HESA for Planners
Objectives
• Identify best practice around quality assurance and
use of data
• Improve our understanding of check documentation
and how it can be utilised
• Introduce the downloadable files and how they can
be used
• Outline the future information landscape
• Better understand the IRIS outputs
• Learn from each other
“You never finish HESA, you abandon it”
Utilisation of time – ‘opportunity cost’
Efficient and cost-effective procedures
Best practice
Collaborative approach to data
Resource
Systems that work for the organisation
How to be good…
• Data ownership:
- Systems (storage issues)
- People
• Translation:
- From HEIs internal data language to an external data language
- The extent to which these match
- The variety of external languages that an HEI has to work with
• Documentation
- How, who, when
• Education
- Value of data and transparency
Evidence (or anecdote) from the KIS
• New requirement – high profile
• Data spread across institutions
–
–
–
–
–
No documentation
Little/no control
No standardisation/comparability
Variable quality
Variable approaches to storage
• …being assembled and managed in spreadsheets
Spreadsheets
• Often created by people who don’t understand
principles of sound data management
• Conflate data and algorithms
• Almost impossible to QA
• Spread and mutate like a virus
Search “Ray Panko spreadsheets”
The institutional perspective
HESA for planners
Wednesday, 15 May 2013
Alison Hartrey
Head of Planning
SOAS, University of London
HESPA – what we do
• Higher Education Strategic Planners Association
 provide a forum & network to discuss shared areas of interest
 provide a focus for planning input to statutory bodies etc.
 promote awareness and understanding of planning issues
 contribute to the professional development of planners
 link with planning & associated communities
11
HESPA - governance
• Executive drawn from across the sector
• includes representation from England, Scotland & Wales
• post-1992 and pre-1992 institutions
• various mission groups and independent HEIs
• working towards a full transition under the PHES umbrella
• flat rate membership fee per institution (2013/14)
• [email protected]
12
HESA – planning role at SOAS
• Direct responsibility for:
• Student Record
• Aggregate Offshore Record
• Institutional Profile Record
• Key Information Set
• Oversight of other HESA returns and ability to download check
documentation and data supply
• Produce NSS data for Ipsos MORI and supply DLHE data to the
University of London Careers Service
13
HIN target list and UCAS files
• Used when we are adapting our “as delivered” HESA extracts to
ensure the correct data is being extracted
• UCAS files (*J and level 3 qualifications expansion file) used as a
double-check against the qualifications records held in the student
records system
14
Check documentation
• Used when answering Minerva queries
• Used for basic data checks (cost centres, major source of tuition fees)
• Used across years for credibility checks
• Used for FOI responses
15
Data supply
• Used in a variety of institutional reporting to ensure consistency of
student population across years – in particular
• annual review & financial statements
• OFFA/widening participation reporting
• equality & diversity reporting
•
annual programme review updates
• FOI requests
…. but we could use it for a lot more
16
IRIS
• Another check on cost centres and student load (HESES recreation)
• Used for a wide variety of HEFCE checks and HEFCE funding
streams - RDP, SNC, TRAC(T), NSP
• Tendency to concentrate on just the reports needed at the time due to
concentration on the HESA Student Record and the time lines
17
HESA performance indicators in HE in the UK
• Underlying data from the HESA performance indicators is written
back into the core student record system:
LPN, state school, previous HE, entry qualifications,
SEC, region of domicile, young/mature, mode, level
• Used by Planning and the Widening Participation Team for onward
analysis and reporting
• Allows us to more easily compare whole population and special
interest groups as well as assess the impact of initiatives across a
time line
18
Embedding HESA into institutional
thinking – a rough guide
HESA for Planners, May 2013
John Busby, Deputy Director of Corporate Planning
The contention

Institutions that embed HESA and HESA requirements in
their thinking are more likely to:

submit higher quality data;

extract more value from HESA data to inform their
development (benchmarking, business intelligence, …).

be better place to respond where policy impact/funding is
derived from HESA data (HEFCE SNC, NSP …)

Thinking = people / resources, skills, policy, standards,
processes (and attitude?)

