My concerns about benchmarking, targets and related matters, whilst not universal appears to have some adherants! During the last week have discussed it amongst colleagues at Socitm (Yorkshire & Humber) and with Paul Canning and Public Sector Web Managers Group.
I also discoved a paper from the U.S. General Services Administration – Improving Citizen Customer Service V 1.0, which also supports my theory and also uses the term ‘yardstick’ which I think is a much better term when dealing with purely internal metrics as opposed to (possible) target setting. If you don’t want to read it all, just focus on chapters 5 and 6.
Four of the eight guidelines in the conclusions are:
“A quantitative “value” for citizen satisfaction can be used as a yardstick for trends. This value can be defined in various ways. Agencies can track the percentage of citizens who expressed complete satisfaction with their contact or use a scoring system defined internally or by a third party.
Qualitative satisfaction questions and information will help agencies analyze citizens’ expectations and areas in which they are not meeting those expectations.
Quantitative (and to some extent qualitative) satisfaction data should be used to examine the correlation between the performance metrics and benchmarks used in this document and citizen satisfaction. For example, if improving average handle times at an agency is not resulting in an increase in satisfaction scores, the agency’s time and effort is better spent elsewhere in the service environment.
Surveys can be conducted at the end of a contact or within a reasonable timeframe after
and also states:
“Performance metrics described in this document are only effective if they are captured, reported and analyzed in a timely manner and reach the right decision maker. Also, metrics should be used not in isolation but in the context of a strategy and methodology.”
Of course I’m not arguing to import this wholeheartedly from the USA, if one reads the document it is still rather onerous for a small organisation but data integration and analyis or Extraction, Transformation and Loading (ETL) can be done – if only GovMetric weren’t so expensive ! It’d blow NI14 into last year…