# 质量管理怎么做？

员工只做你考核的，不做你倡导的。 — 郭士纳

People do what you inspect, not what you expect. — Louis V. Gerstner, Jr.

**流程**

流程，就是一组有效的经验集合。在长期的、大团队合作时，她能让参与者围绕着方向前进，不跑偏。

以软件开发流程（软件行业一般称为模式）为例，常见有以下几种：

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**工具**

工具，可以让我们脱离手工作业，合适的工具，能让我们高效完成工作任务。

常规的质量管理工具有以下几种，在TQC（全面质量管理）江湖，号称“七种武器”。

主要目的：分析原因种类

**When to Use a Fishbone Diagram**

- When identifying possible causes for a problem.
- Especially when a team’s thinking tends to fall into ruts.

**Fishbone Diagram Procedure**

Materials needed: flipchart or whiteboard, marking pens.

- Agree on a problem statement (effect). Write it at the center right of the flipchart or whiteboard. Draw a box around it and draw a horizontal arrow running to it.
- Brainstorm the major categories of causes of the problem. If this is difficult use generic headings:

-Methods

-Machines (equipment)

-People (manpower)

-Materials

-Measurement

-Environment - Write the categories of causes as branches from the main arrow.
- Brainstorm all the possible causes of the problem. Ask: “Why does this happen?” As each idea is given, the facilitator writes it as a branch from the appropriate category. Causes can be written in several places if they relate to several categories.
- Again ask “why does this happen?” about each cause. Write sub–causes branching off the causes. Continue to ask “Why?” and generate deeper levels of causes. Layers of branches indicate causal relationships.
- When the group runs out of ideas, focus attention to places on the chart where ideas are few.

主要目的：收集、统计

**When to Use a Check Sheet**

- When data can be observed and collected repeatedly by the same person or at the same location.
- When collecting data on the frequency or patterns of events, problems, defects, defect location, defect causes, etc.
- When collecting data from a production process.

**Check Sheet Procedure**

- Decide what event or problem will be observed. Develop operational definitions.
- Decide when data will be collected and for how long.
- Design the form. Set it up so that data can be recorded simply by making check marks or Xs or similar symbols and so that data do not have to be recopied for analysis.
- Label all spaces on the form.
- Test the check sheet for a short trial period to be sure it collects the appropriate data and is easy to use.
- Each time the targeted event or problem occurs, record data on the check sheet.

主要目的：展示比例分布

**When to Use a Histogram**

- When the data are numerical.
- When you want to see the shape of the data’s distribution, especially when determining whether the output of a process is distributed approximately normally.
- When analyzing whether a process can meet the customer’s requirements.
- When analyzing what the output from a supplier’s process looks like.
- When seeing whether a process change has occurred from one time period to another.
- When determining whether the outputs of two or more processes are different.
- When you wish to communicate the distribution of data quickly and easily to others.

**Histogram Construction**

- Collect at least 50 consecutive data points from a process.
- Use the histogram worksheet to set up the histogram. It will help you determine the number of bars, the range of numbers that go into each bar and the labels for the bar edges. After calculating W in step 2 of the worksheet, use your judgment to adjust it to a convenient number. For example, you might decide to round 0.9 to an even 1.0. The value for W must not have more decimal places than the numbers you will be graphing.
- Draw x- and y-axes on graph paper. Mark and label the y-axis for counting data values. Mark and label the x-axis with the L values from the worksheet. The spaces between these numbers will be the bars of the histogram. Do not allow for spaces between bars.
- For each data point, mark off one count above the appropriate bar with an X or by shading that portion of the bar.

主要目的：展示累计比例和关键因素

**When to Use a Pareto Chart**

- When analyzing data about the frequency of problems or causes in a process.
- When there are many problems or causes and you want to focus on the most significant.
- When analyzing broad causes by looking at their specific components.
- When communicating with others about your data.

