Jisc and HESA presentation on a national business intelligence service and research and development project using an agile data analysis model across UK University planning departments
5. Heidi Plus
A new service offering;
Improved data content and functionality (new data
warehouse to optimise utility and processing speed)
Delivery of data sets through commercially-available data
explorer tool
New visualisations and dashboards
New training programme and support materials
Application programming Interface (API) retained for those
using own BI and analytics systems
6. More disaggregated (but still anonymised) student and staff
data
New approach developed to ensure Data Protection
compliance based on advice of top Data Protection barrister
Comprises:
framework of organisational and user agreements
new Data Protection training programme
three levels of access permission plus new Lead Contact
role
Access to more detailed and flexible data
7. Beta 1 release - 9 organisations participated; ended on 4
September
Beta 2 release – underway now, 25 organisations
participating, ending 6 November.
Production release planned for:
Monday 30 November
Production release to include range of data sets with others
being added up to April 2016
Current Heidi decommissioned November 2016
Development schedule
8. Data Protection webinar training being delivered to Lead Contacts
and optionally to Gold level users
Lead Contact workshops planned for November and December in
London, Liverpool, Belfast and Edinburgh: hands-on training in using
the system
See www.hesa.ac.uk/seminars-2015 for details of the workshops
Training programme being planned for 2016
Wide range of training materials also under construction
Training sessions and materials
13. Jisc is the UK higher, further education
and skills sectors’ not-for-profit organisation
for digital services and solutions
Operate shared digital
infrastructure
and services
Provide trusted advice and
practical assistance for
universities, colleges and
learning providers
We…
Negotiate sector-wide deals
with IT vendors and
commercial publishers
13
14. A new national analytics research and development project.
Focuses on business questions that can’t be addressed through Heidi
Plus.
Support improvement in sector efficiency through the submission
and analysis of professional services cost benchmarking data
Technical; MS SQL Web & Business (elastic), DocumentDB (elastic),
Alteryx, Tableau server
Heidi Lab
15. As a: Outreach officer
When: Planning widening participation
recruitment
I want
to:
Better understand potential
student demographics
So I can: Achieve my targets in the most
efficient way
16. Data catalogue
Image: Anton Bielouso CC BY_SA 2.0Image: dankueck CC BY SA 2.0
Link to live Catalogue
Contribute a user story http://bit.ly/heidilab-user-stories
17. Efficiency and ModernisationTask Group Report (2011),
recommendations 1 & 2
Universities UK ‘Delivering Efficiency through effective
benchmarking’
Taxonomy of business processes and associated cost categories
New data capture and integration service
HEIs choose whether to engage, what level of taxonomy to use, which other
HEIs can see their data
HEIs share and benchmark costs in ‘cognate’ groups
Service pilots in February/March 2016
Professional Services Cost Benchmarking
20. Benefits of Agile
Stakeholder engagement
Transparency
Early delivery
Predictable costs and schedule
Allows for change
Focus on business value and on customers
Improves quality
23. 18 institutional Development team members (0.2 FTE HE BI / analyst /
data experts)
Joining 4 regional teams
4 senior BI / analyst / data advisors (Product owners) @ 7 days / team
1 for each team (names and titles)
4 Data / agile support staff (Development team members) @ 7 days /
team
1 for each team
4 Jisc facilitators (Scrum masters) @ 7 days / team
1 for each team
Heidi Lab winter teams
Overview of production and R&D services
Collaborators UK Higher education statistics agency (HESA) and Jisc
Heidi Plus – the service initially drawing on HESA data collections
Heidi Lab – the Research and development project identifying other data for mash up analysis and new production content
Dashboards and visualisations delivered via Tableau server to 180 Higher Education Providers and bodies
HESPA acting as consultants to the project – Giles and Jackie.
