Universities' HR Benchmarking Program Central Queensland University

Transcription

1 Benchmarking Program 2010 HR Performance Indicators for Central Queensland compared with Australian Universities for the period Prepared by the Human Resources Department Queensland of Technology

2 COPYRIGHTS: Copyright Queensland of Technology (QUT) Program Team: Graham MacAulay, Jane Banney, Henry Wong, Michael Hounslow, Barbara Cilliers Published by Queensland of Technology (QUT) ABN QUT Human Resources Department, GPO Box 2434 Brisbane QLD 4001 AUSTRALIA. CONFIDENTIALITY & USE OF DATA: We are aware of the confidential nature of the data and information provided to us and stress that we appreciate and protect this. QUT will not under any circumstance disclose any specific information or data pertaining to your university to any third party without written consent or permission from your university. CONTENT & PUBLICATION: All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form, or by any means, electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher. While every care has been taken to ensure the accuracy of the information included in the publication, no warranty is given in respect thereof. Any request to reproduce material from this publication, in written or any other form, must be addressed to Queensland of Technology (QUT): HENRY WONG Senior HR Advisor (Business Development & External Relations) Human Resources Department Queensland of Technology (QUT) GPO Box 2434 Brisbane QLD 4001 AUSTRALIA CLIENT SERVICES & SUPPORT: Program & Administrative Enquiries: Henry Wong Technical Support & Enquiries: Michael Hounslow Or us on: hrbenchmarking@qut.edu.au Page 2 of 109

3 Section 1 - Introduction Table of Contents Introduction Changes for the 2010 Program What is Benchmarking? Medians, Means, Percentiles and Quartiles Section 2 - Summary of Results Key Findings Summary of Results Page 5 Page 6 Page 7 Page 9 Page 12 Page 15 Section 3 Program Results Workforce Profile Indigenous Staffing Female Participation HR Function Staffing Ratio Turnover Voluntary Employee Initiated Turnover Voluntary Initiated Turnover Involuntary Initiated Turnover Fixed Term Contract Expiration Recruitment Recruitment Rate Recruitment Source Applicant Interest Recruitment Days to Offer Recruitment Days to Start Unscheduled Absence Taken per Employee Academic Doctoral Qualifications Academic Promotion Rate Applications for Promotion Rate Academic Promotion Success Rate Honorary/Visiting Academics Age Profile Length of Service Employment Costs as a % of Revenue OH&S Page 20 Page 40 Page 42 Page 44 Page 45 Page 47 Page 49 Page 51 Page 53 Page 55 Page 57 Page 59 Page 61 Page 63 Page 65 Page 67 Page 69 Page 71 Page 73 Page 75 Page 76 Page 82 Page 88 Page 89 Section 4 Detailed Data Tables Detailed Data Tables Page 93 Section 5 Definitions Key Definitions List of Measures Page 107 Page 109 Page 3 of 109

4 Section 1 Introduction Understanding the program and report presentation Page 4 of 109

5 Benchmarking Program 2010 Introduction The Universities HR Benchmarking Program was established in 2003 as a result of collaboration between a number of Australian Universities who wanted to be able to compare and contrast human resource data with like institutions. The program has expanded substantially and in 2010 consists of 45 members from Australia, New Zealand, South Africa and Fiji. 42 of those members contributed data for this year s report. Members collate and submit information about their university, which is analysed and reported across a number of measures, drawing comparisons to the university sector as a whole or a defined sub-group of universities. This report contains results across 39 measures which fall into one of the following categories: Staff Profiles Academic Workforce Profile Turnover Absence Recruitment Efficiency and Effectiveness Age Length of Service Occupational Health and Safety Employment Costs The ability to draw comparisons relevant to each member s university can offer great insight into individual and sector-wide practices. Importantly, this data can add significant value through informing human resources-related strategy and policy decisions. Comparisons Each member will, as part of its membership, receive three reports. The first provides comparative results against the sector as a whole (ie all contributing members). The second provides comparative results against a specific sub-group of the sector (eg GO8, ATN and IRU). Members were asked to nominate the sub-group with which they wish to be compared when registering for the program. The third provides comprehensive data relating to age and length of service for employees. Each of these reports is identified clearly on the title page of the report, as well as the header of each page of the report. The number of members contributing to the results for a particular measure (the sample size) is also shown within the relevant report. Additional reports, comprising either a customised sub-group of universities or an existing formalised sector grouping, may be purchased. For further information, including costs, please contact Henry Wong, by phoning or ing hrbenchmarking@qut.edu.au. Page 5 of 109

6 Changes for the 2010 Program A number of changes have been made for the 2010 Benchmarking Program and the Definitions Manual. These changes are largely the result of feedback from and consultation with members of the program during CHANGES TO MEASURES Functional Staffing Ratios The Functional Staffing Ratios for Information Technology, Student Administration and Student Services have been retired after being trialled in HR Functional Ratio has been retained. The decision to retire these measures was made following a review which found that there were difficulties in collecting the data for a significant proportion of members and that the measures were often difficult to use as comparative data. Reporting of Staffing Measures Staffing measures will be reported as a percentage of total staff rather than as a ratio as it has been previously. This will make comparisons and analysis clearer and assist in interpretion of the data. This will not affect data submissions as it will utilise current and historical submissions. Addition of Indigenous Measures A new measure for Indigenous staff has been added. Data will be collected separately for the Australian Sector and the New Zealand Sector. Members from outside these two counties will not be able to submit for these measures. Changes to OHS Measures Following a review of OHS measures by a working party (which included dedicated sector OHS practitioners) one new OHS measure has been added and an existing one altered. We are now reporting on Compensation Costs as a percentage of Employment Costs and have altered the Incidence Rate to use headcount rather than FTE. The latter change will not have any impact on the collection of data. DATA COLLECTION TIMING Number of years collected To increase the relevance of our trend data, the number of years for which data is reported will increase to five years from 2010 onwards. Page 6 of 109

