Category Archives: Uncategorized

EDUCAUSE 2014 insights, contacts and actions arising

A few notes here outlining next steps for me and my portfolio in light of my attendance at the conference


Contact made with Yves Épelboin from EUNIS RE BI Taskforce and BI Maturity exercise via Bob Strunz
Contact made with Hank Childers of HEDW (and therefore Aaron Waltz) and agreement gained to support UK BI Maturity measurement exercise
Opened the door at EDUCAUSE to comment the plans for Jisc Challenges on Prospect to Alumnus, Learner Analytics and the Jisc HESA Business Intelligence initiative. Aim to choose a specific area for genuine collaborative effort and mutual benefit. Alert Paul, Simon and HESA.
Update work plan to account for the Program Committee deadlines, seek adjunct readers and watch out for contact from Tim, Chair of stream
Excellent poster on a flexible toolkit to help non-project managers to deliver project success from Edinburgh University
and UCISA Project Management Practice Group toolkit (Mark Ritchie)
Need for a getting started EA modelling tool vs a complex expensive scalable tool. But the former needs some sustainability. Could be as simple as open source subscriptions (Luke)
Archie to develop a repository, multiple user support and cloud service (Nathalie)
Spreading EA capability across roles rather than a single EA modeller (Nathalie)
Need for a 3 way conversation between Jisc, UCISA, Archie (Luke)
Internet2 – a North American organisation providing various shared services to HEIs (Bill)
Develop the Mind Map of UK Analytics and BI initiatives and supply to Sector Intelligence
Work with Sector Intelligence to develop visual representation of same at a high level / overview of user benefits not project jargon
Isights in to the work d of the CIO – see stream of session chaired by Louisa
Invitation to an Educause event on Enterprise analytics in Seattle in June 2015
Issuing students with lap tops for 3 years of their course then reissuing to staff for the remaining lifetime. Putting students before staff. Coventry University.

Educause 2014 Day 2 PM

Session 1 MavCLASS


I was drawn to this session as it’s linked in with Purdue and is supported by Gates foundation, not to mention the abstract.

2014-10-01 13.25.42

The first session I’ve attended that is using a Gdoc to support.

‘Course Analytics’ providing individualised information about learners course assessments and activities to help them learn. Provides an example of a 500 seat course and presented the assessment regime. By providing students with increased instances of personalised feedback those struggling would seek more help resulting in better knowledge gain, performance and satisfaction.
Used learner assessment data to provide targeted feedback suggesting learning pathways for a human. This forms the Maverick comprehensive learning analytics support service (MavClass). Itegrates across Desire2Learn etc and provides insights to GAs as clickable RAG status giving insight into behaviours.

2014-10-01 13.53.18

KEY LEARNING POINTS; Providing students with RAG status based on assessments can trigger them to reach out for help. It’s not effective for all though. Significant knowledge gains were noted for those seeking help. Meaningful learner analytics requires early meaningful assessment. Know the data story you want to find, but let the data tell it and be accepting of the insights gained.

Session 2 Building a foundation for campus wide business intelligence – two perspectives

Heath Tuttle Director of Learning, emerging technologies and analytics University of Nebraska
CIO Gonzaga University


Realtime transitional data is a new way of thinking for HE and there’s more demand for it to, for example;

Provide information to grow enrolment and increase retention
provide a world class learning experience
Provide needed technologies

The information to answer these was available but scattered in different silos, by different stewards.

Existing data sources; Peoplesoft (student data, room, class, timetabling, room capacity), Conquest RMS (manages and monitors equipment and rooms) Purchase request system (home grown purchase/accounting system)

KEY LEARNING; Conquest RMS allows monitoring of equipment usage hence allows retirement and maintenance decisions for efficiency gains (200 gourds left on an projector lamp, lack of use of a BlueRay player etc). Connecting data silos revealed errors in the data. IT are delighted to gather student retention and registration data and providing it to relevant people. They have no sway in how it is used. So good at providing the insights, not interested in actioning them.

Gonzaga University
Used the MS BI Stack and BB analytics for insights. Being in charge of a BI / Analytics / Decision making service is like being a parent, the responsibility never ends. Nice diagram here of the process (BI and Analytics, not parenting);

2014-10-01 15.07.46

The killer analytics app – identify those students likely to gain the highest salaries and target them early for alumni relations and benefaction!
Need for a ‘translator’ someone who can talk registrar / HR / role XXX then translate to geek for developers. Nice idea.

A few of the data silos at Gonzaga University – Ouch!

2014-10-01 15.22.00

I’m out of power. In the words of Bugs Bunny. That’s all folks…..

Educause 2014 Day 2 AM

As I crossed the street from Convention Centre to join a meeting with Eden Dahlstrom (EDUCAUSE Director of Research Data, Research and Analytics) and Hank Childers (the Higher Education Data Warehouse) I came across an adult alligator in the bushes. Turned out to be plastic. No one was around to observe the dumb Brit running of the staircase!


Session 1 Student success is everyones business
A. Pam University of South Carolina ‘beyond the classroom matters’
Issues; accountability, transparency, increasing demand
Support Provision; ‘student affairs and academic support’ focuses on the whole person; intellectual, physical, emotional, social, vocational, spiritual.
Success Indicators; Learning, retention, graduation and employment

Aim to see the entire undergraduate experience in data. Essentially tracking student interactions with institutional systems beyond the academic program, something in the UK I know as Engagement Analytics. The problem faced is that student information systems do note record non-academic engagement and this is the subject of ‘beyond the classroom matters’.

