It’s 2006, and we’re at Duke, for a meeting of the Common Solutions Group.

On the formal agenda, Paul Courant seeks to resurrect an old idea of Ira Fuch‘s, for a collective higher-education IT development-and-procurement entity provisionally called Educore.

On the informal agenda, a bunch of us work behind the scenes trying to persuade two existing higher-education IT entities–Internet2 and National LambdaRail–that they would better serve their constituencies, which overlap but do not coincide, by consolidating into a single organization.

The merged organization would both lease capacity with some restrictions (the I2 model) and “own” it free and clear (the NLR model, the quotes because in many cases NLR owns 20-year “rights to use”–RTUs–rather than actual infrastructure.) The merged organization would find appropriate ways to serve the sometimes divergent interests of IT managers and IT researchers in higher education.

Most everyone appears to agree that having two competing national networking organizations for higher education wastes scarce resources and constrains progress. But both NLR and Internet2 want to run the consolidated entity. Also, there are some personalities involved. Our work behind the scenes is mostly shuttle diplomacy involving successively more complex drafts of charter and bylaws for a merged networking entity.

Throughout the process I have a vague feeling of déjà vu.

Partly I’m wistfully remembering the long and somewhat similar courtship between CAUSE and Educom, which eventually yielded today’s merged EDUCAUSE. I’m hoping that we’ll be able to achieve something similar for national higher-education networking.

And partly I’m remembering a counterexample, the demise of the American Association for Higher Education, which for years held its annual meeting at the Hilton adjacent to Grant Park in Chicago (almost always overlapping my birthday, for some reason). AAHE was an umbrella organization aimed comprehensively at leaders and middle managers throughout higher education, rather than at specific subgroups such as registrars, CFOs, admissions directors, housing managers, CIOs, and so forth. It also attracted higher-education researchers, which is how I started attending, since that’s what I was.

AAHE collapsed, many think, because of the broad middle-management organization’s gradual splintering into a panoply of “caucuses” that eventually went their own ways, and to a certain extent its leaders aligning AAHE with too many faddish bandwagons. (To this day I wince when I hear the otherwise laudable word “assessment”.) It was also affected by the growing importance of discipline-specific organizations such as NACUBO, AACRAO, and NASPA–not to mention Educom and CAUSE–and it always vied for leadership attention with the so-called “presidential” organizations such as ACE, AAU, APLU, NAICU, and ACC.

Together the split into caucuses and over-trendiness left AAHE with no viable general constituency or finances to continue its annual meetings, its support for Change magazine, or its other crosscutting efforts. AAHE shut down in 2005, and disappeared so thoroughly that it doesn’t even have a Wikipedia page; its only online organizational existence is at the Hoover Institution’s archives, which hold its papers.

At the Duke CSG meeting I’m hoping, as we work on I2 and NLR leaders to encourage convergence, that NLR v. I2 won’t turn out like AAHE, and that instead the two organizations will agree to a collaborative process leading to synergy and merger like that of CAUSE and Educom.

We fail.

Following the Duke CSG meeting, NLR and I2 continue to compete. They manage to collaborate briefly on a joint proposal for federal funding, a project called “U.S. UCAN“, but then that collaboration falls apart as NLR’s finances weaken. Internet2 commits to cover NLR’s share of U.S. UCAN, an unexpected burden. NLR hires a new CEO to turn things around; he leaves after less than a year. NLR looks to the private sector for funding, and finds some, but it’s not enough: its network shuts down abruptly in 2014.

In the event, Internet2 survives, especially by extending its mission beyond higher education, and by expanding its collective-procurement activities to include a diversity of third-party products and services under the Net+ umbrella. It also builds some cooperative ventures with EDUCAUSE, such as occasional joint conferences and a few advocacy efforts.

Meanwhile, despite some false starts and missed opportunities, the EDUCAUSE merger succeeds. The organization grows and modernizes. It tackles a broad array of services to and advocacy on behalf of higher-education IT interests, organizations, and staff.

But now I’m having a vague feeling of déjà vu all over again. As was the case for I2/NLR, I sense, there’s little to be gained and some to be lost from Internet2 and EDUCAUSE continuing as separate organizations.

Partly the issue is simple organizational management efficiency: in these times of tight resources for colleges, universities, and state systems, does higher education IT really need two financial staffs, two membership-service desks, two marketing/communications groups, two senior leadership teams, two Boards, and for that matter two CEOs? (Throw ACUTA, Unizin, Apereo, and other entities into the mix, and the question becomes even more pressing.)

But partly the issue is deeper. EDUCAUSE and Internet2 are beginning to compete with one another for scarce resources in subtle ways: dues and memberships, certainly, but also member allegiance, outside funding, and national roles. That competition, if it grows, seems perilous. More worrisome still, some of the competition is of the non-salutary I’m OK/You’re Not OK variety, whereby each organization thinks the other should be subservient.

We don’t quite have a Timson/Molloy situation, I’m glad to say. But with little productive interaction at the organizations’ senior levels to build effective, equitable collaboration, there’s unnecessary risk that competitive tensions will evolve into feudal isolation.

If EDUCAUSE and Internet2 can work together on the basis of mutual respect, then we can minimize that risk, and maybe even move toward a success like CAUSE/Educom becoming EDUCAUSE. If they can’t–well, if they can’t, then I think about AAHE, and NLR’s high-and-dry stakeholders, and I worry.

Lunch with an old friend, beautiful day in Washington, seated outdoors enjoying surprisingly excellent hamburgers. We’re going to talk about our kids, and what we’re doing this summer, and maybe even about working together on a project some day (as we did decades ago).

But as is so often the case for those of us who work in IT, first there’s a technical question about calendars on his iPhone. He’s not clear on the distinction between the iCloud calendar and the one installed by his campus IT group.

I clarify that one is personal and the other enterprise. That segues into a discussion of calendar/email/contacts services (somewhat inexplicably, his campus still uses Notes), and then into IT services and help desks.

My friend observes that his campus provides an excellent array of IT equipment, software (Notes excepted),  and services. But it also has one of those “your call will be handled by the next available representative” queuing systems on its IT help desk.

“I really hate that,” my friend says, as I swipe some of his sweet-potato fries. Because he so dislikes the queuing system, he says, he can’t think positively about his campus’s IT, no matter how good the rest of it is. The evil that men do lives after them; the good is oft interred with their bones. (Why is the Bard on my mind? Because at home we’ve been watching the excellent BBC/PBS Shakespeare Uncovered series on Netflix.)

It’s a familiar refrain. I’ve just been rereading a 1999 article with advice for new CIOs, where I had this to say:

Information technology most often succeeds when it is invisible–when people do not realize they are using it and focus on larger goals. When you and your staff do things right, even spectacularly, no one will notice. This is immensely frustrating. The only comments you are ever going to hear–from the big bosses, from faculty, from staff, from the student newspaper–will be negative, sometimes vitriolically so. This will drive you crazy. No one outside IT at the institution will sympathize.

We like to think this is peculiar to IT. It isn’t.

Case in point: Registrars. During my tenure at the University of Chicago, we replaced an old terminal-based student system for staff only with a highly flexible, modern web-based system directly accessible by students, faculty, and staff. Students used to wait in line to give their class choices to Registrar clerks, who would then set class lists and enter data in the system manually. Grading, transcripts, and other processes were similar. No one was happy except the Registrar, whose staff and budget necessarily remained large.

The new system (now-defunct SCT‘s now-defunct Matrix product) changed everything: no more waiting in line, simpler scheduling, later deadlines for grades, online transcript requests, you name it. Asked about specifics, almost everyone described almost everything as better.

But no one seemed to feel any better about the University than they had before.

At lunch, my friend pointed to this apparent conundrum as an interesting parallel to “two-factor theory,” the suggestion by Frederick Herzberg that job satisfaction and job dissatisfaction are independent of each other. The Registrar’s customers were less dissatisfied, but that did not mean they were more satisfied.

Messier case in point: Business travel. Time was, one made business-travel arrangements by calling (or having one’s assistant call) a travel agency or travel office to make reservations and get a travel advance, and one accounted for the advance and/or got reimbursed for out-of-pocket expense by filling out (or having one’s assistant fill out) a form, attaching paper receipts to it, mailing it somewhere, and eventually receiving a check.

Today it’s much more typical to make one’s own reservations through an employer-provided website, to pay expenses with a credit card that charges the employer directly, to account for expenses through the same dedicated website, and to have any reimbursement deposited directly. This all goes much faster, and is much more cost-effective for the employer.

For those of us who like rolling our own, it’s also much more appealing. But for those who don’t, and who don’t have assistants, it’s more awkward and burdensome.

We implemented a modern travel system (Concur) while I was at UChicago. I know anecdotally that most users liked its speed and convenience, but the public reaction consisted largely of complaints (most of which really weren’t about the travel system, but rather about the loss of departmental secretaries as the University did away with them in favor of centralized clerical support).

