
Let's take a closer look at thequadrants of this matrix.
And you can see how applyingrisk-based thinking can help us
decide what to do next.
If this decision that you'relooking at is low risk to the
project, and you're reallyconfident in the decision that
you're making, then those areprobably easy wins.
(05:32):
Those things you want todelegate and move fast to
implement.
So say with our product, we havean ancillary cleaning kit that
our customers are asking for.
Our customers are actuallyasking for it.
We know what special solutionsand swipes we need to include in
the kit and how to best cleanour device.
(05:53):
And really, it's a simple ask.
So it's a low impact if we getit wrong.
And we're 90% confident thatcustomers want this.
That's why we may want toconsider moving fast on these
things.
You know, if we get it wrong,it's still a low impact.
Um, that doesn't really change.
But on the other hand, we'rereally not that confident that
(06:15):
we're going to be designing acleaning kit in a good way.
Maybe it's going to have chintzythings in it, or the wrong
stuff, or maybe we're totallymissing the mark on what our
customers want.
In that case, um, that might bea resource sinkhole.
We really need to evaluate if wereally want to invest time or
(06:36):
money to investigate this.
It has low impact to theperformance of our product, and
we're not sure about thedecision.
So we don't want toover-engineer it.
We either want to ship thesimplest possible version or
de-scope it entirely toeliminate waste.
It might be worth doing a fewcustomer touch points on it to
(06:57):
learn a little bit more aboutthis cleaning kit, or maybe we
don't want to include it at all.
This is the most complexquadrant.
Since the impact is low, youshouldn't spend a huge resources
to increase confidence.
Either make the decision simpleenough that the uncertainty is
trivial, or just live with theuncertainty because the cost of
(07:18):
investigation isn't worth thelow payoff.
With our cleaning kit example,we covered half of the matrix,
having to do with a low impactif we're wrong.
Usually these decisions aren'tgiving us a lot of heartburn.
They're things that we mightspend a little too much time on
(07:39):
if we don't understand the risk,which is why it's good to
consider them and map them outwith our risk-based thinking
tools.
The things that do give usheartburn are on the other side
of the matrix.
And they have to do with highimpact if we make the wrong
decision.
Those are the things that wethink about and keep keeps us up
(07:59):
at night, and that can reallyparalyze us from moving forward
with our project if we arehaving a hard time making a
decision.
Let's consider that our producthas a user interface to it.
And right now we're shippingproduct that has a keyboard and
screen interface.
So the user is using a keyboardto type in information into our
(08:23):
product for whatever reason.
Now we want to modernize it anduse a touch screen.
We're going to get rid of theseparate keyboard and screen and
instead have a touch screen userinterface.
Our uncertainty point in thedecision that we're facing is
how we get the users to enter ininformation with this changed
(08:46):
interface.
Luckily, we have an expert onour team who is an expert on UX
and user interface, and we'vehad a lot of customer input and
we've done a lot of research onwhat works.
There are not only academicstudies, but there are also
studies that we performedourselves with mock-up
(09:08):
interfaces with our customers.
This is a big change in the waythat we work with our customers.
So it is still a high impact ifwe make the wrong decision, but
we're feeling really confidentin the decision based on all of
the previous work that we'vedone.
So a high impact and highlikelihood confidence is a
(09:29):
calculated certainty.
With these, we want to proceedwith implementing our ideas, but
we also want to immediatelyfocus on minimizing any of the
downsides to it.
We want to have a plan anddefine how we're going to
monitor, test it, and build infail-safes.
(09:51):
So really these calculatedcertainties are the exciting
part of product design.
The last quadrant in our two bytwo matrix perhaps is the most
interesting.
This is the classic high-riskquadrant.
There's a high potential forfailure combined with a high
uncertainty, and all of thatdemands an investigation to
(10:13):
reduce the risk before weproceed.
These are the critical unknownsthat give us heartburn until
late in the night or really makeus question whether or not we're
able to move forward if we'reready.
We want to prioritize datagathering to shift the
likelihood to high.
The information that we use toassess the impact and likelihood
(10:36):
of our project problem is goingto guide us into what kind of
information that we need and howmuch of it is going to help us
to make a decision.
Here's a situation.
(10:57):
And it was never the intentionto continue to use that in the
final design.
The intention was to eventuallytranslate that or change the
design to be able to use aplastic injection molded part.
But it was a big unknown withthe performance between the 3D
printed part and the injectionmolded part.
(11:18):
The impact to the project in itscurrent state was high.
There's timeline concernsbecause if the mold isn't made
just right, then there could bean eight-week delay to revise
it.
