Trends List and Definitions
We asked about 49 IT trends in this year’s research. The 2019 trends apply across a number of different IT domains.
Adaptive learning: Adaptive learning is typically made possible in digital or technologically mediated environments, although it can also be applied to face-to-face learning environments. In adaptive learning models, when a learner interacts with instructional material, the software adapts to the student’s learning needs, modifying the content and method accordingly. In this way, adaptive learning provides learners with individualized instruction and, in some cases, improved learning outcomes. A unique feature of adaptive learning is that in some cases it can analyze the learning history of the individual using the software and provide interactive adjustments based on the individual’s understanding and ability to learn.
Agile approaches to change: Agile software development calls for adaptive planning, continuous improvement, and rapid and flexible response to change. These concepts can also be applied to change management in general. With the rapid pace of technological advances, the decreasing ability of IT shops to control users’ technology ecosystems, and leadership demands for increased accountability, IT strategies that take an agile approach to change management are critical. The software design strategies of flexibility and continuous improvement are finding their way into efforts related to strategic planning, desktop management, IT governance, and infrastructure planning. In addition, institutions working to develop a culture of innovation may find that agile approaches increase cost-effectiveness.
Alternative credentialing models: Certificates, credentials, and job-related curricula are increasingly relevant alternatives to traditional degrees.
Artificial intelligence (AI): Incorporating AI capabilities (such as natural language processing, cognitive systems, and analytics) into applications, smart machines, and robots has implications for instruction, research, student services, admissions, administrative services, and the higher education workforce.
Bimodal IT (managing two separate IT delivery modes, one focused on stability and the other on agility): This trend attempts to resolve two separate and sometimes competing IT service delivery modes. The first mode can be thought of as traditional IT service delivery, with a focus on stable operation. The second can be thought of as agile or emergent, with a focus on providing IT services in a way that emphasizes speed and innovation. The premise of bimodal IT is that both types of service delivery are needed for IT operations to create value.
Blending of roles and blurring of boundaries between IT and academic/administrative areas: This trend is in evidence across all dimensions that involve the application of IT. Discussions around the issue of digital transformation have suggested new, more integrative roles and skills for the CIO and the IT organization, such as the ability to collaborate and share responsibility with academic and administrative departments and the need to integrate numerous solutions to support institutional and individual decision-making and work. On the teaching and learning side, almost all strategic discussions around academic transformation take as a starting point the need to integrate a variety of campus organizations to further the teaching and learning mission. Entailed in this blending and blurring of roles are new job titles, new governance models, new skill sets, and new demands for professional development.
Business process redesign: Examining and redesigning work processes through business process management can uncover opportunities for greater efficiency, possibly allowing for cost savings or reallocation of resources. For example, business process redesign can decrease the need for customization of enterprise systems and increase alignment between business processes and institutional mission. A move to the cloud can be a catalyst for examining business processes in this way. Because processes tend to span functional-unit boundaries, strategies in this area are most successful when they include multiple units at an institution. Business process is more than simply workflow; it encompasses workflow design, systems capabilities, motivation, human resources, policies, rules, funding, and other resources. All should be considered in a business process redesign strategy.
Campus safety: The safety and security of campus students, faculty, staff, and visitors is a priority for higher education institutions. Institutions regularly evaluate campus operations to strengthen and improve them to provide a safe, secure, and welcoming environment. Similarly, the security of campus resources, including IT resources and data, is a concern. Institutions must regularly review and improve their IT operations to ensure the security of their IT system and data resources.
Changing demographics’ influence on enrollments: Populations of developed countries are aging, and the traditional 18- to 25-year-old student population is shrinking in absolute terms and as a proportion of enrollments.
Changing enterprise system architectures, integrations, and workflows: The many facets of higher education require colleges and universities to run a large set of enterprise-wide computing systems. Options for these computing systems are expanding and becoming more specialized. In addition, the sourcing of those systems is evolving. Whereas IT once ran all enterprise systems on premises, many now choose cloud options, with the result being a mix of systems from different vendors, some on premises and some in the cloud. These changes require IT to focus on system architecture, integrations, and workflows to ensure adequate interconnection between systems and data, enabling many different computer systems to effectively share information, automate data-sharing workflows, and efficiently support task workflows for students, faculty, and staff.
Changing faculty roles (focus on advising and student success, growth in adjuncts, etc.): Prompted by sociological, technological, and economic forces, the role of the faculty member in higher education has significantly transformed over the past 20 years. New instructional models and the innovative use of technology have resulted in faculty serving as coaches, software developers, advisors, and instructional leads to sizable cohorts of adjunct faculty. Team-developed courses and demands for increased access to education that can be delivered in various ways have led to an increased focus on the quality of instruction and the rise of the instructional design profession. In his paper on the unbundling of the faculty role, Vernon Smith points to the disaggregation of faculty work to include teaching, course design, assessment, and advising. The faculty transformation continues as an evolving competitive workplace and rising higher education costs place new demands on the relevance of higher education.
