Reflection Essay: Select an organization that you know very well (this can be the same organization you used in your case analysis or a completely different one), and write a THREE-page essay about th
PRODUCTIVITY MEASUREMENT AND ENHANCEMENT SYSTEM (ProMES) ProMES is a system that focuses on team goals, motivation, and feedback. It has been used with many kinds of teams (assembly line, manufacturing, maintenance, ban employees, painters, and customer service). Team tasks and teamwork are emerging in ever more businesses and agencies, but in the United States and other individualistic countries, people are more used to individual goals and effort. Pritchard and his col-leagues (Pritchard, 1995; Pritchard, Harrell, DiazGranados, & Guzman, 2008; Pritchard, Jones, Roth, Stuebing, & Ekeberg, 1989) developed ProMES as a way to promote a shift from the individual to the team. ProMES begins with the assumption that the main issues behind productivity are knowing how to allocate time and energy. Work tasks involve actions that produce a product or service, and the goal is to increase motivation to perform these actions by determining why some actions are selected over others and how much energy is put into those selected acts. ProMES is designed by teams and facilitated by trained professionals. These design teams proceed in steps. Step 1: identify objectives. The teams are asked to identify productivity objectives using a brainstorming process (every member is encouraged to submit ideas in an BRINKERHOFF AND DRESSLER SEVEN-STEP PROCESS Like so many others, Brinkerhoff and Dressler (1990) defined productivity as output (e.g., bushels of corn, parts manufactured, freight cars loaded, houses cleaned, students taught) over input (e.g., labor, energy, time, cost). Consequently, they focus their ap-proach on detailed measurement of outputs and inputs. Table 8.5 gives many examples of outputs and inputs from a large array of jobs and businesses, including some hard-to-measure white-collar and professional work. More generally, Brinkerhoff and Dressler outlined seven key steps to developing a set of integrated measures that will help guide an organizational unit or the whole organization to future improvement and success. Step 1: mission statement. Regardless of whether the measurement system is being developed for a unit within a larger organization or for the entire organization itself, a mission statement is imperative. A mission statement defines the raison d’être (reason for existence) and identifies the major goals and customers. It defines the essential purpose in clear, unambiguous terms and keeps management and staff focused on important results. The mission statement should be compatible with the strategic plan. Step 2: expectations. Understanding the needs, desires, and expectations of the customer is central to the long-term vitality of an organization (see Chapter 7). These needs, desires, and expectations will change over time, so a methodical practice of administering surveys, conducting interviews, observing focus groups, etc., is obligatory for keeping the customer satisfied. This customer information, along with the mission statement, will guide the selection of key outputs (Step 3) and output measures (Step 5). Step 3: key outputs. There are usually many outputs from any given organization or unit within an organization. Brinkerhoff and Dressler use the example of a training unit that might provide consultations, seminars, workshops, training certificates, training reports, training needs analyses, review services, training schedules, and so on. Not all of these are “key” outputs. Key outputs are those that are valuable to customers and consume a lot of resources. For a training unit, seminars and workshops may be a high priority, whereas review services may not. A common rule of thumb is to apply the 80-20 rule (select the 20% of outputs that account for 80% of the success). The key outputs may not be the easiest to measure, but ease of measurement should not be the basis for selection. Step 4: major functions. This step was covered in detail in Chapter 7 under the production system (Figure 7.2). Acquiring a complete understanding of how inputs are transformed into outputs and delivered to a customer will be indispensible to Steps 5 and 6 and may also aid in the previous Step 3 (identifying key outputs). Step 5: output measurement selection. Unfortunately, there is no dictionary of output measures that managers or staff can consult to select the perfect output indicators. Table 8.5 gives some examples, but these are just examples. Measures need to be cus-tom-made by each organization to suit the unique needs and demands of the operation. However, a few guidelines can be suggested: (a) if two measures are of equal value, pick the one that is easier to collect; (b) do not rely solely on purely quantity measures; measures of quality are more important to the customer and should be incorporated into the selection mix or form part of the output (e.g., in Table 8.5, many of the outputs are adjusted by quality such as undamaged items, accurate reports, and satisfied stu-dents); (c) pick measures that are on a fast cycle (e.g., weekly) rather than ones that only occur occasionally (e.g., annually); (d) in the beginning, start small by picking only a few measures of each key output rather than gathering as many as possible (and pick the less controversial measures to avoid endless discussion of the results); and (e) pick outputs that are associated with known and controllable inputs (see Step 6). Step 6: input measurement selection. The primary criterion for selecting and measuring inputs is that they must be associated with key outputs. Also, as noted above, pick inputs that can be controlled (e.g., if managers have little control over cost or availability of materials, data on these inputs will be pretty useless). Many of the guidelines above for selecting outputs are also relevant for selecting the inputs (all other things being equal, select those that are easy to measure; pick fast cycle measures, and start small). Step 7: index construction. A productivity index is simply an output over an input. Thus, this step could be as easy as dividing a single key output by a single input. Organizational assessment is rarely that simple, however. Normally, there will be several key outputs, and each may be measured by more than one indicator. Therefore, there is a good possibility that the organization will end up with a bunch of indexes. This introduces the problem of how to weight and combine these indexes. Performance indexing, discussed next, is one solution to this issue, but there are other approaches as well (e.g., take a single output and divide by the sum of the input