1. Lessons from Water Accounting for the Energy Statistics Compilers Manual Michael Vardon 6 th Olso Group Meeting 2-6 May 2011 Canberra

2. Lessons There are many audiences Do not for get the basics Emphasise the basics Output tables are not usually good for data collection Allow for change

3. Information Data users Audiences for information: from data to indicators Data items Environmental Accounts and other aggregations Indicators Decision makers & wider public Managers and analysts Researchers Headline indicators Indicators on specific subjects or industries

4. Audiences The audiences vary in terms of background –Compilers in statistics offices as well as other agencies –Mandate and institutional arrangements of compilers –Level of experience of individuals doing collection –History and sophistication of agency

5. Basic statistical process are important and must be emphasised Dimensions of data quality*: Relevance – does the data answer the questions? Accuracy – how closely does the data represent the real word? Timeliness – is that data available in time for decision making? Accessibility – how are the data accessed? Interpretability – can the data be easily interpreted and used? Coherence – how does the data relate to other data? * Source: Statistics Canada: http://www.statcan.gc.ca/bsolc/olc-cel/olc-cel?lang=eng&catno=12-586-X

6. Important issues to emphasise for new compilers Institutional arrangements Process of development –(Including identifying and acknowledging existing data providers and identifying key questions not currently addressed by data) Importance of data collection strategy Key data collection considerations –Frame creation and maintainance –Design of collection instrument –Data collection is on-going

7. It is not the first time you produce data that is important

8. Output tables are not usually suitable for data collection Australian experience with business surveys Good form design is essential (see Dillman) Use language and concepts familiar to those expected to complete form –Do not expect them to understand the concepts required to complete energy balances or energy accounts

9. Diagrams can be helpful In explain concepts in manuals and could be useful in data collection and presentation

10. 10 Lessons from Environment Accounting for Improving Biodiversity Monitoring Lesson 1 – Build on the past Lesson 2 – Must have sound institutional arrangements and legal basis Lesson 3 – Learn by doing and accept what you have Lesson 4 – Regular and on- going beats infrequent and ad hoc Lesson 5 – Need to build capacity Lesson 6 – Integration of biodiversity data with other data is critical Lesson 7 – Determining what to measure and how to measure it Lesson 8 – Deciding how much is enough for effective monitoring Lesson 9 – Ability to access and interpret data Lesson 10 – Defining the questions and flexibility

11. Inland Water Resources Water Supply Sewerage Households ElectricityMiningManufacturing* Agriculture Other industries ?? ?934448412334? ? ?? 722 71533644841320172 339 143 3267 3626 944228 ? ? ? 515 Australia – physical water supply and use, 2008-09 (GL) 1594 79 9336 103927787 ? 2 The Sea 1163 Key Wastewater Water Reuse water 33 * Note shown is the supply of distributed water and reuse water by mining and manufacturing, 25 GL in total.

12. Need to be able to innovate and have access to improved methods A hard copy publication is not the end of the process A knowledge base for recording country practices A forum for on-going interaction of technical experts