Using Systems Mapping to Inform the Strategic Planning Process
in Higher Education
Hyunjung Kim, Ph.D.
Associate Professor
Department of Management
College of Business
California State University, Chico
Phone: 530-898-5939
Fax: 530-898-5501
Email: hkim18@csuchico.edu
Michael T. Rehg, Ph.D.
Department Chair
Department of Management
College of Business
California State University, Chico
Phone: 530-898-5663
Fax: 530-898-5501
Email: mrehg@csuchico.edu
Abstract
In this paper, we present a case of a higher education institution where systems mapping was used in
parallel to a strategic planning process in order to deepen the understanding of connections among sub-
sectors of the system and elicit dynamic insights for decision making and policy implementation. We
describe the process used to generate systems maps and how they were communicated, and provide
examples of dynamic insights that became available from the sessions. The key objective of this
article is to share our experience with the system dynamics community so that we collectively build a
repertoire of effective practices contributing to the strategic planning process, particularly in higher
education.
Introduction
Strategic planning for institutions in higher education can take many forms, but often follows a set of
traditional approaches to strategy. In some cases, previous studies have used basic strategy concepts like
SWOT analysis (Andrews 1971), the five forces model (Porter 1980) and the resource-based view of the
firm (Barney 1991) to engage in strategic planning. Others developed balanced scorecards (Kaplan and
Norton 1995) to align their strategic goals and organizational activities. These institutions sometimes
share their experiences as case studies and reports (for example, Cyert 1988; Morrill 1988), encouraging
other institutions to be more systematic in their planning process.
Researchers and practitioners involved in the strategic planning process in higher education often
recognize that there are unique aspects to higher education institutions that set them apart from other
organizations. Weick (1976) described educational organizations as a loosely coupled system where
different units and elements are attached but also maintain their own identity and separateness. In such
case, the strength of the coupling may change with time and there may be multiple means-ends
relationships in the system. Foote (1988) notes, unlike other organizations, power is shared in universities
among the board, the president, administrators, faculty, and students. Their product is “ideas” that are
impossible to quantify, and insufficient resources must be allocated among the “limitless needs of
students and professors.” Autonomies and intellectual freedom is most valued, but the competitive
environment forces schools to allocate their resources in a strategic manner to meet the student and
industry demands. In public universities, higher institutions are embedded in the broader context of
administration and external constraints influencing their internal decisions.
Recognizing the complexity of the higher education system, some institutions have used a system
dynamics approach to strategic planning. A comprehensive review of system dynamics study of higher
education can be found in Kennedy (2009). Examples of the topics include funding allocation based on
performance (Galbraith 1998), student-faculty ratio dynamics and their implications on teaching and
research effectiveness (Barlas and Diker 2000), resource allocation among departments (Vahdatzad and
Mojtahedzadeh 2000), funding and its implications on performance (Oyo e¢ al. 2008), and student
enrollment and faculty hiring (Trailer 2012). These studies use a combination of approaches including
qualitative systems mapping, formal simulation modeling, system archetypes, and interactive game
interface.
In this article, we present a case of a higher education institution where systems mapping was used in
parallel to the traditional strategic planning process in order to deepen the understanding of connections
among sub-sectors of the system and elicit dynamic insights for decision making and policy
implementations. We describe the process used to generate systems maps and how they were
communicated, and provide examples of dynamic insights that became available from the mapping
sessions.
The key objective of this article is to share our experience with the system dynamics community so that
we collectively build a repertoire of effective practices contributing to strategic planning process,
particularly in higher education. This paper is organized as follows: First, we discuss how strategic
planning can benefit from a system dynamics approach. Then, we will briefly introduce a case of a public
university in the United States where systems mapping was used to inform the strategic planning process.
Then, we will present examples of key dynamic insights generated from the mapping exercises and how
they might have informed the key decision makers. Finally, we will discuss some of the benefits and
challenges we experienced and how future studies can be conducted to support a wider range of planning
activities.
The Need for System Dynamics in Strategic Planning
Mintzberg (1994) noted that corporate strategic planning has been practiced since the mid 1960’s, but
criticized planners for being too formal and too far removed from reality. Many institutions engage in top-
down strategic planning which too often results in a product that is not used to guide decision-making.
