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.

The last time I wrote about network neutrality, higher education was deeply involved in the debate, especially through the Association of Research Libraries and EDUCAUSE, whose policy group I then headed. We supported a proposal by the then Federal Communications Commission (FCC) chairman, Julius Genachowski, to require public non-managed last-mile networks to transmit end-user Internet traffic neutrally.

We worried that otherwise those networks might favor commercial over intellectual content, and so make it difficult for off-campus students to access course, library, and other campus content, and for campus entities such as libraries to access content on other campuses or in central shared repositories. (The American Library Association had similar worries on behalf of public libraries and their patrons.) Almost as a footnote, we opposed so-called “paid prioritization”, an ill-defined concept, rarely implemented, but now reborn as “Internet fast lanes”.

Although courts overturned the FCC on neutrality, for the most part its key principle has held: traffic should flow across the Internet without regard for its source, its destination, or its content.

But the paid-prioritization footnote is pushing its way back into the main text. It’s doing so in a particularly arcane way, but one that may have serious implications for higher education. Understanding this requires some definitions. After addressing those (as Steve Worona points out, an excellent Wired article has even more on how the Internet, peering, and content delivery networks work), I’ll  turn to current issues and higher education’s interests.

What Is Network Neutrality?

To be “neutral”, in the FCC’s earlier formulation, a network must transmit public Internet traffic equivalently without regard for its source, its destination, or its content. Public Internet traffic means traffic that involves externally accessible IP addresses. A network can discriminate on the basis of type–for example, treat streaming video differently from email. But a neutral network cannot discriminate on source, destination, or content within a given type of traffic. A network can  treat special traffic such as cable TV programming or cable-based telephony–“managed services”, in the jargon–differently than regular public Internet traffic, although this is controversial since the border is murky. More controversial still, given current trends, is the exclusion of cellular wireless Internet traffic (but not WiFi) from neutrality requirements.

Pipes

The word “transmit” is important, because it’s different from “send” and “receive”. Users connect computers, servers, phones, television sets, and other devices to networks. They choose and pay for the capacity of their connection (the “pipe”, in the usual but imperfect plumbing analogy) to send and receive network traffic. Not all pipes are the same, and it’s perfectly acceptable for a network to provide lower-quality pipes–slower, for example–to end users who pay less, and to charge customers differently depending on where they are located. But a neutral network must provide the same quality of service to those who pay for the same size, quality, and location of “pipe”.

A user who is mostly going to send and receive small amounts of text (such as email) can get by with very modest and inexpensive capacity. One who is going to view video needs more capacity, one who is going to use two-way videoconferencing needs even more, and a commercial entity that is going to transmit multiple video streams to many customers needs lots. Sometimes the capacity of connections is fixed–one pays for a given capacity regardless of whether one uses it all–and sometimes their capacity and cost adjust dynamically with use. But in all cases one is merely paying for a connection to the network, not for how quickly traffic will get to or arrive from elsewhere. That last depends on how much someone is paying at the other end, and on how well the intervening networks interconnect. Whether one can pay for service quality other than the quality of one’s own connection is central to the current debate.

Users

It’s also important to consider two different (although sometimes overlapping) kinds of users: “end users” and “providers”. In general, providers deliver services to end users, sometimes content (for example, Netflix, the New York Times, or Google Search), sometimes storage (OneDrive, Dropbox), sometimes communications (Gmail, Xfinity Connect), and sometimes combinations of these and other functionality (Office Online, Google Apps).

The key distinctions between providers and end users are scale and revenue flow. The typical provider serves thousands if not millions of end users; the typical end user uses more than a few but rarely more than a few hundred providers. End users provide revenue to providers, either directly or by being counted; providers receive revenue (or sometimes other value such as fame) from end users or advertisers, and use it to fund the services they provide.

Roles

Networks (and therefore network operators) can play different roles in transmission: “first mile”, “last mile”, “backbone”, and “peering”. Providers connect to first-mile networks. End users do the same to last-mile networks. (First-mile and last-mile networks are mirror images of each other, of course, and can swap roles, but there’s always one of each for any traffic.) Sometimes first-mile networks connect directly to last-mile networks, and sometimes they interconnect indirectly using backbones, which in turn can interconnect with other backbones. Peering is how first-mile, last-mile, and backbone networks interconnect.