2014-10-01 08.12.55

The vision here is that student analytics helps advise students of academic courses and non-academic activities to help enhance their chances of achieving well on those success factors. I don’t think this is a done deal but we’re hearing about vision and progress toward it.

KEY LEARNING POINTS; Seek friends and funding – IT have the key to delivering, but are bogged in other priorities. Success is about collaboration across disparate functions led by a champion and a shared vision.

B. Carleton College and Grinnell College qualitative and quantitative research to support student engagement in the support services
A presentation of longitudinal (5 year) studies into the role of student services in retention and progression. 86-95% six(!) year graduation rates. Six is interesting and perhaps reflects the student profile. Looking at 4 year and based on income these are national figures;

2014-10-01 08.28.20

The analysis gave actionable insights to improve the colleges performance against the average. The action brought poor in line with affluent at 4 year point. Students who drop out cost the institution $60K per year.

The major factor affecting student dropout was successful development of relationships. The college proposed to learn from other sectors and propose that the clinician / patient relationship is a helpful source. Who saw the student, what measure did they prescribe, did the student act on the advice, what was the outcome. Tracking and sharing these is the aim. The Co-Tutor system in the Uk does similar things to this.

KEY LEARNING; mine the data and create new ways to visualise to the right people at the right time. Real time systems. Look beyond the tips of your skis – predictive modelling to identify the soon to be at risk form the past. Work together. Look to emulate the medicine / patient model using diagnostic testing to provide insights into learning at an individual level.

Session 2 Analytics that inform: the university challenge
An expert led panel session sponsored by Realize IT.
Analytics – what does sit mean? Taken from BI – can we use the same type of approach to mine student data for insight. Faculty performance, student performance and improving student outcomes. Now using real time analytics to predict. Analogy again is medicine diagnosing and being empirical to diagnose weaknesses and offering a series of interventions to address those. There are powerful ‘code halos’ that can be wrapped around educators, students, institution to yield information and through algorithms drive a nexus of learning between the student and the institution. My, what a mouthful! Transactional data into insight, insight into interventions. We can accelerate students’ learning based on their competencies, prior knowledge and aspirations. We are finding ways to enhance learning for students who are perhaps not as driven as those who used to be successful. They are able to enjoy education more, finding it exciting, thrilling. The example was hiding the pill in the peanut butter – provide the less palatable materials within those a student finds enjoyable. So different ways of designing content. Individual curriculum design. Multi-modal ways of learning are the norm for the student body. The education industry needs to look at how new models of different paths to arrive at the same outcome can be embraced. Be careful what you wish for; Look at – correlation of play lists to mean SAT scores – analytics can be made to prove anything but meaningful correlation isn’t always present!

KEY LEARNING POINTS; We are at the early stages of analytics. We are data rich and information poor. A code halo – how you mash the institution data with other – the ethics are important – hurrah – first time ethics has been mentioned in these sessions. Sequencing courses and curriculum should come soon. Diagnostic testing in medicine is expected, the notion needs to be embedded in education! An aggregated federated repository of related information is one vision of what needs to happen. Educational models need to be multi modal to suit individual learners and the needs of these learners should be profiled by analytics. Analytics will help inform how faculty spend their time and efforts with students. Deconstructing faculty roles; some will develop content, some to deliver, some to assess, some to deal with other student holistic needs. Analytics will change the fundamental role of faculty. Analytics will provide quantitative measures for the value add of Higher Education. They will obviate the need of end of module surveys and pave the way to performance related pay(!) for those faculty having the best instruction to their students (even if they may not be popular). A curriculum designer needs a different set of dashboards to a teacher.

Educause 2014 Day 1 PM


Session 1; Building organisational capacity for learning analytics.
A fast paced expert panel session including Linda L Baer (without Don Norris) reporting on their 2013 white paper with the same title. Linda outlined the stages of development resource as well as the ECAR Analytics Maturity Index for Higher Education.

2014-09-30 14.37.07

2014-09-30 14.35.38

Next Ellen Wagner talked about PAR data sets, common framework and vocabularies. Importantly Linda outlined the Student Success Matrix; ‘knowing what to do next’ an analysis of actions institutions have taken and how effective they were. See data cookbook;

University of Wisconsin described their journey of building organisational capacity for Learning Analytics;

1. Tech infrastructure, analytics tools and applications
2. Policies, processes, practices and workflows
3. Values and skills (includes learning analytics faculty support role)
4. Culture and behaviour
5. Leadership

Last Improving retention and advancement through the ‘education and career positioning’ system – Wisconsin. The suggestion here is to stop making things complicated. Students need to make informed decisions to achieve ‘advancement’ through education. Give students appropriate access to their data to help with this. This is personalising analytics – tailor it to the students. Comparison between travel self navigation vs education – career self navigation. The former is mature, the latter lacking.

KEY LEARNING: Predictions might lift the likelihood of identifying at risk students by 20%, 25%, 30%. This should be seen as a success. See the PAR Data Cookbook for actionable insights and the actions most successful in addressing them. Download the Baer and Norris 2013 white paper to help get started with Learning Analytics. This includes common data definitions and some practical tools which look well worth further exploration. UNISON is a consortium of American Universities working in collaboration to develop Learning Analytics in ways they have been unable to individually. Call for more pressure on IMS Global from US HE.

