- Trust
- Consumerization
- Sourcing
- Big Data and Big Content
- Storage
- Cloud
- Mobility
A brief definition of each is useful:
Trust
There is a crisis of trust in higher education. Employers do not trust that our graduates are adequately prepared for the workplace. This perception is not limited to undergraduate degrees (see the New York Times on legal education). Parents question the investment needed to get students through college. Students are concerned about the amount of debt compared to the employment value of their degree. We see an increase in state and national mandates for data reporting, with funding linked to graduation rates. In some cases, this translates into new mandates for reporting data to external agencies in new formats and using new methods.
While this crisis of trust expands externally, we also feel internal pressures. As students, parents and legislators ask "Why is the cost of tuition so high?", we ask this question internally of our own operations. Our universities are increasingly asking, "Why is the cost of technology, software, hardware, and networks, and the provision of these services, so high?" We need to be able to answer questions that come from external and internal sources.
For technology organizations, we use established standards and protocols so that we can clearly explain costs and provide transparency to our budgets and processes. We use the Project Management Body of Knowledge and the Information Technology Infrastructure Library to clearly manage and communicate our projects and services. We create strong governance models to make sure our projects align with the university mission and strategic goals. We respond with measures about accountability and efficiency.
BUT.... that leads us to Impact 2:
Consumerization
While we try to create an orderly, transparent and accountable structure for the IT organization, the campus community is "going shopping." There's no IT strategic plan for that app that someone wants to purchase. We are increasingly dealing with individual decisions that do not scale and do not provide the accountability or efficiency we need to deal with the trust issues. Consumerization is more than discussion about the impact of iPads and BYOD (bring your own device). We need to include conversations about how decisions are made, particularly for procurement, planned support models and scalability.
Sourcing
That brings us to sourcing models. We are using a right-sourcing model that utilizes many different sourcing paths:
- Traditional competitive procurement with vendor-supported solutions
- Traditional internal development
- Open source
- Community source
- Individually selected (either through a BYOD model or a university funded model)
- Freemium
Combine the above with the device proliferation we are experiencing and we have many platform configurations to handle, such as:
- Individually owned devices with a mix of personally purchased applications and university purchased applications.
- University owned devices with a mix of personally purchased applications and university purchased applications.
Big Data and Big Content
"Big Data" is characterized by data sets so large that the traditional activities around capture, storage, search, sharing, analytics, security and visualization are difficult. I'm thinking there's another corollary to Big Data that I'll call "Big Content." A sample of that type of content may be in this request we received:
One of our doctoral students is using a large number of photos in his dissertation. It is about half written at this point, and is 442.3 MB. The faculty adviser just wrote to us looking for a way to both work on it (so the adviser can comment and edit and the doctoral student can continue to work on the same document). The dissertation will include embedded links to original music composition and will perform as part of the analysis and findings. Also included are visual images that he created so that the color and light in the photos are important qualities in the image, from an artistic perspective and cannot be downgraded.
Big Data and Big Content require new tools and technologies to manage, but also, we need to think differently about how we interact and present in these environments. We are still trying to make things fit into files and pages. We need to rethink the environment and move beyond the boundaries presented by files and pages. The interaction needs to be interactive and immersive; I perceive as more like moving through a current role-based online game rather than reading a book. Even our e-books need to be redesigned for a different approach that is more suited to the technology. It is an experience and the experience must be emphasized or enhanced. Experience is also constrained by our traditional campus time-management tools; experience doesn't know the boundaries of term and academic year. A side read to prep us for rethinking and the depth of change: Planned Obsolescence: Publishing, Technology and the Future of the Academy
(Thanks, Catherine Yang, for sharing).
Storage
If we have Big Data and Big Content, where will we put it all? And we have to recognize the growth of visual content and the space needed; the Art Exhibit of the Day (thanks, Mark Zocher, San Diego, for sharing) recently brought this to some understanding with an exhibit of printing photos. How will we store it all? Where will we store it all? And how will we preserve what we've stored? IBM recently announced the Yellowstone Project to support research into weather, climate, oceanography and related fields. What does disaster recovery look like when you have a computer capable of 1.6 petaflops? This is not about scalability of recovery, but about rethinking what recovery means.
Cloud
The concept of cloud computing will provide some solutions, and will give us a variety of agile and effective choices. There are issues with labeling and understanding Software as a Service, hosted solutions, Information as a Service, Infrastructure as a Service, cloud storage, purchased computing cycles, and all the permutations of what we can buy. Join the cloud concepts with the trends for consumerization and sourcing models, and we have a very complex technology model to build and manage - all within the model for building trust.
Mobility
We are operating in orbit. Our data, our content, our devices, and the faculty, staff and students using all components, are all in motion, and may be on different orbiting paths. Adding motion to the complex technology model previously described is yet another layer of complexity. If everything is in motion, then the expectation is for access over wireless networks, and I've written about those challenges already. The growth of the "mobile only" generation, that group that never or infrequently uses desktop Internet, will further push us to rethink what we deliver and how we deliver content and services. There has to be "real value by being relevant in a mobile moment." That means segmentation of content, data and services, full utilization of communications streams, and provision based on location-aware and context-aware technologies.
How does all of this impact us?
We need different technology solutions. We need different tools and maybe tools that haven't been invented yet. We need to move away from place-centric thinking and consider the impact of motion. We need to approach procurement and solution selection differently. We need to rethink the learning experience involving data and content and unconstrained by terms and academic year. We need to quickly identify and remove obstacles. We need to enhance agility. We need to change our organizations and our human resource structures.
I need to keep working at this to wrap my brain around the full picture.
This is a fresh summary of ideas originally presented at the Fall ACM SIGUCCS Management Symposium, San Diego, November 2011.
This is a fresh summary of ideas originally presented at the Fall ACM SIGUCCS Management Symposium, San Diego, November 2011.
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