To use another imperfect analogy, first mile networks are on-ramps to backbone freeways, last-mile networks are off-ramps, and peering is where freeways interconnect. But here’s why the analogy is  imperfect: sometimes providers connect directly to backbones, and sometimes first-mile and last-mile networks have their own direct peering interconnections, bypassing backbones. Sometimes, as the Wired article points out, providers pay last-mile networks to host their servers, and sometimes special content-distribution systems such as Akamai do roughly the same. Those imperfections account for much of the current controversy.

Consider how I connect the Mac on my desk in Comcast‘s downtown office (where a few of us from NBCUniversal also work) to hostmonster.com, where this blog lives. I connect to the office wireless, which gives me a private (10.x.x.x) IP address. That goes to an internal (also private) router in Philadelphia, which then connects to Comcast’s public network. Comcast, as the company’s first-mile network, takes the traffic to Pennsylvania, then to Illinois, then back east to Virginia. There Comcast has a peering connection to Cogent, which is Hostmonster’s first-mile network provider. Cogent carries my traffic from Virginia to Illinois, Missouri, Colorado, and Utah, where Hostmonster is located and connects to Cogent.

If Comcast and Cogent did not have a direct connection, then my traffic would flow through a backbone such as Level3. If Hostmonster placed its servers in Comcast data centers, my traffic would be all-Comcast. As I’ll note repeatedly, this issue–how first-mile, last-mile, and backbones peer, and how content providers deal with this–is driving much of today’s network-neutrality debate. So is the increasing consolidation of the last-mile network business.

Public/Private

“Public” networks are treated differently than “private” ones. Generally speaking, if a network is open to the general public, and charges them fees to use it, then it’s a public network. If access is mostly restricted to a defined, closed community and does not charge use fees, then it’s a private network. The distinction between public and private networks comes mostly from the Communications Assistance to Law Enforcement Act (CALEA), which took effect in 1995. CALEA required “telecommunications carriers” to assist police and other law enforcement, notably by enabling court-approved wiretaps.

Even for traditional telephones, it was not entirely clear which “telecommunications carriers” were covered–for example, what about campus-run internal telephone exchanges?–and as CALEA extended to the Internet the distinction became murkier. Eventually “open to the general public, and charges them fees” provided a practical distinction, useful beyond CALEA.

Most campus networks are private by this definition. So are my home network, the network here in the DC Comcast office, and the one in my local Starbucks. To take the roadway analogy a step further, home driveways, the extensive network of roads within gated residential communities (even a large one such as Kiawah Island), and roadways within large industrial facilities (such as US Steel’s Gary plant) are private. City streets, state highways, and Interstates are public. (Note that the meaning of “public network” in Windows, MacOS, or other security settings is different.)

Neutrality

In practice, and in most of the public debate until recently, the term “network neutrality” has meant this: except in certain narrow cases (such as illegal uses), a neutral-network operator does not prioritize traffic over the last mile to or from an end user according to the source of the traffic, who the end user is, or the content of the traffic. Note the important qualification: “over the last mile”.

An end user with a smaller, cheaper connection will receive traffic more slowly than one who pays for a faster connection, and the same is true for providers sending traffic. The difference may be more pronounced for some types of traffic (such as video) than for others (email). Other than this, however, a neutral network treats all traffic the same. In particular, the network operator does not manipulate the traffic for its own purposes (such as degrading a competitor’s service), and does not treat end users or providers differently except to the extent they pay for the speed or other qualities of their own network connections.

“Public” networks often claim to be neutral, at least to some degree; “private” ones rarely do. Most legislative and regulatory efforts to promote network neutrality focus on public networks.

Enough definition. What does this all mean for higher education, and in particular how is that meaning different from what I wrote about back in 2011?

The Rebirth of Paid Prioritization

Where once the debate centered on last-mile neutrality for Internet traffic to and from end users, which is relatively straightforward and largely accepted, it has now expanded to include both Internet and “managed services” over the full path from provider to end user, which is much more complicated and ambiguous.