Session 2; BI Driven Social and Cultural Change
Session being streamed around the world. How exciting!
Michael Hanson Finance Director and Director of the BI Institute, Oregon State
Lois Brookes CIO Oregon State
and colleagues from George Washington University

BI initiative came from CIO in response to demand for data.
1. Data Warehouse from
2. Self Service Reporting

2010-12 failed implementation of a vendor BI solution – why – no SRO, technical challenges, user satisfaction levels, project cost escalated due to staffing, maintenance agreements and hardware. Terminated in April 2013 after 1.8 million dollar spend with little progress.

Restarted the BI initiative and have a fully successful service after 18 months. Here’s how;
Identified why the initiative was core to the university;

‘Data is a strategic asset if the university but only to the extent that it is available, true and actionable’

Used Agile development (iterative cycles) and have 300 plus reports with 1600 users by addressing Organisational and Technological issues

2014-09-30 15.56.03

Automatic role based authorisation

2014-09-30 15.58.05

Requires a Business Intelligence Competency Centre

2014-09-30 15.59.40

KEY LEARNING Organisational; View data as a strategic asset. Make data a part of the strategic plan. Discover what the senior managers need and turn them into champions. Introduce the notion of Data Stewardship – to smooth the way to organisational acceptance. Communicate the project at every opportunity. Trust employees. Be responsive to demands (aim to iteratively produce analyses in 2-3 days).
Technological; Build a data architecture. Enforce a no modifications policy at local level. Use Open Source and existing licenses where possible. Role based security to cope with number of users.
Talend for ETL
Tableau for report development

Educause 2014 Day 1 AM

September 2014 finds me in Orlando at the Educause 2014 conference.

Back in February Diana Oblinger invited me to join the 2015 program committee. That makes me the sole international member, good job my shoulders are broad!
So I’m here with 4 aims;

1. Gathering intelligence on BI and analytics conference session content, quality and formats
2. Seeking overlaps and opportunities through side meetings and meeting the 2015 program committee
3. Linking in with the Jisc sector intelligence team and seeking updates on the CIO sessions and various meetings they are undertaking
4. Contributing any relevant intelligence to the planning of Jisc Digifest 2015

With over 400 sessions in 2 full days and 7K plus delegates the advice I’ve picked up is pragmatic – choose carefully, build in time to reflect, make the most of the commercial area as its full of expertise.


This blog post will be deliberately concise. It won’t be a detailed record of the event as my previous posts have attempted. I’m going to try to provide a summary of each session I attend, then distill out the key learning points that struck me below. Here goes.

Session 1 Disrupting Innovation and the future of higher education – Clay Christianson
A key note talk in a room the size of an airport hangar, works surprisingly well.

Bit left field for me this but bear with, it may be worth it…..

Disrupting innovations are hard to catch up with as the case for sustainability isn’t there. Sustaining innovation tips include ‘competing against consumption’. ‘Non-consumption’ is the slack in the market.

Art Example; Putting up a picture in your house; For 3 weeks you enjoy it and are a consumer of art. After 3 weeks you pay less attention and become a non-consumer. A business may exist to offer a screen that provides new art every 3 weeks. It exploits the non-consumption.

‘The right product architecture depends on the basis of competition
Proprietary interdependent architectures’.

Mobile phone example; Proprietary; Nokia were disrupted by Blackberry which offered email and messaging, then Apple operating a the high end of cost and quality
Modular open architecture; Android is over running the market

PC example; Modular open; Dell, Acer, Quanta cannot distiniguish products fast enough. When modularity occurs the module providers make the money – intel and Microsoft.
Closed Proprietary; Apple highly distinguished, high end and expensive

App Development example; Closed proprietary – Microsoft and Apple – you can’t change the Windows code Open Modular – Linux

Dell and AsusTek example; Asus Tek started by making motherboards for Dell, Dell managed assembly, distribution, design etc (the modularity). AsusTek offered to take over each of these more cheaply. Dell accepted each noting increased profitability while assets and costs shrunk. Eventually Asus Tek were able to go to vendors and explain they were making the best computers in the world, they can supply them cheaper as a cheaper brand. Dell disappeared.

So where might we apply this to Higher education? As HE goes online we see open modular supply and accreditation for components of a degree across multiple institutional education suppliers. Standards are coming in to exploit this. The money is going to be made by the suppliers of the ‘components’. Scale becomes important as they can reach hundreds of thousands of students. Institutions beware or you may disappear entirely. Well. That’s the theory!

KEY LEARNING POINTS; models of disruptive innovation, closed proprietary and open modular are all relevant to the future of Higher Education.

Session 2 Leveraging Data for Strategic Advantage
A round table (EDUCAUSE CIO) discussion session led by experts Sharon Blanton (CIO Hawaii Pacific), John Phillips (Dell), Stephen Landry (CIO Seton Hall), Fred Richards (Ellucian and Cognos)
The convenors used to gather responses to various questions rather than a ‘raise of hands’.

