ECAR Research Study 4, 2007
IT Collaboration in Higher Education
6
Forming and Managing
Collaborations
Key Findings
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The most important factors when forming collaborations are selecting partners with whom one shares objectives
(72 percent), having a personal relationship with the IT leader (44 percent), and having institutional missions that
are like one’s own (43 percent).
While most respondents perform multiple activities to assess the value of collaboration, only 24 percent
formally vet their collaboration partners.
There was no statistically significant difference in respondents’ assessments of the benefits of collaboration
between those who do and those who do not focus on setting targets and quantifying the projected benefits
of the collaboration at the outset.
Many respondents (42 percent) report that their most significant collaborations have adopted formal governance methods.
The formality of governance appears to be influenced mostly by the nature of the collaboration. The choice
of formal governance is likely driven by collaborations that engage numerous institutions (such as shared
services and development projects) or by those that require formal legal structures to facilitate fund-raising
or hiring of staff.
Most respondents (75 percent) adopt formal agreements to define their collaborations. The most prevalent
form is a memorandum of understanding.
Respondents agree most that their significant collaborations have adopted agreements that clearly delineate their
financial responsibilities and decision-making authority. They agree the least that their agreements clearly delineate
the risks assumed by participants.
Collaborations with shared objectives accepted by all participants enjoy more efficient decision making.
Collaborators’ familiarity appears to have little influence on the nature of the agreement.
The form of agreement selected likely flows most directly from the choice of governance structure.
Emperor penguins go to incredible lengths
to incubate the eggs of their offspring. The
male penguins must keep the eggs warm by
balancing them on their feet while enduring
the incredibly harsh cold of the Antarctic
winter. As depicted in the movie March of
the Penguins, the animals survive this harshness by depending upon one another. The
©2007 EDUCAUSE. Reproduction by permission only.
EDUCAUSE Center for Applied Research
49
IT Collaboration in Higher Education
penguins huddle in a circle for warmth. Each
takes turns moving from the cold of the
outer ring to the warmth of the inner ring in
a process that rivals the best choreographed
Broadway show.
Penguins sustain their collaboration
through instinct and a shared drive for survival.
What sustains collaborations between organizations? Are they also driven by a mutual
need for survival (albeit of a different kind)?
Barry Walsh, associate vice president for
enterprise software at Indiana University, sees
a mutual dependency among organizations
as critical to sustaining collaboration. He calls
it the lack of a plan B. “We are like Cortez,”
Walsh explains. “There is no plan B. If you had
an alternative in mind, you wouldn’t be as
committed as you need to be.” From Walsh’s
perspective, IT collaborations can achieve the
same sustainability of their collaborations as
emperor penguins by cutting off the ability to
fall back on alternatives.
In this chapter, we will look at how
collaborators form, manage, and sustain
their ventures. In the first part of the chapter
we report our findings on how respondents
analyze collaboration opportunities and
choose their partners. In the second portion
of the chapter we look in greater detail at how
survey respondents report that they structure
and manage their most significant collaborations. We explore multiple aspects of these
collaborations, including governance, decision
making, communications, and trust.
Forming Collaborations
Despite their level of engagement in
collaboration, only 37.5 percent of respondents to the collaborators survey agree or
strongly agree that their IT organizations are
skilled at forming collaborations. A nearly
equivalent number (38.1 percent) provided
a neutral response to the question. Perhaps
respondents are being tough graders, or
perhaps it is just hard to get a read on how
well they are doing. Forming a collaboration
50
ECAR Research Study 4, 2007
can be as difficult as forming a personal relationship. Rosabeth Moss Kanter has written
that “corporate collaborations begin, grow,
develop—or fail—much like relationships
between people” (Kanter, 1994, p. 99).
Russell Linden, who studies collaborations
in government and nonprofits, intentionally
uses the metaphor of a personal relationship
to describe the four phases that he believes
collaborations travel through as they form.
He has divided the tasks of collaboration
into courtship, getting serious, commitment,
and leaving a legacy (Linden, 2002, p. 170).
Linden’s and Kanter’s work seems to drive
home the point that collaborations are relationships between individuals as much as
they are ventures between organizations.
It is this personal aspect that makes them
inherently difficult.
Due Diligence
We asked survey respondents to identify
the due diligence activities they routinely
perform before deciding to collaborate.
Respondents engage in a broad set of activities
to evaluate the quality of a collaboration opportunity. As Figure 6-1 illustrates, the majority
of respondents perform most of the due diligence activities we inquired about. The most
frequently performed activities are to evaluate
the onetime and recurring costs of the collaboration. This is a vital aspect of due diligence,
given our earlier observation that the decision
to collaborate is at its heart an evaluation of
whether the transaction costs of forming the
collaboration outweigh the potential benefits.
The least frequently performed activities are to
develop a set of quantifiable objectives for the
collaboration and to measure baseline service
levels (pre-collaboration). About a third of
respondents do not perform either one or both
of these activities.
Most collaborating respondents perform
most or all of these due diligence activities. In
fact, about 60 percent of respondents perform
six or more of the due diligence activities. Figure
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
6-2 shows the breakdown of the number of
these activities respondents perform.