Coincidentally, my current employer switched to Concur from a paper-based system shortly before I arrived, and I observe the same pattern: widespread private appreciation completely overwhelmed by isolated objection (much of which is actually about changes in policy, such as having to justify non-preferred hotels, rather than the system itself).

What to do? For the most part we can’t use Mark Antony’s technique: through sarcasm (“Brutus is an honourable man“–imagine the air quotes), he discredits assertions of Caesar’s evil. However, it’s unwise for us to treat our customers’ complaints sarcastically.

Rather, a principal strategy for those of us in domains where dissatisfaction automatically overwhelms satisfaction must be to minimize the former. For example, I wrote,

One way to gain unproductive visibility is by unnecessarily constraining choice. To avoid this, wherever possible use carrots rather than sticks to encourage standardization, so that homogeneity is the product of aggregated free choice rather than central mandate… Try to keep institutional options open. Avoid strategies, vendors, architectures, and technologies that constrain choice. Seek interoperability. Wherever possible, have spillover vendors… Think carefully ahead about likely small disasters, many of which are caused by backhoes doing minor excavation, contractors oblivious to wiring closets, incompetent hacking, vandalism, or broken pipes.

But although minimizing unproductive visibility is important, it’s not enough. Mark Antony didn’t rely entirely on discrediting Brutus; he also cited Caesar’s good:

He was my friend, faithful and just to me… He hath brought many captives home to Rome, whose ransoms did the general coffers fill… When that the poor have cried, Caesar hath wept…

Mark Antony understood that discrediting Brutus and extolling Caesar aren’t the same thing. But it was necessary for him to do the former in order to succeed at the latter.

So let it be with IT. We need to recognize more explicitly that maximizing the good things we in IT do to satisfy our customers and campuses (or other organizations) is important, but those good things are different from and do not counterbalance the unproductively visible ways we dissatisfy them.

…as Oscar Wilde well might have titled an essay about campus-wide IT, had there been such a thing back then.

Enterprise IT it accounts for the lion’s share of campus IT staffing, expenditure, and risk. Yet it receives curiously little attention in national discussion of IT’s strategic higher-education role. Perhaps that should change. Two questions arise:

• What does “Enterprise” mean within higher-education IT?
• Why might the importance of Enterprise IT evolve?

What does “Enterprise IT” mean?

Here are some higher-education spending data from the federal Integrated Postsecondary Education Data Service (IPEDS), omitting hospitals, auxiliaries, and the like:

Broadly speaking, colleges and universities deploy resources with goals and purposes that relate to their substantive mission or the underlying instrumental infrastructure and administration.

• Substantive purposes and goals comprise some combination of education, research, and community service. These correspond to the bottom three categories in the IPEDS graph above. Few institutions focus predominantly on research—Rockefeller University, for example. Most research universities pursue all three missions, most community colleges emphasize the first and third, and most liberal-arts colleges focus on the first.

• Instrumental activities are those that equip, organize, and administer colleges and universities for optimal progress toward their mission—the top two categories in the IPEDS graph. In some cases, core activities advance institutional mission by providing a common infrastructure for the latter. In other cases, they do it by providing campus-wide or departmental staffing, management, and processes to expedite mission-oriented work. In still other cases, they do it through collaboration with other institutions or by contracting for outside services.

Education, research, and community service all use IT substantively to some extent. This includes technologies that directly or indirectly serve teaching and learning, technologies that directly enable research, and technologies that provide information and services to outside communities—for examples of all three, classroom technologies, learning management systems, technologies tailored to specific research data collection or analysis, research data repositories, library systems, and so forth.

Instrumental functions rely much more heavily on IT. Administrative processes rely increasingly on IT-based automation, standardization, and outsourcing. Mission-oriented IT applications share core infrastructure, services, and support. Core IT includes infrastructure such as networks and data centers, storage and computational clouds, and desktop and mobile devices; administrative systems ranging from financial, HR, student-record, and other back office systems to learning-management and library systems; and communications, messaging, collaboration, and social-media systems.

In a sense, then, there are six technology domains within college and university IT:

• the three substantive domains (education, research, and community service), and
• the three instrumental domains (infrastructure, administration, and communications).

Especially in the instrumental domains, “IT” includes not only technology, but also the services, support, and staffing associated with it. Each domain therefore has technology, service, support, and strategic components.

Based on this, here is a working definition: in in higher education,

“Enterprise” IT comprises the IT-related infrastructure, applications, services, and staff
whose primary institutional role is instrumental rather than substantive.

Exploring Enterprise IT, framed thus, entails focusing on technology, services, and support as they relate to campus IT infrastructure, administrative systems, and communications mechanisms, plus their strategic, management, and policy contexts.

Why Might the Importance of Enterprise IT Evolve?

Three reasons: magnitude, change, and overlap.

Magnitude

According data from EDUCAUSE’s Core Data Service (CDS) and the federal Integrated Postsecondary Data System (IPEDS), the typical college or university spends just shy of 5% of its operating budget on IT. This varies a bit across institutional types:

We lack good data breaking down IT expenditures further. However, we do have CDS data on how IT staff distribute across different IT functions. Here is a summary graph, combining education and research into “academic” (community service accounts for very little dedicated IT effort):

Thus my assertion above that Enterprise IT accounts for the lion’s share of IT staffing. Even if we omit the “Management” component, Enterprise IT comprises 60-70% of staffing including IT support, almost half without. The distribution is even more skewed for expenditure, since hardware, applications, services, and maintenance are disproportionately greater in Administration and Infrastructure.

Why, given the magnitude of Enterprise relative to other college and university IT, has it not been more prominent in strategic discussion? There are at least two explanations:

• relatively slow change in Enterprise IT, at least compared to other IT domains (rapidly-changing domains rightly receive more attention that stable ones), and
• overlap—if not competition—between higher-education and vendor initiatives in the Enterprise space.

Change

Enterprise IT is changing thematically, driven by mobility, cloud, and other fundamental changes in information technology. It also is changing specifically, as concrete challenges arise.

Consider, as one way to approach the former, these five thematic metamorphoses:

• In systems and applications, maintenance is giving way to renewal. At one time colleges and universities developed their own administrative systems, equipped their own data centers, and deployed their own networks. In-house development has given way to outside products and services installed and managed on campus, and more recently to the same products and services delivered in or from the cloud.
• In procurement and deployment, direct administration and operations are giving way to negotiation with outside providers and oversight of the resulting services. Whereas once IT staff needed to have intricate knowledge of how systems worked, today that can be less useful that effective negotiation, monitoring, and mediation.
• In data stewardship and archiving, segregated data and systems are giving way to integrated warehouses and tools. Historical data used to remain within administrative systems. The cost of keeping them “live” became too high, and so they moved to cheaper, less flexible, and even more compartmentalized media. The plunging price of storage and the emergence of sophisticated data warehouses and business-intelligence systems reversed this. Over time, storage-based barriers to data integration have gradually fallen.
• In management support, unidimensional reporting is giving way to multivariate analytics. Where once summary statistics emerged separately from different business domains, and drawing inferences about their interconnections required administrative experience and intuition, today connections can be made at the record level deep within integrated data warehouses. Speculating about relationships between trends is giving way to exploring the implications of documented correlations.
• In user support, authority is giving way to persuasion. Where once users had to accept institutional choices if they wanted IT support, today they choose their own devices, expect campus IT organizations to support them, and bypass central systems if support is not forthcoming. To maintain the security and integrity of core systems, IT staff can no longer simply require that users behave appropriately; rather, they must persuade users to do so. This means that IT staff increasingly become advocates rather than controllers. The required skillsets, processes, and administrative structures have been changing accordingly.

Beyond these broad thematic changes, a fourfold confluence is about to accelerate change in Enterprise IT: major systems approaching end-of-life, the growing importance of analytics, extensive mobility supported by third parties, and the availability of affordable, capable cloud-based infrastructure, services, and applications.

Systems Approaching End-of-Life

In the mid-1990s, many colleges and universities invested heavily in administrative-systems suites, often (if inaccurately) called “Enterprise Reporting and Planning” systems or “ERP.” Here, again drawing on CDS, are implementation data on Student, Finance, and HR/Payroll systems for non-specialized colleges and universities:

The pattern of implementation varies slightly across institution types. Here, for example, are implementation dates for Finance systems across four broad college and university groups:

Although these systems have generally been updated regularly since they were implemented, they are approaching the end of their functional life. That is, although they technically can operate into the future, the functionality of turn-of-the-century administrative systems likely falls short of what institutions currently require. Such functional obsolescence typically happens after about 20 years.

The general point holds across higher education: A great many administrative systems will reach their 20-year anniversaries over the next several years.

Moreover, many commercial administrative-systems providers end support for older products, even if those products have been maintained and updated. This typically happens as new products with different functionality and/or architecture establish themselves in the market.