HESA = in the broadest sense (not just Student, and a
provider of information as well as a collector)
Signs of embedding

Senior Management awareness and interest (depth of
involvement in institutional sign off, reporting)

Close working between compilers of HESA Student, HESA
Staff and HESA Finance-HEBCIS, other exercises (e.g. KIS,
TRAC(T), OFFA, REF), Finance, Planning, HEFCE liaison

Widespread use of HEIDI, purchases of bespoke data by
institution or amongst groups of institutions to develop BI

HESA collections seen as a requirement but also an
opportunity (institutional reflection, comparative data)

Understanding permeates academic departments /
schools / faculties
A self-assessment

Last report to most senior governance body on trends
from HESA data? Extent of involvement in sign-off?
(Senior Management awareness)

Last time HESA Student and Staff compiler met, or met
with the TRAC(T) compiler, or REF team? (Close working)

Last time HESA data from HEIDI was warehoused, or a
bespoke data set specified and purchased? (Use of data)

Last time collection of a HESA field prompted institutional
reflection? (HESA as opportunity)

Last time a member of academic staff was helped to
understand HESA data? (Widespread knowledge)
Potential obstacles

Pace of change and team workloads

Institutional boundaries between key functional areas
(Registry, Planning, Finance, HR, QA function ...)

Disconnect between the business processes on which
data quality depend and those that compile returns and
interpret derived data

HESA compiler hidden in the ‘broom cupboard’?

Lack of senior management buy-in
What may help?

HESA integration or HESA co-ordination group (formal,
informal, self-help)

Consider physical location of key systems teams and
HESA compilers around Planning / Finance

Promote senior management awareness through:

Development of insightful business intelligence and tools
from HESA data (internal reflection and comparator
benchmarking)

Emphasise league table impact

Talk to your academic community about your data (social
science researchers, ...)
Examples of using HESA data (Student)
Examples of using HESA data (Student)
Examples of using HESA data
(benchmarking)
Some closing observations

Warehouse the HESA Student data supply tables from
the data collection system (helps with interpretation of
DDS, derived data exercises from HEFCE, FOIs)

Try the HEIDI API

Look forward to the new Cost Centre structure

Audits and auditors can be extremely useful

Ensure that there is joined up discussion in your
institution of the expanded Institutional Profile return