But planning has been defined as “a formalized procedure to produce an articulated result, in the form of
an integrated system of decisions.” (p. 12, italics added) It should be obvious to researchers and
practitioners of system dynamics that an integrated system of decisions is exactly what system dynamics
maps and models produce, and are used to support decision-makers. System dynamics is well-suited for
organizational planners faced with complex decisions, such as those in higher education institutions.
Rowley, Lujan, and Dolence (1997) noted the difference between traditional planning and strategic
planning along several dimensions, and the failure of higher education institutions with strategic planning
due to the inherent differences between universities and businesses. Dill (1996) pointed out that university
planning has been poorly designed due to informal planning processes, self-interest among units, and the
use of practices borrowed from others rather than ones developed organically. He makes the case that the
planning process in universities “...must be designed as a primary means of organizational integration”
(p. 40, italics in the original), and should also promote collaboration. In system dynamics, maps and
models serve as the boundary objects (Black 2013), and organizational integration and collaboration are
one of the key goals of the system mapping and modeling process, especially when using the Group
Model Building (Richardson and Andersen 1995; Andersen and Richardson 1997; Vennix et al. 1997;
Hovmand et al. 2011).
Both Rowley et al. (1997) and Dill (1996) call for a process that is inclusive of all stakeholder:
buy-in from those implementing the plan will be achieved, and to promote an approach that is fair and
open. As Willson (2006) found in the Cal-Poly Pomona experience, traditional planning approaches fall
prey to the pressures of budget shortfalls and disparate goals of groups across campus and cannot generate
the trust required to achieve the buy-in being sought. Using stakeholders to develop systems maps and
simulation models is a more effective means to promote both of these goals of a university planning
process. However, most of the literature on planning clearly advocates a process that is linear in nature,
and “calculating” as Mintzberg (1994) states. Kennedy and Clare (1999) pointed out the problems of
using a linear approach found in input/output models, which “ignore the dynamic interaction between the
input /output factors and the nature of the ‘transformation’ taking place.” (p. 5). When a set of initiatives
is listed under various categories, or goals, the interactions and feedback loops among the initiatives
cannot be seen, and decision makers cannot possibly comprehend them due to the limits of bounded
rationality (Sterman 1994). The decision maker is left with falling back on their own judgment about what
is most important, critical in the short run, or least costly to implement. The result is likely to be biased to
the decision maker’s values, and be met with resistance from those who implement the actions, but feel
that they have not been consulted.
We contend that a greater understanding of the system structure will promote buy-in among the
stakeholders of a university, more so than traditional forms of strategic planning have accomplished.
Naturally, this depends on the level of involvement of those stakeholders, and whether ownership of the
systems maps and simulation models has been truly transferred to the stakeholders. Nevertheless, we
believe there is more potential of this happening with the system dynamics approach than in other
strategic planning exercises. The result will be less planning and more synthesis, as Mintzberg (1994)
advocated.
Case Description: Systems Mapping for Academic Planning
The authors of this article have been involved in the academic planning process of a public university in
the U.S. In 2013, the provost kicked off a new academic year with an approach to revising an expired
academic plan. To guide the process, a committee of 14 members was formed consisting of
administrators, deans, department chairs, student representatives and clerical staff leaders. More than 600
members of the campus community were invited to participate in a total of 61 “possibility conversations”
- meetings across campus with various groups of faculty, staff and students to answer three basic
questions, including how to prepare students to thrive in the 21" century.
In the following semester, the committee performed a content analysis of the data collected from the
possibility conversations, and from the data emerged various ideas for success in six key themes:
Support and Prepare students for lifelong success
Promote excellence in teaching and learning
Build Community through connections, relationships and collaboration
Commit to faculty renewal
Commit to staff renewal
Qe a Go Se
Enhance organizational processes, ication and t
The committee members were then divided into the six theme groups, and they invited diverse
stakeholders around the campus to come up with a list of action plans for achieving success in their
assigned area. Recently, the groups have combined the action plans and presented the materials to the
provost for prioritization and implementation of the actions.
System dynamics was first introduced to the committee as the groups were organized around the six
theme areas. At the time, the groups were in the process of organizing and analyzing the data from the
initial conversations and engaging relevant stakeholders to elicit action items. While working in their own
area, the groups were concerned about being in the silos and wanted to explore how different issues and
actions in their area have a system-wide impact. The authors offered systems mapping as a way to
represent the system-level connections and understand the dynamics generated by feedback loops,
accumulations, and time delays.