These two milestones—functional obsolescence and loss of vendor support—mean that many institutions will be considering restructuring or replacement of their core administrative systems over the next few years. This, in turn, means that administrative-systems stability will give way to 1990s-style uncertainty and change.

Growing Importance of Analytics

Partly as a result of mid-1990s systems replacements, institutions have accumulated extensive historical data from their operations. They have complemented and integrated these by implementing flexible data-warehousing and business-intelligence systems.

Over the past decade, the increasing availability of sophisticated data-mining tools has given new purpose to data warehouses and business-intelligence systems that have until now have largely provided simple reports. This has laid foundation for the explosive growth of analytic management approaches (if, for the present, more rhetorical than real) in colleges and universities, and in the state and federal agencies that fund and/or regulate them.

As analytics become prominent in areas ranging from administrative planning to student feedback, administrative systems need to become better integrated across organizational units and data sources. The resulting datasets need to become much more widely accessible while complying with privacy requirements. Neither of these is easy to achieve. Achieving them together is more difficult still.

Mobility Supported by Third Parties

Until about five years ago campus communications—infrastructure and services both—were largely provided and controlled by institutions. This is no longer the case.

Much networking has moved from campus-provided wired and WiFi facilities to cellular and other connectivity provided by third parties, largely because those third parties also provide the mobile end-user devices students, faculty, and staff favor.

Separately, campus-provided email and collaboration systems have given way to “free” third-party email, productivity, and social-media services funded by advertising rather than institutional revenue. That mobile devices and their networking are largely outside campus control is triggering fundamental rethinking of instruction, assessment, identity, access, and security processes. This rethinking, in turn, is triggering re-engineering of core systems.

Affordable, Capable Cloud

Colleges and universities have long owned and managed IT themselves, based on two assumptions: that campus infrastructure needs are so idiosyncratic that they can only be satisfied internally, and that campuses are more sophisticated technologically than other organizations.

Both assumptions held well into the 1990s. That has changed. “Outside” technology has caught up to and surpassed campus technology, and campuses have gradually recognized and begun to avoid the costs of idiosyncrasy.

As a result, outside services ranging from commercially hosted applications to cloud infrastructure are rapidly supplanting campus-hosted services. This has profound implications for IT staffing—both levels and skillsets.

The upshot is that Enterprise, already the largest component of higher-education IT, is entering a period of dramatic change.

Beyond change in IT, the academy itself is evolving dramatically. For example, online enrollment is becoming increasingly common. As the Sloan Foundation reports, the fraction of students taking some or all of their coursework online is increasing steadily:

This has implications not only for pedagogy and learning environments, but also for the infrastructure and applications necessary to serve remote and mobile students.

Changes in the IT and academic enterprises are one reason Enterprise IT needs more attention. A second is the panoply of entities that try to influence Enterprise IT.

Overlap

One might expect colleges and universities to have relatively consistent requirements for administrative systems, and therefore that the market for those would consist largely of a few major widely-used products. The facts are otherwise. Here are data from the recent EDUCAUSE Center for Applied Research (ECAR) research report The 2011 Enterprise Application Market in Higher Education:

The closest we come to a compact market is for learning management systems, where 94% of installed systems come from the top 5 vendors. Even in this area, however, there are 24 vendors and open-source groups. At the other extreme is web content management, where 89 active companies and groups compete and the top providers account for just over a third of the market.

One way major vendors compete under circumstances like these is by seeking entrée into the informal networks through which institutions share information and experiences. They do this, in many cases, by inviting campus CIOs or administrative-systems heads to join advisory groups or participate in vendor-sponsored conferences.

That these groups are usually more about promoting product than seeking strategic or technical advice is clear. They are typically hosted and managed by corporate marketing groups, not technical groups. In some cases the advisory groups comprise only a few members, in some cases they are quite large, and in a few cases there are various advisory tiers. CIOs from large colleges and universities are often invited to various such groups. For the most part these groups have very little effect on vendor marketing, and even less on technical architecture and direction.

So why do CIOs attend corporate advisory board meetings? The value to CIOs, aside from getting to know marketing heads, is that these groups’ meetings provide a venue for engaging enterprise issues with peers. The problem is that the number of meetings and their oddly overlapping memberships lead to scattershot conversations inevitably colored by the hosts’ marketing goals and technical choices. It is neither efficient nor effective for higher education to let vendors control discussions of Enterprise IT.

Before corporate advisory bodies became so prevalent, there were groups within higher-education IT that focused on Enterprise IT and especially on administrative systems and network infrastructure. Starting with 1950s workshops on the use of punch cards in higher education, CUMREC hosted meetings and publications focused on the business use of information technology. CAUSE emerged from CUMREC in the late 1960s, and remained focused on administrative systems. EDUCOM came into existence in the mid-1960s, and its focus evolved to complement those of CAUSE and CUMREC by addressing joint procurement, networking, academic technologies, copyright, and in general taking a broad, inclusive approach to IT. Within EDUCOM, the Net@EDU initiative focused on networking much the way CUMREC focused on business systems.

As these various groups melded into a few larger entities, especially EDUCAUSE, Enterprise IT remained a focus, but it was only one of many. Especially as the y2k challenge prompted increased attention to administrative systems and intensive communications demands prompted major investments in networking, the prominence of Enterprise IT issues in collective work diffused further. Internet2 became the focal point for networking engagements, and corporate advisory groups became the focal point for administrative-systems engagements. More recently, entities such as Gartner, the Chronicle of Higher Education, and edu1world have tried to become influential in the Enterprise IT space.

The results of the overlap among vendor groups and associations, unfortunately, are scattershot attention and dissipated energy in the higher-education Enterprise IT space. Neither serves higher education well. Overlap thus joins accelerated change as a major argument for refocusing and reenergizing Enterprise IT.

The Importance of Enterprise IT

Enterprise IT, through its emphasis on core institutional activities, is central to the success of higher education. Yet the community’s work in the domain has yet to coalesce into an effective whole. Perhaps this is because we have been extremely respectful of divergent traditions, communities, and past achievements.

We must not be disrespectful, but it is time to change this: to focus explicitly on what Enterprise IT needs in order to continue advancing higher education, to recognize its strategic importance, and to restore its prominence.

9/25/12 gj-a  

Looking into the near-term future—say, between now and 2020—we in higher education have to address two big challenges, both involving IT. Neither admits easy progress. But if we don’t address them, we’ll find ourselves caught between a rock and a hard place.

• The first challenge, the rock, is to deliver high-quality, effective e-learning and curriculum at scale. We know how to do part of that, but key pieces are missing, and it’s not clear how will find them.
• The second challenge, the hard place, is to recognize that enterprise cloud services and personal devices will make campus-based IT operations the last rather than the first resort. This means everything about our IT base, from infrastructure through support, will be changing just as we need to rely on it.

“But wait,” I can hear my generation of IT leaders (and maybe the next) say, “aren’t we already meeting those challenges?”

If we compare today’s e-learning and enterprise IT with that of the recent past, those leaders might rightly suggest, immense change is evident:

• Learning management systems, electronic reserves, video jukeboxes, collaboration environments, streamed and recorded video lectures, online tutors—none were common even in 2000, and they’re commonplace today.
• Commercial administrative systems, virtualized servers, corporate-style email, web front ends—ditto.

That’s progress and achievement we all recognize, applaud, and celebrate. But that progress and achievement overcame past challenges. We can’t rest on our laurels.

We’re not yet meeting the two broad future challenges, I believe, because in each case fundamental and hard-to-predict change lies ahead. The progress we’ve made so far, however progressive and effective, won’t steer us between the rock of e-learning and the hard place of enterprise IT.

The fundamental change that lies ahead for e-learning
is the the transition from campus-based to distance education

Back in the 1990s, Cliff Adelman, then at the US Department of Education, did a pioneering study of student “swirl,” that is, students moving through several institutions, perhaps with work intervals along the way,before earning degrees.

“The proportion of undergraduate students attending more than one institution,” he wrote, “swelled from 40 percent to 54 percent … during the 1970s and 1980s, with even more dramatic increases in the proportion of students attending more than two institutions.” Adelman predicted that “…we will easily surpass a 60 percent multi-institutional attendance rate by the year 2000.”

Moving from campus to campus for classes is one step; taking classes at home is the next. And so distance education, long constrained by the slow pace and awkward pedagogy of correspondence courses, has come into its own. At first it was relegated to “nontraditional” or “experimental” institutions—Empire State College, Western Governors University, UNext/Cardean (a cautionary tale for another day), Kaplan. Then it went mainstream.

At first this didn’t work: fathom.com, for example, a collaboration among several first-tier research universities led by Columbia, found no market for its high-quality online offerings. (Its Executive Director has just written a thoughtful essay on MOOCs, drawing on her fathom.com experience.)

Today, though, a great many traditional colleges and universities successfully bring instruction and degree programs to distant students. Within the recent past these traditional institutions have expanded into non-degree efforts like OpenCourseWare and to broadcast efforts like the MOOC-based Coursera and edX. In 2008, 3.7% of students took all their coursework through distance education, and 20.4% took at least one class that way.