Please support HESPA!
Any questions?
John Busby, [email protected]
Discussion
• Discuss the following as a table:
• How good are you at HESA?
- Consider factors such as data ownership, documentation,
staffing, knowledge, resilience, training, systems, data
quality process – how extensive and sophisticated it is.
How often you use HESA data and what for and how is
the process and data managed/structured internally.
What are the barriers and how do you overcome them?
• Now consider and rate your own institution:
1st class
2:1
2:2
3rd
Unclassified
Using check documentation
What is check
documentation?
An Excel workbook
which displays the data
in a series of tables
Used by analysts at
HESA for quality
assurance
Available after any
successful test or full
commit
Why should I use it?
 Check documentation gives an overview of the submitted
data which can help identify potential issues
 Provides context to the queries raised by HESA
 The institution will be able to spot anomalies that HESA would
not
 Comparison feature also useful for later commits/test
commits to monitor changes
Check doc is one of many reports and is best used in conjunction
with other reports
Task
1. In your groups, or individually, complete check
documentation tasks 1-4
How can check doc be used?
• Use the check documentation guide produced by
HESA as a starting point
• Many of the items provide year on year comparisons:
Using check documentation
Different populations and groupings are used for each
item in the check documentation, including derived
fields
For 2012/13 the definitions sheet has moved to
the coding manual
Who are those 5 students??
• To get the most out of check documentation and
work out whether something is an error, you need to
identify the records behind the table
• To do this you can use Data Supply which contains
much of the raw data submitted alongside the
derived fields used by HESA
• Pivot tables can be used to recreate items and
identify particular cells
Identifying students:
• The HESA for Planners manual contains instructions
on recreating the populations and conditions used in
check documentation
• As an example we will recreate item 6a ‘Student
cohort analysis’….
Check doc changes for 2012/13
• Revised tolerances
• Items 1, 2 & 3 will now highlight year on year changes of
+/- 10%/50 students
• Item 11 will look at sector averages rather than just the
previous year
• Move to JACS3 and new cost centre coding frame
• New Fees tab
• More detailed breakdowns, summations and
percentage changes added to enable checking
Item 2a - Qualifications awarded
What is the difference between 2 and 2a?
Item 2
Item 2a
Shows the qualifications awarded to
students in the format that will be
published in the student volume
Displays the year on year differences
using the qualifiers field of XQLEV501
(including the split out of PGCE and Post
grad cert in Education.
Used to check that the qualification
awarded are, in the main, those which
they were aiming for
More consistent with the SFR variance
figures
Item 2a - Qualifications obtained by students on HE course by level of qualification obtained and mode of study (2012/13 and 2011/12)
Item 7 – Highest qualifications on entry
• Now split into 7a & 7b ‘proportion of highest
qualification on entry for first years’
• Subtotals also added to item 7a
Item 12 – average instance FTE
• This item has been
broken down further to
provide a three way
split of starters, leavers
and ‘others’.
• The different groups
may have very different
FTE values that impact
the average
Other reports
Minerva
…is the data query database operated
by HESA
• During data collection HESA (and
HEFCE) raise queries through Minerva
and institutions answer them
• These responses are then reviewed
and stored for future use by HESA
and the institution
Data
submitted
Quality
assurance
Queries
raised
Queries
resolved
Sign-off
Using Minerva for quality assurance
• Responses from previous years are retained in the
Issue Report
• Review targets set for the current year
• Queries raised by HESA are prioritised:
Contextual Intelligence
• At the request of the National Planners Group HESA
have formulated a ‘public’ version of Minerva
• Designed to give users of the data additional context
• HESA has published a query to Minerva to which HEIs
can add notes about their institution e.g. ‘we
recently opened a new department’
• HESA will not interact with what is added
• Will remain open throughout the year
• HESA will extract and send the information to
accompany data requests
Using downloadable files
Downloadable files
• Data Supply (Core, subject, cost centre, module and
qualifications on entry tables)
• NSS inclusion (person and subject) and exclusion files
• POPDLHE
• TQI/UNISTATS
• All available after every successful full and test
commit
Using downloadable files
•
-
The files should be utilised to:
Carryout additional DQ checks
Benchmarking
Planning/forecasting
Improve efficiency (recreating data from scratch
unnecessary)
League tables
• Student staff ratios by institution and cost centre
• First degree (full-time for Guardian) qualifiers by institution and league
table subject group
• Average total tariff scores on entry for first year, first degree students by
institution and league table subject group.
