了解如何提升工作效率和提高质量标准，学会分析和改善服务业或制造业商务流程。主要概念包括流程分析、瓶颈、流程速率和库存量等。成功完成本课程后，您可以运用所学技能处理现实商务挑战，这也是沃顿商学院商务基础专项课程的组成部分。
第 4 单元班次 6 视频课程
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Do curso por University of Pennsylvania
运营管理概论（中文版）
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第 4 单元 - 质量
质量并不是运营管理唯一的重点，但是质量对于企业长期发展和成功至关重要。本模块将介绍运营中与质量的几个主要方面，导致缺陷的常见原因、发现质量问题以及保障可靠性和标准的常用实践方法。本模块教学结束后，您将了解缺陷可能发生的原因，并且能针对质量和稳定性提出合理的方法。
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Christian TerwieschAndrew M. Heller Professor at the Wharton School, Senior Fellow Leonard Davis Institute for Health Economics Co-Director, Mack Institute of Innovation Management
The Wharton School
Once you encounter abnormal variation, or once you detect a defect, you have to
start investigating the root causes. But how do you find the root cause?
In this session, we'll introduce some truths for root cause problem solving.
Specifically, we will introduce the concept of an Ishikawa diagram, as well as
of as of a Pareto chart. Most of these tools belong to a toolbox
known as Kaizen The idea of the Toyota production system is that quality and
process improvement tasks don't have to be carried out by the management but are
carried out by the front line employees. So our jobs is to put together a simple
set of toolbox, so that we can equip with the front line workers to go about
improving their work. Ishikawa diagrams are structured
brainstorming techniques that help employees think about the root cause for a
problem. Let's get back to our chocolate example.
Maybe you want to figure out why the weight that we'll measure it for a
particular set of bags or it's too heavy. Let's think about the potential root
causes of this. One set of root causes might relate to
their being too many. Pieces of chocolate in the bag.
Another root cause might relate to each of the pieces being too heavy.
Then in turn, it might have been the bag that was too heavy, or maybe the scale was
broken, and the batch was of the right weight.
And so we're struggling with a measurement problem.
Within each of these root causes, there are potential subroot causes.
A famous technique in the Toyota production system is known as the five
Why's. When you root cause problem solving, you
keep on asking why, why, why. The bag was too heavy.
Why? Well, there were too many pieces in there.
Why? Well, the machine that was putting the
pieces in was poorly calibrated. Why?
And so on, until you really get to the root cause.
Now, you notice, there's no rocket science involved in these diagrams, .
It's just a useful brain storming techniques.
If you draw nicer than I do, You notice that this little diagram looks
a little bit like a fish, With kind of the head of the fish up here,
And these being the fishbones. For this reason, this is also called a
fishbone diagram. Once you have mapped out the potential
root causes, you go into the field and start collecting data about the actual
defects. You'll then map out the defect
occurrences, or the number of defects for each of the types here in the Ishikawa
diagram for each of the defect types and that leads to a graph that looks like
this. So you sort them by number of occurrences,
we'll say too many pieces in the lead. And then all the way maybe having, you
know, just two problems where the bag was the root cause.
And then you can plug the cumulative number of problem occurrences in a curve
that looks like this. Typically, you'll find an 80-20 logic.
80% of the defects could be explained by twenty percent of the root causes.
This is known as a Pareto principle. Allow me to use the examples of the
Ishikawa diagram and the Pareto chart to make some philosophical reflections about
operations management. Most of what we do as academics, and most
of what we have done in this course, is create models of the underlying
operations. Now models are always an imperfect
approximation, a hopefully good approximation but they're still imperfect
approximation of the underlying reality in the operations.
Now as academics, consultants and managers, we're always at risk that the
ideas that we come up here are just based on our thoughts and models that we've
generated in our brain, but they don't work in reality.
What you have noticed with the problem solving in Kaizen is that there's a strong
emphasis on iteration between the world of reality and the world of thought.
The trigger for the improvement project is happening in the field when there are
defects. Because of G.
Doka, we stop the process, and start thinking about it.
This reflection is happening in the world of thought.
The Ishikawa diagram forces us to think about many root causes and that probably
will start triggering some improvement ideas.
But we don't just jump to the idea that we like.
Instead, we go back out in the field and collect data.
That's what the Pareto chart does. It's an empirical support for which root
cause we should go after first. Once we've identified the root cause that
accounts for the majority of the defects, we'll take that back into the world of
thought and start exploring some alternative solutions.
Again, we're not gonna run out and standardized these solutions so quickly.
We'll take it back on the field and run some small scale experiments.
Only once we have done so can we standardize the process and say that's
really a better process. So this oscillation between the world of
thought. And reality, is the key signature of good
problem solving. Rapid iteration is at the heart of
creativity. Notice that both the Six Sigma production
system, as well as the Toyota production system, emphasize this quick iteration
between the world of thought and reality. Pareto charts and Ishikawa diagrams
certainly look very simplistic, and almost trivial, compared to some of the material
that we covered earlier on in this course. Remember when we computed the expected
weight time, and the queue with M servers, the square root and the exponent there?
But, don't hold the simplicity of the tool, of the Ishikawa diagram and the
Pareto chart against them. To really drive Kaizen through your
organization, you have to equip your frontline employees with simple
frameworks. Both of these tools are emphasizing data
collection in an empirical approach to problem solving,
Very similar to statistical process control and six sigma.
Instead of corporate BS, long PowerPoint presentations, we're going to follow the
data to find the root cause behind the defect.
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