The relatively smaller numbers of respondents who develop quantifiable objectives or
measure baseline service levels likely indicate
the added complexity of performing this
analysis. Most IT organizations struggle to
develop and implement a standard set of
service metrics. Future benefits are difficult to
quantify and credibly forecast. The reality may
be that respondents have less visibility into the
projected benefits of collaboration than they
do into the costs when making a decision.
The relative lack of baseline metrics will
make it more difficult for collaborators to
track and report the actual benefits realized
by the collaboration. We did examine whether
institutions that develop baseline service-level
Quantify baseline service levels
(N = 142)
66.9
Establish quantifiable objectives
(N = 145)
66.2
Evaluate skills of collaboration
partners (N = 149)
Figure 6-1.
80.5
Evaluate alternative solutions
(N = 145)
Due Diligence
Activities
89.7
Performed by
91.2
Quantify potential benefits (N = 148)
Collaborators
Estimate onetime costs (N = 153)
98.0
Estimate recurring costs (N = 152)
98.0
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Percentage of Respondents
None, 2%
Two, 2%
Three, 6%
Four, 12%
Figure 6-2.
Seven, 39%
Number of
Due Diligence
Activities
Performed
(N = 157)
Five, 18%
Six, 21%
EDUCAUSE Center for Applied Research
51
IT Collaboration in Higher Education
metrics and set quantifiable objectives for
their collaborations assess their benefits differently from those who do not. Interestingly,
we found no difference between those who
rely on quantifiable measures and those who
do not. There was no statistically significant
difference in respondents’ assessments
of the benefits in terms of risk reduction,
cost savings, enhancement of IT capability,
or speed of technology adoption between
those who do and those who do not focus
on assessing projected benefits.
In fact, we found no statistically significant
relationship between performance of any of
the due diligence activities we evaluated and
respondents’ sense of the benefits of their
collaborations. We also found no relationship
between the number of due diligence activities an institution performs and their evaluation of the benefits of their collaborations.
We are cautious about what conclusion to
draw from this finding. First, we must consider
the limitations of our ability to statistically
test the relationship between these variables.
Only a small number of respondents do not
perform several of the due diligence activities,
which degrades our ability to test for statistically significant relationships. Common sense
suggests that all of these due diligence activities are important in making the decision to
collaborate. We do not accept the conclusion
that they are unimportant to the quality of
collaborations. What is more likely is that
other factors are even more important to
determining the success of collaboration.
Selecting Collaboration
Partners
In Chapter 5, we observed that respondents are most comfortable partnering with
institutions and IT leaders with whom they
have a personal relationship. However, this is
not the only factor that goes into selecting a
partner. Alignment of institutional mission and
a common set of objectives for the collaboration also play an important role. Collaborators
52
ECAR Research Study 4, 2007
are looking not only for individuals they know,
but they are also looking for partners their
institution will recognize (similar mission) and
who want the same thing out of a collaboration that they do. Table 6-1 identifies the
top-three factors respondents said they look
for in a collaboration partner.
Most respondents’ primary concern is finding
other institutions that want to use collaboration to accomplish similar goals. Collaboration
researchers consider this the most important
task during the formation of collaborations.
Achieving a common understanding of why you
are collaborating and forging a consensus as to
what you will accomplish requires significant,
iterative conversation.
Secondarily, respondents are looking for
someone who is like them. As Table 6-1
illustrates, slightly more than 40 percent of
respondents told us they choose partners they
have a relationship with and from institutions
similar to their own. The tertiary set of factors
has to do with the quality of the prospective
partner, followed by understanding the technology capability, IT staff skills, and willingness
to share risk of a potential partner. We found
no significant differences in the relative importance of these factors by collaboration type.
Perhaps because institutions are collaborating with familiar partners, they feel they
already know much about their partners’
capabilities. Or, it is possible that these
factors are just not of paramount concern
to them. Respondents may be counting
on their relationship with their partners to
resolve any issues that arise and therefore
take a less critical look at the capabilities of
their co-collaborators. If this is true, we must
again raise the question of how this holds if
institutions are collaborating with partners
they don’t know as well. Can they assume
that issues of capability don’t matter as much,
or will they take on a more prominent role in
decision making?
For now, it appears that personal relationship takes the place of formal vetting of
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
Table 6-1. Most Important Factors in Selecting Collaboration Partners (N = 157)
Factor
Percentage Selected as Among Top Three
Common objectives
72.6%
Relationship with IT leaders
43.9%
Common institutional mission
43.3%
Technology capability
31.2%
Willingness to share risk
28.0%
Geographic proximity
27.4%
IT staff skills
21.0%
Relationship with institutional leaders
12.7%
Other
4.5%
collaboration partners. Among respondents,
very few reported that they engage in a
structured, formal process to understand
their partners’ strengths, weaknesses, and
readiness. Only 23.6 percent agreed that
they formally vet their collaboration partners.
Most respondents (41 percent) were neutral
on this question. Interestingly, we found no
significant difference in approach to vetting
partners between public and private institutions or those who were or were not part of
a higher education system. It appears that
even those outside of the natural peer groups
created by public systems are finding partners
that they feel they know well enough and do
not need to vet in any formal manner.