• Data is restricted to tariffable qualifications on entry (QUALENT3 = P41,
P42, P46, P47, P50, P51, P53, P62, P63, P64, P65, P68, P80, P91) (Times
applies ‘under 21’ restriction, Guardian applies ‘full-time’ restriction)
• Full-time, first degree, UK domiciled leavers by Institution, League table
subject, Activity
• Full-time, first degree, UK domiciled leavers entering employment
• Graduate employment/Non graduate employment/Unknown
• Positive destinations /Negative destinations
• Expenditure on academic departments (Guardian)
• Expenditure on academic services (Guardian, Times, CUG)
• Expenditure on staff and student facilities (Times, CUG)
Who cares? Why bother?
• …because you can’t afford not to care
• In what space does student recruitment
take place?
• Extended coverage…
• Subject based…
• Supply and demand are linked to
measures of quality
• Internationalisation of Higher Education
But be aware of the tail wagging the dog…
• Collectively we can become obsessed about specific
measures…
• …and dangerously on the wrong type of measures…
• …and instead of good (or accurate) ranking being
born out of doing your day to day business well, it
becomes fuelled by quick fixes
• Measurement culture tends to trade long-term value
for short-term gains…
• …this holds true in ‘data world’
But there are gains to be sought – both in terms of
quality and benchmarking
“Firstly, you need a team with the skills and motivation
to succeed.
Secondly, you need to understand what you want to
achieve.
Thirdly, you need to understand where you are now.
Then, understand ‘aggregation of marginal gains’. Put
simply….how small improvements in a number of
different aspects of what we do can have a huge impact
to the overall performance of the team.”
Dave Brailsford, Performance Director of British Cycling
But there are gains to be sought – both in terms of
quality and benchmarking
“Firstly, you need a team with the skills and motivation
to succeed.
Secondly, you need to understand what you want to
achieve.
Thirdly, you need to understand where you are now.
Then, understand ‘aggregation of marginal gains’. Put
simply….how small improvements in a number of
different aspects of what we do can have a huge impact
to the overall performance of the team.”
Dave Brailsford, Performance Director of British Cycling
Is there a correlation between this spread and league table positioning?
Before you begin…
• Remember the different populations
• Use derived fields (those beginning with an X!)
• The INSTCAMP field can be used to better analyse
and understand your data
Demonstration…
Performance indicators
• The PI tables (available from the HESA website) give
sector wide data on:
- Non-continuation rates
- Widening participation of under-represented groups
and those in receipt of DSA
- Research output
- Employment of leavers
• Included are benchmarks and definitions
DDS
• http://www.hesa.ac.uk/content/view/2664
Scenario planning
The impact of fee increases on applications
Total applications 05/06 – 11/12
heidi
60,000
50,000
40,000
The Nottingham Trent University
30,000
Sheffield Hallam University
20,000
10,000
0
04/05
05/06
06/07
07/08
08/09
09/10
10/11
11/12
% change of total applications
heidi
20.0
15.0
10.0
5.0
0.0
05/06
06/07
07/08
08/09
09/10
10/11
-5.0
-10.0
-15.0
-20.0
-25.0
The Nottingham Trent University
Sheffield Hallam University
11/12
Total applications by regions
heidi
300,000
250,000
200,000
Total Yorkshire & the Humber
150,000
Total East Midlands
100,000
50,000
0
04/05
05/06
06/07
07/08
08/09
09/10
10/11
11/12
NSS 05/6 results versus 06/7 applications heidi
Student:Staff ratios 2005/06
% change in applications by subject for sector
6
4
Nursing
2
Education
0
-2
-4
Creative arts
-6
-8
Law
-10
Mass communications
-12
Total applications % change 2006/07
2006/07 Subject profile
Nottingham Trent University
Check documentation
Sheffield Hallam University
Performance indicators 2006/07
2005/06 Building condition Total Non-residential - condition A & B
90
80
70
60
50
40
30
20
10
0
The Nottingham Trent University
Sheffield Hallam University
2005/06 Building condition Total Non-residential - condition A & B
What we ‘know’…
- Some subject areas are more price elastic than
others?
- Applicants take note of NSS?
- Condition of the estate matters to applicants?
- Some socio-economic groups are more affected by
fee increases than others
• Each of these variables might have a value of x
number of applicants
What we don’t know…
•
-
…but could scenario plan for…
Future government policy on HE funding
Social/cultural/economic impact
The power of perception
NSS 2011/12
Overall satisfaction
90
80
70
60
50
40
30
20
10
0
Nottingham Trent Unviersity
Sheffield Hallam University
Student:Staff ratios
2011/12 Subject profile
Nottingham Trent University
Check documentation
Sheffield Hallam University
Performance indicators 2011/12
• Was 2.3% difference, now 0.2%
100
90
80
70
60
50
40
30
20
10
0
2005/06 Building condition Total Non-Residential - Condition A & B
The Nottingham Trent University
2010/11 Building condition Total Non-Residential - Condition A
Sheffield Hallam University
heidi - % change of total applications
20.0
15.0
10.0
5.0
0.0
05/06
06/07
07/08
08/09
09/10
10/11
-5.0
-10.0
-15.0
-20.0
-25.0
The Nottingham Trent University
Sheffield Hallam University
11/12
