Name: Mohua Tanjin Payel
ID: 18241075
Section: A
Application 7.1: Collecting and Analysis Diagnostic Data at Alegent Health.
1. What interview measures were taken for data collection in Alegent Health?
Ans: 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 learning’s into the future.
One of the crucial parts was the interview measures where people of different levels and
hierarchy were asked some direct questions.
● Initial interviews were conducted with executives and physicians about (1) the context of
change at Alegent, including 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 interviews with people who were closely
connected with the implementation of each clinical service area strategy.
● A third set of interviews were a 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.
● In addition to these initial interview results, data from the second round of
implementation interviews 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 formation of the clinical strategies.
2. Which quantitative tools were used for quantitative data analysis?
Ans: The most common quantitative tools are means, standard deviations, and frequency
distributions; scatter grams 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 economical 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.
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 understanding of the
data. The frequency distribution i s a graphical method for displaying data that shows the
number of times a particular response was given.
● Scatter grams and Correlation Coefficients:
In addition to describing data, quantitative techniques also permit OD consultants to
make inferences about the relationships between variables. Scatter grams and correlation
coefficients are measures of the strength of a relationship between two variables.
● Difference Tests:
The final technique for analyzing quantitative data is the difference test. It can be used to
compare a sample group against some standard or norm to determine whether the group
is above or below that standard. It also can be used to determine whether two samples are
significantly different from each other.
The second use of difference tests involves assessing whether two or more groups differ
from one another on a particular variable, such as job satisfaction or absenteeism.
Difference tests also can be used to determine whether a group has changed its score on
job satisfaction or some other variable over time. The same questionnaire can be given to
the same group at two points in time. Based on the group’s means and standard
Deviations at each point in time, a difference score can be calculated.