Managing and
Sustaining Collaboration
When designing our research methods, we
wanted to include a mechanism to understand
how institutions structure and operate their
collaborations and what impact those choices
have on their performance and ultimate
success. To accomplish this, we included in
the collaborators survey a set of detailed questions about the respondents’ most significant
collaborations. We asked respondents to tell
us about the governance, communication,
risk sharing, decision making, and management of those collaborations. In formulating
our questions, we drew upon the research
EDUCAUSE Center for Applied Research
of the Wilder Foundation.1 Led by researcher
Paul Mattessich, Wilder researched successful
collaborations across industries. Their research
center has reviewed a broad set of collaboration studies to identify those factors that
most frequently appear to drive the success
of collaborations.
From this research, Wilder identified 20
success factors that most frequently influence
the success of collaborations. These success
factors group in six categories: environment,
membership characteristics, process and structure, communication, purpose, and resources.
Wilder converted these factors into self-assessment questions that collaborators can use to
judge the health of their own collaborations
(Mattessich, Murray-Close, & Monsey, 2004).
With the foundation’s permission, we included
many of these questions in our collaborators
survey. We will draw periodically on the Wilder
research findings throughout our discussion
of respondents’ assessments of their most
significant collaborations.
Collaboration Case Studies
Most respondents chose to describe a
collaboration to provide a shared IT resource
as their most significant collaboration. Almost
42 percent of the respondents identified this
form of collaboration as their most significant, followed by collaborations to receive
IT services from another institution (24
53
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
percent). Figure 6-3 shows the breakdown
of collaborations selected for our in-depth
questions, by collaboration type. We will note
throughout this section instances where we
found evidence that the type of collaboration
influences decisions about how collaborations
are formed and managed.
Respondents’ primary motivations for
entering into these collaborations were to
save money or to enhance their technology or
technology services. Nearly half of the respondents were driven to collaborate by influences
from outside the IT organization. Respondents
highlighted compliance with a mandate (18.5
percent) or acting consistently with a broader
institutional commitment to collaboration (24.2
percent) as among their top-three reasons
for entering into the collaboration. Relatively
fewer respondents pursued collaboration as a
means to speed technology implementation,
gain access to scarce IT skills, or decrease reliance on commercial vendors. Table 6-2 lists
the collaboration drivers respondents indicated
were among their primary reasons for pursuing
their most significant collaborations.
To extend our profile of the collaborations,
we asked respondents to describe the role
they play in the collaboration. The majority
Other, 4%
Receive IT
resources, 24%
Figure 6-3.
Provide shared IT
resource, 42%
Respondents’
Most Significant
Collaboration, by
Collaboration Type
(N = 156)
Provide another
institution, 11%
Develop an IT
resource, 19%
Table 6-2. Top-Three Factors That Drove the Decision to Participate in the Collaboration
Driver
Reduce costs/gain efficiencies
54
Percentage
68.8%
Enhance IT services
52.9%
Access better technology
29.3%
Part of broad institutional commitment to collaboration
24.2%
Speed implementation of technology
22.3%
Comply with mandated collaboration
18.5%
Gain access to scarce IT skills
14.0%
Decrease reliance on commercial solution providers
12.1%
Complete a onetime project more effectively
8.9%
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
of respondents (64 percent) highlighted
collaborations in which they are a participant
or essential participant. More than a third indicated that they are either leaders or founders
of their collaborations. Figure 6-4 illustrates
the breakdown of the collaboration case study
by respondent role in the collaboration.
Respondents also describe differences in
how authority is shared within their collaborations. The majority are in collaborations
of equals in which each participant holds
equivalent authority. Many of these were also
collaborations to operate a shared service (46
of 85), the nature of which seems to lend itself
to a participation of equals. One-quarter of
respondents reported that within their most
significant collaborations, authority is held by
a single lead institution.
While the small number of respondents
prevents us from concluding anything with
statistical significance, we did observe an
interesting distribution of responses among
those collaborators who receive an IT resource
from another institution. Of the 38 institutions engaged in this collaboration form, 16
respondents reported that participants shared
authority equally and 14 respondents reported
that the authority rests with a single institution.
One might have hypothesized that authority
would most frequently rest solely with the
providing institution. The relatively large
number of receiving institutions that perceive
their authority as being equal to that of the
providers may be a sign of the health of these
collaborations. Through formal agreement,
relationship building, or both, these respondents feel their rights as customers give them
power equivalent to that of their suppliers.
Table 6-3 summarizes respondents’ assessments of the distribution of authority within
their collaborations, by collaboration type.
The collaborations that respondents highlighted for our in-depth analysis do vary in
type, motivation, and respondent role, and
these differences provided us with a rich set of
questions to explore throughout our analysis.
For example, do respondents driven to collaboration by external forces (such as mandates or
institutional strategy) structure their collaborations differently? Do they need to take more
formal measures to align the participants’
objectives? Are they less concerned about
picking the right partners due to a diminished
motivation for the collaboration?
Likewise, the respondent’s role in the
collaboration also presents interesting avenues
Observer, 2%
Founder, 14%
Participant, 34%
Figure 6-4.
Respondents’
Leader, 23%
Roles in Their
Most Significant
Collaborations
(N = 153)
Essential participant, 27%
EDUCAUSE Center for Applied Research
55
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
Table 6-3. Distribution of Authority in the Collaboration, by Collaboration Type
Collaboration Type
Authority
A single institution has
predominant authority.