The authors used the mapping language consistent with the system dynamics practice: causal loop
diagramming (CLD) and stock and flow diagramming. The mapping exercises took some of the key
scripts from the Group Model Building processes (Andersen and Richardson 1997; Hovmand et al. 2011).
However, the mapping exercises were not problem-driven, and they were more intended to capture the
big picture across the group conversations.
The committee members had the following goals for the systems mapping exercise:
1. Represent the connections between different actions and their outcomes beyond the theme
boundaries
Provide a way to understand and manage the system complexity
Identify high-impact actions
Identify stakeholders possibly impacted by different actions
Provide coherent narratives for selected actions
wr wWhd
In the current stage of the project, the systems mapping has achieved the first two goals. The third goal is
partially met, but a formal simulation model would be needed to quantify the degree of impacts. The
fourth goal would require an additional analysis of stakeholders and reorganization of the systems maps
around the stakeholders. The final goal can be achieved when the systems maps are further developed and
modified by decision makers who select and implement actions.
Process Used to Generate Systems Maps
In this section, we summarize the systems mapping process used in the case.
Initial Preparation. Before engaging with the six groups in the committee each working on a different
subsector of the system, the authors created a handful of systems maps based on the report that analyzed
the data collected from 61 possibility conversations. For each group, two to three maps were created. The
purpose of these maps was to introduce the mapping language, initiate conversations, and encourage
member inputs—similar to Concept Models (Richardson 2013) in Group Model Building. These maps
were modified later with the group inputs, if not discarded completely.
First Round of Meetings with the Groups. The first round of the mapping exercise was carried out with
the six groups—one group at a time. Each group was composed of two to four members from different
levels and functions of the university. The meeting typically took about 2 hours per group. During the
meeting, the basic CLD and stock and flow concepts were briefly introduced. This took less than 10
minutes. Then, the pre-generated systems maps pertaining to the group’s key area were shared and input
from the members was collected. The conversations mostly focused on the key issues, possible policies
and their expected outcomes.
Generation and Modification of Systems Maps. After the first round of group meetings, the authors
created 16 sub-sector maps representing different parts of the institution. The maps were organized by
issues and involved stakeholders, and a typical map would incorporate inputs from multiple groups. We
also created an overview map showing how the 16 sub-sector maps were connected.
Second Round of Meetings with the Groups. We returned to each group with the sub-sector maps
relevant to the group’s area for their review. Each group reviewed four maps on average, and a meeting
typically lasted for an hour. In these meetings, the modelers elicited further inputs from the group and
made sure the maps were appropriately representing the group’s perspectives.
Modification of Systems Maps and Key Insights Generated. With the inputs from the second round of
meetings, the sub-sector maps were modified and further polished. For new issues that emerged in the
meetings, additional maps were created. After the second round of the meetings, we ended the mapping
exercises with 20 sub-sector maps. In this paper, we discuss some of the findings from the systems
mapping exercises, using three of the maps as examples.
Dynamic Insights Gained from the Mapping Exercise
Across the six theme groups, we generated 20 sub-sector maps representing various issues and aspects of
the system. In this section, we present three examples illustrating how the maps have identified important
dynamic complexities in the system.
1. Curriculum and Pedagogical Innovations
Curriculum and pedagogical innovations were one of the key issues mostly discussed in the “teaching and
learning” group. However, many of the specific innovation ideas were discussed in the “student success”
group, and the faculty workload influenced by the innovations was discussed in the “faculty renewal”
group. Therefore, the map was generated with the inputs from the three groups.
The map below conceptualizes the faculty workload in teaching as a pressure coming from the ratio of
teaching hours needed to available. The number of students would be the major factor influencing the
demand side, but even with the same number of students, if the quality of student-faculty interaction were
to increase, more teaching hours would be needed. The quality of student-faculty interaction is positively
associated with teaching effectiveness, which would result in a greater rate of student success. (Figure 1-1)
When there is an increase in the teaching demand, the pressure for faculty teaching hours can be
alleviated by three major means: (1) faculty hiring, (2) greater allocation of faculty work hours to
teaching, and (3) bigger class/section size. These are all balancing loops trying to address the problem in
the system.