7 What is Benchmarking? Put simply, benchmarking provides an opportunity to 'improve ourselves by learning from others'. Benchmarking begins with regularly comparing aspects of performance (functions or processes) with identified best practitioners or with a peer group defined for the purposes of comparison. The ability to make these comparisons assists an organisation to develop plans on how to make improvements or adopt best practice, thereby improving some aspect of performance. The Program Report provides data across a wide range of measures and includes percentile rank information, trend data (ie data spanning a number of years) and a detailed breakdown of your university s data compared with the sector/sub-group. This information will enable you to: Understand your university s workforce situation both current and recent past; Understand the sector s (/sub-group s) workforce situation, both current and recent past; Draw comparisons between your results and those of the sector or relevant sub-group; and Identify areas of interest and consider appropriate responses to improve performance. As part of the Program, QUT hosts an annual Benchmarking Conference. The conference aims to supplement the Report by: Reviewing the process and results of the Program; Sharing relevant HR strategic success stories, including workforce management strategies; Exploring workforce practices and university specific case studies in workforce planning; Learning about best practice in workforce management, and Providing valuable networking opportunities for HR practitioners. What is Best Practice? Best practice is the process of seeking what is considered the most effective or efficient way of performing certain processes or functions. Although benchmarking does not in itself identify best practice, it helps members understand areas where they have comparatively strong results, versus those areas in which they have comparatively weak results. The Program s annual Conference endeavours to identify and share HR best practice, both within and external to the sector. The Conference and the Program Wiki provide opportunities for members to collaborate, share ideas and to discuss various aspects of human resources processes and strategies. Important Considerations When viewing and sharing the results in this report, it is important to note the following points: 1. Where results are not displayed for a measure or specific breakdowns (ie classification level or gender split), data was not available to allow this calculation to be made. This may be the numerator and/or the denominator that is used in the calculation. 2. Where data has been entered for some, but not all classification groupings (ie general, academic or senior staff sections), a total result will not be calculated. This could affect a number of measures; however, one of the more likely measures that this would affect is Unscheduled Absence. 3. In the case of median age or length of service measures, where there were no occurrences for the period for the, no results will be displayed. 4. For Functional Staffing Ratios, results will only appear if the member has submitted data for both the specific function and FTE Including Casuals. 5. Members may note differences between current and previous years publications when comparing trend results. As new members submit data for previous years, and continuing members add or modify previous years data, the trend data is likely to change between publications. Page 7 of 109

8 Making Sense of Data Trends All measures in the Reports show trends across five years. Analysing the data over a period of time can give greater meaning to the results. Aberrations may be more easily identified and interpreted and impacts from internal strategies and the external environment may be evidenced. A useful example of interpreting trend data lies in the Applicant Interest measure. The recent trend shows a decrease in the average number of applications per advertised vacancy. This may be attributed largely to a tightening labour market over that period. In this particular context, a stable trend for your university would be a positive result, because despite labour market conditions and sector trends, your university s average number of applications did not decrease. The value in Sector Sub-Group reports Reporting against a defined sector sub-group may be particularly useful. The ability to narrow comparisons to a like cohort of universities may give even greater relevance and validity to the results. Currently, the Program defines six sub-groups: Group of Eight (GO8) Australian Technology Network (ATN) Regional Universities New Generation Universities Innovative Research Universities New Zealand Universities Members were asked to nominate the sub-group with which they wish to be compared when registering for the program. Members may request a customised sub-group report. You may wish, for example, to consider a relevant peer group comparison according to: Market positioning (eg. distance education providers, industry-focussed universities, researchuniversities); Geographical location (eg. by state, regional universities, city-based universities); or background / history / culture. For further information on customised reports, including conditions and costs, please contact Henry Wong, by phoning or ing hrbenchmarking@qut.edu.au. Other sources of information Using multiple sources of data can add value to your benchmarking information. Certain results may prompt your university to obtain more detailed internal data to better understand or further explore an area of interest. Governing bodies provide very useful information. Government departments such as DEEWR (Australia), Ministry of Education (New Zealand) and Department of Education (South Africa) provide a range of statistics that are publicly available on a number of staff-related areas such as diversity, qualifications and age. This information can be a useful complement to the Universities HR Benchmarking Program, depending on your area of interest. Other community statistics can also be used to complement your analysis. For example, unemployment rates and age demographics are readily available from government sources and may be used in conjunction with the Program results where further analysis is required. Page 8 of 109

