Category Archives: Uncategorized

Campus Readiness: Communicating IT Changes to the Campus Community

Title:  Campus Readiness:  Communicating IT Changes to the Campus Community


  • Jo-Ann Cuevas, Campus Readiness Specialist, Stanford University
  • Ammy Woodbury,  Campus Readiness Specialist, Stanford University
  • Christine Jacinto, Assistant Director of IT, Humanities & Sciences, Stanford University


SLIDE:  Campus Readiness at Stanford University

  • 28K constituents
  • About 20 client-facing projects released every year
  • 2 people responsible for getting the word out to the campus


SLIDE:  When an IT Need is ID’ed…

  1. A document management solution to facilitate collaboration and manage data security
  2. PM receives approval to start the project
  3. PM creates charter
  4. PM assembles team, including campus readiness
  5. Campus readiness reviews the charter
  6. Have a meeting to review the charter (impact, audience, training, marketing, documentation, communication).  Campus readiness forecasts hours based on the discussion.


SLIDE:  Communication Plan

A living document that’s updated frequently.  Focuses on communication across phases, IDs key stakeholders and end users.  This functions as a to-do list and a kind of “shadow project plan.”  Includes a running narrative and summary.

Four main sections to the rest of the communication plan:

  1. Awareness and engagement:  who do we need who will be informed about the project?  Might include help desk, key decision-makers, governance groups, administrative assistants, power users, and so on.
  2. Training and documentation:  all the elements we need to create for ongoing needs, current employees, new employee on-boarding.  Instructional designers decide on the best approach for training, because it will vary.
  3. Reinforcement and post-implementation feedback:  what does help desk need to promote for struggling users.  We use qualtrix for survey-taking.
  4. Ok, I missed one step here – my bad.  Can’t type fast enough…


Plan Execution

Includes a ton of work:  E-mail communication, hands-on training, surveys, change training, UX testing, documentation, service promotion, e-learning dev, campus communication, instructional design, user advocacy, presentations.

We function as the user advocate and engage in a lot of geek-to-English translation.


SLIDE:  Case Studies

Case 1:  Mobile Device Management

  • Early intervention led to iteration in the development
  • UX testing led to significant improvements in usability.
  • Adoption was strong
  • When adoption plateaued, Campus Readiness held user interviews determining that further improvements were largely out of Stanford’s control.  Promotion methods were altered to address those issues and use different approaches.

The dev team embraced Campus Readiness input as they saw the impact on adoption.  Team talked a bit about some bumps in the room with AirWatch and how they mitigated some of those issues.  UX issues are considered so important now that the team can delay roll-outs to accommodate needed changes.


Case 2:  Converged Communications VoIP Rollout

Change that affects administrators; on-site training that was all-inclusive accommodated client’s busy schedules.  We started with Humanities and Math & Science departments, then went campus-wide.  Phones would be on the desk after staff went through training, ready-to-roll.

It’s definitely a good idea to reach out to your connectors, ’cause someone is always the “go-to” tech helper in a department.


Case 3:  International Travel Data Security

It’s no longer just about visas and vaccines, it’s also about data security!  You have to be conscious of where your data is going.  We have three preferences of how we want people to work (in order of preference)

  1. What would we most like you to do?
  2. What’s a good approach?
  3. What’s the minimum required?

Their shop has loaner iPads for overseas trips.  If the user MUST take their own computer, it is imaged prior to departure and is restored upon their return (and PRIOR to the computer going back on the network).


Case 4:  e-mail and calendar upgrade

At launch, the campus readiness team provides:

  • Video tutorials (what’s new and different)
  • Daily tips by e-mail
  • Front-line support
  • Demos
  • Hands-on training
  • Campus partners

Each session had a roomful of people, since implementation of such a product affects pretty much everyone.  We would also engage with key stakeholders and representatives from each area to hear what their pain points were.  We would then help these “decentralized” folks formulate their own plans for communicating changes to their teams.  This helps build community.


A “Campus Readiness Specialist” has experience with:

  • Communications/business writing
  • ID and training
  • Presentations to large and small groups
  • Help desk support
  • e-learning development
  • UX testing

Key Qualities

  • Warm, friendly and outgoing style
  • Ability to rapidly learn new systems
  • be a geek-to-English translator



Are you a part of the PMO?  No, we’re matrixed but mostly report to documentation team.

What communication mechanisms do you use…Social Media?  We do use Facebook and Twitter, we also use an IT access page as well as a space for messaging on our ticketing page.  We also use the “Stanford Report,” a daily e-mail communication managed by university communications.

Do you participate in requirements gathering phase?  Yes!  But not always…

How many people normally attend your weekly monthly meetings?  Depends, from 40 or less on weekly meetings to 81 for monthly meetings.





Big Data Enables Student Retention: Student Success & SAP HANA

Title:  Big Data Enables Student Retention:  Student Success & SAP HANA


  • James David Hardison, DMD, MBA, Industry Principal, Higher Education
  • Vince Kellen, Ph.D., Senior Vice Provost Academic Plan Analytics and Technologies


SLIDE:  Screen shots of the “Powers of Ten” film

What if you could…(I smell a sales pitch coming)

  • Manage data, have the current data, have the right answers


SLIDE:  30 year old data modeling is slow and inefficient, in-memory is the new hotness!  (My words, not theirs)

HANA:  High Performance ANalytic Appliance


SLIDE:  HANA for Higher Education through University Alliances

  • SAP donates licenses to 1,300+ univesities
  • 1.2 million students educated on HANA
  • Certifications, etc.