An increase in the section size may be the quickest fix to meet the teaching demand, but it will not be a
fundamental solution for the system due to its negative implication on the quality of student-faculty
interaction.
Enhancing the quality of student-faculty interaction without adding faculty workload pressure is a
challenging task. Can we address these tradeoffs with curriculum and pedagogical innovations? In general,
curriculum innovations would focus on what is taught (i.e. program) and pedagogical innovations would
focus on how it is taught (i.e. practice). In the systems map below, curriculum innovations and
pedagogical innovations (CI/PI) are conceptualized as a supply chain of innovation projects. (Figure 1-2)
Although it is important to note that different innovation initiatives have different goals and expected
outcomes, such differences are not captured in the map.
Student-Faculty
Interaction
- + Teaching
Effectiveness
[students |
Section Size
Total aay gp Pressure for Faculty Total Faculty
Teaching Hours ——— Teaching Hours
+ ae Available
Ke Faculty Hiring
Faculty Hours
Allocated to
Teaching
Figure 1-1.
Curriculum & +
a Curriculum & =
108
Innovations in
4
New Cl/PI Initatives ci/Pi Completed
CI/PI Projects
Discontinued
XC
CI/PI Success Rate
Bog
z=
Innovations In Use Ci/PI Dropped
Time to Complete
CI/PI Projects
(R)
+
Learning from
Ci/PI Experience
Figure 1-2.
The reinforcing loops in Figure 1-2 depict a learning curve: As more curricular innovation projec
fully completed and launched, we gain more experience in curriculum and pedagogical
success
innovations. The collective experience increases the success
are
rate, which will encourage new initiatives
and reduce the number of discontinued projects. The experience also reduc
s the time to complete
innovation projects. These reinforcing cycles will result in the growth of curriculum and pedagogical
innovations in use.
Figure 1-3 connects the curriculum and pedagogical innovations to their impact on teaching effectiveness
and the faculty workload. When these innovative projects are under development, they require additional
faculty work hours leading to greater workload pressure. This will discourage faculty commitment in
starting new innovation initiatives. This is a balancing loop counteracting the efforts to increase the
curriculum and pedagogical innovations.
On the other hand, some curriculum and pedagogical innovations are targeted to enhance faculty teaching
efficiency. When successfully launched, they will reduce the faculty teaching hours needed relieving the
workload pressure. This can positively influence the start of new initiatives, creating a reinforcing
dynamics.
There are other curriculum and pedagogical innovations that may not necessarily increase the faculty
teaching efficiency but may target other positive outcomes such as innovative practices for enhancing
student engagements and currency in teaching.
Quality of
Student-Faculty
Interaction ~~
+
Effectiveness
Innovative Practices for
Enhancing Student
Sn
Engagement
renal rac i Currency in
otal Faculty Pressure for Faculty Curriculum and
—
Teaching Hours Teaching Hours Pedagogy
Needed
+
Efficiency in
Teaching
'
wmmte |, Curriculum & mS
Pedagogical
Innovations in
pe
= ogi
New C\/PI Initatives ci/P| Completed Innovations In Use CI/PI Dropped
Figure 1-3.
From this mapping exercise, the following dynamic insights are gained: First, the curriculum and
pedagogical innovations that achieve faculty efficiency in teaching and at the same time increas
engagement may present a high impact opportunity.
Second, even with the innovations enhancing faculty teaching efficiency, there may be a worse-before-
better effect in the faculty workload, because there is a greater faculty time commitment in the
development stage. This initial negative outcome should not discourage the efforts and investment in the
curriculum and pedagogical innovations, as they will mitigate the faculty workload pressure in the long
term. Therefore, strong administrative support to alleviate the initial workload pressure in faculty is
needed.
Third, once the system learns to effectively develop and launch innovative projects, the reinforcing
dynamics will promote more innovations. Until the system reaches this self-growth phase, administrative
support for innovations is needed as a push in the right direction.
2. Faculty Hiring and Service Load
Faculty hiring is one of the key decisions in the higher education system. Tenure track hiring is often
associated with the school’s long-term strategic plan as well as the tenure density (i.e. the ratio of tenure
track and tenured faculty to adjunct faculty). Hiring adjunct faculty can fill immediate teaching needs
with less impact on financial resources. (Figure 2-1)
ee)
Adjunct Faculty
Leaving
Adjunct Faculty
Adjunct Faculty
Hired
¥¢
Faculty Leaving Strategic Commitment
Immediate Teaching
Need ——*™ Pressure to Hire Adjunct -
+ Faculty over TT Faculty “Tenure Density
fo
TT Hiring Delay Financial Resources
Available for Hiring
Figure 2-1.