9 Medians, Means, Percentiles and Quartiles What they mean and when to use them Many readers will be familiar with the basic statistical terms used in the reports, but not fully understand how or when to use the terms. This section describes the use of these terms. Measures of Central Tendency: Median versus Mean The terms median and mean are both used to describe the central or typical number, but are not the same thing, and can have distinctly different values. Many of us more commonly speak of means (or averages), but the median figure can prove to be much more valuable in certain circumstances. The Program reports use the median for the reasons explained below. The mean (or Average ) is calculated as follows: Mean= Sum of all data values Example: a + b + c Number of all data values 3 The mean is easy to calculate and works well for lists that are simply combined. The problem with using the mean is that outliers (or extreme values) can have a significant affect on the result. The median is the item in the middle of a sorted list'. If there are two middle numbers (even number of items), simply take their average. Example Look at the following set of numbers 1, 2, 3, 4, 100 The mean is 22, ie. ( )/5 The median is 3, ie (same number of data values on either side) Although the mean of this set is 22, 22 doesn t really represent the distribution. We re more likely to get a number closer to 3 than to 22. The mean has been pulled up by 100, an outlier. The median solves this problem by taking the number in the middle of a sorted list. The significant advantage of using a median is that it handles outliers well and is often the most accurate representation of a group. Figures like housing prices and incomes are often given in terms of the median, since we want an idea of the 'middle of the pack. One person earning a million extra one year would increase the average income, but it isn t relevant to how a regular person s wage changed. We aren t interested in adding incomes or house prices together we just want to find the middle one. Spread of Results: Quartiles and Percentiles While the measures of central tendency (median and mean) provide the average values, the spread or range of results can paint a very useful picture. The maximum and minimum give you the range of results for the population but they do not tell the full story. A percentile is a measure that tells us what percent of the total frequency scored at or below that measure. Percentiles are useful for giving the relative standing of an individual result in a population. The percentiles used in the Report are: 100 (also the maximum) (also the median) (also the minimum) With the exception of the 10th and 90th percentiles, these form the boundaries of the quartiles. The 10th Page 9 of 109

10 and 90th percentiles are used to indicate where there are outliers or extreme values in the population. In the example below - Academic Total - the median or percentile is 7.2%. That means that of the 40 universities (as shown by the sample), 20 have a result higher than 7.2% and 20 have a lower rate. The percentile shows that there are 75% (30 members) with a result lower than 8.51%. Similarly, at the 90th percentile 90% (36 members) have a result less than 10.02% and 10% (4 members) have a result greater than that number. Quartile is another term referred to in percentile measure. The total of 100% is broken into four equal parts: 25%, 50%, 75% and 100%. Quartiles are essentially ranking mechanisms. While the quartiles can be shown numerically in a table as shown above, a graphical representation can show trends quickly and easily as illustrated in the graph below. In the graph below, the blue square represents the member's results. From the graph we can conclude the following: the member is in the pink or red quartiles in each classification; the member tends to have results around the percentile; the range for the two central quartiles is small, meaning that there is little variation between the majority of members. This is supported when looking at the percentile tables, where the values of the 90th percentile and maximum, and the 10th percentile and the minimum are significant. This indicates that most members have a similar result with a small number of members with either very high or very low results. Page 10 of 109

11 Section 2 Summary of Results The key findings from the report with a summary table of the results Page 11 of 109

12 Key Findings Benchmarking Program 2010 Key Sector Findings The Workforce Profile in relation to Division to Faculty, General to Academic and Faculty Faculty General remained steady over the five year period with no apparent patterns emerging across the Sector. Fixed Term Contracts (total) increased by 8.5% over the five year reporting period (27.0% in % in 2009) and at 43.5% is significantly higher for academic staff compared to general staff (28.4%). Total Turnover across the sector decreased by 1.4% (18% in 2008) to 16.6% in the last 12 months also at its lowest since 2006 (19.0%). The Voluntary Employee Initiated Turnover rate (8.0%) decreased by 2.4% in 2009 and is at its recorded in the five year period. The Recruitment Rate for the sector, at 11.9% is the lowest recorded for the past 5 years with a decrease in the last 12 months from 16.3% in For general staff (13.2%), the recruitment rate decreased by 5.8% (19% in 2008) whilst there was a reduction in 3.3% for academic staff (13.6% in 2008 and 10.3% in 2009). Applicant Interest rates continued its upward trend from 10.5 applications per advertised position to 17.6 in The Sector experienced efficiencies for both Recruitment Days to Offer (51.7) and Recruitment start (84.5). Applications for Promotions continued to decrease over the past five years from 7.4% (2005) to 2009 across the sector. Employment cost as a % of revenue at 52.0% is at its lowest since 2005 (62.0%). Workforce Profile The Workforce Profile in relation to Division to Faculty, General to Academic and Faculty Academic to Faculty General has remained steady over the five year period with no apparent patterns emerging. Senior staff/mgt percentages showed a steady increase from 2005 (2.9%) to 2009 (3.6%) of total workforce excluding casuals. The overall proportion of Fixed Term Contracts increased by 8.4% over the five year period (27.5% in 2005 to 35.9% in 2009) and at 43.8% is significantly higher for academic staff compared to general staff (29%) for Similarly, Faculty Fixed Term Contracts increased by 10.6% over the past five years (32.0%- 42.6%). This is higher than the 3.3% growth over the same period for Divisions across the Sector (19.6% -22.9%). Fixed Term Contracts for faculties (42.6%) is significantly higher than for divisions (22.9%) across the sector. Most notable, is the consistently higher proportion of Fixed Term staff (FTE) for the academic level A (86.2%) category. A slight but steady increase of 2.2% in Part Time staff (FTE) is evident over the five year reporting period. The HEW 2 staff category represents the highest average of Part Time staff at 32.1% and the HEW 10 category, the lowest average at 6.6%. The overall Female Participation rate continued to rise from 52.3% to 54.3% over the past five years. Female Participation in senior staff/mgt levels mirrored this increase over the same five year period from an average of 32.4% in 2005 to a 35.6% participation rate in Similarly, the proportion of female academics also increased by 3.2% over the five year period from 39.8% in 2005 to 43.0% in Indigenous Staffing at 1.1% has shown an increase from 2005 (0.8%), however is slightly lower than the 2008 average of 1.3%. Page 12 of 109