Here are the questions;
1. What is the current state of BI on your campus?
2. Where on the BI Maturity Model (Gartner) does your campus lie?
3. What does BI look like on your campus?
4. What functions are currently being addressed in your BI solution?
5. Who is the leader or champion of your BI implementation?
6. What is the greatest current challenge for BI on your campus?

Gartner BI maturity levels; Adhoc BI – repeatable BI – defined BI – managed BI – optimised BI

Here’s the survey;

It would have been good to have mapped this to a national survey such as these;
The Data Warehouse BI Maturity Tool
EUNIS BI Taskforce Survey 2013

KEY LEARNING POINTS; Of the 120 plus CIOs present in the session most declared low BI Maturity. NACUBO – the US equivalent of BUFDG are seen as key consumers and powerful proponents. Business process is a key preliminary step to successful BI implementation. Most here have no senior champion for BI. A committee of senior stakeholders was more common. A federated governance using a Business Intelligence Competency Centre (BICC) is declared as best practice while an Agile Development approach was described using sprints. The main challenge is seen as disparate data sources and data quality.
Top Quote; ‘there’s no such thing as mastering BI, it expands faster than you can catch it’

Session 3 Managing the digital campus from enrolment to graduation
I’m quite intrigued by this as Jisc is part way through a wide UK consultation termed ‘Prospect to Alumnus’ identifying issues, opportunities and thinning these down to 4 candidate areas for the development of new services to the UK HE sector.

Theme; Improving the student experience
Issue; admissions process was slow, self service meant students would upload data multiple times creating a backlog
Solution; Peoplesoft 9.0 implementation underpinned by a single student record

Theme; Accelerating the success of new hired employees
Issue; a 19 page document describes the manual processes to support this
Solution; Electronic checklist system for managers to complete

Theme; Electronic Content Management is paper reliant and prime for an update
Issue; Financial arrangements are delayed, paper storage is expensive, access is poor
Solution; Vendor provided solution implemented. Reports a 550% ROI based on the improvements. Essentially a records management initiative coupled with an electronic document management system cutting swathes through inefficiency and with some compelling impact measurement.

Summer of Student Innovation 2014

September 2014 and I’m at Jisc offices London at the final 2014 summer school event with the 21 projects Jisc funded to develop their ideas for technology underpinned innovation in Higher Education. Here’s a summary of the initiative and the project.


My own interest here is the ‘next steps’; which of these projects shows the best potential for a partnership with Jisc moving toward a respected service for our members.

Brettenham House

The summer school has provided an expert support group who, through working with the projects have developed and implemented a series of masterclasses to help move the student teams on toward ‘start up’ viability. Today we’ve got one expert led session then we move on to project ‘pitches’ to the expert support group with a view to giving feedback on next steps such as;

• Transition toward service
• Piloting
• Mentoring
• Supporting collaboration/synergy
• Development support
• Open community support
• Hosting and marketing
• Other e.g. introductions to start ups, investors, related initiatives

First off we’re hearing from Alan Greenberg, former Director of Apple Education EMEA and Asia @alangreenberg.

The vision; develop an educational business for Apple made available through Podcasting, ‘iTunes U’ (a billion downloads of free access content) and mobile.
Setting the scene; the Open University model 9K students curricula delivered online and run ‘as a business’. It can be done and there are big opportunities for technology underpinned mays to teach smarter, quicker, more effectively noting the Chinese, Indian and South American markets are prime.
Opportunities; Curation (there’s a lot of free content available, how does one find the right content, how to best use it, how is it being used).
Cradle to grave; lifelong learning and understanding the value proposition the initiatives here are offering to improve that process
Learn anything using the worlds best resources
Track all your learning; professional, academic and informal
Provide enterprise with a modular way of understanding a persons collection of skills (matching people to opportunities)
Next generation in innovative assessment
The inappropriateness of ‘exit strategies’ – user needs, opportunities, development, disruption, sustainability, spin out; an iterative process not a concluding event
Importance of ‘Pilots’ – working collaboratively with an organisation who can tell you want your product can do for them – the value of building ‘exemplars’ to test the environment – not what you tell people, what you can do. This is an area Jisc should focus on helping happen
The importance of a mentor / wider team than tech dev – the developer is focused on the technology – but can they communicate what the benefits are, what the technology actually does for people? This is an issue I’ve seen projects grapple with, those that fail here make little progress.
Sustainability – does it have legs, does it have a lifetime can it support itself
Learn how to learn – the importance of this in the education system – the apparent lack of skills to support this in entrants to HE (personal work planning and management, collaborative working, communication skills to deal with different stakeholders from purchasing decision makers to teachers using the product (and the opportunities for technology to help out).
The Summer of Student Innovation is a fantastic learning opportunity and must be about fun – enjoy the experience!
Bring Your Own Device – a lot of nonsense – students have devices, content is available – adding value; relevance of content, managing content, curating content, these are the issues to address

Information Strategies Event RSC / UEL July 2014

31 July 2014 finds me at a Jisc RSC hosted event exploring Information Strategies and associated issues for the HE and FE sector. Hosted by UEL and arranged by Martin Sepion and Julian Bream of Jisc RSC London.


I’m joining a diverse set of people from Enterprise Architect, Data Architect, Heads of Enterprise Solutions, Chief Information Officer and that ilk. I’m presenting a session on our Jisc / HESA Business Intelligence project later this morning. My own aims are to raise awareness of the initiative and gather feedback on the sorts of issues people need to address in order to design and implement an Information Strategy and what linkages there may be to the proposed National BI Service Jisc are developing with HESA and HESPA.