N
A group of institutions
have predominant
authority.
N
All participants are
equal.
N
Total
Percentage
Percentage
Percentage
N
Percentage
Provide
Shared
Service
Develop
IT
Resource
Receive
IT
Resource
Provide
Another
Institution
Other
10
7
14
9
0
15.4%
24.1%
36.8%
52.9%
0.0%
9
11
8
1
1
13.8%
37.9%
21.1%
5.9%
16.7%
46
11
16
7
5
70.8%
37.9%
42.1%
41.2%
83.3%
65
29
38
17
6
100.0%
100.0%
100.0%
100.0%
100.0%
for analysis. For example, do leaders and
founders of collaborations have different
perspectives on governance and decision
making than other participants? How does
one’s role influence perceptions of the effectiveness of communications and consultation? In a similar vein, we also looked at how
the distribution of authority influences the
formation and results of collaborations. We
assessed whether collaborations with centralized authority and responsibility differed from
those with more dispersed authority.
Finally, we wondered how the significant
proportion of respondents who reported
on collaborations involving the provision or
receipt of IT resources would influence our
results. Would we see a greater emphasis
on metrics and formal agreements, since so
many of the collaborations involved service
provision? Would governance be more important to those engaged in multi-institutional
partnerships to deliver services than to those
in other forms of collaboration?
In the sections that follow, we report
on the results of our detailed analysis of
the collaboration case studies respondents
described. We organize the discussion around
the following subtopics: governance, formal
agreements, decision making, and communications. In each section, we highlight any
56
relevant differences in the results we found
that appear to relate in some way to the differences in the nature of the collaboration.
Governance
The formality of oversight that institutions have adopted for their most essential
collaborations spans a continuum from
informal cooperation to legally separate
entities with formal governance structures.
Many respondents (42.2 percent) report
that their collaboration is governed by a
formal mechanism that specifies how decisions are made. Similar numbers of respondents report either no formal governance
(22.1 percent) or reliance on informal means
of governance (19.5 percent). The smallest
number of respondents (13.6 percent)
report that their collaboration has taken
the step to create a separate legal entity to
govern their collaboration.
Collaboration types, such as shared
services or joint development projects, that
are more likely to include multiple institutions may also adopt more formal governance structures. Less formal governance
prevails among respondents engaged in
collaborations to provide an IT resource to
another institution. In this collaboration
type, individual institutions more frequently
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
retain complete and separate autonomy
from their collaboration partner. Such
service provision can usually be managed
within the framework of a written agreement and does not require formal or participative forms of governance such as boards
or separate legal entities.
Shared services and development collaborations are more likely to form separate legal
entities than other collaboration types. The
need for a separate legal entity may be
driven by a desire to create an actual entity
in which a large number of participants can
have a stake. Or, this form of governance
may facilitate the hiring of full-time staff or
the raising of funds to resource the collaboration. Table 6-4 provides a breakdown of the
governance structures respondents employ,
by collaboration type.
The formality of governance appears to
be influenced mostly by the nature of the
collaboration. Other factors such as the
partners’ familiarity with one another or the
characteristics of the participating institutions do not appear to influence choice of
governance. Respondents who believe more
strongly that they partner with institutions
with whom they are familiar are no more
or less likely to use formal governance than
other respondents. Likewise, we found no
greater incidence of formal or informal governance among respondents who are part of
higher education systems. The mere fact
that the participants in the collaboration are
familiar with one another does not appear
to cause them to eschew formal governance.
Rather, the choice of formal governance
seems more likely driven by collaborations
that engage numerous institutions (such as
shared services and development projects) or
by those that require formal legal structures
to facilitate fund-raising or hiring of staff.
Wilder’s collaboration research has not
identified any singular model of governance
that drives collaboration success. On the
contrary, they found that collaborations
must be flexible and adaptable to succeed.
Successful collaborations are those that find
ways to develop a clear understanding of the
rights, roles, and responsibilities of all parties
Table 6-4. Form of Governance, by Collaboration Type
Collaboration Type
Provide
Shared
Service
Governance
Each organization retains
control of its own decision
making.
N
An informal mechanism
exists to coordinate decision
making.
N
Percentage
Percentage
A formal mechanism exists to N
coordinate decision making.
Percentage
The collaboration is overseen
by a separately incorporated
organization.
Other
Total
N
Percentage
N
Percentage
N
Percentage
EDUCAUSE Center for Applied Research
Develop Receive
Provide
IT
IT
Another
Resource Resource Institution Other
Total
13
3
8
8
2
34
20.3%
10.7%
21.1%
47.1%
28.6%
22.1%
14
2
9
3
2
30
21.9%
7.1%
23.7%
17.6%
28.6%
19.5%
24
18
17
5
1
65
37.5%
64.3%
44.7%
29.4%
14.3%
42.2%
11
5
4
1
0
21
17.2%
17.9%
10.5%
5.9%
0.0%
13.6%
2
0
0
0
2
4
3.1%
0.0%
0.0%
0.0%
28.6%
2.6%
64
28
38
17
7
154
100%
100%
100%
100%
100%
100%
57
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
to the collaboration (Mattessich, MurrayClose, & Monsey , 2004). On this measure,
respondents to our survey are performing
well: Nearly 88.4 percent of respondents
report that their collaborations achieve a
clear delineation of roles and responsibilities
regardless of specific structure and form.