13 Turnover Total Turnover decreased by 1.4% to 16.6% in the last 12 months and is also at its lowest since 2006 (19.0%) for the Sector. The turnover rate for academic level A continued its trend and at 33.6% is significantly higher than the rest of the classification levels across the Sector. The Voluntary Employee Initiated Turnover rate (8.0%) fell by 2.5% in 2009 and is at its lowest recorded in the five year period. Fixed Term Contract Expirations remained steady over the five year report period and only slightly increased in the last 12 months from 6.3% to 6.6%. Most notable is the consistently high rate of Fixed Term Contract expirations for the academic level A and at 21.8% (2009) is the highest rate recorded in the past 5 years. Unscheduled Absence rates (5.2%) stayed relatively steady across the sector over the five year period with a marginal increase of 0.1 in last 12 months. General staff averages were higher at 7.5 days per employee. Recruitment Applicant Interest Rates continued its upward trend from an average of 10.5 applications per advertised position in 2006 to 17.6 in 2009 and is also the highest recorded over the 5 year reporting period. The sector experienced efficiencies for both Recruitment Days to Offer (51.7) and Recruitment Days to Start (84.5). Academic levels D and E continued to record higher averages for Recruitment Days to Offer (100.9 days and days) and Recruitment Days to Start (164 days and 172.8) compared to the other classification levels across the sector. 41.5% of vacancies were filled from the internal workforce across the sector. This a slight increase of 0.6% from 2008 (40.9%). Internal recruitment for senior staff/management fell 9.5% from 2008 (43.3%) to 2009 (33.8%). The Recruitment Rate at 11.9% for the sector is the lowest recorded for the past 5 years with a 4.4% decrease in the last 12 months from 16.3% in For general staff (13.2%) the recruitment rate decreased by 5.8% (19% in 2008) whilst recruitment for academic staff decreased by 3.3% (13.6% in 2008 and 10.3% in 2009). A significant decrease in recruitment activity for the HEW level 1 is also notable from 19.5% to 5.2%. Academic Measures Doctoral Qualifications continued its steady upward trend from 58.2% in 2005 to 62.3% in The averages are highest for academic level E (89.0) and D (85.5%) and lowest for academic level A at 38.9%. Applications for Promotions continued to decrease over the past five years from 7.4% (2005) to 6.0% for 2009 across the Sector. The application rate for academic level E (8.2%) also decreased from 2008 (9.5%) but remains highest among the academic classifications for the sector. The overall Academic Promotion Success rate (70.7% in 2009 and 69.4% in 2008)) increased by 1.3% in the last 12 months and continued its steady increase since 2005 (63.7%). The Academic Promotion Success rate is highest for academic level B at 85%. The overall Academic Promotion rate decreased from 4.7% in 2005 and at 4.3%, for 2009, is the lowest rate recorded for the five year reporting period. The average proportion of Honorary/Visiting Academics continued an upward trend from 80.2 per 100 academics in 2005 to 89.3 in The Median Age of New Recruits decreased by 4.3 years from 41.2 in 2005 to 36.9 in Similarly, the Median Age of Separated staff decreased by 6.3 years from 46.7 years for 2005 to 40.4 years in Most notable is the median separation ages for academic level E (59.4), level D (57.0) and senior staff/mgt (55.2) which is higher compared to the other levels. The Median Length of Service of current staff, at 5.1 years, is the lowest since 2005 (6.2). Page 13 of 109

14 Employment Cost Employment cost as a % of total revenue at 52.0% is at its lowest since 2005 (62.0%). Occupational Health and Safety Average Time Lost (18.36 days) decreased in the last 12 months from (2008) whilst the OHS Incident Rate fluctuated between its lowest at 0.8% (2009) to 1.0 (2007) over the past five years. Compensation Cost as a percentage of Employment Cost (0.4%) remained relatively consistent over the past five years with the highest result recorded in 2005 at 0.5%. Page 14 of 109

15 Summary of Results Please refer to Section 3 - Program Results - for definitions of each measure. Workforce Profile Workforce Profile: by Employment Kind (Excluding Casuals) Central Queensland General Total % % % % Academic Total % % % % % Senior Staff/Mgt 4.41 % % 8.86 % 8.61 % Workforce Profile: by Employment Kind (Including Casuals) General Total % % % % 61.2 Academic Total % % % % % Senior Staff/Mgt 4.01 % 4.07 % 4.98 % 7.46 % 7.52 % Workforce Profile: by Faculty and Division (Excluding Casuals) Central Queensland Division - Total % % % % % Faculty - Total % % % % % Workforce Profile: by Faculty and Division (Including Casuals) Central Queensland Division - Total % % % % % Faculty - Total % % % % % Workforce Profile of Faculty: by Employment Kind (Excluding Casual) Central Queensland Faculty - General % % % % % Faculty - Academic % % % % % Workforce Profile of Faculty: by Employment Kind (Including Casual) Central Queensland Central Queensland Faculty - General % % % % Faculty - Academic % % % % AUS Average % % % % % % % % % % % 2.91 % 3.45 % 3.62 % AUS Average % % % % % % % % % % 2.35 % 2.48 % 2.51 % 2.99 % 3.2 AUS Average % % % % % % % % % % AUS Average % % % % % % % % AUS Average % % % % % % % % % % AUS Average % % % % % % % % Page 15 of 109