An early indicator was AT&T’s proposal to let providers subsidize the delivery of their traffic to AT&T cellular-network end users, specifically by allowing providers to pay the data costs associated with their services to end users. That is, providers would pay for how traffic was delivered and charged to end users. This differs fundamentally from the principle that the service end users receive depends only on what end users themselves pay for. Since cellular networks are not required to be neutral, AT&T’s proposal violated no law or regulation, but it nevertheless triggered opposition: It implied that AT&T’s customers would receive traffic (ads, downloads, or whatever) from some providers more advantageously–that is, more cheaply–than equivalent traffic from other providers. End user would have no say in this, other than to change carriers. Thus far AT&T’s proposal has attracted few providers, but this may be changing.

Then came the running battles between Netflix, a major provider, and last-mile providers such as Comcast and Verizon. Netfllix argued that end users were receiving its traffic less expeditiously than other providers’ traffic, that this violated neutrality principles, and that last-mile providers were responsible for remedying this. The last-mile providers rejected this argument: in their view the problem arose because Netfllix’s first-mile network (as it happens, Cogent, the same one Hostmonster uses) was unwilling to pay for peering connections capable of handling Netflix’s traffic (which can amount to more than a quarter of all Internet traffic some evenings). In the last-mile networks’ view, Netflix’s first-mile provider was responsible for fixing the problem at its (and therefore presumably Netflix’s) expense. The issue is, who pays to ensure sufficient peering capacity? Returning to the highway metaphor, who pays for sufficient interchange ramps between toll roads, especially when most truck traffic is in one direction?

In the event Netflix gave in, and arranged (and paid for) direct first-mile connections to Comcast, Verizon, and other last-mile providers. But Netflix continues to press its case, and its position has relevance for higher education.

Colleges and Universities

Colleges and universities have traditionally taken two positions on network neutrality. Representing end users, including their campus community and distant students served over the Internet, higher education has taken a strong position in support of the FCC’s network-neutrality proposals, and even urged that they be extended to cover cellular networks. As operators of networks funded and designed to support campuses’ instructional, research, and administrative functions, however, higher education also has taken the position that campus networks, like home, company, and other private networks, should continue to be exempted from network-neutrality provisions.

These remain valid positions for higher education to take in the current debate, and indeed the principles recently posted by EDUCAUSE and various other organizations do precisely that. But the emergence of concrete paid-prioritization services may require more nuanced positions and advocacy.  This is partly because the FCC’s positions have shifted, and partly because the technology and the debate have evolved.

Why should colleges and universities care about this new network-neutrality battleground? Because in addition to representing end users and operating private networks, campuses are increasingly providing instruction to distant students over the Internet. Massively open online courses (MOOCs) and other distance-education services often involve streamed or two-way video. They therefore require high-quality end-to-end network connections.

In most cases, campus network traffic to distant student flows over the commercial Internet, rather than over Internet2 or regional research and education (R&E) networks. Whether it reaches students expeditiously depends not only on the campus’s first-mile connection (“first mile” rather than “last mile” because the campus is now a provider rather than simply representing end users), but also on how the campus’s Internet service provider connects to backbones and/or to students’ last-mile networks–and of course on whether distant students have paid for good enough connections. This is similar to Netflix’s situation.

Unlike Netflix, however, individual campuses probably cannot afford to pay for direct connections to all of their students’ last-mile networks, or to place servers in distant data centers. They thus depend on their first-mile networks’ willingness to peer effectively with backbone and last-mile networks. Yet campuses are rarely major customers of their ISPs, and therefore have little leverage to influence ISPs’ backbone and peering choices. Alternatively, campuses can in theory use their existing connections to R&E networks to deliver instruction. But this is only possible if those R&E networks peer directly and capably with key backbone and last-mile providers. R&E networks generally have not done this.

Here’s what this all means: Higher education needs to continue supporting its historical positions promoting last-mile neutrality and seeking private-network exemptions for campus networks. But colleges and universities also need to work together to make sure their instructional traffic will continue to reach distant students. One way to achieve this is by opposing paid prioritization, of course. But FCC and other regulations may permit limited paid prioritization, or technology may as usual stay one step ahead of regulation. Higher education must figure out the best ways to deal with that, and collaborate to make them so.

 

 

 

 

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.