Climate change: Responding to concerns about climate change, colleges and universities are taking steps to mitigate the magnitude of their environmental impact through green and sustainable technologies. Institutions are also adapting to the impact of increased severe weather events on areas including operations, risk management, disaster recovery, and travel.
Compliance environment: The regulatory environment impacting higher education IT systems and the data contained in those systems can seem labyrinthine. Data elements in many IT systems may be protected by a number of different federal, state, and local laws and industry regulations. The complicated regulatory environment can be difficult to understand, making it even harder to secure IT systems in a compliant manner.
Concerns about institutional sustainability or even survival: Higher education institutions are besieged by a host of external challenges that include competition from for-profit institutions, alternative educational models, decreased revenue from tuition dollars, and, in the case of public institutions, decreased state budget allocations. Combined with internal demands to provide the best educational experiences possible for students, these pressures may undermine the long-term stability of many colleges and universities.
Contributions of IT to institutional operational excellence: IT can be used to improve operational efficiency and effectiveness through areas including automation, personalization, mobile access, outsourcing, shared services, and process improvement.
Cross-institutional and international scholarly and research collaborations: Research collaborations are increasingly common, and institutions need to be ready to support not only a greater quantity of collaborations but also more complex collaborations. These include working with multiple institutions and working across international lines. Collaborating with colleagues beyond the institution is getting easier through a variety of options that include enterprise-level collaboration tools and free web-based tools. Enterprise tools offer more assurance of privacy and security through the institution’s identity management system.
Cross-institutional partnerships and consortia: In an effort to be as efficient as possible with enterprise IT systems and services, many institutions look to cross-institutional partnerships and consortia as a possible way to reduce costs or gain efficiency. In a purchasing consortium, for example, a group of institutions develops a contractual relationship that allows for collective cost savings and the opportunity to work more closely with system and software vendors, including cloud vendors.
Data-driven decision-making: As a corollary to analytics, colleges and universities are increasingly deriving meaning from the data and determining the best actions to take. Data-driven decision-making can be incorporated into existing planning and management activities and processes, or it can be programmed into applications to generate real-time, personalized triggers, alerts, and advice for students, faculty, advisors, and other constituents.
Declining international enrollments: The political climate has made US higher education less appealing to international students. In addition, other countries are investing aggressively in expanding their own higher education sectors.
Deregulation of higher education: The US Department of Education is revisiting several key Obama-era programs, which could lead to less regulatory oversight.
DevOps movement to bring development and operations staff together to better manage an end-to-end view of an application or IT service: DevOps efforts usually emphasize people over tools, focusing on building a collaborative relationship between development and operations staff to improve efficiency and provide better service. Strategies may include streamlining operations by automating and standardizing repetitive tasks and creating self-service applications. An institutional strategy that considers DevOps can take advantage of past work and save time on testing, potentially freeing resources for other activities. Lack of a current standard definition can create confusion, and the DevOps implementation that works for one institution may not work for another. A strategy that adopts a simplified definition can be a good starting point for developing a common understanding for developers and operations staff.
Digital transformation: Digital transformation is a cultural, technological, and workforce shift. In its cultural dimension, it requires a new approach to how campus leaders interact with each other as well as an emphasis on change management and a movement toward institutional agility and flexibility to meet quickly changing needs. For IT, this means adopting a role of strategic and transforming partner in alignment with institutional mission. In terms of technology, IT leaders and their organizations must adopt innovative practices and create new digital architectures that give it unprecedented agility and flexibility to enable the institution to rapidly and efficiently achieve its strategic aims. Finally, digital transformation has broad implications for the institutional workforce, requiring dramatic shifts in workplace skills at all levels and for professional development that enables the workforce to keep pace with the rapid tempo of change.
Digitization of scholarly and research data (data management, visualization, discipline-specific tools, etc.): Data today are typically produced in a digital format and are increasingly being used, manipulated, and studied in scholarship and research in digital ways. Data management practices must be updated to work with digital data throughout its life cycle. Higher education IT must also be aware of and able to provide researchers with the tools and resources necessary to work with and manage these data, including discipline-specific tools and practices, data visualization, research support for both traditional and more nascent areas of study (such as digital humanities), interdisciplinary research support, and more.