16 Summary of Results Workforce Profile: by Contract Type Central Queensland Workforce Profile: Composition by Contract Type (Fixed Term) % % Workforce Profile: Composition by Contract Type (Ongoing) % % Workforce Profile: by Employment Status Central Queensland Workforce Profile: Composition by Employment Status (Full Time) % % % Workforce Profile: Composition by Employment Status (Part Time) 9.34 % 9.99 % % Other Workforce Profile Measures Central Queensland Female Participation % % % % HR Function Staffing Ratio 3.71 % 2.91 % % 3.1 Indigenous Staffing (Aust) 1.55 % AUS Average % % % % % % % % AUS Average % % % % % % % % AUS Average % % % % % 1.91 % 1.87 % % 1.82 % 0.77 % 0.98 % 0.93 % 1.31 % 1.05 % Turnover Central Queensland Fixed Term Contract Expiration % 7.11 % 9.72 % 3.1 Involuntary Initiated Turnover 0.41 % 0.33 % 0.58 % 0.19 % 0.19 % Total Turnover % % % % Voluntary Employee Initiated Turnover 8.39 % % % % 6.29 % Voluntary Initiated Turnover 0.24 % 0.08 % 4.67 % % AUS Average 6.92 % 6.68 % 6.15 % 6.25 % % 0.71 % 0.49 % 0.43 % % % % % % 9.14 % 9.77 % % % 7.97 % 1.57 % 2.17 % 1.28 % 0.93 % 1.5 Absence Central Queensland Unscheduled Absence Taken per Employee AUS Average Page 16 of 109

17 Summary of Results Recruitment Central Queensland Applicant Interest Recruitment Days to Offer Recruitment Days to Start Recruitment Rate 8.39 % 9.03 % 6.82 % % % Recruitment Source % % % AUS Average % % % % % % % % % Academic Central Queensland Academic Promotion Rate 5.29 % 5.21 % 2.95 % 3.31 % 3.08 % Academic Promotions Success Rate % % % % Applications for Promotion Rate 7.81 % 5.73 % 6.78 % 6.63 % 5.54 % Doctoral Qualifications % % % % % Honorary/Visiting Academics 5.83 % 9.02 % % % % AUS Average 4.72 % 5.12 % 4.68 % 4.86 % 4.25 % % % % % % 7.39 % 7.39 % 6.54 % % % % % % % % % % % % Age Profile Central Queensland Age Profile < 25 Years of Age 2.86 % 7.43 % 6.33 % % Age Profile Years of Age 4.33 % 9.94 % 8.73 % 6.65 % 6.85 % Age Profile Years of Age % % % 9.47 % 7.26 % Age Profile Years of Age % % % % % Age Profile Years of Age % % % % % Age Profile Years of Age % % % % Age Profile Years of Age % % % % Age Profile Years of Age % % % 14.1 Age Profile Years of Age 4.24 % 5.76 % % 6.6 Age Profile 65 + Years of Age 0.78 % 2.14 % 2.55 % 1.53 % 2.63 % Median Age of New Recruits Median Age of Separated Staff AUS Average 3.27 % 3.21 % 3.16 % 3.21 % 3.27 % 8.49 % 8.57 % 8.71 % 8.69 % 9.18 % % % % % % % % % % % % % % % % % % % % % % % % % % % % % 5.71 % 6.05 % 6.36 % % 1.35 % 1.51 % 1.61 % % na na na na na na na na na na Page 17 of 109

18 Summary of Results Length of Service Profile Central Queensland LOS Profile < % 8.79 % 2.9 LOS Profile % % % LOS Profile % % 8.56 % LOS Profile % % % LOS Profile % % % LOS Profile % % LOS Profile % 3.01 % 3.84 % LOS Profile % 1.19 % 1.45 % LOS Profile % % Median LOS - Current Staff Median LOS - Separating Staff AUS Average % % % % % % % % % % % % % % % % % % % % % % % % % 9.72 % % 3.76 % 4.97 % 5.07 % 5.43 % 2.37 % 2.09 % % 2.22 % 1.89 % 2.02 % 2.47 % 2.46 % 2.37 % na na na na na na na na na na OHS Central Queensland Average Time Lost OH&S Compensation Costs as a percentage of Employment Costs 0.5 OH&S Incident Rate 0.98 % 1.09 % 0.88 % 0.93 % 0.48 % AUS Average % 0.39 % 0.32 % 0.32 % 0.39 % 0.93 % 0.81 % 0.95 % 0.77 % 0.78 % Employment Cost Central Queensland Employment Costs as a % of Revenue % % % % AUS Average % % % % Page 18 of 109

