1. Data Quality – Destinations of Leavers from Higher Education Fiona Sandford Lucy Burrows

2. Destinations of Graduates: key facts  We have to achieve a response rate of:  80% for UK-domiciled full time  50% for all other EU students  80% for Research Council funded students  We are not required (yet) to follow up non-EU graduates (but we do!)  Two collection periods – January and April  First by email ~ 40% response – then telephone

3. Quiz 1 The highest salaries last year were £500,000 and £270,000. Which courses? What are they doing?  £500,000 MSc Human Rights  £270,000 BSc International Relations  Advising Hedge Funds on emerging markets  Catwalk and Campaign Model (who deferred her job offer from I-Bank for a year)

4. Destinations of Graduates: league tables Based only on UK first degree leavers – 592 graduates Graduate prospects = (n graduates in ‘graduate level work + n graduates in full time study/total replies) So ‘graduate level’ work is critical.

5. Coding Quiz  Trader for Madison Tyler  Assistant to Chief Executive Civitas  Sales trainee Ondra a. Market trader b. Share dealer c. Financial Analyst a. Personal Assistant b. Executive Assistant c. Other d. (Social Science Researcher) e. Sales related occupation f. Other g. (Financial Analyst)

6. “ Believe nothing, no matter where you read it, or who said it, no matter if I have said it, unless it agrees with your own reason and your own common sense.” Prince Gautama Siddharta, the founder of Buddhism, 563-483 B.C.

7. Our data checks  Timescales  Set in stone,~6 months after they graduate with a defined date ‘what were you doing on…’  Method  All responses checked for inconsistencies, logged to monitor response rates. Running checks on n responses per course, and unemployment status. All those reporting unemployed are followed up by a careers adviser  Coding and Inputting  All coding done by careers advisers, for their departments. Coding seminars run regularly (ish)  Returning data to HESA  Amending / checking contradictory details

8. Standard methodology for data generation Good collaborative effort across the School Standard checking criteria/documentary guidance Pretty sound Checks by senior staff 8/10 Single point of failure x Too reliant on one person Sufficient statistical trainingFull use of LSE Excel training Good clarification of responsibility of data providers and users ? Room for improvement Data treated as part of standard management information yes Sufficient appreciation of “political” dimension of data ? Needs constant reinforcing

9. Good data costs  DLHE = 51MSLs for a Band 6  + ~ £6500 for student callers  + 47 * 2.5 hours evening shifts of supervision by members of team.  + hours of coding by Careers Advisers (band 7)  + hours of time from ARD

10. Three most important things  All staff understand the importance of the ‘political’ nature of the data  Common sense!  Data quality relies on good base data (and, for us, good contact information)

11. Finally..  DLHE return only as good as SITS data  We rely (heavily) on accurate contact information using LFY and Advance – any help from departments MOST gratefully received!  LSE post graduate internship scheme helped last year to get unemployment under 7% (beating Imperial for the first time) Please take more interns next year!!