heidi - % change of total applications
20.0
15.0
10.0
5.0
0.0
05/06
06/07
07/08
08/09
09/10
10/11
-5.0
-10.0
-15.0
-20.0
-25.0
The Nottingham Trent University
Sheffield Hallam University
11/12
12/13
Aggregation of marginal gains
The power of perception
• …can be influenced by the power of data
http://www.youtube.com/watch?v=ZWTJ_TPraLQ
• If you don’t like what they’re saying, change the
conversation…
• …what data are you using on the website and is it the
right data?
• …repositioning - find what you are good at and sell it
(both internally and externally)….
• …but never neglect what you need to improve
• http://www.ucl.ac.uk/about-ucl
`
Higher Education Information Database for Institutions
Estates
Destinations
Finance
HE-BCI
Student
Staff
Applications
Equality
National
student
survey
Derived
statistics
Available to all HEIs
heidi.hesa.ac.uk
Capabilities
Collate, crossreference and interpret
information
View, create and
export reports, charts
and custom tabulations
Generate aggregations,
ratios and percentages
Benchmark the
performance of your
institution against
others
Use heidi data within
your own business
intelligence software
Embed heidi reports
and charts into your
own website(s)
Adjust the year or the group from within the report
Notes and
definitions
provided
Sharing
• New to heidi
• Allows reports and
charts to be shared with
others
– Including non-heidi users
• Share by email using
the ‘send to’ link
• Use the HTML code to
embed reports or charts
into websites
Download to any version of PowerPoint
Adjust the year or
the groups from
within the chart
Use groups and
sub-groups to
compliment
analysis of charts
Charts
New Radar Chart
Application Programming Interface
• Does your HEI have it’s own data warehouse or BI
system?
• Use API to specify wanted heidi data and retrieve in a
usable format
• API is aimed at users familiar with writing and
understand programming code. HESA can provide
support to colleagues involved with API at your
institution
The future
Re-designed
DLHE data set
Federated
user accounts
Benchmarking
functionality
We are always keen to
hear feedback, especially
ideas and suggestions for
future release of heidi.
Please send any
comments to
[email protected]
Sign up
heidi account
• Contact your Local
Administrator for access to
heidi
– Expert account allows
access to all features
– Standard account allows
access on a view mode
[email protected]
JISC
• Mailing service which allows
heidi users to make new
contacts, ask questions and
share knowledge and best
practice
www.jiscmail.ac.uk
Welcome slide
HESA for Planners
(Student Record) Seminar
Anthea Beresford – Data Assurance Consultant, HEFCE
May 2013
HEFCE’s Data Assurance Team
activity April 2013 to March 2014
The aim of this session is to advise you of:
• areas of HEFCE’s Data Assurance Team’s coverage from April 2013
to March 2014.
Data assurance activity of the
Data Assurance Team
• team of 3, supplemented by a consultant;
• we are part of the overall data assurance framework;
• annual audit plan agreed by our Funding Round Process Board
(internal Executive oversight) and our Audit Committee to which we
report regularly and provide an annual report on audit outcomes;
• ever changing activity, for example, as funding rules change and new
areas become important;
• interested in both funding and non-funding issues with data.
Core roles of the Data Assurance
Team
3 distinct types of activity:
• data audit;
• data verification;
• data reconciliation.
Areas identified for attention
from April 2013 to March 2014
• Student funding data work:
•
HESA student data verification work pre-sign-off;
•
HESES verification work pre-sign-off;
•
2011-12 outturn review of FT UG HEFCE-funded student non-completion rates.
• Research Funding data work:
•
Research income from Charities;
•
Research income from Business;
•
Research HESA student data exploratory work.
• Key Information Set (KIS) 2013/14
• Destination of Leavers from Higher Education (DLHE) 2011/12
Areas identified for attention
from April 2013 to March 2014
(cont.)
• National Scholarship Programme (NSP)
• 2011-12 Funding and Monitoring Data (FAMD) (reconciliation)
exercise
• BIS Service Level Agreement work:
•
Access to Learning Fund (ALF).
• Higher Education Business and Community Interaction Survey (HEBCIS)
• Student Number Control (SNC)
• Equivalent and Lower Qualifications (ELQ)
Data audit – established work
• 2011-12 outturn review of FT UG HEFCE-funded student noncompletion rates:
•
desk based review of a 5% random sample of FT UG HEFCE-funded students.
• National Scholarship Programme (NSP):
•
desk based request for explanations of differences between HESES11, HESA
2011-12 and HESES12 new entrant student numbers.
• Research income from Charities and Business; Key Information Set
(KIS) 2013/14; Destination of Leavers from Higher Education
(DLHE) 2011/12; Access to Learning Fund (ALF):
•
Pre-audit visit review of data; on-site visit; post visit follow-up; issue of audit
report with recommendations; completed action plan for approval; closure
of audit; implementation of funding adjustments following the Appeals
process, where relevant.
Data audit – established work
• Current audit programmes can be found at:
http://www.hefce.ac.uk/whatwedo/invest/institns/funddataaudit/dataaudit/
