Hey, what's up, Toby? We've made another week.
Nice. Hey, man. I know. It's processed out. We're
going to jump right in. Let's do it. Today's
topic comes from operations and manufacturing.
And it's around the Six Sigma, or the Sigmas,
or the number of failures within omnipotent records,
which Six Sigma is what? Three parts per million?
Is that a defect? Yeah. Well, it feels like all
we ever talk about, if we talk about sigmas in
the workplace, we tolerate nothing less than
six. That's all we talk about. And I think part
of it is we refer to that kind of work around
air reduction as Six Sigma work or lean work.
Yeah, so. It's three parts per million. I think
about manufacturing. That makes sense, right?
If we're rolling tires or ball bearings off the
line, we don't want to be digging through those.
I get that. Yep. But gosh, three errors per million
transactions. So all right. So what one sigma.
So one sigma is. 30 .9 % All right, so that's
690 ,000 defects per million So that's terrible
That is a 30 % success rate, which is on par
with probably most of the PowerPoints we've seen
Yeah, so 31 % defect rate which means only 61
% of them are defect free Yeah Did I say that
right? Yeah, I know it's backwards. So like among
a million, there's only going to be 310 ,000
that are defect, that are free of defect. That's
one sigma. Right. Okay. So that's, you know,
so the, your good output, another way to say
that your good output on one sigma is 30 .9%.
Okay. It's brutal. Yeah. But I mean, again, for
knowledge work, PowerPoints that I have seen.
It's a good example though, right? I mean, yeah,
like how many defects does a PowerPoint have?
And that's, and that's a really good rule. What
are the consequences of a spelling error in a
PowerPoint or what are the consequences? It could
be an issue if it's an extra zero and you're
talking about loss reduction or sales targets.
Folks get antsy. If it's an indent, if it's a
font error, things are the same, right? I would
say that many defects are hidden by polished
PowerPoints. Like what would McKinsey be without
a polished PowerPoint? That's a frightening thought.
Yeah. All right. Okay. So one of the things about
manufacturing is that to move up a sigma takes
about the same effort, right? So going from one
sigma to two sigma is basically going from 30
.9 % good to 69 .1 % good. So just moving it
up, just one standard deviation basically. Which
means that, you know, still 70%. This is probably
most I would say that this is probably most knowledge
work. Yeah. If we think about that in the broadest
sense, everything from communication to assorted
manual tasks. Yeah. Yeah. Anything where a system's
not guiding our action. Yep. Yeah. That feels
pretty reasonable. Yeah. So if you think about
one sigma, it's basically the process fails most
of the time or it's highly inconsistent. Yeah.
Right your PowerPoint presentation Template changes
multiple times a quarter, right? Like seconds,
you know to two Sigma or you know, it's 69 %
good output. Yeah still there or areas occur
frequently Okay, now let's move that just up
one level right and so the three Sigma It jumps
from close to 70 % good to 93 .3 % good. Heart
change. Yeah. It literally like, up to three
sigma, it's kind of almost like a hockey stick.
Right? So again, it's, you know, from one sigma
to two sigma, it's 39 % better. From two sigma
to three sigma, it is 23 % better. And then the
next jump from four sigma to five sigma, it's
93 % to 99 .38%. It's literally 7%. And then
to five sigma, it jumps basically percentages
like 0 .4%. And these are literally the same
amount of effort. Right. And yet I don't think
when we think of business processes and knowledge
work, we don't actually think about it as changing
the process to improve the output. But it's about
the consistency too. Yes. Right. And so when
we do highly variable tasks, it's hard to get
a sense of our actual consistency. Correct. So
the, did I deliver it on time is, is not really
a Sigma ish kind of outcome because it depends
on the task. So I think that's, you know, as
we're talking about this, I'm thinking about
having done, we've talked a lot about this, having
done a lot of process improvement work years.
You know, sometimes it's process improvement
at one desk or sometimes it's an entire team.
But it feels like so often everybody is the big,
is the organization gets larger, the work niches
down and people have increasingly specialized.
And so to be able to have, you know, to your
point, the difference of shifting from high level
of defects at one Sigma to a marked reduction
at two Sigma, you know, in a large organization,
you have to touch a lot of people. Yeah. Even
as we're talking about this, it makes me think,
ah, this is why we start to see formal payroll
systems being implemented or financial systems
being upgraded and driving a lot of consistent
behaviors just to reduce variability. Oh, no,
totally true. And what's interesting is like,
I think oftentimes in knowledge work, we don't
think of it as a process of delivery. We think
of it as a task that we need to go. more of like
doing the dishes or something. I don't even know
how, I don't know, that was a terrible example.
But we think of it as like, oh, my boss wants
me to do the thing. Right. And we don't think
of it, you know, we've talked about this quite
a bit where if the thing is repeatable, turn
it into a process. Totally. Yeah. But it's funny.