Learning management systems, electronic reserves, video jukeboxes, collaboration environments, streamed and recorded video lectures, online tutors, the innovations that helped us overcome past challenges—little of that progress was designed for swirling students who do not set foot on campus.

We know how to deliver effective instruction to motivated students at a distance. Among policy issues we have yet to resolve, we don’t yet know how to

• confirm their identity,
• assess their readiness,
• guide their progress,
• measure their achievement,
• standardize course content,
• construct and validate curriculum across diverse campuses, or
• certify degree attainment

in this imminent world. Those aren’t just IT problems, of course. But solving them will almost certainly challenge IT.

The fundamental change that lies ahead for enterprise technologies
is the transition from campus IT to cloud and personal IT

The locus of control over all three principal elements of campus IT—servers and services, networks, and end-user devices and applications—is shifting rapidly from the institution to customers and third parties.

As recently as ten years ago, most campus IT services, everything from administrative systems through messaging and telephone systems to research technologies, were provided by campus entities using campus-based facilities, sometimes centralized and sometimes not. The same was true for the wired and then wireless networks that provided access to services, and for the desktop and laptop computers faculty, students, and staff used.

Today shared services are migrating rapidly to servers and systems that reside physically and organizationally elsewhere—the “cloud”—and the same is happening for dedicated services such as research computing. It’s also happening for networks, as carrier-provided cellular technologies compete with campus-provided wired and WiFi networking, and for end-user devices, as highly mobile personal tablets and phones supplant desktop and laptop computers.

As I wrote in an earlier post about “Enterprise IT,” the scale of enterprise infrastructure and services within IT and the shift in their locus of control have major implications for and the organizations that have provided it. Campus IT organizations grew up around locally-designed services running on campus-owned equipment managed by internal staff. Organization, staffing, and even funding models ensued accordingly. Even in academic computing and user support, “heavy metal” experience was valued highly. The shifting locus of control makes other skills at least as valuable: the ability to negotiate with suppliers, to engage effectively with customers (indeed, to think of them as “customers” rather than “users”), to manage spending and investments under constraint, to explain.

To be sure, IT organizations still require highly skilled technical staff, for example to fine-tune high-performance computing and networking, to ensure that information is kept secure, to integrate systems efficiently, and to identify and authenticate individuals remotely. But these technologies differ greatly from traditional heavy metal, and so must enterprise IT.

The rock, IT, and the hard place

In the long run, it seems to me that the campus IT organization must evolve rapidly to center on seven core activities.

Two of those are substantive:

• making sure that researchers have the technologies they need, and
• making sure that teaching and learning benefit from the best thinking about IT applications and effectiveness.

Four others are more general:

• negotiating and overseeing relationships with outside providers;
• specifying or doing what is necessary for robust integration among outside and internal services;
• striking the right personal/institutional balance between security and privacy for networks, systems, and data; and last but not least
• providing support to customers (both individuals and partner entities).

The seventh core activity, which should diminish over time, is

• operating and supporting legacy systems.

Creative, energetic, competent staff are sine qua non for achieving that kind of forward-looking organization. It’s very hard to do good IT without good, dedicated people, and those are increasingly difficult to find and keep. Not least, this is because colleges and universities compete poorly with the stock options, pay, glitz, and technology the private sector can offer. Therein lies another challenge: promoting loyalty and high morale among staff who know they could be making more elsewhere.

To the extent the rock of e-learning and the hard place of enterprise IT frame our future, we not only need to rethink our organizations and what they do; we also need to rethink how we prepare, promote, and choose leaders for higher-education leaders on campus and elsewhere—the topic, fortuitously, of a recent ECAR report, and of widespread rethinking within EDUCAUSE.

We’ve been through this before, and risen to the challenge.

• Starting around 1980, minicomputers and then personal computers brought IT out of the data center and into every corner of higher education, changing data center, IT organization, and campus in ways we could not even imagine.
• Then in the 1990s campus, regional, and national networks connected everything, with similarly widespread consequences.

We can rise to the challenges again, too, but only if we understand their timing and the transformative implications.

Note to prospective readers: This post has evolved, through extensive revision and expansion and more careful citation, into a paper available at http://gjackson.us/it-he.pdf.

You might want to read that paper, which is much better and complete, instead of this post — unless you like the pictures here, which for the moment aren’t in the paper. Even if you read this to see the pictures, please go read the other.

“Which way to Millinocket?,” a traveler asks. “Well, you can go west to the next intersection…” the drawling down-east Mainer replies in the Dodge and Bryan story,

“…get onto the turnpike, go north through the toll gate at Augusta, ’til you come to that intersection…. well, no. You keep right on this tar road; it changes to dirt now and again. Just keep the river on your left. You’ll come to a crossroads and… let me see. Then again, you can take that scenic coastal route that the tourists use. And after you get to Bucksport… well, let me see now. Millinocket. Come to think of it, you can’t get there from here.”

PLATO and its programmed-instruction kin were supposed to transform higher education. So were the Apple II, and then the personal computer – PC and then Mac – and then the “3M” workstation (megapixel display, megabyte memory, megaflop speed) for which Project Athena was designed. So were simulated laboratories, so were BITNET and then the Internet, so were MUDs, so was Internet2, so was artificial intelligence, so was supercomputing.

Each of these most certainly has helped higher education grow, evolve, and gain efficiency and flexibility. But at its core, higher education remains very much unchanged. That may no longer suffice.

What about today’s technological changes and initiatives – social media, streaming video, multi-user virtual environments, mobile devices, the cloud? Are they to be evolutionary, or transformational? If higher education needs the latter, can we get there from here?

It’s important to start conversations about questions like these from a common understanding of information technologies that currently play a role in higher education, what that role is, and how technologies and their roles are progressing. That’s what prompted these musings.

Information Technology

For the most part, “information technology” means a tripartite array of hardware and software:

• end-user devices, which today range from large desktop workstations to small mobile phones, typically with some kind of display, some way to make choices and enter text, and various other capabilities variously enabled by hardware and software;
• servers, which comprise not just racks of processors, storage, and other hardware but rather are aggregations of hardware, software, applications, and data that provide services to multiple users (when the aggregation is elsewhere, it’s often called “the cloud” today); and
• networks, wireless or wired, which interlink local servers, remote server clouds, and end-user devices, and which typically comprise copper and glass cabling, routers and switches and optronics, and network operating system plus some authentication and logging capability.

Information technology tends to progress rapidly but unevenly, with progress or shortcomings in one domain driving or retarding progress in others.

Today, for example, the rapidly growing capability of small smartphones has taxed previously underused cellular networks. Earlier, excess capability in the wired Internet prompted innovation in major services like Google and YouTube. The success of Google and Amazon forced innovation in the design, management, and physical location of servers.

Perhaps the most striking aspects of technological progress have been its convergence and integration. Whereas once one could reasonably think separately about servers, networks, and end-user devices, today the three are not only tightly interconnected and interdependent, but increasingly their components are indistinguishable. Network switches are essentially servers, servers often comprise vast arrays of the same processors that drive end-user devices plus internal networks, and end-user devices readily tackle tasks – voice recognition, for example – that once required massive servers.

Access to Information Technology

Progress, convergence, and integration in information technology have driven dramatic and fundamental change in the information technologies faculty, students, colleges, and universities have. That progress is likely to continue.

Here, as a result, are some assumptions we can reasonably make today:

• Households have some level of broadband access to the Internet, and at least one computer capable of using that broadband access to view and interact with Web pages, handle email and other messaging, listen to audio, and view videos of at least YouTube quality .
• Teenagers and most adults have some kind of mobile phone, and that phone usually has the capability to handle routine Internet tasks like viewing Web pages and reading email.
• Colleges and universities have building and campus networks operating at broadband speeds of at least 10Mb/sec, and most have wireless networks operating at 802.11b (11Mb/sec) or greater speed.
• Server capacity has become quite inexpensive, largely because “cloud” providers have figured out how to gain and then sell economy of scale.
• Everyone – or at least everyone between the ages of, say, 12 and 65 – has at least one authenticated online identity, including email and other online service accounts; Facebook, Twitter, Google, or other social-media accounts; online banking, financial, or credit-card access; or network credentials from a school, college or university, or employer.
• Everyone knows how to search on the Internet for material using Google, Bing, or other search engines.
• Most people have a digital camera, perhaps integrated into their phone and capable of both still photos and videos, and they know how to send them to others or offload their photos onto their computers or an online service.
• Most college and university course materials are in electronic form, and so is a large fraction of library and reference material used by the typical student.
• Most colleges and universities have readily available facilities for creating video from lectures and similarly didactic events, whether in classrooms or in other venues, and for streaming or otherwise making that video available online.