A problem can arise when a tenure track or tenured (TT/T) faculty member leaves and an adjunct faculty
is hired to fill the immediate teaching need. While adjunct faculty can pick up the teaching load, the vast
majority do not share the service duties with the TT/T faculty. New adjunct faculty members need
mentoring, performance reviews and appraisals. This increases the service load of individual TT/T faculty
and could eventually cause faculty burnout and a lower level of morale. This is a reinforcing dynamic,
10
because the burnout can result in higher TT/T faculty turnover, requiring more adjunct faculty hiring to
fill in the position. (Figure 2-2)
Therefore, it is important to pay attention to the TT/T faculty service load as well as strategic
sid
s (such as maintaining AACSB accreditation in the case of business schools) to make
faculty hiring decisions. When faced with an immediate teaching demand with a limited financial
resource, hiring adjunct faculty can be a temporary solution, but it compromises the service and research
activities of TT/T faculty.
Pant
Tenured Faculty
Leaving
jenand Tenured Faculty
Faculty Morale
(R) 7
+
TTELEcuty, Total Faculty Service Load
* Faculty Burn Out
Individual TT/T +
Faculty Service Load
Figure 2-2.
There is another dimension to faculty hiring. There are service duties that can be performed mostly or
solely by the tenured faculty—such as the review of Retention, Tenure, and Promotion (RTP) packages or
junior faculty mentoring. Thus, hiring TT faculty can lead to a higher service load for the tenured faculty
until the TT faculty become tenured, a process which usually takes 4 to 6 years. In that sense, there is a
worse-before-better effect when hiring TT faculty to alleviate the service load. (Figure 2-3)
11
Faculty Positions
Need to Be Filled ~
Tenured Faculty
Leaving
2 renured Faculty
Tenured
/ Faculty Morale
% (R) }
TT Faculty Leaving
Tenure Track Faculty
TT Faculty Hired
TT to T Faculty Ratio
\. Faculty Burn Out
RTP and Peer Mentoring
Workload for Tenured :
aculty
Figure 2-3.
3. Faculty Compensation
In the public university system described in the case, inequity in faculty salary has been one of the major
factors negatively affecting faculty morale. The phenomenon is sometimes referred to as salary inversion,
and it occurs when the existing faculty’s
lary rate fails to catch up with the increase in the market salary
rate.
As shown in Figure 3-1, when the market salary rate for TT faculty increase, there is a pressure to
increase the TT faculty hiring salary in order to match the market rate. Otherwise, the school must lower
the hiring qualifications to fill the needed positions. If the hiring qualifications were lowered, they would
have a negative impact on the faculty teaching and research effectiveness. Therefore, the school makes an
effort to keep the hiring salary rate somewhat comparable to the market rate.
Due to the system budget constraints, the salary rate of existing faculty has failed to reflect the changes in
the market salary rate. There are cases of salary inversion where the existing faculty salary is lower than
the newly hired TT faculty salary. This salary inequity leads to low faculty morale and increases the
faculty turnover. When existing faculty leave (in Figure 3-2, represented as tenured faculty leaving), the
hiring must take place at the TT level at the market salary rate. If we assume a continuous increase in the
market salary rate, the new TT hiring will push up the hiring salary rate, leading to even greater gap
between existing and new faculty salaries. This is a reinforcing dynamics (R).
12
Tenure Track Faculty
TT Faculty Hired Tenured
Pressure to Increase
Hiring Salary Rate
TT Hiring Success Rate
Tenured Faculty
Hiring Salary Rate
TT Faculty Leaving
Tenure Track Faculty
Tenured
TT Faculty Hired
Pressure to Increase
Teaching/Research
Salary Rate of
Existing Faculty
¢
Hiring Salary Rate
Salary Inequity
(3)
(8) =
Gap in Salary Pressure to Lower pe Teaching/Research
Hiring Qualifications Effectiveness
+
:@
Hiring Salary Rate
Market Salary Rate
Figure 3-1.