There's cost.
Injection mold tooling is reallyexpensive.
It could be around$45,000.
And they may also need tocomplete revalidation, which
(11:40):
adds more thousands of dollarsand more weeks to the project
schedule.
Being able to state what theunknown is, in this case, will
an injection molded part performas well as our 3D printed
prototype in use conditions?
That's our problem and thequestion that we're grappling
with.
And we spell out the impact ifit's wrong.
(12:00):
We have timeline, costs, andother revalidation and testing
risks if we make the wrongdecision.
So those are our high impact.
Now we want to get more clarityaround the likelihood that we'll
make the right decision.
We get these variables out inthe open for our team to be able
to explore and discuss.
(12:21):
Material properties differsignificantly, so we're not
quite sure about that.
There's no stress testing on themolded version yet because we
don't have one in hand.
And we know that geometrychanges like ribs and draft
angles can alter load path whenexposed to stress.
Because of all these reasons,we're not feeling very good
(12:42):
about our design decisions.
We have a low confidence thatour product is going to perform
adequately if we move forwardwith what we know today.
If we find ourselves in thiscritical unknown quadrant, this
exercise is going to give usinformation against which we can
decide what to do next.
(13:04):
What kind of testing or modelingor research do we need to
increase the likelihood ofsuccess in this decision?
You can use this matrix in acouple of ways.
You can use this in your cubicleor your office by yourself to
start gauging how you feel aboutthis design decision.
(13:24):
And you can use it to help youidentify proposals you make to
management, project managementor your engineering management
on what to do about it or how tomake it better.
You're essentially explainingthe risk of this decision and
making recommendations of whatyou can do about it.
Or you could use this matrixwith your team, with your
(13:46):
project team.
If you're the only one thatknows about this problem or is
concerned about it or it'skeeping you up at night, if
you're the only one concernedabout it, uh that could be a
team management problem becauseyour whole team should know
about this high impact risk thatyou're dealing with.
(14:07):
And there may be aspects of itthat you're not aware of, which
would either make the risk lessheavy, or there may be
additional risks or problemsthat are related to it or
associated with it that youhadn't even thought of yet.
So another great reason to usethis tool is to talk out these
problems with your greater teamso that you have a smoother
(14:29):
project execution.
This impact likelihood matrix wecovered today, it's not in
Pierce the Design Fog, the book.
The book covers front-end riskanalysis for concept evaluation.
This two by two matrix is forback-end technical execution.
Different stage, different tool.
(14:50):
If you're working on conceptdevelopment, grab the book.
If you're past that and facingtechnical validation decisions,
this Substack series might befor you.
If you're facing these types ofdecisions where it's later stage
in the product development andyou need risk-based methods to
do it and ways to move forward,then consider joining us on
(15:12):
Substack.
It'll be a three-month serieshere in October, November, and
December of 2025.
On Substack, there will be deepdive posts, QA, and live chats
on these topics, so considersubscribing.
This has been a production ofDeanny Enterprises.
Thanks for listening.
Once you know how to do risk-based thinking, it
really is a game changer.
However, there are somepitfalls.
We talked about some of them inthe last episode, about picking
the wrong tool.
When we're applying risk-basedthinking and we're reaching for
risk analysis tools to help us,if we're focused on the wrong
thing, we can get into risktheater.
(01:43):
Let's talk more about that afterthe brief introduction.
Welcome to Quality DuringDesign, the place to use quality
thinking to create productsothers love, for less time, less
money, and a lot less headache.
I'm your host, Diana Deaney.
I'm a senior quality engineerwith over 20 years in
manufacturing and productdevelopment and author of Pierce
(02:05):
the Design Fog.
I help design engineers applyquality and reliability thinking
throughout product development,from early concepts through
technical execution.
Each episode gives youframeworks and tools you can
use.
Want a little more?
Join the Substack for monthlyguides, templates, and QA where
I help you apply these to yourspecific projects.
(02:27):
Visit qualityderingdesign.com.
Let's dive in.
I've heard of this complaintquite frequently that people are
doing FMEAs and they're a littlebit confused about what's going
on and how to use it, or they'regetting results that don't line
up with the decisions thatthey've already made, and now
(02:49):
you have a conflict.
And it can feel frustratingbecause you're doing these risk
analyses that are supposed tohelp you implement risk-based
thinking, but all they're reallydoing is being a checkbox,
something that you have to dobefore you can move on to the
next stage of your development.
And it's not helping you makedecisions or drive changes.