The new and improved…
We are a registered charity and champion the use of digital technologies in UK education and research. We develop shared services for our members, most recently by partnering with vendors. We provide trusted advice and support, reduces sector costs across shared network, digital content, IT services and procurement negotiations
A first attempt at large scale cross institutional collaboration to create new BI dashboards and analyses based on wide data collections for a national service to all UK education and research. A national project engaging with 70 experts from 60 HEPs to identify new business questions, likely data and undertake analysis for new service content
Our BI Experts group (comprises 60 strategic planners from 70 Universities) provided initial community design input. They tried to identify the decision making needs of a wider range of staff roles than currently use BI. They;
Came up with 49 user stories and merged them to 18
Mapped in some likely data sources where insights may lay
Devolve into agile R&D data prep, load and analysis teams (you)
Agile working to provide new service candidates as dashboards and visualisations
Successful outputs migrate to Heidi-Plus or new Jisc service
Key learning – people tend to know about high end, locked up data sets requiring data sharing agreements / subscriptions
We describe a 'library' of data for potential use in BI for education and research. While all data is available in the library, some is more difficult to access. We propose the distinctions of top shelf (requiring rungs of a ladder) and low shelf (easily picked)
Low shelf This data is publicly available but has other barriers to access; vast, distributed, no common vocabulary, complex, not designed to be combined with other data. Examples include demographic, geo-spatial, international, census The project seeks to ease access to these for BI purposes by cataloguing, preparing, linking, loading and making available for experimentation purposes
Top shelf This is data is either available by subscription or is locked to third party organisations who may provide their own analyses at cost. Examples include funding and regulatory, local councils, Government bodies, fees and admissions, careers and trajectory, current study data, staff, research, financial, estates or even institutions themselves The project seeks to unlock this for BI purposes by negotiating access on behalf of the wider sector, licensing, preparing, linking, loading and making available for experimentation purposes
The data catalogue is a living online resource in use by the analysis teams, developing
Agile is a development method that’s been around for some time.
It values the words in bold over those not
Development teams follow the arrows around the circle quickly – typically no more than 2 week increments over no more than 3 months
Three pillars of Agile; transparency, inspection, and adaptation
Emphasise ‘working products’ in our terms the dashboards and visualisations are the only thing the customer values and customer value is prime. Not project documentation, agile development or the data catalogue and data acquisitions.
Responding to change not following the plan. Make the plan fit the work so regular re-planning (monthly).
Three pillars Agile manifesto: from http://www.agilemanifesto.org/
Manifesto for Agile Software Development
10.45 – 11.00 Alicja
Sprints last 4 weeks, we have 3 of them
1 day F2F Planning, weekly scrum vurtually, Sprint review, retrospective and plan the next 4 week sprint
Refining and creating user stories
Identifying and acquiring data
Analysing to make minimum viable product (dashboards etc) to meet the Sprint Goal
Writing supporting narrative for safe onward use
Regularly communicating with your Sector Advisor (product owner) for feedback
Adjusting scope, defining, re-developing, and making frequent early releases until signed off.
Meet the team then – the red text is Agile jargon – it’s a barrier but we thought you’d like to see it in action so you can use it when back at base
Development team – all the skills to get the job done
Product owners - a proxy for the customer, responsible for the planning and prioritisation, offers steer
Data / agile support to smooth the way and fill in capacity
Scrum masters Agile coaches, protects the team from over committing, logs impediments and tries to solve them
Also have
Tableau and Alteryx support from Information Lab
Heidi lab toolset to get the work done
Data catalogue – a tool to help us explore and prioritise our data orders
Basecamp – a tool to help us work together
Other techs – G Drive, G Hangouts etc
Meet the team then – the red text is Agile jargon – it’s a barrier but we thought you’d like to see it in action so you can use it when back at base
Development team – all the skills to get the job done
Product owners - a proxy for the customer, responsible for the planning and prioritisation, offers steer
Data / agile support to smooth the way and fill in capacity
Scrum masters Agile coaches, protects the team from over committing, logs impediments and tries to solve them
Also have
Tableau and Alteryx support from Information Lab
Heidi lab toolset to get the work done
Data catalogue – a tool to help us explore and prioritise our data orders
Basecamp – a tool to help us work together
Other techs – G Drive, G Hangouts etc
Our national survey mirrors that run in the US via the Higher Education Data Warehouse Forum and Europe via EUNIS offering wider than UK benchmarking. 50 Universities shared their capacity with regard to a number of widely accepted facets of BI implementation. It gives an indication of national state of capability as well as identifying leaders and laggers for the service to match up and help. We will provide the full analysis in late October 2015.
Dimensions with 5 levels of maturity as Institutional Intelligence Team, Scope, Source Business Unit Role, range of data products in use (dashboards, scorecards, advanced analytics etc), User coverage as range of staff roles / groups (admin, teachers and researchers, students, alumni), User engagement (role of users in information supply chain - unaware, aware, drivers - active partners in the process), Data management (existence and effective application of data lifecycle management - data access, integration, retention, archive, Business Value (impact through effective use), Strategic support (formalisation of the institutional intelligence strategy)
We’d be happy to try and answer any questions. Anything we can’t answer directly today we’ll take back to project colleagues and come back to you.