Respondents employ various elements
of good governance to achieve this positive outcome. The majority (67.4 percent)
have documented policies and procedures.
Significantly fewer (33.6 percent) have gone
beyond policies to draft formal bylaws. The
collaborations that do have bylaws likely
require them to create a separately incorporated entity to oversee the collaboration.
The number of respondents with boards to
oversee their collaboration (48.6 percent) far
exceeds those that have formed a separate
legal entity to manage the collaboration (13
percent). So, many have adopted boards
not because they have to (as required to
establish a new legal entity) but because they
find them effective. Table 6-5 identifies the
percentage of respondents that employ each
element of governance.
Full-time executive staff oversee 42
percent of respondents’ most significant
collaborations. The use of full-time staff
occurs across many collaboration types.
Proportionate to the number of collaborations of each type, they are used most
frequently by collaborations to develop an
IT resource and collaborations in which a
respondent receives an IT resource from
another institution. Nearly 40 percent of all
shared services collaborations also employ
full-time executive staff. The only collaboration type in which they are not used fairly
extensively is where one institution is the sole
provider of a service to another.
It is interesting and somewhat puzzling
that respondents who receive a service
from a collaboration have dedicated a fulltime staff member to oversee the receipt
of service but those on the provider side
do so in significantly smaller numbers.
The presence of full-time executive staff
follows the formality of the collaboration’s
governance in the manner one would
expect. The more formal the governance
structure, the more likely we are to see a
full-time executive staff. Which is cause and
which is effect is an interesting question.
Do collaborations hire executive staff who
then recommend the creation of formal
governance? Or, do the best practices of
formal governance suggest the hiring of
executive staff? Our data cannot tell us
definitively. Our hypothesis is that both
explanations are likely valid. Figure 6-5
and Figure 6-6 illustrate the breakdown
of the use of full-time executive staff by
collaboration type and governance structure. As we move through the analysis, we
will report how the use of full-time staff to
direct collaborations impacts communications, decision making, and ultimately the
outcomes of the collaboration.
Formal Agreements
Formal agreements are another important
aspect of achieving clarity of purpose, defining
authority, and establishing roles, and they are
Table 6-5. Elements of Governance in Use by Respondents
Element of Governance
58
Percentage
Defined roles and responsibilities
88.4%
Written policies
67.4%
Boards
48.6%
Full-time executive staff
44.7%
Bylaws
33.6%
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
Separate legal entity (N = 19)
16
Figure 6-5. Full-
Formal coordination (N = 61)
Time Executive
38
Staff and
2
Informal coordination (N = 27)
Formality of
Local control (N = 31)
Governance
6
0
5
10
15
20
25
30
35
40
Number of Respondents with Full-Time Executive Staff
Receive service (N = 36)
18
Figure 6-6. Full-
2
Provide another institution (N = 16)
Time Executive
Develop (N = 29)
Staff and Form of
17
Collaboration
25
Shared service (N = 62)
0
5
10
15
20
25
30
Number of Respondents with Full-Time Executive Staff
important to the success of a collaboration. As
anyone who has engaged in a negotiation has
experienced, the process of creating an agreement is at least as important as, if not more
important than, the actual agreement itself.
Julie Buehler, associate CIO at the University
of Rochester, believes up-front discussion can
be more important than governance agreements. “Artificial governance agreements
lead to failure,” she told us. “What works is
discussion up front about expectations, vision,
and responsibility. Once you have agreement,
governance can hold it together.”
Three-quarters of respondents report their
collaborations are governed by some form
of an agreement. The most common form
is a memorandum of understanding signed
by the parties involved in the collaboration.
Nearly one-fifth of respondents (19 percent)
have created detailed legal documents with
comprehensive terms and conditions. Not
surprisingly, detailed formal agreements
go hand in hand with more formal gover-
EDUCAUSE Center for Applied Research
nance structures. We found no statistically
significant relationship between the type of
formal agreement and collaboration type.
For example, service level agreements with
defined metrics were no more likely to be
found among collaborations to provide or
receive IT resources than among collaborations to develop an IT resource or operate a
shared service. The collaborators’ familiarity
also has little influence on the nature of the
agreement. Respondents who are part of
university systems (and presumably collaborating with institutions they know) and those
who believe strongly that they partner with
IT leaders they know were no more or less
likely to use formal agreements than other
respondents. The form of agreement selected
likely flows most directly from the choice of
governance structure. Table 6-6 compares the
formality of collaborators’ agreements with
their choice of governance structure.
