Emissions offset project auditing as quality assurance discipline: a forest inventory perspective

1. Emissions offset project auditing as quality assurance discipline: a forest inventory perspective 2013 Western Mensurationists Meeting, Leavenworth, WA 25 June 2013

2. Three questions: • What do forest inventory professionals know about quality assurance? • What do auditors know about quality assurance? • Can quality assurance ideas from the world of auditing be of any interest in a forest inventory setting?

3. “Timber cruiser”, Ken Brauner, 1992 http://www.kenbrauner.com/home/kb1/page_477_218/timber_cruiser_art_print.html 

4. http://www.zazzle.com 

5. Emissions offset projects http://commons.wikimedia.org/wiki/File:Smokestacks_3958.jpg http://commons.wikimedia.org/wiki/File:Douglas_Firs_Mount_Hood_National_Forest.jpg

6. The number (usually expressed in metric tonnes CO2-equivalent)

7. The number (usually expressed in metric tonnes CO2-equivalent) • Spreadsheets • Access/SQL Server databases • Scripted processes • Modeling software (e.g., growth-and-yield models)

8. A framework for quality assurance (Adapted from financial auditing methods via ISO 14064-3:2006)

9. Complexity of the system • Multiple forest inventories? • Different growth models?

10. Key risks in the system • Manual transfer errors • Spreadsheet calculation errors • Errors in software operation

11. Quality control processes • Built-in data validation? • Manual quality control checks? • Sniff test?

12. Remaining areas of risk • Focus on biggest areas of “residual” risk • Likelihood of residual risk determines how much to check

13. Tools for data testing

14. Vouching

15. Retracing

16. Recomputation

17. The number (usually expressed in metric tonnes CO2-equivalent) • Spreadsheets • Access/SQL Server databases • Scripted processes • Modeling software (e.g., growth-and-yield models) • Measured forest inventory data • Assumptions/parameters • Other input values

18. Tools from emissions offset auditing can: • Help us to strategically assess our own quantitative procedures for weakness and possible improvements. • Facilitate critical evaluation of data originating from within other organizations (or even our own organization)

19. Questions? Zane Haxtema zhaxtema@scsglobalservices.com +1-510-292-5968 direct zane.haxtema Skype

20. Supplementary Slides

21. A sample size framework (Adapted from financial auditing principles*) MAR = AR / (IR * CR) MAR = Max. audit risk (risk that errors not caught by audit) AR = allowable risk (acceptable risk of a “false positive”) IR = Inherent risk (inherent risk of errors occurring) CR = Control risk (risk that errors not caught by controls) *As specifically described in PCAOB AU Section 350, accessed online 13 June 2013 at http://pcaobus.org/standards/auditing/pages/au350.aspx

22. A sample size framework (Adapted from financial auditing principles*) MAR = AR / (IR * CR) MAR = Max. audit risk (risk that errors not caught by audit) AR = allowable risk (acceptable risk of a “false positive”) IR = Inherent risk (inherent risk of errors occurring) CR = Control risk (risk that errors not caught by controls) *As specifically described in PCAOB AU Section 350, accessed online 13 June 2013 at http://pcaobus.org/standards/auditing/pages/au350.aspx

23. A sample size framework (Adapted from financial auditing principles*) MAR = AR / (IR * CR) MAR = Max. audit risk (risk that errors not caught by audit) AR = allowable risk (acceptable risk of a “false positive”) IR = Inherent risk (inherent risk of errors occurring) CR = Control risk (risk that errors not caught by controls) *As specifically described in PCAOB AU Section 350, accessed online 13 June 2013 at http://pcaobus.org/standards/auditing/pages/au350.aspx

24. A sample size framework (Adapted from financial auditing principles*) MAR = AR / (IR * CR) MAR = Max. audit risk (risk that errors not caught by audit) AR = allowable risk (acceptable risk of a “false positive”) IR = Inherent risk (inherent risk of errors occurring) CR = Control risk (risk that errors not caught by controls) *As specifically described in PCAOB AU Section 350, accessed online 13 June 2013 at http://pcaobus.org/standards/auditing/pages/au350.aspx

25. A sample size framework (Adapted from financial auditing principles*) MAR = AR / (IR * CR) MAR = Max. audit risk (risk that errors not caught by audit) AR = allowable risk (acceptable risk of a “false positive”) IR = Inherent risk (inherent risk of errors occurring) CR = Control risk (risk that errors not caught by controls) *As specifically described in PCAOB AU Section 350, accessed online 13 June 2013 at http://pcaobus.org/standards/auditing/pages/au350.aspx

26. A sample size framework (Adapted from financial auditing principles*) MAR = AR / (IR * CR) MAR = Max. audit risk (risk that errors not caught by audit) AR = allowable risk (acceptable risk of a “false positive”) IR = Inherent risk (inherent risk of errors occurring) CR = Control risk (risk that errors not caught by controls) *As specifically described in PCAOB AU Section 350, accessed online 13 June 2013 at http://pcaobus.org/standards/auditing/pages/au350.aspx

27. An example... Allowable risk = 5% Inherent risk = 50% Control risk = 10% Maximum audit risk = 5% / (50% * 10%) = 100%

28. A sample size framework (Adapted from financial auditing principles*) MAR = AR / (IR * CR) MAR = Max. audit risk (risk that errors not caught by audit) AR = allowable risk (acceptable risk of a “false positive”) IR = Inherent risk (inherent risk of errors occurring) CR = Control risk (risk that errors not caught by controls) *As specifically described in PCAOB AU Section 350, accessed online 13 June 2013 at http://pcaobus.org/standards/auditing/pages/au350.aspx

29. Adapted from Table 1, PCAOB AU Section 350, accessed online 13 June 2013 at http://pcaobus.org/standards/auditing/pages/au350.aspx