Diversity, equity, and inclusion: Diversity and inclusivity are the lifeblood of higher education. Science and scholarship can only proceed on the basis of encouraging a diversity of opinions and insights proffered by myriad sources. Technology is a key enabler of this dimension, making it possible to draw on diverse information resources and allowing all voices to be heard. In the domain of teaching and learning, the issue of accessibility—one dimension of diversity/inclusivity—jumped from 7th to 4th in the ELI key issues survey. For the IT organization, diversity/inclusivity issues are highly relevant to the issue of sustainable staffing as well as to IT workforce issues.
Evaluation of technology-based instructional innovations: Evaluating the impact of technology-based innovations in teaching and learning has long been a key issue. In light of increasing demands for technology and support, often dogged by dwindling resources, the need to know which innovations have the greatest positive impact is more acute than ever. ECAR research on faculty and IT shows that the greatest motivator for faculty to incorporate technology into their teaching is evidence of its benefit to students. Due to the complexity of measuring pedagogical impact, a variety of evaluation methods must be utilized to produce the evidence persuasive to key stakeholders.
Financial uncertainty for the institution: A combination of factors, including declining enrollments and reduced government funding, is endangering some institutions’ financial health and outlook.
Freedom of speech: When free speech, inclusion, and civility are at odds, individual safety and institutional reputations can be at risk. This issue is playing out on campuses through controversies around trigger warnings, invited speakers, and expression of controversial viewpoints. Social media plays a role.
Growing complexity of security threats: The security threat landscape is increasingly complex, with cloud applications, the Internet of Things, complicated technology architectures, and sophisticated emerging threats requiring a flexible and layered institutional information security approach. Finding new tools and technologies to help identify and mitigate these threats is of great importance to IT professionals.
Higher education’s reputation and relevance: The value of a college degree and an educated citizenship are under increasing scrutiny.
Incorporating open standards into enterprise IT architecture: Getting the typical institution’s wide variety of complex enterprise systems to interconnect is difficult. Most enterprises adopt an existing framework or standard for how complex business workflows, data architectures, and communications standards between systems will work to produce a truly integrated computing environment. For example, The Open Group Architecture Forum framework for enterprise architecture is a widely adopted set of standards, methods, terminology, business workflow descriptions, and tools for standardizing systems-planning language and methods and for avoiding dependence on proprietary vendor solutions.
Incorporating risk-management approaches into IT strategy and service delivery: The term “risk management” refers to a detailed, thoughtful process whereby an institution identifies and assesses the risks that could keep it from meeting its goals and then creates a plan for prioritizing and addressing those risks. It is a mechanism for managing uncertainty. As IT strategy and service delivery models evolve beyond traditional offerings, addressing IT risk strategically involves focusing on information technology’s impact on the achievement of institutional goals rather than on the simple identification of risks related to physical inventories of assets in isolation.
Increasing complexity of technology, architecture, data: As the IT environment grows, and as cloud services are added to the environment, IT complexity increases. New technologies need to be incorporated into the environment, older technologies need to be updated, and end users expect it all to work seamlessly.
Institution-wide data management and integrations: New digital architectures provide agility, scalability, and cost-effectiveness through a growing combination of applications and sourcing strategies. However, it also complicates the challenge of making all those disparate systems communicate with each other. To provide useful information from so many different systems and applications, IT needs an institution-wide strategy for data management that takes multiple stakeholder needs into account and focuses on data integration across many different types of systems.
Internet of Things: The number of computers and servers connected to the internet is being dwarfed by the number of other physical objects with embedded internet-capable technology. Gartner estimates that the IoT will encompass more than 20 billion devices by 2020, a fourfold increase from 2015. Two-thirds of those devices will be consumer-level devices. This enormous change will increase bandwidth needs, contribute to privacy and security challenges, introduce new computation needs, and potentially provide enormous opportunities for institutions as they begin to support smart campuses of the future. Perhaps the most obvious opportunities initially will be in automating and enhancing infrastructure management. But wearables and other person-based devices offer the potential for learning more about people’s behavior, particularly if such devices begin to interact with institutional applications.
IT as an agent of institutional transformation and innovation: IT has always had a dual role with respect to transformation and innovation: IT can be the vehicle by which an innovation is realized, and new breakthroughs in IT can open the door for a new set of innovations and opportunities that were scarcely imaginable before. There is no indication that IT will relinquish this dual role; indeed, if anything, the pace of such change only seems to be accelerating. Finally, the power of IT can greatly increase the scope and scale of current initiatives—for example, the collection and analysis of greater amounts of data provide the basis for new directions for business modeling and technology-enabled student advising.
Lifelong learning: The potential student population can extend to all adults, as the need for ongoing learning and retooling increases.