SLIDE:  Newton’s Second Law of Motion

Students at risk are not likely to change their behavior without intervention.  Used snowball rolling downhill as an example…easy to stop at the top of the hill, but irresistible at the bottom.


SLIDE:  Using Fast Analytics to Help Improve Student Retention

High response rates to mobile micro surveys, about 40,000 responses in 4 weeks.  Questions include things like “how much are you working this term, how stressed are you (1-5 Likert scale), do you think you’ll be successful this term, etc.

In-memory analytics requires different architecting of the data modeling; We don’t do traditional ETL (Extract Transform Load techniques).

Took an approach of making data available, rather than keeping it “close to the vest.”

We can answer the question:  do we know how many left-handed Hungarian ping-pong players we retained?  How do we break our analysis into little pieces to answer practical problems and questions.

Also collecting “technographic” information on student device types and OS, frequency of use, number of devices, etc.

Been prototyping this with lecture capture and full-text search (what he referred to as “wayfinding”), i.e. ability to find specific terms, apply metadata, ability to link out to other materials, and so on.

Graph databases are generally not used by university degree audit reports, which precludes the use of “what if” scenarios.  This is useful for day-to-day business needs.  Incidentally, graph database technology is widely used in the Social Media space, but for some reason it seems to be all new and exciting to many of the wide-eyed higher ed attendees.  Hmm…

They’re using HANA data with Tableau to make pretty graphs.  Also, showed an Enrollment Plot of Chemistry 105


SLIDE:  Academic Health Notifications: View in Student Mobile App


SLIDE:  Using this data in a personalized student profile



SLIDE:  Taxonomy?  Automatic metadata?  Automatic atomic metadata?

  • Let learners navigate an a/v stream
  • Let the system learn what the top terms are.  Let the system map terms to concepts.  Let instructional designers lightly bump the taxonomy.

Thinking of Google AdWords-style presentation of information that’s relevant to the student’s click-stream and status.


SLIDE:  Organizational Considerations

  • Hired Ph.D. level data scientists (there was some turnover)
  • Translated old architectures to HANA and retired old IR data warehouse
  • Opened data, many have access, personal data is protected
  • Raised skill sets in colleges and units and provide support.


SLIDE:  Some best practices

  • Be safe and secure
  • Be collegial
  • Help improve data quality
  • Be open-minded and inquisitive
  • Share (don’t be a taker)



Do you plan to include co-curricular data into your system?  Obvious items are participation in clubs and organizations, and surfacing internships and job opportunities.  Yes, it’s on the roadmap.

Are you collecting data on effectiveness of tutoring?  Yes.


The Edward Snowden Affair: A Teachable Moment for Student Affairs and Higher Ed

The erosion of our collective privacy has been going on for a very long time.  Most of us are (sometimes grudgingly) comfortable with the exchange of our personal information for useful products and services.  The biggest problem most people seem to have with the revelations about the NSA’s surveillance program is that it can and does gather digital information about everyone, and can use it at any time for any reason.  The fact that a relative “schlub” in the organization can access and use that information is one of the main points Snowden’s whistleblowing meant to get across.  This got me thinking about how we use data in higher education.

In higher ed, we’ve been collecting lots of data for a long time, and we’re bound by law (FERPA, HIPAA, etc.) to protect and retain student data.  Our student information systems have detailed security policies outlining granular role-based access, aka which employees get to see which student information.  These policies are generally structured on a “need-to-know” basis.  Here’s my two-part question to the reader:  first, how many of us in higher ed have articulated a policy about the data we collect on our students and how we use it?  Second – and more importantly – how many of us have published such a policy that has been specifically drafted for our students?

Every Student Affairs professional I know wants to use data to help our students be successful.  When properly applied, it’s a boon to our profession.  It helps us determine our students’ interests so we can help them choose an appropriate degree program.  We know this reduces both time to graduation and major changes.  Data helps us identify clubs, affinity groups, and other co-curricular activities our students can participate in.  We know that co-curricular activity participation increases retention, especially among first and second year students.  In our day-to-day jobs, we regularly use student data to determine satisfactory academic progress, GPA, eligibility to vote in student elections, reporting of all kinds, and so on.  With the move toward self-service web applications, we’re increasingly presenting data to our students and shifting more decision-making responsibility onto their shoulders.  This is a great opportunity for us to educate students on how we use data to help them, while increasing transparency about their data’s use.

In my opinion, that last bit about transparency is the key element for higher education. There are no shortage of articles about “big data” tools and how organizations use them for competitive advantage (whatever that means).  However, the tools themselves don’t address the more fundamental nature of how we “connect the dots” between disparate data points.  We should inform our students how we use their information so they can make better choices.  We should teach our students how they can use this information to their advantage.  We should help students understand that they are the masters of their own data.  In the same way that provides insight into how we spend our money, our student data should provide insight that lets students thoughtfully determine where they should spend most of their effort.

What do you think?