Feels like I’m in the right room.

Martin Sepion (Jisc RSC London)
Jisc RSC London have been working with UEl on developing and implementing an Information Strategy.

Martin described a common scenario of data flow throughout an education provider and how this might be optimised. This throws up a significant number of barriers with procurement being a key issue along with many others such as staff skills, vision and strategy (collective).

How do you know whether your information systems are doing a good job? A self assessment process was designed which sounds very much like a variation on the Jisc Strategic ICT Toolit. (LINK) I’ll chase down a link to this.

Gordon Millner (RSC East Midlands) described a data strategy template that has been developed and made available. He also touched don Dashboards, Visualisations and Big Data as issues and opportunities.

Me, Teresa, Jisc/HESA BI Service Initiative

Our slides are here. The session went well. The show of hands for BI definition fell heavenly between Gartner (top down) and Microsoft (bottom up). The Jisc definition failed to attract as single vote so one for us to revisit! We showed the Liverpool University Business Intelligence Case Study Video (a previous Jisc funded project) on YouTube (LINK). I asked the question – who has this capability? The answer was no one but UEL (also a previous Jisc funded BI project). This really backs up the notion of the Jisc/HESA BI Service offering a ‘leg up’ to those with little capability and the opportunity to gather momentum and evidence toward a business case for investment.
I asked the question ‘who here would like to have the Liverpool capability’. The answer not surprisingly was everyone.
Teresa and I posed 5 questions we’re seeking the answers to and will be gathering input on this later in the day;

1. In relation to your current role what is the most burning question that you would like to be able to answer which you are not currently able to? In short: What would you most like to know?

2. Why do you feel you are currently unable to answer the question you outlined above?

3. From your point of view, who in your organisation would be interested in having access to BI information?

4. Thinking about BI systems in your institution, where would you place it right now on a scale from 1 to 10?

5. We are planning to run a survey on maturity of BI systems in organisations. Would you be interested in participating, or know someone who would?

6. What sorts of services should the Heidi Plus offer
to move people along with BI agenda?

We compiled a list of likely responses to the discussions planned later, namely what issues will need to be solved in implementing an Information Strategy (and hence capability to develop and benefit from BI RE question 6 above). These could form the basis the sorts of services needed within the Jisc/HESA BI Project and repeat these below;

Strategy development and the technological enablers to allow implementation
Records and information management
Data quality assurance
Data governance
Master data management
Vendor selection and purchasing
Developing good data visualisations

Non-technological enablers to for strategy implementation;
To ensure dashboard data is embedded into institutional processes

Andy Cook (CIO UEL) and Gurdish Sandhu (UEL)
This presentation describes the UEL journey of Information Strategy design and implementation and is worthy of a look through. Here’s the presentation. Pay attention to the SWOT and the issues and timescales repeated below.



Several key points to this, the ones that struck me were on staff skills (and presumably culture) so linkages to Jisc ‘Digital literacies’, single point of truth (data warehousing / data cleansing) linked to key people (improve data quality by assigning ownership – Information Asset Owners, Information Asset Managers, Data Stewards), concentrating on key business areas and systems (research, finance, student, staff etc), proliferation of small Access / Excel databases (Andy has removed Access training for staff) noting people do this because corporate systems don’t meet their needs.

Group discussion findings
The groups were tasked with discussing related issues from what they’d heard today and based on the two key slides SWOT analysis and Delivering IS.
Here are the headline areas (ideal for a mapping to Jisc resources and a gap analysis)

1. How people use the data provided – skills and culture change
Attendee tips; self assessment based on KPIs via monthly management group meetings
Jisc resources; Digital Literacies InfoKit, Organisational Change InfoKit, Data Visualisation InfoKit

2. Embedding Information Culture, establishing a business case for a large investment, KPIs for the improvements BI brings
Attendee tips; aligning business acumen on enhancing institutional performance with key data literate people
Jisc resources; Business Intelligence InfoKit (building a business case)

3. Data Quality and how to assess how advanced this is in an institution

4. Siloed manual intensive data and reporting. Culture shift, top level buy in.
Jisc resources;

5. Master data and technical issues to assist the strategy implementation. Includes enabling technologies such as good wifi

6. Role of Enterprise Architecture in optimising and controlling the underlying systems required to promote Information Strategy implementation

7. Good information and records management as an iterative process that must be embedded as a cyclical exercise not a one off

8. Ambitious strategy to include organisational and external data but being realistic on time scale to help encourage a vision of what good information use can achieve

9. Cleaning up all the data, or just the bits you need

10. Analytics skills as reality – BI can be a big part of the solution and the problem – introducing a level of complexity that magnifies the problems of data literacy and the interpretation burden on other staff

11. Doing something of value in a short time period – moving to action to demonstrate opportunity and value, examples of what can be achieved to drive momentum, support and investment

12. Top down support to provide authority and break log jams impenetrable by those building the systems

13. Trying to do it all is akin to boiling the ocean, small steps to achieve highly visible impact could be helpful

14. It’s all about the value and the benefit and how to report that back to the business – high profile wins need to be celebrated in a visible manner. It’s not about providing the technology or bombarding people with information and systems that don;t meet end user needs. Top table guidance is important. Bottom up approach isn’t enough.