It’s striking how many of these assumptions were invalid even as recently as five years ago. Most of the assumptions were invalid a decade before that (and it’s sobering to remember that the “3M” workstation was a lofty goal as recently as 1980 and cost nearly $10,000 in the mid-1980s, yet today’s iPhone almost exceeds the 3M spec).

Looking a bit into the future, here are some further assumptions that probably will be safe:

• Typical home networking and computers will have improved to the point they can handle streamed video and simple two-way video interactions (which means that at least one home computer will have an add-on or built-in camera).
• Most people will know how to communicate with individuals or small groups online through synchronous social media or messaging environments, in many cases involving video.
• Authentication and monitoring technologies will exist to enable colleges and universities to reasonably ensure that their testing and assessment of student progress is protected from fraud.
• Pretty much everyone will have the devices and accounts necessary for ubiquitous connectivity with anybody else and to use services from almost any college, university, or other educational provider.

Technology, Teaching, and Learning

In colleges and universities, as in other organizations, information technology can promote progress by enabling administrative processes to become more efficient and by creating diverse, flexible pathways for communication and collaboration within and across different entities. That’s organizational technology, and although it’s very important, it affects higher education much the way it affects other organizations of comparable size.

Somewhat more distinctively, information technology can become learning technology, an integral part of the teaching and learning process. Learning technology sometimes replaces traditional pedagogies and learning environments, but more often it enhances and expands them.

The basic technology and middleware infrastructure necessary to enable colleges and universities to reach, teach, and assess students appears to exist already, or will before long. This brings us to the next question: What applications turn information technology into learning technology?

To answer this, it’s useful to think about four overlapping functions of learning technology.

Amplify and Extend Traditional Pedagogies, Mechanisms, and Resources

For example, by storing and distributing materials electronically, by enabling lectures and other events to be streamed or recorded, and by providing a medium for one-to-one or collective interactions among faculty and students, IT potentially expedites and extends traditional roles and transactions. Similarly, search engines and network-accessible library and reference materials vastly increase faculty and students access. The effect, although profound, nevertheless falls short of transformational. Chairs outside faculty doors give way to “learning management systems” like Blackboard or Sakai or Moodle, wearing one’s PJs to 8am lectures gives way to watching lectures from one’s room over breakfast, and library schools become information-science schools. But the enterprise remains recognizable. Even when these mechanisms go a step further, enabling true distance education whereby students never set foot on campus (in 2011, 3.7% of all students took all their coursework through distance education), the resulting services remain recognizable. Indeed, they are often simply extensions of existing institutions’ campus programs.

Make Educational Events and Materials Available Outside the Original Context

For example, the Open Courseware initiative (OCW) started as publicly accessible repository of lecture notes, problem sets, and other material from MIT classes. It since has grown to include similar material from scores of other institutions worldwide. Similarly, the newer Khan Academy has collected a broad array of instructional videos on diverse topics, some from classes and some prepared especially for Khan, and made those available for anyone interested in learning the material. OCW, Khan, and initiatives like them provide instructional material in pure form, rather than as part of curricula or degree programs.

Enable Experience-Based Learning 

This most productively involves experience that otherwise might have been unaffordable, dangerous, or otherwise infeasible. Simulated chemistry laboratories and factories were an early example – students could learn to synthesize acetylene by trial and error without blowing up the laboratory, or to fine-tune just-in-time production processes without bankrupting real manufacturers. As computers have become more powerful, so have simulations become more complex and realistic. As simulations have moved to cloud-based servers, multi-user virtual environments have emerged, which go beyond simulation to replicate complex environments. Experiences like these were impossible to provide before the advent of powerful, inexpensive server clouds, ubiquitous networking, and graphically capable end-user devices.

Replace the Didactic Classroom Experience

This is the most controversial application of learning technology – “Why do we need faculty to teach calculus on thousands of different campuses, when it can be taught online by a computer?” – but also one that drives most discussion of how technology might transform higher education. It has emerged especially for disciplines and topics where instructors convey what they know to students through classroom lectures, readings, and tutorials. PLATO (Programmed Logic for Automated Teaching Operations) emerged from the University of Illinois in the 1960s as the first major example of computers replacing teachers, and has been followed by myriad attempts, some more successful than others, to create technology-based teaching mechanisms that tailor their instruction to how quickly students master material. (PLATO’s other major innovation was partnership with a commercial vendor, the now defunct Control Data Corporation.)

Higher Education

We now come to the $64 question: what role might trends in higher-education learning technology play in the potential transformation of higher education?

The transformational goal for higher education is to carry out its social and economic roles with greater efficiency and within the resource constraints. Many believe that such transformation requires a very different structure for future higher education. What might that structure be, and what role might information technologies play in its development?

The fundamental purpose of higher education is to advance society, polity, and the economy by increasing the social, political, and economic skills and knowledge of students – what economists call “human capital“. At the postsecondary level, education potentially augments students’ human capital four ways:

• admission, which is to say declaring that a student has been chosen as somehow better qualified or more adaptable in some sense than other prospective students (this is part of Lester Thurow‘s “job queue” idea);
• instruction, including core and disciplinary curricula, the essentially unidirectional transmission of concrete knowledge through lectures, readings, and like, and also the explication and amplification of that through classroom, tutorial, and extracurricular guidance and discussion (this is what we often mean by the narrow term “teaching”);
• certification, specifically the measuring of knowledge and skill through testing and other forms of assessment; and
• socialization, specifically learning how to become an effective member of society independently of one’s origin family, through interaction with faculty and especially with other students.

Sometimes a student gets all four together. For example, MIT marked me even before I enrolled as someone likely to play a role in technology (admission), taught me a great deal about science and engineering generally, electrical engineering in particular, and their social and economic context (instruction), documented through grades based on exams, lab work, and classroom participation that I had mastered (or failed to master) what I’d been taught (certification), and immersed me in an environment wherein data-based argument and rhetoric guided and advanced organizational life, and thereby helped me understand how to work effectively within organizations, groups, and society (socialization).

Most students attend college whose admissions processes amount to open admission, or involve simple norms rather than competition.  That is, anyone who meets certain standards, such as high-school completion with a given GPA or test score, is admitted. In 2010, almost half of all institutions reporting having no admissions criteria, and barely 11% accepted fewer than 1/4 of their applicants. Moreover, most students do not live on campus — in 2007-08, only 14% of undergraduates lived in college-owned housing. This means that most of higher education has limited admission and socialization effects. Therefore, for the most part higher education affects human capital through instruction and certification.

Instruction is an especially fertile domain for technological progress. This is because three trends converge around it:

• ubiquitous connectivity, especially from students’ homes;
• the rapidly growing corpus of coursework offered online, either as formal credit-bearing classes or as freestanding materials from entities like OCW or Khan; and
• perhaps more speculative) the growing willingness of institutions to grant credit and allow students to satisfy requirements through classes taken at other institutions or through some kind of testing or assessment.

Indeed, we can imagine a future where it becomes commonplace for students to satisfy one institution’s degree requirements with coursework from many other institutions. Further down this road, we can imagine there might be institutions that admit students, prescribe curriculum, certify progress, and grant degrees – but have no instructional faculty and do not offer courses. This, in turn, might spawn purely instructional institutions.

One problem with such a future is that socialization, a key function of higher education, gets lost. This points the way to one major technology challenge for the future: Developing online mechanisms, for students who are scattered across the nation or the world, that provide something akin to rich classroom and campus interaction. Such interaction is central to the success of, for example, elite liberal-arts colleges and major residential universities. Many advocates of distance education believe that social media such as Facebook groups can provide this socialization, but that potential has yet to be realized.

A second problem with such a future is that robust, flexible methods for assessing student learning at a distance remain either expensive or insufficient. For example, ProctorU and Kryterion are two of several commercial entities that provide remote exam proctoring, but they do so through somewhat intensive use of video observation, and that only works for rather traditional written exams. For another example, in the aftermath of 9/11 many universities figured out how to conduct doctoral thesis defenses using high-bandwidth videoconferencing facilities rather than flying in faculty from other institutions, but this simply reduced travel expense rather than changed the basic idea that several faculty members would examine one student at a time.

Millinocket

If learning technologies are to transform higher education, we must exploit opportunities and address problems. At the same time, transformed higher education cannot neglect important dimensions of human capital. In that respect, our goal should be not only to make higher education more efficient than it is today, but also better.

Drivers headed for Millinocket rarely pull over any more to ask directions of drawling downeasters. Instead, they rely on the geographic position and information systems built into their cars or phones or computers, which in turn rely on network connectivity to keep maps and traffic reports up to date. To be sure, reliance on GPS and GIS tends to insulate drivers from interaction with the diversity they pass along the road, much as Interstate highways standardized cross-country travel. So the gain from those applications is not without cost.

The same is true for learning technology: it will yield both gains and losses. Effective progress will result only if we explore and understand the technologies and their applications, decide how these relate to the structure and goals of higher education, identify obstacles and remedies, and figure out how to get there from here.

