arrows represent the forces, and the length of the arrows corresponds to the strength of the forces. The information could have been collected in a group interview in which members were asked to list those factors maintaining the current level of group per- formance and those factors pushing for a higher level. Members also could have been asked to judge the strength of each force, with the average judgment shown by the length of the arrows.
This analysis reveals two strong forces pushing for higher performance: pressures from the supervisor of the group and competition from other work groups performing similar work. These forces for change are offset by two strong forces for maintaining the status quo: group norms supporting present levels of performance and well-learned skills that are resistant to change. According to Lewin, efforts to change to a higher level of group performance, shown by the darker band in Figure 7.2, should focus on reducing the forces maintaining the status quo. This might entail changing the group’s performance norms and helping members to learn new skills. The reduction of forces maintaining the status quo is likely to result in organizational change with little of the tension or conflict typically accompanying change caused by increasing the forces for change.
Application 7.1 describes another installment in the change evaluation process at Alegent Health. (The introduction of this longitudinal case began in Chapter 4.) In this application, the research team collected data from interviews and questionnaires, but
New Technology
Better Raw Materials
Competition from Other Groups
Supervisor Pressures
Forces for Change Forces for Maintaining Status Quo
Current Level of Performance
Higher Level of Performance Group Performance Norms
Fear of Change
Member Complacency
Well-Learned Skills
Force-Field Analysis of Work Group Performance
[Figure 7.2]
[Figure 7.2]
Collecting and Analyzing Diagnostic Data at Alegent Health
The two applications in Chapter 4 described the entry and contracting processes at the Alegent Health (AH) organization. As a result of a recent merger and the hiring of a new CEO and chief innovation officer (CIO), the organization had implemented a series of large-group interventions, known as decision accelerators (DAs), to generate innovative strategies in the six clinical service areas of women’s and children’s services, oncology, behavioral health, neuroscience, orthopedics, and cardiology. Alegent Health then hired two OD researchers to evaluate its change progress. The evaluation was intended to help AH understand what had changed, what had been learned, the impact of those changes, and how they might extend those changes and learnings into the future. The diagnostic phase involved the col- lection and analysis of unobtrusive, interview, and survey data.
Unobtrusive Measures
Immediately following each DA, the Right Track office (a group set up to manage the DA experi- ence) compiled a report listing participant names and affiliations, an agenda, instructions and elapsed times for each activity and process, photographs of different activities and all small-group outputs, and nearly verbatim transcripts of the large-group reports outs, activity debriefings, and discussions.
These reports were analyzed to understand the process and outcomes associated with the each DA. The researchers created a coding scheme and process to capture the characteristics of the partici- pants, the nature of the process, and a description of the DA outputs. Two coders analyzed the data to ensure the reliability of the analysis.
First, the results suggested that the DAs varied in their composition. For example, some DAs were composed of higher percentages of physicians or community members than other DAs. Second, some DAs were more “intense” than others as indicated by the amount of debate over decisions or issues, the number of different stakeholders who participated in the debates and discussions, and the extent to which the DA’s activities deviated from the preset agenda. Finally, some DAs produced comprehensive visions and strategies for the clini-
cal area, while others produced visions that were more narrowly focused.
Interview Measures
A second data set consisted of interviews with various stakeholder groups. Initial interviews were conducted with executives and physicians about (1) the context of change at Alegent, includ- ing organization history, strategy, and recent changes; (2) their reflections on the DA process;
and (3) clinical area implementation progress. The researchers conducted a second round of inter- views with people who were closely connected with the implementation of each clinical service area strategy. They were asked questions about the clarity of action plans, the level of involve- ment of different people, and implementation progress. Finally, a third set of interviews were conducted with a sample of staff nurses who had not participated in the original DAs or been directly involved in implementation activities, such as steering committees or design teams.
Each set of interview data was content analyzed for key themes and perspectives. A few of the summary results from the initial interviews are presented here.
When asked, “How clear were the action plans coming out of the DA?”, the executives were evenly split in their beliefs that the action plans were clear as opposed to the plans being essentially absent.
Executives were also asked, “What is going well/not so well in implementation of the different service line strategies?” About 20% of executives believed that the strategies were aligned with the mission/
vision of the health system and that the DAs had provided a clear vision to work toward. However, more than half of executives expressed concern that the organization lacked a real change capability.