Faculty Positions
Need to be Filled
—
G) GQ
Tenured Faculty
Leaving
Tenured Faculty
Effectiveness Ss.
Faculty Morale
Therefore, at the sys
Figure 3-2.
tem level, a better solution would be raising the existing faculty salary rate to address
the salary inequity. That way, the school retains the faculty and there is less need to hire new TT faculty
13
at the market rate. This is more cost effective approach and it will also enhance the faculty morale leading
to a better faculty performance.
Conclusions and Discussion
In this paper, we described a case of higher education institution where system mapping was used in
parallel with the traditional strategic planning process to gain an understanding of the system complexity
and its dynamic implications. The mapping process was inspired by the Group Model Building (GMB)
scripts (Andersen and Richardson 1997; Hovmand et al. 2011), but it was modified to meet the need of
the academic planni i Consis' with the recc dation of Bell, Cooper, Kennedy, and
Warwick (2000), we worked with key decision-makers in the process, at least at the level of academic
affairs, which holds one of the vice presidential positions on the campus. In addition, seven of eight
academic deans were involved, and several department chairs. Further stakeholder involvement was
achieved with numerous meetings across campus during the process. The resultant themes that emerged
encompassed a wider range of stakeholders than were identified by Kennedy and Clare (1999).
While working with the six theme groups within the planni i we d 20 sub-sector
maps—where each map incorporated the inputs from two to three groups. In this paper, we presented
three of those 20 maps, and described some of the key dynamic insights gained from the systems maps. In
general, insights from the process and outcomes of the systems mapping exercises can be summarized as
follows:
First, systems maps show how different parts of the system are connected. These connections exist
beyond the sector boundaries, and the maps present an organized way to visualize and understand the
complexity of the system. In strategic planning, understanding these connections are critical for
effectively defining goals, performance measures, outcomes, and stakeholders.
Second, systems maps show the effect of feedback dynamics (i.e. reinforcing and balancing) in the
system. They draw attention to vicious/virtuous cycles and policy resistances, and this enriches the
strategic planning process by identifying leverage points and unintended consequences.
Third, systems maps show the effect of system delays. They provide perspectives on the short-term and
the long-term effect of different policies and possible trade-offs. For strategic planning, this allows goals
to be set with different time frames, and expected outcomes to be more realistic.
Overall, systems maps are effective communication tools that can illustrate the connection between
stakeholders, goals, actions, and their impacts in a dynamic sense. This understanding is valuable in
laid ludj
in any organization, higher education institutions, where each unit in the
system functions independently with its own goals and resources yet embedded in a highly integrated
context.
As the authors carried out the systems mapping sessions, we were also faced with a number of challenges:
14
First, because the mapping exercises were incorporated in the academic planning process as the need has
emerged, the modelers could not optimally align the mapping progress with the planning process. The
two processes mostly ran in parallel. Based on anecdotes, we believe the systems mapping contributed to
the academic planning Process by bringing i in additional insights. However, if the mapping sessions were
s IL d in the demi ing process from the initial stage, it could have made more
impact with clear objectives, defined deliverables, and learning outcomes.
Second, the mapping process was inevitably affected by an unforeseen leadership change in the
organization. Two months into the second year of the academic. planning process, there was a turnover of
the provost who had initiated the process, The academic pl ittee continued the process, but a
key administrator who supported the system dynamics effort was no longer present.
Third, because the maps were intended to bridge the communication among different groups within the
academic planning committee, effective distribution and communication of the systems maps proved to
be important. This ication aspect of modeling is add
d in limited system dynamics literature
(Ghaffarzadegan et al. 2011), and we hope more research is done in this area to develop a repertoire of
best practices.
Finally, as our case, some systems mapping exercises may be geared towards generating a holistic
representation of the system without a clear problem definition. In such case, we may need to adopt
mapping activities or deliverables different from that of GMB. In GMB, groups collectively define
problems and build causal loop diagrams around the problem. The causal loop diagrams serve as a
qualitative sketch for the formal simulation model structure. However, in our case, the maps present
complex connections between different parts of the whole system, and turning those maps into a formal
simulation model would not have lead to a problem focused model—unless a model pick a specific
problem embedded in the larger system depicted in the maps. Systems thinking literature may be helpful
in this case, but we also call for system dynamics modelers to d their ing and modeli
processes, so that we can collectively learn from our experiences.
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