Last note from me – the organisers added their own report of the day here

National Centre for Student Entrepreneurship in Education

15 July 2014 and I’m in Leeds attending The National Centre for Entrepreneurship in Education (NCEE) Student/Graduate Start-up Support and Enterprise Talent Development Programme seminar (bit of a mouthful but bear with, it’s interesting stuff).

I’m involved in the Jisc ‘Summer of Student Innovation’ initiative.
We identify ideas for IT based enhancements to the student experience from students themselves, support them through a series of 3 day expert led entrepreneurship based boot camps, provide mentorship and peer action learning, run a showcase event, shortlist for potential ‘transition to service’ projects and identify partnership opportunities going forward to provide services to the Jisc membership.

See for the 2013 and 2014 initiatives.

So I’m hoping to see overlaps and perhaps identify opportunities…..

The sessions describe examples of what has been done in the North of England Region of NCEE and introduce the June 2014 Lord Young report ‘Enterprise for All’

Leeds Grand Depart

Session 1 – Benefits, Impacts and Learning from the North West Enterprise Champions Project Dr Simon Brown
The NCEE is an accountable body supported by the North West European Unit via the European Regional Development Fund (ERDF). Delivery partners are Bolton, Chester, Liverpool, Salford, UCLAN, Edge Hill, Lancaster, Liverpool John Moores. A programme has been running since 2007, so in its 7th year with an extension granted. The programme aims were to work through University leaders to develop more entrepreneurial cultures in member institutions. The outputs would include addressing the low-level of graduate startups. Methodologies include;

    Enhance understanding of what it takes to create more graduate start ups
    Feed good practice into curricula and extra curricula
    Build expertise
    Enhance the regional economy

These were not seen as core aspects of University business. A key aim here is to make this so.

The latest phase has focused on 1353 pre-start assists, 266 new business, 333 new jobs.

Evaluations on the programme have shown;

That Universities with strong research excellence tend to engage aspirant entrepreneurs via extra curricula activities. Those with more vocational programmes tend to engage through the curriculum.

    Everyone is having difficulties in getting the messages to the students – whatever channels tried. Ditto for tutors.

Jisc have found that whatever channels are employed, word of mouth and social networking seem the most effective methods to reach students.

The timing of getting the messages across is key – posters are often prevalent, but students and staff interest window is peaked at certain stages and so ‘keeping the message going’ is important. Jisc is considering keeping the ‘Elevator’ (the site we use to collect proposals from students) live all year round with a window of selection so this seems appropriate.

‘Employability’ is being talked more openly in institutions from prospect to graduate and is a driver, however enterprise and entrepreneurship (which as phrases can frighten people off) should be a set of graduate attributes, not a career path.

Entrepreneurship needs to be stated in key University strategies, owned by a member of SMT, devolved through ‘Champions’, linked to business, celebrated and measured for impact. So n that sense not different to most new initiatives aiming to amend and embed institutional culture.

Session 2 – University benefits and impacts: The University of Chester experience Paul Kirkbright
Chester set out a strategic vision, a typology for innovation and enterprise, a survey (which found the vast majority of students want to work for themselves at some point in their careers), instigate a culture change programme, support the creation of a ‘society’ with;

240 students actively participating in enterprise activity
130 in pre start activity

And an Innovation, Enterprise and Business Support Model

Chester Model

Note ‘Create, Collaborate, Accelerate’ embedded in various aspects of institutional culture. The earliest stages are funded in partnership with Santander, the latest stage is to create a University investment fund which ties into Alumni – keep those entrepreneurs giving back to the region, get them to talk to the incoming students.

This is by no means a common approach!

Session 3 – Benefits, Impacts and Learning from the Yorkshire and the Humber’s Graduate Entrepreneurship Project Dr Kelly Smith

This is a regional project running from 2007 – 2014 and is now in an ERDF phase. Phase 1 created 274 jobs, 269 new businesses, assisted (in blocks of 12 hours of support) 218 businesses through 2554 blocks. I had a chat with Kelly before the event began, She is Head of and Principal Fellow for Enterprise at Huddersfield managing the student and graduate start up unit and advising on embedding into the curriculum. Kelly is keen on demonstrating the impact of enterprise in the curriculum leading to start ups noting that BIS have put up funding through vehicles such as the National Association of College and University Entrepreneurship (NACUE). Kelly also mentioned the ‘IDEA Award‘ – a programme seeking to inspire digital enterprise in 16 – 25 year olds led by the Duke of York

Aim; to provide the best enterprise and business start up support possible to students and graduates of the region.
Objectives; Promote entrepreneurship and business start up
Combine resources and best practice
Manage a broad framework of support activity
Partners are broad numbering 11 regional HEIs
Outputs; Phase 1; 20 SME assistances, 30 new jobs created, 50 new businesses created. Phase 2; 90 SMEs, 71 jobs, 44 new businesses

Benefits to members; a collaboration of trusted partners, ability to shape activity to own context, sharing of processes and practice (not competitors as supporting own students), demonstrable impact on beneficiaries.


ERDF requirements and continuation have been a major concern in the room. ERDF is reduced. Local Enterprise Partnerships (LEPs) are the replacement. New funding arrangements will be around January but a reliably to go through LEPs.

