1. Effective stakeholder surveying SISA Injury Management General Meeting Danielle Martin, General Manager, Corporate Communications We would like to acknowledge this land that we meet on today is the traditional lands for the Kaurna people and that we respect their spiritual relationship with their country. We also acknowledge the Kaurna people as the custodians of the Adelaide region and that their cultural and heritage beliefs are still as important to the living Kaurna people today.

2. 2 WorkCover SA Agenda  Stakeholder surveying - why do it?  WorkCover case study  Outcomes  Survey methods  Key steps  Beware the pitfalls

3. 3 WorkCover SA Stakeholder surveying – why do it?  Performance monitoring/measurement  Service delivery  Product, systems evaluation  Project development / approvals  Stakeholder perception  Issues identification, management  Concept testing  Strategic planning  Risk management  Benchmarking / continuous improvement  Assess, review, improve

4. 4 WorkCover SA WorkCover case study – what?  Assessment of stakeholder satisfaction with services provided by new claims agent  Initial benchmark, subsequent performance assessment  Qualitative survey to identify ‘satisfaction drivers’  Quantitative survey to measure satisfaction (annual)  Two key stakeholder groups:  Injured workers  Employers  Action planning, strategic planning

5. 5 WorkCover SA WorkCover case study – why?  Decision to appoint single claims agent – 1 July 2006  Agent contract linked performance to remuneration  Specific KPI for stakeholder satisfaction  Ability to earn significant $$  Importance of rigour, validity  Robust benchmark against which to measure performance  Continuous improvement  Significant reputation implications for WorkCover  Complement existing mechanisms for interaction  Commitment to stakeholder consultation, service

6. 6 WorkCover SA WorkCover case study – how?  Two parts: 1.Qualitative – what are the drivers of ‘satisfaction’ for each stakeholder group 2.Quantitative – statistically-valid, robust measurement  Qualitative - McKinna Strategic Insights  Objectives:  stakeholder values – ‘hearts and minds’  inform questions for quantitative survey  explore general understandings, attitudes and beliefs  Methodology:  Seven focus groups (5 x injured workers, 2 x employers)

7. 7 WorkCover SA WorkCover case study – how?  Focus groups explored:  Overall nature of relationship  Understanding and beliefs of system, modus operandi  Overall satisfaction with relationship  Major issues and concerns  What constitutes ‘satisfaction’ with services of each group

8. 8 WorkCover SA WorkCover case study – how?  Quantitative – McGregor Tan Research  Objectives:  Statistically-valid data collection on stakeholder satisfaction  Methodology:  telephone surveys – computer assisted  1,000 employers  1,500 injured workers  dataset accuracy +/- 2.9% at 95% confidence interval

9. 9 WorkCover SA Outcomes  Benchmark satisfaction ratings  Reliable performance measurement  Target setting  Issues / environment scan, predictor  Pinpoint strengths / weaknesses – external perception  Action plan for continuous improvement  Independent credibility

10. 10 WorkCover SA Survey methods  Self-completion surveys  Email and internet surveys  Interviewer-based surveys (face-to-face, telephone)  Combination  Qualitative vs quantitative  Statistically-valid vs smaller sample  Integrity of data collected critical

11. 11 WorkCover SA Key steps  Planning and designing  Define the purpose, objectives and output required  Well-defined output minimises risk of invalid results  Testing and modifying  Pilot test of questions can reveal problems with wording, layout, understanding or respondent reaction  Conducting the survey  Select right sample  Processing and analysing  Data integrity  Close feedback loop  Evaluate for improvement of future surveys

12. 12 WorkCover SA Beware the pitfalls  Survey errors  Sampling Error  Sample size - increase sample size, decrease sampling error  Population variability - items of interest vary within population  Sample design - probability of selection not known (ie, quota)  Bias  Non-response - refusals, non-contact, language difficulties  Inadequate sampling frames  Characteristics of non-respondents differ from respondents  Quota sampling  Certain number of responses in particular categories

13. 13 WorkCover SA Beware the pitfalls  Various factors can influence ‘satisfaction’  Allow people to opt out  Survey fatigue  Recent experiences  Other environmental factors  Failure to act on results  Close the feedback loop  Provide progress report

14. 14 WorkCover SA