(03:10):
It's just something that youneed to get done and put on
file.
And then when you do put it infile, you never really look at
it again.
That's what I call the risktheater.
You're going through themotions, but we're not really
using the information to be ableto make decisions.
In the last episode, we talkedabout how to know when to reach
for what tool.
And this episode, I want to talkmore about making the risk-based
(03:34):
decision.
So not necessarily looking forpotential risks, but you know
what the risk is, or that youknow that you have a problem,
you have a risk, and you need toassess it to be able to help you
make a decision.
What I want to introduce you totoday is an impact versus
likelihood matrix.
So it's a two by two matrix.
(03:56):
On the x-axis is the impact ifwe're wrong, if we make the
wrong decision.
Y-axis is our likelihood orconfidence in making this
decision.
Generally, a high likelihoodmeans that we're confident that
our current design or belief iscorrect.
We have some initial evidence ora strong past precedent.
(04:20):
A low likelihood means we're notconfident in the current belief
or design decision.
We have conflicting data, nodata, or a high degree of
technical uncertainty.
So you're mapping out how riskyis it and how confident am I in
the decision that I'm making.
And why do this?
Because wherever you land onthis matrix gives you more of a
(04:44):
clue towards next steps.
And even before that, just beingable to name the problem and the
impacts to your project withyour team, because they have a
different viewpoint andunderstanding of the problem
too.
So work with your team andreally define the impact that
this decision is going to haveon your project.
And then you're naming out loud,you're putting a pin in how
(05:09):
confident you are heading intothis decision.
Let's take a closer look at thequadrants of this matrix.
And you can see how applyingrisk-based thinking can help us
decide what to do next.
If this decision that you'relooking at is low risk to the
project, and you're reallyconfident in the decision that
you're making, then those areprobably easy wins.
(05:32):
Those things you want todelegate and move fast to
implement.
So say with our product, we havean ancillary cleaning kit that
our customers are asking for.
Our customers are actuallyasking for it.
We know what special solutionsand swipes we need to include in
the kit and how to best cleanour device.
(05:53):
And really, it's a simple ask.
So it's a low impact if we getit wrong.
And we're 90% confident thatcustomers want this.
That's why we may want toconsider moving fast on these
things.
You know, if we get it wrong,it's still a low impact.
Um, that doesn't really change.
But on the other hand, we'rereally not that confident that
(06:15):
we're going to be designing acleaning kit in a good way.
Maybe it's going to have chintzythings in it, or the wrong
stuff, or maybe we're totallymissing the mark on what our
customers want.
In that case, um, that might bea resource sinkhole.
We really need to evaluate if wereally want to invest time or
(06:36):
money to investigate this.
It has low impact to theperformance of our product, and
we're not sure about thedecision.
So we don't want toover-engineer it.
We either want to ship thesimplest possible version or
de-scope it entirely toeliminate waste.
It might be worth doing a fewcustomer touch points on it to
(06:57):
learn a little bit more aboutthis cleaning kit, or maybe we
don't want to include it at all.
This is the most complexquadrant.
Since the impact is low, youshouldn't spend a huge resources
to increase confidence.
Either make the decision simpleenough that the uncertainty is
trivial, or just live with theuncertainty because the cost of
(07:18):
investigation isn't worth thelow payoff.
With our cleaning kit example,we covered half of the matrix,
having to do with a low impactif we're wrong.
Usually these decisions aren'tgiving us a lot of heartburn.
They're things that we mightspend a little too much time on
(07:39):
if we don't understand the risk,which is why it's good to
consider them and map them outwith our risk-based thinking
tools.
The things that do give usheartburn are on the other side
of the matrix.
And they have to do with highimpact if we make the wrong
decision.
Those are the things that wethink about and keep keeps us up
(07:59):
at night, and that can reallyparalyze us from moving forward
with our project if we arehaving a hard time making a
decision.
Let's consider that our producthas a user interface to it.
And right now we're shippingproduct that has a keyboard and
screen interface.
So the user is using a keyboardto type in information into our
(08:23):
product for whatever reason.
Now we want to modernize it anduse a touch screen.
We're going to get rid of theseparate keyboard and screen and
instead have a touch screen userinterface.
Our uncertainty point in thedecision that we're facing is
how we get the users to enter ininformation with this changed
(08:46):
interface.
Luckily, we have an expert onour team who is an expert on UX
and user interface, and we'vehad a lot of customer input and
we've done a lot of research onwhat works.
There are not only academicstudies, but there are also
studies that we performedourselves with mock-up
(09:08):
interfaces with our customers.