19 Section 3 Program Results The results of your compared with Australian Universities Page 19 of 109

20 Workforce Profile: Composition by Employment Kind (Excluding Casuals) DEFINITION Total Academic/General/Senior Staff FTE Total Staff FTE This measure compares the proportions of Academic and General staff (FTE) of the total staff FTE excluding casual staff. Results indicate the proportion of support/general staff appointed within the Faculties to provide support services to Academic staff. This support service is defined as decentralised service support as suppose to support services delivered by Divisional staff which is defined a centralised services. The result may be impacted by factors such as an increased need for service support as a result of the increase in research activities within faculties, realignment of staffing structures and specific university targets, centralisation of corporate and support functions, outsourcing of certain functions and service delivery differentiation. CQU results versus Australian Universities 2009 Quartiles and Range CQU results by Classification for % % % Academic Total General Total Senior Staff/Mgt General Total Academic Total Senior Staff/Mgt Top Quartile Third Quartile Second Quartile First Quartile - Min 10th 90th Max Avg Sample Academic Total % % % % % % % % % 36 Academic Total (M) % % % % % % % Academic Total (F) % % % % % % % % % 36 General Total % % % % % % % % % 36 General Total (M) % % % % % % % % % 36 General Total (F) % % % % % % % % 36 Senior Staff/Mgt 8.61 % 0.62 % 1.82 % 2.69 % 3.81 % 4.43 % % 3.62 % 36 Senior Staff/Mgt (M) % 0.85 % 2.67 % 4.03 % 5.44 % 6.93 % 8.26 % % 5.11 % 36 Senior Staff/Mgt (F) 6.18 % % 1.45 % 2.29 % 3.29 % % 2.37 % 36 Page 20 of 109

21 Workforce Profile: Composition by Employment Kind (Excluding Casuals) General Total (T) Academic Total (T) Senior Staff/Mgt (T) 9 % 8 % 7 % 6 % 5 % 4 % 3 % 2 % 1 % Page 21 of 109

22 Workforce Profile: Composition by Employment Kind (Including Casuals) DEFINITION Total Academic/General/Senior Staff FTE Total Staff FTE This measure compares the proportions of Academic and General staff (FTE) of the total staff FTE including casual staff. Results indicate the proportion of support/general staff appointed within the Faculties to provide support services to Academic staff. This support service is defined as decentralised service support as suppose to support services delivered by Divisional staff which is defined a centralised services. The result may be impacted by factors such as an increased need for service support as a result of the increase in research activities within faculties, realignment of staffing structures and specific university targets, centralisation of corporate and support functions, outsourcing of certain functions and service delivery differentiation. CQU results versus Australian Universities 2009 Quartiles and Range CQU results by Classification for % % Academic Total General Total Senior Staff/Mgt General Total Academic Total Senior Staff/Mgt Top Quartile Third Quartile Second Quartile First Quartile - Min 10th 90th Max Avg Sample Academic Total % % % % % % % % % 32 Academic Total (M) % % % % % % % 32 Academic Total (F) % % % % % % % % % 32 General Total % % % % % % 32 General Total (M) % % % % % % % General Total (F) % % % % % % % % % 32 Senior Staff/Mgt 7.52 % 0.68 % 1.89 % 2.46 % 3.35 % 4.02 % % Senior Staff/Mgt (M) % 0.95 % 2.91 % 3.54 % 4.75 % 5.91 % 7.04 % % 4.58 % 32 Senior Staff/Mgt (F) 5.18 % 0.44 % 0.83 % 1.37 % 2.11 % 2.67 % 4.49 % 5.18 % 2.09 % 32 Page 22 of 109

23 Workforce Profile: Composition by Employment Kind (Including Casuals) General Total (T) Academic Total (T) Senior Staff/Mgt (T) 8 % 7 % 6 % 5 % 4 % 3 % 2 % 1 % Page 23 of 109

24 Workforce Profile: Composition by Faculty and Division (Excluding Casuals) DEFINITION Total Faculty/Division Staff FTE Total Staff FTE This measure compares the proportions of Faculty and Division staff (FTE) of the total staff FTE excluding casual staff. This result indicates the proportion of centralised divisional support staff compared to staff appointed to deliver core business and decentralised support services within faculties. Factors that may impact on the result include centralisation of corporate support, outsourcing and service delivery differentiation. CQU results versus Australian Universities 2009 Quartiles and Range CQU results by Classification for % % Faculty - Total Division - Total Division - Total Faculty - Total Top Quartile Third Quartile Second Quartile First Quartile - Min 10th 90th Max Avg Sample Faculty - Total % % % % % % % 33 Faculty - Total (M) % % % % % % % % % 33 Faculty - Total (F) % % % % % % Division - Total % % % % % % % 33 Division - Total (M) % % % % % % % % % 33 Division - Total (F) % % % % % % Page 24 of 109

25 Workforce Profile: Composition by Faculty and Division (Excluding Casuals) Faculty - Total (T) Division - Total (T) Page 25 of 109

26 Workforce Profile: Composition by Faculty and Division (Including Casuals) DEFINITION Total Faculty/Division Staff FTE Total Staff FTE This measure compares the proportions of Faculty and Division staff (FTE) of the total staff FTE including casual staff. This result indicates the proportion of centralised divisional support staff compared to staff appointed to deliver core business and decentralised support services within faculties. Factors that may impact on the result include centralisation of corporate support, outsourcing and service delivery differentiation. CQU results versus Australian Universities 2009 Quartiles and Range CQU results by Classification for % % Faculty - Total Division - Total Division - Total Faculty - Total Top Quartile Third Quartile Second Quartile First Quartile - Min 10th 90th Max Avg Sample Faculty - Total % % % % % % % % % 31 Faculty - Total (M) % % % % % % % % 31 Faculty - Total (F) % % % % % % % 31 Division - Total % % % % % % % % % 31 Division - Total (M) % % % % % % % % 31 Division - Total (F) % % % % % % % 31 Page 26 of 109