In oversimplified caricature, many colleges and universities have traditionally staffed the line, management, and leadership layers of their IT enterprise thus:

Students with some affinity for technology (perhaps their major, perhaps work-study, perhaps just a side interest) have approached graduation not quite sure what they should do next. They’ve had some contact with the institution’s IT organizations, perhaps having worked for some part of them or perhaps having criticized their services. Whatever the reason, working for an institutional IT organization has seemed a useful way to pay the rent while figuring out what to do next, and it’s been a good deal for the IT organizations because recent graduates are usually pretty clever, know the institution well, learn fast, and are willing to work hard for relatively meager pay.

Moreover, and partly compensating for low pay, the technologies being used and considered in higher education often have been more advanced than those out in business, so sticking around has been a good way to be at the cutting edge technologically, and college and universities have tended to value and reward autonomy, curiosity, and creativity.

Within four or five years of graduation, most staff who come straight into the IT organization have figured out that it’s time to move on. Sometimes a romantic relationship has turned their attention to life plans and long-term earnings, sometimes ambition has taken more focused shape and so they seek a steeper career path, sometimes their interests have sharpened and readied them for graduate school — but in any case, they have left the campus IT organization for other pastures after a few good, productive years, and have been replaced by a new crop of recent graduates.

But a few individuals have found that working in higher education suits their particular hierarchy of needs (to adapt and somewhat distort Maslow). For them, IT work in higher education has yielded several desiderata (remember I’m still caricaturing here): there’s been job security, a stimulating academic environment, a relatively flat organization that offers considerable responsibility and flexibility, and an opportunity to work with and across state-of-the-art (and sometimes even more advanced) technologies. Benefits have been pretty good, even though pay hasn’t and there have been no stock options. Individuals to whom this mix appeals have stayed in campus IT, rising to middle-management levels, sometimes getting degrees in the process, and sometimes, as they have moved into #3 or #2 positions, even moving to other campuses as opportunities present themselves.

Higher-education IT leaders — that is, CIOs, the heads of major decentralized IT organizations, and in some cases the #2s within large central organizations — typically have come from one of two sources. Some have come from within higher-education IT organizations, sometimes the institution’s own but more typically, since a given institution usually has more leadership-ready middle managers than it has available leadership positions, another institution’s. (Whereas insiders once tended to be heavy-metal computer-center directors,  more recently they have come from academic technologies or networking.) Other leaders have come from faculty ranks, often (but not exclusively) in computer science or other technically-oriented disciplines. Occasionally some come from other sources, such as consulting firms or even technology vendors, or even from administration elsewhere in higher education.

The traditional approach staffs IT organizations with well educated, generally clever individuals highly attuned to the institution’s culture and needs. They are willing and able to tackle complex IT projects involving messy integration among different technologies. Those individuals also cost less that comparable ones would if hired from outside. Expected turnover among line staff notwithstanding, they are loyal to the institution even in the face of financial and management challenges.

But the traditional model also tilts IT organizations toward idiosyncrasy and patchwork rather than coherent architecture and efficiency-driven implementation. It often works against the adoption of effective management techniques, and it can promote hostility toward businesslike approaches to procurement and integration and indeed the entire commercial IT marketplace. All of this has been known, but in general institutions have continued to believe that the advantages of the traditional model outweigh its shortcomings.

I saw Moneyball in early October. I liked it mostly because it’s highly entertaining, it’s a good story, it’s well written, acted, directed, and produced, and it involves both applied statistical analysis (which is my training) and baseball (my son’s passion, and mine when the Red Sox are in the playoffs). I also liked it because its focus — dramatic change in how one staffs baseball teams — led me to think about college and university IT staffing. (And yes, I know my principles list says that “all sports analogies mislead”, but never mind.)

In one early scene, the Oakland A’s scouting staff explains to Brad Pitt’s character, Billy Beane, that choosing players depends on intuition honed by decades of experience with how the game is played, and that the approach Beane is proposing — choosing them based on how games are won rather than on intuition — is dangerous and foolhardy. Later, Arliss Howard’s character, the Red Sox owner John Henry, explains that whenever one goes against long tradition all hell breaks loose, and whoever pioneers or even advocates that change is likely to get bloodied.

So now I’ll move from oversimplification and caricature to speculation. To believe in the continued validity of the traditional staffing model may be to emulate the scouts in Moneyball. But to abandon the model is risky, since it’s not clear how higher-education IT can maintain its viability in a more “businesslike” model based on externally defined architectures, service models, and metrics. After all, Billy Beane’s Oakland A’s still haven’t won the World Series.

The Beane-like critique of the traditional model isn’t that the advantage/shortcoming balance has shifted, but rather that it depends on several key assumptions whose future validity is questionable. To cite four interrelated ones:

• With the increasing sophistication of mobile devices and cloud-based services, the locus of technological innovation has shifted away from colleges and universities. Recent graduates who want to be in the thick of things while figuring out their life plans have much better options than staying on campus — they can intern at big technology firms, or join startups, or even start their own small businesses. In short, there is now competition for young graduates interested IT but unsure of their long-term plans.
• As campuses have outsourced or standardized much of their IT, jobs that once included development and integration responsibility have evolved into operations, support, and maintenance — which are important, but not very interesting intellectually, and which provide little career development.  Increased outsourcing has exacerbated this, and so has increased reliance on business-based metrics for things like user support and business-based architectures for things like authentication and systems integration.
• College and university IT departments could once offset this intellectual narrowing because technology prices were dropping faster than available funds, and the resulting financial cushion could be dedicated to providing staff with resources and flexibility to go beyond their specific jobs (okay, maybe what I mean is letting staff buy gadgets and play with them). But tightened attention to productivity and resource constraints have large eliminated the offsetting toys and flexibility. So IT jobs in colleges and universities have lost much of their nonpecuniary attractiveness, without any commensurate increase in compensation. Because of this, line staff are less likely to choose careers in college or university IT, and without this source of replenishment the higher-education IT management layer is aging.
• As IT has become pervasively important to higher education, so responsibility for its strategic direction has broadened. As strategic direction has broadened, so senior leadership jobs, including the CIO’s, have evolved away from hierarchical control and toward collaboration and influence. (I’ve written about this elsewhere.) At the same time, increasing attention to business-like norms and metrics has required that IT leaders possess a somewhat different skillset than usually emerges from gradual promotion within college and university IT organizations or faculty experience. This has disrupted the supply chain for college and university IT leadership, as a highly fragmented group of headhunter firms competes to identify and recruit nontraditional candidates.

I think we’re already seeing dramatic change resulting from all this. The most obvious change is rapid standardization around commercial standards to enable outsourcing — which is appealing not only intrinsically, but because it reduces dependence on an institution’s own staff. (On the minus side, it also tends to emphasize proprietary commercial rather than open-source or open-standards approaches.) I also sense much greater interest in hiring from outside higher education, both at the line and management levels, and a concomitant reappraisal of compensation levels. That, combined with flat or shrinking resources, is eliminating positions, and the elimination of positions is promoting even more rapid standardization and outsourcing.

On the plus side, this is making college and university IT departments much more efficient and businesslike. On the minus side, higher education IT organizations may be losing their ability to innovate. This is yet another instance of the difficult choice facing us in higher-education IT: Is IT simply an important, central element of educational, research, and administrative infrastructure, or is IT also the vehicle for fundamental change in how higher education works? (In Moneyball, the choice is between player recruitment as a mechanism for generating runs, and as a mechanism for exciting fans. Sure, Red Sox fans want to win. But were they more avid before or after the Curse ended with Bill James’s help?)

If it’s the latter, we need to make sure we’re equipped to enable that — something that neither the traditional model nor the evolving “businesslike” model really does.

To understand why policy debates sometimes seem to make no sense, to circle endlessly, or to become bafflingly confused, it’s important to remember that the demography of higher education isn’t politically straightforward. By “demography” I don’t mean Gen X, Gen Y, and echo booms, but rather straightforward counts of degree-granting institutions and students. And by “politically” I don’t mean Republicans and Democrats, but rather the relative importance of different constituencies with different resources and goals.

Here’s a graph (I’ll append a more detailed table at the end). The data come from the National Center for Educational Statistics 2008 IPEDS surveys. They describe the 4,474 public and private degree-granting institutions in the United States, classified into the usual Carnegie categories. I’ve collapsed Carnegie and size categories:  “Small” means enrollment under 2,500, and “Large” means enrollment of 20,000 or more. The categories whose labels I’ve italicized are mostly private, those I’ve underscored are mostly public, and those I’ve both italicized and underscored are split between public and private institutions.

Most of us know some key demographic facts about higher education — for example, that the largest group of students is in 2-year colleges, followed closely by research universities. We also know that an awful lot of commentary and influence in higher education comes from people in or connected with research universities, and therefore many of us have trouble thinking about other kinds of institutions, let alone new kinds.

