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Developing measurements for a process requires a mind-set for accountability. With the spirit of accountability, the team can identify measurements that reflect the performance of the process itself and its relationship with the performance of the company. Measurements must be understandable, quantifiable, and economic. The data must be easy to collect and analyze. The measurements intended use is to identify opportunities for improvement instead of to punish someone for errors. The process measurements must also be linked to the Six Sigma Business Scorecard. A sample of measurements for various functions is shown in Figure 6-7.

CD_NAME --------------Blue Court and Spark IN_STOCK -------42 22

In order to achieve this appearance, the objects have been assigned the following properties:

9:

As you can see, using the IN predicate to define a list is a fairly straightforward process and a useful one when you know exactly which values you want to compare your columns to. It also is a simpler method than defining separate predicates for each value, as in the following example:

SELECT FROM WHERE OR OR OR CD_NAME, IN_STOCK COMPACT_DISC_INVENTORY IN_STOCK = 12 IN_STOCK = 22 IN_STOCK = 32 IN_STOCK = 42;

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Measurements Number of Errors per Requisition Total revenue Number of new customers Value of repeat business Number of proposals accepted to total proposals submitted Variance in on-time completion of design Completeness of design outputs Variance of design from target performance Changes after design release Reproducibility of design Receivables age Timeliness of financial measures or reports Invoicing errors Cost of poor quality Number of recurring problems Improvement opportunities Rate of improvement Planning Communication Employees satisfaction

This statement will return the same results as the SELECT statement in the previous example; however, as you can see, it s much more cumbersome. Now let s take a look at a SELECT statement that uses a subquery in the IN predicate. Suppose you want to create a query that returns CD names and their artists. You want your query results to include only those CDs that have more than 10 copies in stock. If you refer back to Figure 9-4, you ll see that the COMPACT_DISC_ARTISTS table includes the CD names and their artists. However, as you can also see, the IN_STOCK values are stored in the COMPACT_DISC_INVENTORY table, which means you ll need to reference that table in order to return the correct rows. To do so, you can create the following SELECT statement:

SELECT TITLE, ARTIST FROM COMPACT_DISC_ARTISTS WHERE TITLE IN ( SELECT CD_NAME FROM COMPACT_DISC_INVENTORY WHERE IN_STOCK > 10 );

CHAP. 5]

If you execute this statement, you ll receive the following results:

TITLE -------------------Famous Blue Raincoat Blue Court and Spark Past Light Out of Africa Blues on the Bayou ARTIST ---------------Jennifer Warnes Joni Mitchell Joni Mitchell William Ackerman John Barry B.B. King

FIGURE 6-7.

Notice that only six rows have been returned. These are the six CDs listed in the COMPACT_ DISC_INVENTORY table that have an IN_STOCK value greater than 10. Now let s take a closer look at the SELECT statement in order to give you a better understanding of how the IN predicate works. The WHERE clause contains only one predicate. It begins with the name of the column (TITLE) whose values you want to verify. The TITLE

Figure 10-4

10:

Fig. 5.18 shows the Menu Editor, with the entries required to change the color within the circle. Notice the caption (Colors) and the name (mnuColor) assigned to the first menu item. Also, note the use of separators between the menu items.

and that value would be the current user identifier. If you do not specify a default value for the ORDERED_BY column, you can use the special value to insert the user. For example, the following INSERT statement inserts a row into the CD_ORDERS table:

For each process measurement, the team must establish a trend chart to drive the rate of improvement. Since the goal for rate of improvement is aggressive, the range of values on the y axis changes significantly and can become invisible at lower values due to the wide range. The Log Normal trend chart, where each major division represents an order of magnitude instead of a linear increment of the value, can correct this situation. Figure 6-8 shows a chart with the goal line set for 3 years. A similar chart can be made for 1 year as well to magnify presentation of the data.

INSERT INTO CD_ORDERS VALUES ( 'Rhythm Country and Blues', 14, CURRENT_USER );

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