We asked respondents to evaluate
how effectively their agreements—and,
59
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
Table 6-6. Formality of Collaboration Agreements, by Form of Governance
Form of Governance
Local
Control
(N = 33)
Informal
Coordination
(N = 29)
Formal
Coordination
(N = 64)
Separate
Legal
Entity
(N = 21)
Other
(N = 4)
8
8
15
3
4
24.2%
27.6%
23.4%
14.3%
100
17
12
28
4
0
51.5%
41.4%
43.8%
19.0%
0
5
4
10
4
0
15.2%
13.8%
15.6%
19.0%
0
3
5
11
10
0
9.1%
17.2%
17.2%
47.6%
0
N
33
29
64
21
4
Percentage
100
100
100
100
100
Formality of Agreement
No formal agreement
N
Percentage
Memorandum of
understanding signed by
both parties
N
Service level agreement
with specific metrics
N
Detailed contract with
comprehensive terms and
conditions
N
Total
Percentage
Percentage
Percentage
by extension, the processes to establish
them—delineate participants’ risk sharing,
financial contribution, decision rights, and
intellectual property rights. Overall, respondents felt their agreements perform best
at delineating the financial contributions
of the parties involved in the collaboration
and least well at delineating the risks borne
by each party. More than three-quarters
(85.5 percent) agreed or strongly agreed
that their agreements clearly specify the
financial contributions required of each
party. In contrast, 44.5 percent of respondents agree or strongly agree that their
agreements make clear each party’s risks.
It appears that the more tangible and quantifiable financial aspects of a collaboration
are easier to predict and define than are
less quantifiable aspects such as risk. The
majority of respondents (68.3 percent) also
believe their agreements effectively define
each participant’s decision-making authority
(13.5 percent disagree). For most, it appears
that the time spent creating agreements
helps them reach an understanding of how
decision making will occur.
60
Respondents’ assessments of their agreements’ effectiveness does appear to link in
part to agreement type. In general, the more
formal the agreement, the more respondents
are likely to feel it effectively delineates each
party’s risks, contributions, and rights. This
is likely a by-product of both the value of a
more detailed agreement and beneficial time
spent to establish it. It is reasonable to assume
that a more detailed agreement takes more
time to negotiate. That additional time may
enable the parties to engage in more extensive discussions about their expectations for
the collaboration, which in turn creates more
confidence in the quality of the agreement.
Table 6-7 displays respondents’ assessments of how effectively their agreements
delineate various aspects of their rights and
risks by type of agreement. The data show
a stair-step pattern with increasing satisfaction with the quality of agreements as
they become more formal. We see a jump
between memorandums of understanding
and service level agreements, and a similar
jump for detailed contracts. We hypothesize
that these more detailed forms of agreement
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
Table 6-7. Respondents’ Assessments of the Effectiveness of Their Agreements
Delineates
Risks
Financial
Contribution
DecisionMaking
Authority
IP Rights
2.54
3.46
3.2
2.64
35
35
35
33
Std. Deviation
0.852
1.039
0.901
0.994
Mean*
3.12
3.95
3.61
3.04
N
58
61
59
54
Std. Deviation
0.993
0.902
0.871
1.081
Mean*
3.57
4.3
4.14
3.62
21
23
22
21
1.028
0.703
0.56
0.973
Mean*
3.9
4.41
3.97
3.63
N
29
29
29
27
Formality of Agreement
Mean*
No formal agreement
Memorandum of understanding
signed by both parties
Service level agreement with
specific metrics
Detailed contract with
comprehensive terms and
conditions
Total
N
N
Std. Deviation
Std. Deviation
0.724
0.501
0.823
0.884
Mean*
3.2
3.98
3.66
3.15
N
143
148
145
135
1.025
0.907
0.884
1.069
Std. Deviation
Q: The agreement governing this collaboration clearly delineates the following rights.
*Scale: 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree
may take more time and effort to create,
but from that effort respondents see better
results. The payback is not just in terms of the
effectiveness of the agreement itself. As we
discuss in Chapter 7, the evidence suggests
that the time spent creating more formal
structures and agreements also contributes
to the overall success of the collaboration.
The distribution among participants of risk
and financial responsibility for the collaboration appears to influence neither the formality
of the agreement respondents sought nor
their satisfaction with how well the agreements functioned. We asked respondents to
describe how risk and financial responsibility
are distributed among the participants in
their most significant collaboration. Slightly
more than half report that risk and financial
responsibility are shared evenly among all
collaborators. In the remaining collaborations, the majority of the financial risk and
responsibility are borne by one or a small
EDUCAUSE Center for Applied Research
group of institutions. Interestingly, we found
no statistically significant difference among
respondents’ use of formal agreements
based on the distribution of risk and financial responsibility. Collaborations with highly
distributed responsibility for risk and financial
support are no more likely to employ formal
agreements than those with highly centralized
responsibility. Nor are collaborators in such
arrangements any more likely to be satisfied
when their agreements specify participants’
risk and financial responsibilities.
Decision Making and Trust
Effective collaboration requires all members
of the collaboration to have a stake in the
process and the outcomes. Members need
to feel ownership of how the group works
(Mattessich, Murray-Close, & Monsey, 2004).
The challenge and, some would argue,
the power of collaborations is that they
don’t rely on the traditional command and
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IT Collaboration in Higher Education
control hierarchies of formal organizations
or the power structures in which individuals
accumulate authority by accumulating information (Evans & Wolf, 2005). Traditional
organizations and cultures, including higher
education, reward managers who know the
answers, avoid conflict, and act decisively.
Collaborations require leaders who facilitate
decisions by connecting individuals with
knowledge (Evans & Wolf, 2005) and who
provide effective frameworks that enable
teams to have productive conflicts (Weiss &
Hughes, 2005).