Here are some things we tend to forget:

• There really aren’t very many research and doctoral universities — they account for fewer than 10% of institutions even though they enroll over 25% of all students.
• Although there are lots of big community colleges and they enroll lots of students, not all 2-year colleges are big community colleges; rather, more than half of them are small, and most of those are private.
• Most small 4-year and master’s institutions are also private, and although they comprise almost 20% of all institutions, they enroll only 5% of all students.
• There are a lot of specialized institutions — that is, freestanding business, health, medical, engineering, technical, design, theological, and other similar institutions — but they don’t enroll very many students.
• Enrollment isn’t quite a Pareto distribution (that’s the classic 20-80 rule), but it’s pretty close: 33% of institutions enroll 80% of the students.

What this tells us is that the politics of higher education — and, indeed, the politics of organizations, like my own EDUCAUSE, that try to represent all of higher education — are very different depending on whether we focus on students or on institutions.

If we focus on students, the politics are pretty straightforward. Big community colleges, big master’s institutions, and doctoral and research universities count, and all other institutions don’t. The group that counts is mostly public institutions, so state governments and state system offices also count. Research and doctoral universities employ lots of faculty to whom research is as important as teaching, and who are vocal about its importance, so disciplinary groups and research funders are also relevant.

From the enrollment perspective, how higher education evolves depends critically on what happens in big community colleges and in research and doctoral universities, since that’s where students are. Conversely, unless those institutions adapt to what students expect, we can expect cataclysmic change in higher education.

But community colleges and universities are at opposite ends of the cultural spectrum. To give just two examples, the former rely heavily on faculty hired ad hoc to teach specific courses, the latter rely on tenured or tenure-track faculty, and the former have no interest in research productivity or eminence whereas the latter stake their reputations on it. So the two most important sectors (in the enrollment sense) often are misaligned if not at odds about policy choices, and the changes they contemplate and implement are likely to be divergent rather than synergistic.

The other 3,000 institutions are different. Of the 4,474 institutions, almost 2/3 are private, and almost 2/3 are small, with lots of overlap: just over half of all institutions are small and private. If we focus on institutions rather than enrollment, we attend to a very large number of small, private institutions that often have different missions and challenges, typically do not work together, and, with a few exceptions, are not organized or collectively vocal.

For these institutions, the difference between survival and demise can depend on tiny changes in enrollment or financial aid or even audit policies, since their small size denies them the operating cushions and economies of scale available to their larger and public counterparts. This also means that these institutions have no excess resources to invest in innovation, so they are unlikely to adapt to changing student needs.

In a sense, focusing on enrollment tends to yield interesting and strategic (if conflicting) attention to the future, whereas focusing on institutions tends to balance (if not replace) this with a focus on tactical survival and the intricacies of current policy.

But my point isn’t about specific policy options or imperatives. Rather, it’s this: what’s important varies dramatically depending whether we focus on institutions or students. And that, I think, not only contributes to the complexity of our conversations within the status quo of higher education, but also complicates thinking about its future.

Degree-Granting Institutions by Type, Control, and Size, IPEDS 2008 Data

“There are two possible solutions,” Hercule Poirot says to the assembled suspects in Murder on the Orient Express (that’s p. 304 in the Kindle edition, but the 1974 movie starring Albert Finney is way better than the book, and it and the book are both much better than the abominable 2011 PBS version with David Suchet). “I shall put them both before you,” Poirot continues, “…to judge which solution is the right one.”

So it is for the future role, organization, and leadership of higher-education IT. There are two possible solutions. There’s a reasonably straightforward projection how the role of IT in higher education will evolve into the mid-range future, but there’s also a more complicated one. The first assumes institutional continuity and evolutionary change. The second doesn’t.

IT Domains

How does IT serve higher education? Let me count the ways:

1. Infrastructure for the transfer and storage of pedagogical, bibliographic, research, operational, and administrative information, in close synergy with other physical infrastructure such as plumbing, wiring, buildings, sensors, controls, roads, and vehicles. This includes not only hardware such as processors, storage, networking, and end-user devices, but also basic functionality such as database management and hosting (or virtualizing) servers.
2. Administrative systems that manage, analyze, and display the information students, faculty, and staff need to manage their own work and that of their departments. This includes identity management, authentication, and other so-called “middleware” through which institutions define their communities.
3. Pedagogical applications students and faculty need to enable teaching and learning, including tools for data analysis, bibliography, simulation, writing, multimedia, presentations, discussion, and guidance.
4. Research tools faculty and students need to advance knowledge, including some tools that also serve pedagogy plus a broad array of devices and systems to measure, gather, simulate, manage, share, distill, analyze, display, and otherwise bring data to bear on scholarly questions.
5. Community services to support interaction and collaboration, including systems for messaging, collaboration, broadcasting, and socialization both within campuses and across their boundaries.

“…A Suit of Wagon Lit Uniform…and a Pass Key…”

The straightforward projection, analogous to Poirot’s simpler solution (an unknown stranger committed the crime, and escaped undetected), stems from projections how institutions themselves might address each of the IT domains as new services and devices become available, especially cloud-based services and consumer-based end-user devices. The core assumptions are that the important loci of decisions are intra-institutional, and that institutions make their own choices to maximize local benefit (or, in the economic terms I mentioned in an earlier post, to maximize their individual utility.)

Most current thinking in this vein goes something like this:

• We will outsource generic services, platforms, and storage, and perhaps
• consolidate and standardize support for core applications and
• leave users on their own insofar as commercial devices such as phones and tablets are concerned, but
• we must for the foreseeable future continue to have administrative systems securely dedicated and configured for our unique institutional needs, and similarly
• we must maintain control over our pedagogical applications and research tools since they help distinguish us from the competition.

Evolution based on this thinking entails dramatic shrinkage in data-center facilities, as virtualized servers housed in or provided by commercial or collective entities replace campus-based hosting of major systems. It entails several key administrative and community-service systems being replaced by standard commercial offerings — for example, the replacement of expense-reimbursement systems by commercial products such as Concur, of dedicated payroll systems by commercial services such as ADP, and of campus messaging, calendaring, and even document-management systems by more general services such as Google’s or Microsoft’s. Finally, thinking like this typically drives consolidation and standardization of user support, bringing departmental support entities into alignment if not under the authority of central IT, and standardizing requirements and services to reduce response times and staff costs.

How might higher-education IT evolve if this is how things go? In particular, what effects would it have on IT organization, and leadership?

One clear consequence of such straightforward evolution is a continuing need for central guidance and management across essentially the current array of IT domains. As I tried to suggest in a recent article, the nature of that guidance and management would change, in that control would give way to collaboration and influence. But institutions would retain responsibility for IT functions, and it would remain important for important systems to be managed or procured centrally for the general good. Although the skills required of the “chief information officer” would be different, CIOs would still be necessary, and most cross-institutional efforts would be mediated through them. Many of those cross-institutional efforts would involve coordinated action of various kinds, ranging from similar approaches to vendors through collective procurement to joint development.

We’d still need Brads.

“Say What You Like, Trial by Jury is a Sound System…”

If we think about the future unconventionally (as Poirot does in his second solution — spoiler in the last section below!), a somewhat more radical, extra-institutional projection emerges. What if Accenture, McKinsey, and Bain are right, and IT contributes very little to the distinctiveness of institutions — in which case colleges and universities have no business doing IT idiosyncratically or even individually?

In that case,

• we will outsource almost all IT infrastructure, applications, services, and support, either to collective enterprises or to commercial providers, and therefore
• we will not need data centers or staff, including server administrators, programmers, and administrative-systems technical staff, so that
• the role of institutional IT will be largely to provide only highly tailored support for research and instruction, which means that
• in most cases means there will be little to be gained from centralizing IT,
• it will make sense for academic departments to do their own IT, and
• we can rely on individual business units to negotiate appropriate administrative systems and services, and so
• the balance will shift from centralized to decentralized IT organization and staffing.

What if we’re right that mobility, broadband, cloud services, and distance learning are maturing to the point where they can transform education, so that we have simultaneous and similarly radical change on the academic front?

Despite changes in technology and economics, and some organizational evolution, higher education remains largely hierarchical. Vertically-organized colleges and universities grant degrees based on curricula largely determined internally, curricula largely comprise courses offered by the institution, institutions hire their own faculty to teach their own courses, and students enroll as degree candidates in a particular institution to take the courses that institution offers and thereby earn degrees. As Jim March used to point out, higher education today (well, okay, twenty years ago, when I worked with him at Stanford) is pretty similar to its origins: groups sitting around on rocks talking about books they’ve read.

It’s never been that simple, of course. Most students take some of their coursework from other institutions, some transfer from one to another, and since the 1960s there have been examples of network-based teaching. But the model has been remarkably robust across time and borders. It depends critically on the metaphor of the “campus”, the idea that students will be in one place for their studies.

Mobility, broadband, and the cloud redefine “campus” in ways that call the entire model into question, and thereby may transform higher education. A series of challenges lies ahead on this path. If we tackle and overcome these challenges, higher education, perhaps even including its role in research, could change in very fundamental ways.