27 Workforce Profile: Composition by Faculty and Division (Including Casuals) Faculty - Total (T) Division - Total (T) Page 27 of 109

28 Workforce Profile of Faculty: Composition by Employment Kind (Excluding Casuals) DEFINITION Faculty General/Academic Staff FTE Total Faculty Staff FTE This measure compares the proportions of Academic and General staff (FTE) of the total Faculty staff FTE excluding casual staff. Results indicate the proportion of support/general staff appointed within the Faculties to provide support services to Academic staff. This support service is defined as decentralised service support as suppose to support services delivered by Divisional staff which is defined a centralised services. The result may be impacted by factors such as an increased need for service support as a result of the increase in research activities within faculties, realignment of staffing structures and specific university targets, centralisation of corporate and support functions, outsourcing of certain functions and service delivery differentiation. CQU results versus Australian Universities 2009 Quartiles and Range CQU results by Classification for % Faculty - General Faculty - Academic Top Quartile Third Quartile Second Quartile First Quartile % Faculty - General Faculty - Academic Min 10th 90th Max Avg Sample Faculty - Academic % % % % % % % % 33 Faculty - Academic (M) % % % % % % 33 Faculty - Academic (F) % % % % % % % 33 Faculty - General % % % % % % % % 33 Faculty - General (M) % % % % % % 33 Faculty - General (F) % % % % % % % 33 Page 28 of 109

29 Workforce Profile of Faculty: Composition by Employment Kind (Excluding Casuals) Faculty - General (T) Faculty - Academic (T) Page 29 of 109

30 Workforce Profile of Faculty: Composition by Employment Kind (Including Casuals) DEFINITION Faculty General/Academic Staff FTE Total Faculty Staff FTE This measure compares the proportions of Academic and General staff (FTE) of the total Faculty staff FTE including casual staff. Results indicate the proportion of support/general staff appointed within the Faculties to provide support services to Academic staff. This support service is defined as decentralised service support as suppose to support services delivered by Divisional staff which is defined a centralised services. The result may be impacted by factors such as an increased need for service support as a result of the increase in research activities within faculties, realignment of staffing structures and specific university targets, centralisation of corporate and support functions, outsourcing of certain functions and service delivery differentiation. CQU results versus Australian Universities 2009 Quartiles and Range CQU results by Classification for % Faculty - General Faculty - Academic Top Quartile Third Quartile Second Quartile First Quartile % Faculty - General Faculty - Academic Min 10th 90th Max Avg Sample Faculty - Academic % % % % % % % % 30 Faculty - Academic (M) % % % % % % % 30 Faculty - Academic (F) % % % % % % % % % 30 Faculty - General % % % % % % % % 30 Faculty - General (M) % % % % % % % 30 Faculty - General (F) % % % % % % % % % 30 Page 30 of 109

31 Workforce Profile of Faculty: Composition by Employment Kind (Including Casuals) Faculty - General (T) Faculty - Academic (T) Page 31 of 109

32 DEFINITION Workforce Profile: Composition by Contract Type (Fixed Term) Number of Fixed Term Staff (FTE) Total Staff Count This measure describes the proportion of total staff (FTE) who are employed on a fixed term basis. The circumstances for engaging employees on a fixed term may include specific budget allocation for a particular project, additional assistance required to meet peak workloads, or replacing permanent employees who are absent from their substantive position. The rate of fixed term appointments can reflect the need for a flexible work environment allowing the to meet certain business requirements. A high percentage of fixed term appointments may be reflective of a flexible workforce or an increase in project work or a need for specific expertise for a defined period. A high result should be considered within the context of the universities business objectives and longer term workforce strategies. CQU results versus Australian Universities 2009 Quartiles and Range Senior Staff/Mgt HEW 6-10 HEW 1-5 General Total Division - Total Total Faculty - Total Academic E Academic D Academic C Academic B Academic A Academic Total Top Quartile Third Quartile Second Quartile First Quartile - Academic A results have been removed from this graph as they distort the graph. The results are included in the table below. Total (T) Total (M) Total (F) 45 % 4 35 % 3 25 % 2 15 % 1 5 % 4 35 % 3 25 % 2 15 % 1 5 % 45 % 4 35 % 3 25 % 2 15 % 1 5 % Page 32 of 109