A misperception of collaborations perhaps
brought about by the popularity of open
source development and reinforced by popular
phenomena such as social networking is that
they are devoid of structure. The assumption
is that all authority has devolved to the individual. While it is true that many successful
collaborations (and work teams) thrive when
empowered, it does not imply that they
lack structure. As Indiana University’s Walsh
points out, collaboration cannot be sustained
without structure. “Governance and structure
are key the longer the initiative goes. You
can start out without them and get by on
adrenaline and vision. Later, though, you have
to have an orderly decision-making process.
You can’t have a cult of personality.”
As one would expect, devolving all
authority to all individuals is a recipe for
chaos. The literature on successful collaborations argues that the answer is not to impose
traditional governance and decision-making
processes but rather to adopt more teambased concepts of leadership and management. As Evans and Wolf observed in their
study of Linux development and Toyota
collaborations, effective decision making
occurs when individuals feel empowered,
leaders are facilitators, and information is
available and efficient.
As we observed in the prior section,
respondents to the collaborators survey
were generally satisfied that they had put in
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ECAR Research Study 4, 2007
place agreements and structures that defined
how decision making would occur. As noted
previously, only 13.5 percent of respondents
disagreed that their collaborations had
clearly defined decision-making authority.
The majority of our respondents reported
significant trust among the participants in
their collaborations and willingness among
the participants to compromise. More than
60 percent also agreed that they have structured their decision-making processes to allow
sufficient time for participants to be consulted
before a decision needs to be made. Table 6-8
summarizes respondents’ mean responses to
our detailed questions about their collaborations’ decision making.
Respondents appear to have defied
the stereotype of higher education as too
consensus-driven to be efficient at decision
making. The mean responses we received
reveal a relative confidence in the decision
making of respondents’ collaborations. The
standard deviations for each question were
also relatively small, suggesting that most
responses clustered close to the mean. In
fact, relatively few respondents hold a negative opinion of their collaborations’ decisionmaking capabilities. For each question, fewer
than 13 percent of respondents disagreed with
the statements in Table 6-8. The danger of not
getting decision making right is a slip back
toward an inefficient operating model that is
difficult to sustain. Beth Chancellor, associate
CIO for the University of Missouri-Columbia,
characterized these risks. “Governance and
decision making are areas with room for
improvement,” she told us. “Everything takes
too long. It has gone from collaboration to
consensus, which hardly ever works.”
A key factor influencing respondents’
satisfaction with decision making appears to
be whether their collaborations have agreed
to a common set of objectives. Respondents
without shared objectives encounter greater
difficulty at decision making than those with
shared objectives. Recall that respondents
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
Table 6-8. Respondents’ Assessments of Decision Making in Their Collaborations
N
Mean*
Std.
Deviation
Participants in the collaboration share common objectives.
153
3.93
0.762
Participants in the collaboration trust one another.
153
3.85
0.741
The agreement governing this collaboration clearly delineates the
decision-making authority of each participant.
148
3.66
0.877
When the collaborative group makes a decision, there is sufficient time
for consultation with my institution.
151
3.65
0.802
Participants in the collaboration are willing to compromise on
important aspects of the collaboration.
147
3.60
0.791
Assessment
*Scale: 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree
also told us that achieving a common vision
and shared objectives was one of the most
important and difficult actions required at
the outset of a collaborative partnership. The
effort appears to be worth it. We observed
no significant difference in respondents’
assessments of decision making by type of
collaboration or authority model (degree
of centralization of authority). Nor did the
respondents’ roles in the collaboration
alter their perceptions of decision making:
Founders of collaborations are no more satisfied or dissatisfied with the effectiveness of
decision making in their collaborations than
are respondents who are participants.
Communications
Open and frequent communications and
informal communication channels among
participants are two repeatedly found
factors that influence collaborations’ success
(Mattessich, Murray-Close, & Monsey, 2004).
Many of our qualitative interviews echoed
this sentiment. Brad Wheeler, chief information officer, dean, and professor at Indiana
University, called it a “pizza and beer” investment. “You have to provide time and forums
for relationships to build and communication
to be established,” he counseled. “You need
to budget for pizza and beer gatherings.”
Effective communication seems critical to
accomplishing many of the attributes of
EDUCAUSE Center for Applied Research
successful collaborations. One cannot expect
to build trust, sustain common objectives, or
execute effective decision making without
strong communications.
Frequent and effective communication is a
prerequisite for any complex project within an
institution. Collaboration introduces another
level of complexity, as each partner brings his
or her own unique culture and local methods
to the collaboration. One collaborator we
interviewed talked with us anonymously of
the challenges of merging cultures. “You are
bringing together cultures from other institutions. It is difficult to walk the minefield
of your own culture, and now you have to
recognize a solution might not be suitable for
a partner because of the culture.”
Fred Siff, vice president and CIO of the
University of Cincinnati, views culture differently. Siff said he focuses more on sustaining
the common objectives of the collaboration
and less on melding cultures. “I used to worry
about culture, but no longer. Collaborations
should align with institutions’ interests before
you start. Each participant must have interests
that are aligned with the collaboration goals.
Participants can manage their own cultures
as long as they are supporting the needs of
the collaboration.”