Managing mobility (people, data, institutional resources): As mobile devices become more ubiquitous, as the Internet of Things expands, and as stakeholders expect seamless connectivity through mobile devices to institutional resources and data, institutions need to consider a number of IT and business processes that cover the management, administration, and support for mobile services. Finding a balance between access and control is important.
Moving from transactional to strategic vendor–institution relationships: Digital transformation is characterized by a shift in IT’s role from being a technology provider to a service broker and partner. This shift allows for a different level of conversation between institution and vendor, as IT can broker a strategic conversation between the two, bringing technology investments into closer alignment with institutional mission in the process. In the broker role, IT can ensure that cloud contracts meet institutional needs for data management, security, backup, and more.
National and global political uncertainty: Political uncertainty and unrest can lead to uncertainty about non-US enrollments, employment of non-US citizens, institutional and grants-based funding, compliance requirements, performance-based funding, free speech, and more. This may have implications for IT operations, funding, and priorities.
New business models for higher education: Institutions are experimenting with new business models, some of which entail collaborations with nonprofit and for-profit institutions, involve digital resources, and have concrete ROI expectations.
Online degree or certificate programs: Many institutions are considering or adding new online programs to grant degrees or certifications.
Reduced reliance on service desk as the primary model for support (includes shift to self-help, automated provisioning, BYO-support, etc.): Knowledge management and automation are enabling IT organizations to provide alternatives to supplement the traditional model of service desk support, a walk-in or call center. This helps offload growing demand for IT support, as faculty, staff, and students increasingly want to access institutional resources from their personal devices and environments. Support staff are challenged to keep up with the complexity of supporting so much variety. Web- or app-based self-help is also an efficient way to supplement the hours of the help desk to provide 24/7 support, as are outsourced IT service desks to either supplement or, in some cases, replace institution-staffed service desks.
Service management (ITSM, ITIL): As colleges and universities increasingly expect their IT departments to deliver services and, more importantly, value, ITSM and ITIL are receiving considerable attention. ITSM (IT service management) is the practice of running the IT organization with a focus on delivery of services to constituents in a repeatable, measurable, and proactive way that is aligned with organizational needs. ITIL (information technology infrastructure library) is a framework of service management processes—such as change, incident, and configuration management—designed to optimize the internal operations of the IT organization. ITIL is a way to operationalize ITSM concepts. Other, complementary processes and frameworks that support ITSM include COBIT (for governance, audit, and compliance), Lean (for continuous improvement), Agile (for development), and DevOps (to integrate development and service delivery).
Shared services: Shared services is the provision of services by one part of an organization or group that were previously provided by more than one part of the organization. Shared services offers an economy of scale that may lead to decreased costs and greater value for the institution. However, attaining that economy of scale can require a large and challenging scope expansion. A shared-services solution differs from centralization in that the former focuses on collaboratively developing business processes and service level agreements that deliver value to the business. Centralization typically emphasizes compliance and control more than service value. Strategies that include leadership engagement, good change-management practices, shared governance, and a long-term financial model will lead to greater success in shared-services efforts.
Solution providers bypassing IT to work directly with business-area leaders: As cloud-based services become increasingly common, individual departments often negotiate directly with vendors and bypass IT departments to select and purchase technology-related services. This practice makes it difficult for IT staff to maintain standards for architecture and integration, and it complicates concerns for information security, compliance, privacy, data management, and data governance. IT departments are responding in part by developing expertise in relationship management skills, allowing them to communicate better with both campus stakeholders and the vendor community.
Student success focus/imperatives: With an increased focus on student completion, higher education faces a new urgency not only to innovate but also to collaborate across departmental silos to bring about institutional transformation. In an environment of “big data,” institutions are being called on to change the way they address student success, resulting in more students finishing what they start and developing the skills to contribute to society in and beyond the workplace.
Ubiquitous digital sources and streams (social media, IoT, systems and applications, OERs, etc.): Institutional data stores, systems, and applications provide a wealth of information that can be used in analytics initiatives. Increasingly, data from sources such as social media, open educational resources, and the Internet of Things can also be considered as sources of important information, presenting institutions with the challenges of how to collect and harness so much data, as well as how to deal with policy, privacy, and cultural issues related to the use of externally sourced data.
Use of algorithms to influence institutional and individual choices: Applying homegrown or proprietary vendor algorithms to personalize and inform instruction, curricula, educational plans, student outcomes, staff hiring and evaluations, and other areas carries risks as well as benefits.
User-centered design: Colleges and universities need to give extensive consideration to end-user needs and experiences in the design, configuration, deployment, and support of IT services and applications.