33 Workforce Profile: Composition by Contract Type (Fixed Term) CQU Min 10th 90th Max Avg Sample Total 27.3 % 15.9 % 21.5 % 26.7 % % 43.8 % 50.1 % 35.5 % 36 Total (M) 27.8 % 16.3 % 22.8 % 27.3 % 32.7 % 39.3 % 44.5 % 49.6 % 35.1 % 36 Total (F) % 20.7 % 26.4 % 32.2 % 43.1 % 46.6 % 50.4 % 35.9 % 36 Faculty - Total 32.9 % 11.4 % 19.8 % 31.1 % 38.5 % 46.4 % 50.9 % 61.4 % 42.6 % 32 Faculty - Total (M) 30.2 % 10.1 % 20.2 % % 44.4 % 47.2 % 61.5 % 40.6 % 32 Faculty - Total (F) 35.5 % 12.8 % 18.8 % % % 61.3 % 44.5 % 32 Division - Total 23.3 % % 18.7 % 22.8 % 29.1 % % 22.9 % 32 Division - Total (M) 25.4 % % % 30.5 % 34.1 % 40.3 % Division - Total (F) 21.9 % 6.8 % 14.7 % % 27.6 % 31.5 % 35.8 % 22.2 % 32 Academic Total 33.8 % 16.7 % 22.2 % % 45.9 % 56.2 % 69.6 % 43.5 % 36 Academic Total (M) 31.5 % 16.7 % 22.4 % 30.2 % % 51.4 % 62.7 % 40.8 % 36 Academic Total (F) 36.5 % 16.7 % 22.4 % 33.5 % 38.7 % 49.3 % 62.3 % 76.6 % 47.1 % 36 Academic A 76.7 % 36.8 % % 79.7 % 89.4 % 94.6 % 96.6 % 86.2 % 35 Academic A (M) 79.5 % 43.2 % 57.3 % 75.1 % 82.9 % 88.8 % % 35 Academic A (F) 75.1 % 32.3 % 53.7 % 71.3 % 80.2 % 89.6 % 94.2 % 96.5 % 84.8 % 35 Academic B 36.5 % 11.5 % 22.7 % 33.1 % 41.6 % 54.8 % 61.6 % 73.3 % 46.2 % 35 Academic B (M) 39.2 % 11.1 % 24.7 % 33.9 % 43.4 % 53.4 % 63.8 % 70.5 % Academic B (F) 34.1 % 11.9 % 21.7 % 30.7 % 40.3 % 54.2 % 63.5 % 78.9 % 45.5 % 35 Academic C 17.5 % 5.5 % 9.5 % 14.8 % 19.9 % 30.4 % 33.6 % 43.1 % 23.8 % 35 Academic C (M) 18.2 % 5.5 % 8.8 % 14.5 % 20.8 % 30.7 % 34.5 % 41.6 % 24.3 % 35 Academic C (F) % 6.8 % 14.2 % 18.3 % 28.6 % 33.3 % 50.9 % 23.1 % 35 Academic D 17.2 % 2.2 % 9.1 % % 27.9 % 30.8 % 64.4 % Academic D (M) 16.7 % % 12.2 % 18.1 % 26.2 % 32.1 % % 35 Academic D (F) % 10.4 % % 39.2 % % 35 Academic E 2.8 % 2.8 % 11.9 % 15.3 % 22.6 % 34.8 % 41.6 % 71.9 % 26.4 % 35 Academic E (M) 3.1 % 3.1 % 10.6 % 15.3 % 21.8 % % 57.6 % 26.2 % 35 Academic E (F) % % 37.1 % 48.9 % % 35 General Total 19.6 % 10.2 % % 27.7 % 34.4 % 38.5 % 45.7 % 28.4 % 36 General Total (M) 18.5 % 8.7 % 14.4 % 18.4 % 25.1 % 30.9 % 34.7 % 47.1 % 26.3 % 36 General Total (F) 20.2 % 11.2 % 15.4 % 20.8 % 27.6 % 35.3 % 40.5 % 45.2 % 29.6 % 36 HEW % 16.6 % % 36.8 % % 31.1 % 35 HEW 1-5 (M) 27.1 % 10.2 % 17.4 % 22.7 % 27.8 % 33.6 % 37.7 % 52.6 % 29.3 % 35 HEW 1-5 (F) 25.6 % 12.1 % 16.2 % % 38.5 % 41.8 % 48.3 % 31.9 % 35 HEW % 9.5 % 12.7 % 17.9 % 24.3 % 33.5 % 36.5 % 44.1 % 26.2 % 35 HEW 6-10 (M) 12.1 % % 15.9 % 24.5 % 30.4 % 34.9 % % 35 HEW 6-10 (F) 13.3 % 9.1 % 12.9 % 18.1 % 25.9 % 33.2 % 38.5 % % 35 Senior Staff/Mgt 55.6 % % 39.8 % % % 36 Senior Staff/Mgt (M) 51.4 % 20.4 % 25.1 % 37.3 % % 36 Senior Staff/Mgt (F) 61.8 % 8.4 % 24.7 % 34.2 % 57.6 % % % 36 Page 33 of 109

34 DEFINITION Workforce Profile: Composition by Contract Type (Ongoing) Number of Ongoing Staff (FTE) Total Number of Staff (FTE) This measure describes the proportion of total staff (FTE) who are employed on an ongoing basis. Ongoing appointments ensure a consistency of staff that provides stability for both the employee and the organisation. A high result is generally considered in a positive light and shows a more stable workforce. Any result should be considered against the university s current and future workforce strategies including recruitment and retention strategies. CQU results versus Australian Universities 2009 Quartiles and Range Senior Staff/Mgt HEW 6-10 HEW 1-5 General Total Division - Total Total Faculty - Total Academic E Academic D Academic C Academic B Academic A Academic Total Top Quartile Third Quartile Second Quartile First Quartile - Academic A results have been removed from this graph as they distort the graph. The results are included in the table below. Total (T) Total (M) Total (F) Page 34 of 109