Whether bridging differences across
cultures or establishing and sustaining
common objectives, communication seems
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ECAR Research Study 4, 2007
IT Collaboration in Higher Education
to be the foundation upon which collaborations stand. And it is not a onetime effort.
One CIO we interviewed reminded us that
communication supports the continuous
process necessary to sustain commitment.
“There can be a common objective at the
start, but unless there is a continuous dedication of the necessary resources and attention,
problems are introduced that will fragment
the collaboration.”
As Evans and Wolf observed, good communication facilitates effective governance and
decision making in Linux development (Evans
& Wolf, 2005). Given the relatively high marks
respondents gave to decision making, we
would expect respondents to be very positive about the communication within their
collaborations as well. Indeed, respondents
are confident in their communications. Most
report they are well-informed and believe their
collaborations communicate frequently with
stakeholders. The majority of respondents also
believe their collaboration partners are represented by individuals who are empowered
to speak for their institutions and facilitate
efficient decision making. As we observed in
our analysis of decision making, only about 10
percent of respondents negatively assessed
the effectiveness of communication within
their collaborations.
Table 6-9 summarizes respondents’ assessments of the quality of communication within
their collaborations. Again, we see relatively
high mean responses to most of the detailed
statements about the quality of communication. One limitation of our analysis is that
we are reporting leadership perspectives
on communication and are not necessarily
getting the individual participants’ opinions.
Collaborations appear to be doing well on
executive communications, but we don’t
know if they are doing as well at sustaining
communications among the rank and file.
We also observed no significant difference
in collaborators’ assessments of their communications’ effectiveness based on type of
collaboration or authority model. The respondents’ roles in the collaboration (founder
versus participant) also did not influence their
assessments of communication. Finally, the
presence of a full-time executive staff also
did not influence respondents’ assessments
of the effectiveness of communication. Those
involved in collaborations with full-time executive staff did not report a significantly higher
or lower level of satisfaction with the quality
of their communication.
Included in our assessment of communications was a question about whether
respondents measured the benefits of their
collaborations. We placed this question in
the category of communication because we
saw it as an important element of communicating to external stakeholders the benefits
of collaboration. These stakeholders could
be within collaborating institutions or the
higher education community at large. A
minority of respondents (40.6 percent) agreed
Table 6-9. Respondents’ Assessments of Communication within Their Collaborations
Mean*
Std.
Deviation
Each of the people involved in decisions of the collaboration can speak for the
institution they represent. (N = 150)
3.90
0.809
People involved in the collaboration communicate frequently. (N = 154)
3.88
0.816
I am informed as often as I should be about what goes on in the collaboration.
(N = 153)
3.78
0.883
We regularly measure the benefits of this collaboration. (N = 150)
3.19
0.960
Assessment
*Scale: 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree
64
ECAR Research Study 4, 2007
IT Collaboration in Higher Education
that their collaborations routinely measure
benefits; just over one-quarter (26.7 percent)
disagreed, and 32.7 percent were neutral. It
is unclear whether the third of respondents
who were neutral toward the statement chose
this answer because they were unaware of
what their collaboration was doing or were
uncertain that the collaboration was doing
measurement well.
Respondents’ assessments of their
collaborations’ attempts to routinely measure
benefits did not differ by collaboration type.
We also found no significant relationship
between measuring benefits and either
the authority, risk, or cost-sharing model
used by the collaboration. A collaboration
in which many bear the risk and financial
responsibility was no more likely to measure
than those in which one or a few institutions carry the majority of responsibility.
One might have thought that a collaboration
dependent on sustaining the participation of
many members would be more aggressive at
developing measures of benefit.
Summary
In this chapter we examined how collaborations form and are managed. Respondents
perform multiple due diligence activities to
evaluate whether collaboration is an appropriate strategy. Interestingly, once collaboration is identified as the chosen direction, only
a small number of respondents formally vet
their collaboration partners. This is likely a
result of the large number of collaborators
who choose to work with an institution they
know. Familiarity and professional relationships may obviate the need for due diligence
on partners themselves.
EDUCAUSE Center for Applied Research
While formal vetting of partners may be
unnecessary for respondents, they recognize the value of formality in other ways.
Many elect to create formal agreements
and governance structures to oversee their
collaborations. Those who do have these
agreements and structures believe their
collaborations more effectively delineate
the partners’ risks, financial contributions,
and authority. We believe value lies not only
in the structures but also in the process of
establishing them. The effort required to
develop governance boards and to forge
formal agreements provides an opportunity
to build trust and common understanding
among the participants in a collaboration.
The literature suggests these two ingredients
are essential for successful collaboration.
Respondents also positively characterize
their collaborations’ effectiveness of communication and decision making. The literature
suggests that frequent communication is an
integral part of effective decision making. Our
respondents seem to agree, and they gave
high marks to their performance in both these
dimensions. This bodes well for the potential
success of their endeavors.
In the next chapter, we will culminate
our discussion of the collaborators by examining the attributes of their most significant
collaboration that appear to influence
successful outcomes.
Endnote
1. The author is indebted to Paul Mattessich and the
Wilder Foundation for granting permission to insert
several of the Wilder collaboration factor questions
into our survey instrument. Their willingness to
collaborate with us greatly enhances our research.
65