The role of an Enterprise Champion varied widely matching to institutional goals.

Enterprise for All report by Lord Young June 2014, Government response expected Q3 2014.
Of particular note the proposed E* awards for university entrepreneurial attainment, future earnings employment record (ties destinations of leavers with HMRC income), enterprise module for all students, enterprise societies, student business startup taught programme, social enterprise (it’s a good thing, rather than any recommendations).

“None of this is compulsory – it is just a start” – Lord Young

What does this all mean for Jisc and the Summer of Student Innovation initiative?
Opportunities for recruitment of potential projects (via ERDF and LEP regional consortia)
Curriculum content for summer schools (via LEP / HEI members and any Young Report programmes)
Linkages to institutional facilities such as incubators, mentors, courses, funding
Discussions through Kelly Smith and Keith Burnley (CEO of NCEE)
Funding collaboration / opportunities through ERDF / LEPs, NCEE, the ‘IDEA Award
Linkages to networks such as
The National Association of College and University Entrepreneurship (NACUE)
Graduate Entrepreneurship
Enterprise Educators
maybe AGCAS(?)
NCEE themselves

AUA 2014 Conference Business Intelligence Workshop

This week I, along with my colleagues Jonathan Waller, Teresa Tocewicz and Adam Hiles delivered a workshop on Business Intelligence in Higher Education. We offered to write up the findings for delegates and this is it….

Thirty Five delegates from institutions and agencies associated with further and higher education were asked to consider three questions and to write responses (as many as they wish) from their individual perspectives on ‘Post-It Notes’. These Notes were then stuck to the relevant section of the large piece of flipchart paper provided to each table and on which they had previously been asked to draw a giant ‘H’.


Delegates were asked to consider each of these questions in the order shown below and were given 10 minutes for each one:

How effective BI currently helps you in your role, or How you believe it could and should? (“the desired state”)
What organisational, or other, factors are preventing your institutions from delivering the kind of benefits previously surfaced? (“the barriers”)
What needs to happen within your institution to overcome the issues that are holding you back and preventing you from achieving the successful vision of BI you have articulated? (“ideas generation”)

Following completion of the 3rd ‘ideas generation’ exercise. Each delegate was given three ‘sticky dots’ and given five minutes to read all the ideas that had been suggested by other members of their group and to ‘vote’ for the one, or ones, which they felt had the most merit. All three votes/dots could be allocated to one idea, or spread around multiple ideas, based on their own strength of feeling for a particular idea(s).


Resources from Jisc to help with BI when back in the office

Slides from the Session

Keeping in touch
Subscribe to the Jisc / HESA BI Project Jiscmail list to receive updates from the team. We’ll set up a blog site soon and announce it there

The rest of this document is a transcription of each table’s Post it Notes and votes. As promised, this is now available to those who took part and other interested parties as a record of the discussions and views of those present and will also be considered by Jisc and HESA as part of the preparations for the new BI National Shared Service that is currently being planned.


Table 1

 The desired state  The barriers  Ideas generation
Share milestones through dashboards
Define base data 
Very powerful systems
Fire people up to make decisions
Accurate data
Informed decision making
Clear limitations
 User training
Multiple systems
Data ownership
No end user consultation
Time and resources
Part of staff role?
Clear objectives
Engagement from all levels
Lead from executive

Table 2

 The desired state  The barriers  Ideas generation
Provide data that academics recognise and trust
Time saving in long run
GIves consistent info and doesn;t make assumptions about what you need
Accurate data that can be manipulated to repurpose
Effectively displays results, simpl dashboards
Properly resourced planning team
Staff training
Easy to access and use the basics
For everyone – staff, students, other stakeholders
Timeliness of information

Inconsistent interpretation
Cost and resource issues
Intelligence to understand systems and results
Data dispersed in different systems
Politics of access to certain data
Cost of a reporting tool
Lack of flexibility
Understanding managers
Lack of commitment 
Commitment from senior managers and resources
Support and money for capacity and development
Collaborative working across whole organisation
Technical ability to convert existing data into accessible format by a central system

Table 3

 The desired state  The barriers  Ideas generation
Team to provide and clean and monitor data
Access to research reports
Access to performance data
Quickly find detailed complex information
Mapping research income and student numbers year on year
Benchmarking against competitor university departments
Understanding departmental performance against plans
Corporate student satisfaction reports (KIS and NSS)

Not knowing what data is available to use or where to get it from
Lack of consultation with end users
Different databases produce different statistics
Too much time spent in populating reports
Glacial decision making processes
Lack of access to staff members, often restricted to senior managers
Planning department slow to produce information
Multiple dashboards unconnected
Accuracy of data
Lack of communication
Access to planning tools on several levels; senior management, faculty, school, department
Willingness to change and move forward
Planners to communicate what data is available and from where
Guidance as to which statistics should be monitored
Integrated systems
Better training
Better knowledge of existing systems and capabilities 

Table 4

 The desired state  The barriers  Ideas generation
Student performance identifying areas for development
Student demographics
User friendly to all staff
Staff information
Visualisation of data
Quick retrieval
Organise data / decisions made
Consistency across the organisation
Partnership making
Well funded
One click results
Drill downable
Easy access
Identifes student performance and programme, school and institutional level and identify trends