**Pareto Chart Procedure**

- Decide what categories you will use to group items.
- Decide what measurement is appropriate. Common measurements are frequency, quantity, cost and time.
- Decide what period of time the Pareto chart will cover: One work cycle? One full day? A week?
- Collect the data, recording the category each time. (Or assemble data that already exist.)
- Subtotal the measurements for each category.
- Determine the appropriate scale for the measurements you have collected. The maximum value will be the largest subtotal from step 5. (If you will do optional steps 8 and 9 below, the maximum value will be the sum of all subtotals from step 5.) Mark the scale on the left side of the chart.
- Construct and label bars for each category. Place the tallest at the far left, then the next tallest to its right and so on. If there are many categories with small measurements, they can be grouped as “other.”
- Calculate the percentage for each category: the subtotal for that category divided by the total for all categories. Draw a right vertical axis and label it with percentages. Be sure the two scales match: For example, the left measurement that corresponds to one-half should be exactly opposite 50% on the right scale.
- Calculate and draw cumulative sums: Add the subtotals for the first and second categories, and place a dot above the second bar indicating that sum. To that sum add the subtotal for the third category, and place a dot above the third bar for that new sum. Continue the process for all the bars. Connect the dots, starting at the top of the first bar. The last dot should reach 100 percent on the right scale.

Steps 8 and 9 are optional but are useful for analysis and communication.

主要目的：展示相关/偏离性

**When to Use a Scatter Diagram**

- When you have paired numerical data.
- When your dependent variable may have multiple values for each value of your independent variable.
- When trying to determine whether the two variables are related, such as…

-When trying to identify potential root causes of problems.

-After brainstorming causes and effects using a fishbone diagram, to determine objectively whether a particular cause and effect are related.

-When determining whether two effects that appear to be related both occur with the same cause.

-When testing for autocorrelation before constructing a control chart.

**Scatter Diagram Procedure**

- Collect pairs of data where a relationship is suspected.
- Draw a graph with the independent variable on the horizontal axis and the dependent variable on the vertical axis. For each pair of data, put a dot or a symbol where the x-axis value intersects the y-axis value. (If two dots fall together, put them side by side, touching, so that you can see both.)
- Look at the pattern of points to see if a relationship is obvious. If the data clearly form a line or a curve, you may stop. The variables are correlated. You may wish to use regression or correlation analysis now. Otherwise, complete steps 4 through 7.
- Divide points on the graph into four quadrants. If there are X points on the graph,

-Count X/2 points from top to bottom and draw a horizontal line.

-Count X/2 points from left to right and draw a vertical line.

-If number of points is odd, draw the line through the middle point. - Count the points in each quadrant. Do not count points on a line.
- Add the diagonally opposite quadrants. Find the smaller sum and the total of points in all quadrants.

-A = points in upper left + points in lower right

-B = points in upper right + points in lower left

-Q = the smaller of A and B

-N = A + B - Look up the limit for N on the trend test table.

-If Q is less than the limit, the two variables are related.

-If Q is greater than or equal to the limit, the pattern could have occurred from random chance.

主要目的：展示稳定性

**When to Use a Control Chart**

- When controlling ongoing processes by finding and correcting problems as they occur.
- When predicting the expected range of outcomes from a process.
- When determining whether a process is stable (in statistical control).
- When analyzing patterns of process variation from special causes (non-routine events) or common causes (built into the process).
- When determining whether your quality improvement project should aim to prevent specific problems or to make fundamental changes to the process.

主要目的：理解复杂过程

这里的流程图，更多是理解功能/系统的内部数据流、控制流、状态条件等等。

项目管理中，流程的概念已经变得很广义，而且已经变成管理学科一个重要的组成。

**落地**

业界成功/失败的经验，不断在证明一件事：质量是一种结果，是做出来的，而不是说出来的。以下是落地最主要的几件事：

人。所有的一切，都是人来执行。人的长处是决策评审等创新工作，不足是重复性工作容易失误。所以的第三方验证，可视化要求，进一步减少了人为失误，提高质量信心

平台工具。在数字时代，非决策类的工作，如记录、统计、通知、关联等等重复性工作，大部分可以用软件平台工具来替代，可以帮助减少人的重复劳动时间，聚焦于决策类任务

考核引导。请参考本页面顶部的名言，质量靠的是全员参与，把质量和每个人切身利益绑在一起，激发人对高质量工作的动机

持续改进。质量是一个动态机制，类似于锻炼身体，贵在坚持，能积累小的量变，直到质变为整体成熟度的提高

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**学习活动：**

你现在用的软件（或其他专业）的开发流程，使用哪些工具来管理质量，落地执行时的难点，请在后续讨论区分享讨论。