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This Summary Report provides an overview of the findings of a Quality Assurance Review that was conducted for nine key statistical programs during the period September 2006 to February 2007. The review was commissioned by Statistics Canada’s Policy Committee in order to assess the soundness of quality assurance processes for these nine programs and to propose improvements where needed. The Summary Report describes the principal themes that recur frequently throughout these programs, as well as providing guidance for future reviews of this type.
The main conclusions and recommendations are the following:
Program managers are well aware of the risks factors for their programs and are managing them well, within the circumstances and resources available to them.
The programs are well-positioned to identify the improvements that are needed to reduce the risk of errors. Based on the results of this review, programs should be asked to develop proposals for Corporate Planning Committee consideration.
While the risk of errors is well-managed across all programs reviewed, some would benefit more than others from additional investment to further lower the risk of errors. The Consumer Price Index, Balance of Payments and International Trade programs should receive a higher priority for investment to further reduce the risk of errors. We note that as of this writing, funds have been allocated to strengthen the CPI.
Human resources concerns dominate all other risk factors. Investments should first be targeted at addressing the human resources issues affecting the mission-critical programs, to ensure sufficient, well-trained staff to support them.
The existence of a research and analysis capacity separate from the production operation is a key factor in assuring quality. All mission critical programs should have a strong and explicit research and analysis capacity, independent from the production operation, whose role is to challenge the data and to conduct research into the particular subject matter of the program.
There are numerous “best practices” in all programs that can usefully be shared within the Agency. Many of these best practices are small things, but taken together they add up to an effective quality assurance program. These best practices should be the basis of the training program on quality assurance that is currently being developed.
Statistics Canada should develop a formal Quality Incident Response Plan containing standard procedures for dealing with data quality incidents, whether before or after data release. Training would be a part of this initiative.
Proposals to further increase the timeliness of the programs should be regarded with extreme caution, especially if there is a possibility that the time would be taken from the certification or data release steps.
This review of quality assurance practices has been widely regarded by participants as very useful. Statistics Canada should establish an ongoing program of Quality Assurance Reviews, tied to the Integrated Program Reporting cycle, and based on teams of Assistant Directors reporting to a Steering Committee of Directors General.