Time
9 hours 3 minutes
Difficulty
Beginner
CEU/CPE
9

Video Transcription

00:00
Hi, guys. Welcome to measure phase. Why equals f of X? I'm Catherine MacGyver. And today you're gonna learn the relationship between dependent and independent variables. So I'm going to warn you guys apart. This one is a big ease as you think through your yellow belt training. Um,
00:19
with the information that you've come through thus far,
00:22
this is going to be foundational, especially if you're looking to consider to continue your training. When we talk about why if equals f of X and you'll hear this phrase throwing around a lot, think back to, um, high school algebra.
00:37
This is, in fact, a function formula that tells us that it's a linear equation from a process improvement standpoint. Why equals F of X is important because it tells us that our organization's function as a formula.
00:51
So we have inputs. We have a function which is that f eyes pretty cool. Um and then we have outputs or dependent variable. So our organization and our businesses is a whole function is a formula
01:06
with that understanding that they are this formulaic approach. You can change the outputs based off of either changing the inputs or the process. So Now we're going to start talking about dependent and independent variables. So you're why is going to be your dependent variable? This is what you want
01:26
to change in your f of X is going to be your inputs. Excuse me, is going to be your function your f and your ex, which are your independent variables. These air, what you think will change that. So if you think about this from a formulaic approach, I've I decrease my cycle time.
01:45
This is going to be my f of X.
01:48
I can increase my why, which is my customer Satisfaction.
01:53
So you may ask yourself, Why does this matter? Why do we need to think about our organizations in the form of in the form of a formula? So the reason is that the assumption is that if we manage our inputs in our processes, then we will have good outputs and good outputs or what we want, because
02:12
this is what makes our customers happy and customer satisfaction drives competitive edge.
02:16
Um,
02:19
so fundamentally, this is where we as business people on as lean six Sigma practitioners are finally empowered to start dictating the outcomes of our organization. So When you think about why equals f of X, you want to think about all three processes?
02:36
Um, they're all three aspects. You want to think about your deep in it variables. You want to think about your
02:40
independent variables, your exes and you want to think about your functions or your activities. How ever
02:49
that being said, we have all heard this phrase garbage in garbage out If you're independent, variables
02:59
are not
03:00
to the standard that you need them to be. Your dependent variables or your outputs are virtually guaranteed to be poor. And I use that word that phrase word for word because that is what my, um, mentor trained me when I was becoming,
03:17
uh, a lean six Sigma perfection
03:21
professional is if your inputs are poor, your outputs are virtually guaranteed to be poor. So this is why we focus quite a bit on why equals f of X, Because why is our output? This is what we are getting towards, which means a couple of things, one that we need our
03:37
inputs to be our inputs and our independent variables to be up to par,
03:40
and then the second is so that this works in two different aspects. You have your actuals, your garbage in garbage out bad inputs, equal bad outputs. But then you also have this higher level idea about data collection. And if you collect bad data, you then make
04:00
not ideal decisions.
04:02
So it also lays the groundwork for when we're talking about designing our data collection plan. We want to keep in mind that if we don't collect the data we need, we make decisions that we don't necessarily can. We can't necessarily support moving on. But for the sake of y equals f of X, we're talking about dependent and independent variable.
04:23
So when we think about
04:25
independent variables, we're thinking about all those exes. If you remember back to high school algebra, you want them to be independent. These are things that can change. Who your supplier is is an independent variable, low quality of the outcome or the quality of the materials is a deep indent variable.
04:44
Um, so there also are inputs in our processes.
04:46
When we start thinking through our root cause analysis, these there are causes, so we talk a little bit about cause and effect later on, when we start doing our because analysis this is what causes the effect. I was late because I overslept. So the dependent variable is late. Nous
05:06
the end of invariable was oversleeping.
05:10
These are our problems. So it's important to call out the difference between problems and symptoms right now. So problems are what is the actual problem?
05:21
Symptoms are what we observe. So if you think back to our pizza examples that we've been doing off and on, but our problems statement for our pizza, what we observed
05:31
is customer satisfaction Is customer dissatisfaction in error rates with our ordering What? The problem. Maybe maybe lack of employee training. It might be that our interface on our register doesn't make sense. It might be that
05:46
one of our integrations between our register in our kitchen staff doesn't work. It might be that are
05:51
we didn't get all of the supplies that we needed. So we figured we just make a pizza rather than telling the customer no. So problems are different than symptoms. Symptoms are how we know a problem exists. But it was that cause ality it happens before and thin. The symptom happens after. So when we talk about testing,
06:12
independence are controlled. So if you've heard things about randomized testing when we get
06:16
very, very briefly into design of experiment, these are the things that we can shift around, and thus we can then measure or monitor. You talk about dependent variables. We talk about things that these need other things to manifest. These are outputs. These are our effects.
06:34
So if I oversleep, I am late to work. Being late to work is the effect or the dependent variable.
06:41
We talked a little about the difference between problems and symptoms, symptoms or things that we can see. Um, quantify sometimes qualify. So we talk about the differences between Lean and six Sigma. In their experience aspect, symptoms air generally related to experience, monitor these air. The things that we actually measure, we measure
07:00
both
07:01
but dependent variables are going to be the ones that we monitor because they're related to our objectives statements.
07:09
So when we talk about why equals f X and you ask yourself, why is this important?
07:15
W h y. So you want to isolate the independent variables one of the traps that you can get into where your projects aren't necessarily a successful, as you want them to be is because you don't either recognize all of the independent variables or you're measuring dependent variables as if they were independent variables. That tells us that the root cause wasn't quite deep enough.
07:35
Um,
07:35
independent variables drive the dependent variables there of those predecessors you need tohave that relationship for it to be cause ality. If two things happened at the exact same time, there's correlation but not cause ality. So one didn't cause the other one on Dhe, then coming back to our organization as a formula
07:56
inputs Dr
07:57
Outputs. So your company is an algebraic linear equation. Where you have your outcomes are a function. There are based off of activities of those inputs. So that's it for why, if equals f of X. Our next module up is types of data.
08:16
Thanks, guys.

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