Executives were also concerned about being over- whelmed by change, insufficient communication, and the need to involve stakeholders more.
When asked, “What would you list as the ‘high points’ or ‘best success stories’ of the DA process?”
and “What have been some of the least successful activities/concerns?”, the answers were more positive than negative. Nearly all of the interviewees noted
application 7.1
the improved relationships with physicians, and more than a third of executives said there had been some good learnings on how to increase the speed of decision making. Both of these results reflected cul- tural changes in the organization that were among the purposes for conducting the DAs. On the nega- tive side, a small percentage of executives noted the continued difficulties associated with coordinating the operations of a multihospital system.
Another area of interview data concerned execu- tive perceptions of how the DA might evolve in the future. There was a strong generic belief that the DA needed to evolve to fit the changed organ- izational conditions and a widespread perception that this should include a more explicit focus on execution, better change governance, and better follow-up and communication.
In addition to these initial interview results, data from the second round of implementation inter- views were used to develop six cases studies, one for each clinical service area. They described the initial DA event and the subsequent decisions, activities, and events for the 18 months following the forma- tion of the clinical strategies. Importantly, the case studies listed the organizational changes that most people agreed had been implemented in the first 18 months. Each case study was given to the VP in charge of the clinical area for validation.
Survey Measures
The researchers also collected two sets of survey data.
The first survey, administered during the initial round of executive and physician interviews, asked them to rate several dimensions of clinical area strategy and progress. The second survey was administered to
people who attended a “review DA” for three of the six clinical areas. It too measured perceptions of clini- cal strategy and progress.
The survey data were organized into three catego- ries and analyzed by a statistical program. The first category measured five dimensions of strategy for each clinical area: comprehensiveness, innovative- ness, aggressiveness, congruence with Alegent’s strategy, and business focus. Both executives and managers rated the clinical strategies highest on comprehensiveness and lowest on congruence with Alegent’s mission. Executives also rated the strategies lower on innovativeness. In all dimen- sions and for each clinical area, managers rated the five dimensions higher than executives did.
The second category measured how well the imple- mentation process was being managed. Executives
“somewhat agreed” that the clinical area strategies were associated with a clear action plan; however, there was considerable variance, suggesting that some clinical areas had better action plans than others. Similarly, managers “somewhat agreed”
that change governance systems exists and that change was coordinated.
The third category assessed implementation success.
As with the strategy dimensions, managers rated overall implementation progress higher than execu- tives did, but both groups were somewhat guarded (between neutral and agree) in their responses.
Managers were asked a more detailed set of ques- tions about implementation. There was more agree- ment that the clinical strategies were the “right thing to do” and had helped to “build social capital” in the organization, but they were neutral with respect to whether “people feel involved” in the change.
also used observation and unobtrusive measures. The analysis used a combination of qualitative and quantitative techniques. What do you see as the strengths and weak- nesses of the data collection and analysis process?
Quantitative Tools
Methods for analyzing quantitative data range from simple descriptive statistics of items or scales from standard instruments to more sophisticated, multivariate analysis of the underlying instrument properties and relationships among measured variables.14 The most common quantitative tools are means, standard deviations, and frequency
134 PART 2 The Process of Organization Development
distributions; scattergrams and correlation coefficients; and difference tests. These measures are routinely produced by most statistical computer software packages.
Therefore, mathematical calculations are not discussed here.
Means, Standard Deviations, and Frequency Distributions One of the most eco- nomical and straightforward ways to summarize quantitative data is to compute a mean and standard deviation for each item or variable measured. These represent the respondents’ average score and the spread or variability of the responses, respectively.
These two numbers easily can be compared across different measures or subgroups. For example, Table 7.3 shows the means and standard deviations for six questions asked of 100 employees concerning the value of different kinds of organizational rewards.
Based on the 5-point scale ranging from 1 (very low value) to 5 (very high value), the data suggest that challenging work and respect from peers are the two most highly valued rewards. Monetary rewards, such as pay and fringe benefits, are not as highly valued.
But the mean can be a misleading statistic. It only describes the average value and thus provides no information on the distribution of the responses. Different patterns of responses can produce the same mean score. Therefore, it is important to use the standard deviation along with the frequency distribution to gain a clearer understand- ing of the data. The frequency distribution is a graphical method for displaying data that shows the number of times a particular response was given. For example, the data in