This is a big change in the waythat we work with our customers.
So it is still a high impact ifwe make the wrong decision, but
we're feeling really confidentin the decision based on all of
the previous work that we'vedone.
So a high impact and highlikelihood confidence is a
(09:29):
calculated certainty.
With these, we want to proceedwith implementing our ideas, but
we also want to immediatelyfocus on minimizing any of the
downsides to it.
We want to have a plan anddefine how we're going to
monitor, test it, and build infail-safes.
(09:51):
So really these calculatedcertainties are the exciting
part of product design.
The last quadrant in our two bytwo matrix perhaps is the most
interesting.
This is the classic high-riskquadrant.
There's a high potential forfailure combined with a high
uncertainty, and all of thatdemands an investigation to
(10:13):
reduce the risk before weproceed.
These are the critical unknownsthat give us heartburn until
late in the night or really makeus question whether or not we're
able to move forward if we'reready.
We want to prioritize datagathering to shift the
likelihood to high.
The information that we use toassess the impact and likelihood
(10:36):
of our project problem is goingto guide us into what kind of
information that we need and howmuch of it is going to help us
to make a decision.
Here's a situation.
(10:57):
And it was never the intentionto continue to use that in the
final design.
The intention was to eventuallytranslate that or change the
design to be able to use aplastic injection molded part.
But it was a big unknown withthe performance between the 3D
printed part and the injectionmolded part.
(11:18):
The impact to the project in itscurrent state was high.
There's timeline concernsbecause if the mold isn't made
just right, then there could bean eight-week delay to revise
it.
There's cost.
Injection mold tooling is reallyexpensive.
It could be around$45,000.
And they may also need tocomplete revalidation, which
(11:40):
adds more thousands of dollarsand more weeks to the project
schedule.
Being able to state what theunknown is, in this case, will
an injection molded part performas well as our 3D printed
prototype in use conditions?
That's our problem and thequestion that we're grappling
with.
And we spell out the impact ifit's wrong.
(12:00):
We have timeline, costs, andother revalidation and testing
risks if we make the wrongdecision.
So those are our high impact.
Now we want to get more clarityaround the likelihood that we'll
make the right decision.
We get these variables out inthe open for our team to be able
to explore and discuss.
(12:21):
Material properties differsignificantly, so we're not
quite sure about that.
There's no stress testing on themolded version yet because we
don't have one in hand.
And we know that geometrychanges like ribs and draft
angles can alter load path whenexposed to stress.
Because of all these reasons,we're not feeling very good
(12:42):
about our design decisions.
We have a low confidence thatour product is going to perform
adequately if we move forwardwith what we know today.
If we find ourselves in thiscritical unknown quadrant, this
exercise is going to give usinformation against which we can
decide what to do next.
(13:04):
What kind of testing or modelingor research do we need to
increase the likelihood ofsuccess in this decision?
You can use this matrix in acouple of ways.
You can use this in your cubicleor your office by yourself to
start gauging how you feel aboutthis design decision.
(13:24):
And you can use it to help youidentify proposals you make to
management, project managementor your engineering management
on what to do about it or how tomake it better.
You're essentially explainingthe risk of this decision and
making recommendations of whatyou can do about it.
Or you could use this matrixwith your team, with your
(13:46):
project team.
If you're the only one thatknows about this problem or is
concerned about it or it'skeeping you up at night, if
you're the only one concernedabout it, uh that could be a
team management problem becauseyour whole team should know
about this high impact risk thatyou're dealing with.
(14:07):
And there may be aspects of itthat you're not aware of, which
would either make the risk lessheavy, or there may be
additional risks or problemsthat are related to it or
associated with it that youhadn't even thought of yet.
So another great reason to usethis tool is to talk out these
problems with your greater teamso that you have a smoother
(14:29):
project execution.
This impact likelihood matrix wecovered today, it's not in
Pierce the Design Fog, the book.
The book covers front-end riskanalysis for concept evaluation.
This two by two matrix is forback-end technical execution.
Different stage, different tool.
(14:50):
If you're working on conceptdevelopment, grab the book.
If you're past that and facingtechnical validation decisions,
this Substack series might befor you.
If you're facing these types ofdecisions where it's later stage
in the product development andyou need risk-based methods to
do it and ways to move forward,then consider joining us on
(15:12):
Substack.
It'll be a three-month serieshere in October, November, and
December of 2025.
On Substack, there will be deepdive posts, QA, and live chats
on these topics, so considersubscribing.
This has been a production ofDeanny Enterprises.
Thanks for listening.
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