• Current audit reports can also be at that link. Note the new KIS
2012/13 report.
Data audit – developmental work
• Research HESA student data exploratory work; Higher
Education Business and Community Interaction Survey (HEBCIS); Student Number Control (SNC) and Equivalent and
Lower Qualifications (ELQ):
•
Pre-audit visit review of data; on-site visit; post visit follow-up; issue of audit
report with recommendations; completed action plan for approval; closure
of audit; implementation of funding adjustments following the Appeals
process, where relevant.
Data verification
• HESA student data verification work pre-sign-off:
•
Desk based;
•
Working in conjunction with HESA;
•
Querying institutions on their data during the student data collection period
to assist institutions in identifying potential data issues for correction before
sign-off;
•
We will publish guidance nearer the time at:
http://www.hefce.ac.uk/whatwedo/invest/institns/funddataaudit/dataverifi
cation/
• HESES verification work pre-sign-off:
•
Desk based;
•
Working with institutions between initial submission and sign-off, obtaining
explanations for data differences or changes to data.
Data reconciliation
• Reconciliation between HESES11 and HESES11 re-creation based
on HESA 2011-12 data:
•
Desk based;
•
Thresholds for selection;
•
2 stage process this year due to students with undetermined completion
status (FUNDCOMP=3). The ‘Completion Status Survey’ is currently
underway where we are asking institutions to update their completion
status information for those who were returned as FUNDCOMP=3 in their
2011-12 return. The deadline for sign-off for this is 19 July 2013. We have
therefore selected institutions who currently break the selection criteria
thresholds. All institutions will be looked at again following submission of
the Completion Status Survey;
•
Gain explanations of differences;
•
Action plan and amendment of data as necessary;
•
Formal sign-off by institution;
•
Implementation of any funding adjustment following an Appeals process.
Data reconciliation (cont.)
• The link to guidance on our website concerning this area of
activity can be found at:
http://www.hefce.ac.uk/whatwedo/reg/assurance/datareconciliations/
Finally….
Any questions?
Thank you for listening
[email protected]
The HE information landscape
Update
Recommendations to RPG
• Governance for data and information exchange
across the sector
• Development of a common data language
– Data model, lexicon, thesaurus
• Inventory of data collections
• Specific data standards work
– JACS
– Unique Learner Number
2. Data model, lexicon and thesaurus
• Review of existing collections/definitions – the as is
• Better understanding of differences/similarities
– In definitions
– In terminology
• Coming from both angles:
– What are collectors asking for?
– What are institutions supplying?
• To inform future standardisation and data sharing
discussion
• Deliverables:
– Data model, lexicon and thesaurus
– Maintenance plan
3. Inventory of data collections
•
•
•
•
HEBRG survey identified 550 lines of reporting
Very little detail (width)
Is it complete? (length)
We need a solid understanding of the current burden
– To help HEIs become more joined up in their reporting
– To challenge data collectors to reduce duplication
• Deliverables:
– Database of collections
– Maintenance plan
4a JACS development
• Problems:
– JACS could have far broader use
– Current structure has run out of space
• Analysis of requirements
• Exploration of coding options
• Deliverable:
– Road map for future development
4b ULN implementation
• ULN widely accepted as a Good Thing
– Reducing burden by replacing existing IDs
– Adding value through better data linking/sharing
• What are the real barriers to adoption?
• What would it take to resolve these issues?
• Deliverable
– An assessment of where we currently are with ULN
– Commitment to a roadmap?
Governance?
• What will it do?
• What authority does it have to progress actions?
• How will the work be delivered and coordinated?
Proposal
•
•
•
•
A programme of work…
…made up of specific projects…
…overseen by a Programme Board…
…and reporting to a Sponsoring Group
• Utilising best practice from Managing Successful
Programmes
Sponsoring group
Chair of the Programme board
Programme board
Programme
Management Office
SRO/Programme Director
Project
A
Project
B
Project
C
RPG
Chair of the Programme board
Programme board
Programme
Management Office
SRO/Programme Director
Project
A
Project
B
Project
C
RPG
Chair of the Programme board
Programme board
Programme
Management Office
SRO/Programme Director
Project
A
Project
B
Project
C
www.hediip.ac.uk
@hediip
HEDIIP
• Enhance the arrangements for the collection, sharing and
dissemination of data and information
• Programme management office based at HESA
• Publishing and maintaining the inventory of data
collections
• Carry forward the established projects
– Common data language
– Replacement for JACS
– Implementation of the ULN
• Other strategic developments
Keep in touch
If you require additional training help, including
bespoke visits to your institution, get in touch
with the training department…
w: www.hesa.ac.uk/training
e: [email protected]
t:
01242 211472
Follow us on Twitter: @HESATraining
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