The first challenge, which is already being widely addressed in colleges, universities, and other entities, is distance education: how to deliver instruction and promote learning effectively at a distance. Some efforts to address this challenge involve extrapolating from current models (many community colleges, “laptop colleges”, and for-profit institutions are examples of this), some involve recycling existing materials (Open CourseWare, and to a large extent the Khan Academy), and some involve experimenting with radically different approaches such as game-based simulation. There has already been considerable success with effective distance education, and more seems likely in the near future.

As it becomes feasible to teach and learn at a distance, so that students can be “located” on several “campuses” at once, students will have no reason to take all their coursework from a single institution. A question arises: If coursework comes from different “campuses”, who defines curriculum? Standardizing curriculum, as is already done in some professional graduate programs, is one way to achieve address this problem — that is, we may define curriculum extra-institutionally, “above the campus”. Such standardization requires cross-institutional collaboration, oversight from professional associations or guilds, and/or government regulation. None of this works very well today, in part because such standardization threatens institutional autonomy and distinctiveness. But effective distance teaching and learning may impel change.

As courses relate to curricula without depending on a particular institution, it becomes possible to imagine divorcing the offering of courses from the awarding of degrees. In this radical, no-longer-vertical future, some institutions might simply sell instruction and other learning resources, while others might concentrate on admitting students to candidacy, vetting their choices of and progress through coursework offered by other institutions, and awarding degrees. (Of course, some might try to continue both instructing and certifying.) To manage all this, it will clearly be necessary to gather, hold, and appraise student records in some shared or central fashion.

To the extent this projection is valid, not only does the role of IT within institutions change, but the very role of institutions in higher education changes. It remains important that local support be available to support the IT components of distinctive coursework, and of course to support research, but almost everything else — administrative and community services, infrastructure, general support — becomes either so standardized and/or outsourced as to require no institutional support, or becomes an activity for higher education generally rather than colleges or universities individually. In the extreme case, the typical institution really doesn’t need a central IT organization.

In this scenario, individual colleges and universities don’t need Brads.

“…What Should We Tell the Yugo-Slavian Police?”

Poirot’s second solution to the Ratchett murder (everyone including the butler did it) requires astonishing and improbable synchronicity among a large number of widely dispersed individuals. That’s fine for a mystery novel, but rarely works out in real life.

I therefore don’t suggest that the radical scenario I sketched above will come to pass. As many scholars of higher education have pointed out, colleges and universities are organized and designed to resist change. So long as society entrusts higher education to colleges and universities and other entities like them, we are likely to see evolutionary rather than radical change. So my extreme scenario, perhaps absurd on its face, seeks to only to suggest that we would do well to think well beyond institutional boundaries as we promote IT in higher education and consider its transformative potential.

And more: if we’re serious about the potentially transformative role of mobility, broadband, and the cloud in higher education, we need to consider not only what IT might change but also what effects that change will have on IT itself — and especially on its role within colleges and universities and across higher education.

A few nights ago, at a meeting of IT people from a subset of research universities, dinner conversation turned to why IT people work in higher education. If you do IT in higher education, everyone pretty much agreed, it’s not to get rich. Rather, you’re driven by some combination of four reasons.

1. IT jobs in higher education have tended to entail a complicated, challenging, and rewarding set of challenges. IT organizations in colleges and universities tend to be relatively small, and tend to involve teamwork across domains that might otherwise be separate. There’s not the neat division between, say, technical and support staff that one might find elsewhere, and so there has been ample opportunity to grow along various dimensions.
2. IT jobs in higher education have generally involved a certain amount of flexibility. One spends most of one’s time on one’s job, but it’s been commonplace for a certain fraction of time – perhaps as much as 20% — to be essentially the staffer’s to allocate. Much of that time has gone to experimenting with new technologies, or ways to use old technologies, or even to thinking about things not strictly technological. In the aggregate, much of that “uncommitted” time has gone to innovation, some successful and some not. But the opportunity to spend time on activities that are not strictly part of job descriptions, with part of that involving experimentation and innovation, has enabled IT organizations in higher education to be sources of administrative, educational, research, and technological progress.
3. IT in higher education has usually provided good job security. Absent failure to produce or malfeasance, IT staff in education could reasonably assume that they would have jobs so long as they continued to perform well.
4. This one’s somewhat different from the other three reasons. IT jobs in higher education have been an interesting and useful way station for recent graduates with abundant energy and skill but little sense of career or personal-development paths. For many IT staff, the job is not an end in itself, but rather a reasonable way to work for a few years while figuring out what to do next – be that graduate school, marriage and family, relocation, a more remunerative job, or whatever. That is, part of what appeals is working where one recently got – or is soon getting – a degree.

For reasons good and bad, the reasons to work in higher-education IT work have eroded, without commensurate offsets such as better pay. This has had little effect on those who work in higher-education IT for reason #4. So long as economic downturns have affected the corporate and .com worlds more than colleges and universities, it also has had little effect on those who work for #1-3. Since the economy has been on a bit of a roller coaster for some years, we’ve thus seen little erosion of IT staffing in higher education.

But as financial strictures settle firmly into higher education, this is changing. There have been greater compartmentalization of tasks, tighter accounting for time and effort, and layoffs unrelated to performance. These directly undercut reasons #1 through #3 for working in higher-education IT, and they’re beginning to have effects on staffing.

What many perceive is a key shift in the higher-education IT workforce: fewer young staff stick around to rise through the ranks, and loss rates do not reverse with age as they once did. The staff-by-age distribution is becoming bimodal, and whereas the left-hand mode is staying put or moving left – that is, staff who leave are leaving sooner – the right-hand mode, starved for replenishment from the middle, is moving right. As a result, higher-education IT organizations are increasingly starved for middle management, and as a second-order consequence they are decreasingly able to fill leadership positions from within. We therefore see more middle-management and leadership hires from the corporate sector.

Those new hires, unaccustomed to reasons #1-4, are likely to magnify rather than counteract the changes that underlay their hiring. The result, if we can avoid a vicious circle, is that non-pecuniary reasons for working in higher-education IT will give way to pecuniary ones. IT staff in colleges and universities will have more focused, less flexible, and less secure jobs, but they will be paid more to do them. If productivity under the new regime grows sufficiently to offset higher IT payrolls (which may mean that staffing levels decline), then the evolution can succeed. If it doesn’t, then increased spending will fail to yield commensurate progress.

Let’s assume, for the moment, that the evolution is both desirable and successful. What issues might we need to address? Here are five for starters:

1. Whether we like it or not, colleges and universities operate with cultures that are very different from corporate cultures. If staff are hired from the latter, then we need to find effective ways to quickly give them an understanding of the former. This doesn’t mean that outside hires must go native, accepting their new culture as gospel, but rather than they must understand the status quo if they are to change it.
2. If pay does become a dominant reason for people to work in higher-education IT, then colleges and universities must adopt modern approaches to compensation: bonuses for effective work, putting some compensation formally at risk, direct connections between performance reviews and compensation, benefits suited to staff needs, and most important compensation levels that truly compare favorably with the outside market.
3. Even if we successfully integrate and compensate staff from outside higher education, inevitably staff turnover will be higher than it has been in the past: that’s another attribute of corporate IT cultures. This means that college and university IT organizations can no longer rely on long-term employees as the repositories of accumulated experience. Rather, they must adopt formal mechanisms for reaching, making, and recording decisions, for documenting implementation and change, and generally for ensuring that wisdom survives turnover.
4. Idiosyncrasy, long the hallmark of higher-education IT and in many cases the guarantor of continued employment, will give way to standardization. The default for decisions whether to outsource will no longer be “no”. The burden of proof will shift to those opposing outsourcing, and there will be increased scrutiny of “we’ve always done it this way” arguments.
5. Partly as a result of #4, possibilities for inter-institutional collaboration and joint procurement should expand. In some cases this will lead logically to joint-development efforts, especially where higher education has unique needs (for example, student systems, learning-management systems, and many research applications). In other cases it will lead logically to demand aggregation, especially where higher-education needs are consistent, they resemble those outside the academy, and they yield no competitive advantage (for example, email systems or cloud-based storage).

Many of those currently preparing to become leaders within higher-education IT are ill prepared to address issues like these. Many of those who come from outside to take leadership positions in higher-education IT do not understand why issues like these are hard to address in higher education. The solution, as with many of the changes we face, is serious, deep-thinking professional development: places where those rising or jumping into college or university IT leadership can learn what the future is bringing and how to address it. These can be didactic, like EDUCAUSE’s management and leadership institutes, or collaborative, like the Common Solutions Group, the Council of Liberal Arts Colleges, the League for Innovation, and other entities where peers gather to share experiences and best practices.

In the past we’ve built leaders informally, by drawing them from those who have been with us for a long time. As that pool dries up, we need to think differently.