I've been watching the World Series. Yeah. I'm
going to deviate here from our topic here for
a little bit, but Google Cloud has this commercial
on baseball players that hit the base with their
bat and how that leads to hard hits or something
like that. And in my mind, I'm like, that's novel.
I appreciate that. And it is absolutely, there's
no action that you can take. And I find it fascinating
that like a lot of knowledge work comes down
to novelty, which means that you can get, you
can basically hide all your defects in the corner
because as long as it's novel and it follows
some sort of, you know, the cognitive bias of
the person with the highest salary in the room,
then it's okay. Yeah. Processes don't have personalities
to soften. message or build relationships the
same way that people do. Yeah. Yeah. Yeah. But
I just, I just think sometimes we don't, we just
don't think about it as something that even can
be fixed. Yeah. And so, you know, and sometimes
it's the person that needs to fix it as the manager.
And if you're an IC, then it's not yours to fix.
Well, Chris, it kind of makes me. Ask the question
like is it even reasonable to talk about professional
Interactions in this same concept of like air
free transactions You know manufacturing is a
is a highly repeatable super linear process generally
Yeah, not super linear. Then we invest a lot
of time understanding all the permutations that
it could go down Yeah, I think this is where
it falls into like do your system support or
do they complicate and Like it does your sis
like Because I would say that there are some
times in which a one sigma rate is okay Yeah,
and I would say that there are other times where
you know, it needs to be in the in the highly
accurate Highly consistent outcome, right? And
I think sometimes those two get flopped Right,
and I think I think some of it is about the novelty
like and I I Trash on data a lot not because
I don't like data but because data seems to be
whatever you want it to be Yeah, and so I do
think that when it comes to Consistent things
that we do we should aim to make them better
You know and not aim to make them more novel
It's interesting. So novelty is a is a source
of defects and so that also makes me think of
the failure rate that we have around innovation
and that's Unfortunately come kind of this catch
-all buzzword For I have a new approach that
I'm testing to I'm just sloppy and I'm wildly
inconsistent. So they're innovating, you know
well it is interesting because like your upstream
and your downstream has to all match in a manufacturing,
because you've got work in progress, you've got
stuff moving through the line. Totally. Knowledge
work oftentimes ends up being one person doing
one thing. And the transferability of that knowledge
isn't necessarily taken into consideration. I
saw a funny meme on someone doing math of 16
minus 9 as a McKinsey consultant and they're
like, oh, you can obviously see that this is
a sum of squares. And so if you turn that into
three squared and four squared and then you multiply
it all out and they go, they do four or five
steps and they get to 16 minus nine and you're
like, still seven. And there we are. And we made
it to seven. No, it's true. Well, the transfer
of moving pieces and parts versus moving information,
it's easier to know if all the pieces have been
moved from point A to point B. Whereas it's hard
to know if all the information has been translated
from person A to person B. We are terrible at
that as human beings. It's hard to know, isn't
it? Because you don't check. Because we assume
that everybody seems everybody thinks the exact
same way that we do or doesn't action the same
way like if you ever demo anything Like in a
in a scrum you will be like what in the world
is that person doing? Don't they see the button
to the left and then you're like, oh That was
a semi clever way of doing it that I would have
never thought of or figured it out Chris, I think
that's so true. Shadowing somebody to watch how
they navigate a familiar application is fascinating
and painful. Yeah. Because you're right, you
get the same way. Yeah, I built a UI. I was really
happy to build some stuff in there that stuff
just never got used because it just was unusable.
Yeah. Like for me, not doing the day -to -day
work was what I thought would work. But that
ended up being one of these knowledge deviations
because I didn't know the work that was being
done and so I didn't built it in the right way.
The reality is it's like, what's funny, the other
funny thing is oftentimes it's not in the outcome
in which it's. Like we become fascinated with
being distraction. I kind of stopped there a
little bit, but we're fascinated with the distraction
and not the actual process or outcome. And so
it's like, hey, if we, you know, did we sell
the deal? Yeah, we did. Let's go celebrate. Did
we sell the right deal? Did we sell it to the
right client? Does it align with what we're trying,
where we're going? Like those are all really
important. And I think... That's one of the deviation
of saying yes to everything is a bad one. Well,
Chris, I think as we're talking this through,
the piece that I take away is that, A, being
nervous when somebody comes to Six Sigma, your
professional services approach, your college
work, and the piece you just touched on really
resonates with me and it's that we have to step
back and ask the bigger picture question. Where?
Because sometimes a highly defective exchange
can still move the mission forward. That can
still achieve our outcomes. Even if the PowerPoint
is error ridden and has, you know, all kinds
of font mismatches. Yeah. So the other is you
probably hear snoring in the back. That's my
bulldog. Just just crashed out. Not helpful for
a podcast, but having a grand old time just snoring
away. I thought that was your stomach. Better
that it's a bulldog, sir. That's awesome. Well,
we made it again, man. All right. Good stuff.
All right. Catch you next time. All right. See
you.