System restrictions
Lack of systems knowledge
Handling non digitised information
Definition of progression and retention
Inconsistency between programmes
Departments competing against each other
Too many systems not connecting

Management support
IT support
One vision of data needs
redesign of infrastructure
Sharing of knowledge
Data quality management
Consistency of definitions
Real time simple reporting 

Table 5

 The desired state  The barriers  Ideas generation
Greater initial cost outline diminishing as efficiencies occur
One repository for data vs multiple spreadsheets
Helps to improve processes – helps to improve planning / designing
Gives only relevant information i.e. no extras
Customisable – access all fields for user generated reporting
Make decisions on which grant giving bodies to approach for research income
Surfaces data to help with wider business planning
More scope for visualisation
How close are we to reaching targets
Live data
Make decisions on which industry sectors to approach for collaborations
Insight into tracking of deliverables
Mapping student conversion rates from enquiries to registrations
Understanding distinction between data at he micro (departmental) level and macro (institutional)
Benchmarks against previous years

Individuals control on data note easily relinquished
Cost of data systems
Lack of connection between planners / analysts and rest of institution
Time delay in data
People don;t understand how important BI is to their role
Inaccurate and old data
Not sure who to approach for the relevant data
Time lag on data
No synergy between existing data systems
Poor interpretation of data, not understanding the business
No support for collecting and analysing data

Better relationships between planners and users of data
Consult the end users not assume what is needed
Thorough training
Sharing of data and collaboration across stye sector
Exploring how BI is related to wider horizon scanning by Jisc
Central data warehouse 

2014 EUNIS BI Conference Discussion Session

The conference so far has been entirely plenary lecture based. I think we’re all looking forward to some new formats. First up we have an expert led discussion session. Our panel comprises Ora Fish, Stefano Rizzi, Bodo Rieger, Elsa Cardoso. Of the four I’ve managed to make contact with three regarding the work Jisc and HESA have planned on that national business intelligence service for the UK.

The panel are to comment on the following;

1. Critical Success Factors for BI in HE
2. Vision for BI in the next 5 – 10 years
3. Recommendations and expectations for EUNIS Services

My own comments are marked >

1. CSFs for BI in HE
Ora Fish – The CSF is down to the individuals involved in the initiative; their energy, adaptability, relationships and knowledge.
> Nice one Ora – capability of the team, leadership and their efficacy is clearly key. So what attributes does a successful BI service implementation require? What distinguishes this from other projects? Presumably quite a lot as this bridges the divide between IT and Business leaders, tackles cultural issues of data use, touches on records management and attempts to translate data into knowledge palatable to wide range of roles.

Hans Pongratz – agile systems and the business value they bring, how does it meet the needs of consumers (students, lecturers, managers)

Alberto – the content of the data warehouse – look toward employability of graduates as this is your final product
> absolutely true, but attributing graduate employability to a BI implementation seems a little on the tenuous side. Maybe here we’re touching on what are the data sources to assist in predicting employability, providing actionable insights and promoting the opportunity for people to take the actions. I quite like this as an alternative to analytics to predict success at University.

Elsa – People, strategy, technology and processes are the four areas. Ora covered people, map to institutional strategy, technologies should map to architecture, enhance and embrace processes to smooth the way

> Can’t faulty that as a response! From the floor a note of a Key Failure Factor being over reliance on a single person who became so integral the implementation became entirely reliant.

Steffano Rizzi – the importance of a functioning BICC and its role in data cleanliness and quality
> Definitely required capability but the BICC seems to me an ethereal entity comprising many different capabilities to smooth the way to BI uptake.

Ora Fish – The data warehouse is the key to success. Other system aspects can come and go.
> Isn’t that the case – the most difficult things are often a) getting your data (and processes) in order b) cultural change and people. Technologies merely enhance.

2. Next 5 – 10 years
A growth in demand and supply of data scientists capable of providing analytical services
> but also incorporation of data literacies in existing roles across the institution including senior managers
From the floor –
The UK Moodle community are looking (via University of London) at analytical insight across the 137 institutional Moodle instances. The panel are concerned about masking and security of data.
Analytical predictions for insight into likely employability is a capacity we might focus on as well as academic performance. Simply, based on student data exhaust across a range of indicators, what is the likelihood of good employability?
Ora Fish – Look to enhance the value we can bring to Universities, take the focus away from the technologies. More analytics, more ‘what if’ scenario solutions, better examples of Big Data value.
Stefano Rizzi – Delivery technologies (mobile), personalisation and recommendation services based on what others who ran this query did, collaborative business intelligence – a network of university consortia sharing data for BI
Incorporation of cross sector data to provide insight into future performance. In a nut shell analyse school, college and pre university data exhaust to provide insight into changes that could be made to enhance chance of success.
> Yeah yeah yeah…. Minority Report?! In the UK Schools already do a bit of this but pretty basically / badly. Do we really want to model success based on life experiences? Really?

And so my attendance at the EUNIS BI Taskforce 2014 event must conclude. I’ve a Eurostar to catch. It’s been a long old week. I left home on Monday and will be home tonight at 21.30. It’s Friday. I hope my presence here has helped others via the blogs. I hope the contacts I’ve forged are able to move to action with me and with Jisc and the Jisc / HESA BI Project.

It’s been emotional…