Global Data Quality Partnership Expands - Industry News
Global Data Quality Partnership Expands

Global Data Quality Partnership Expands

The Global Data Quality Partnership, a coordinated effort to address ongoing and emerging risks to data quality in the market and social research, consumer insights, and analytics industry, has grown to include The Research Society (Australia), the Canadian Research Insights Council (CRIC), and The Association of Market Research Austria (VMÖ). The initiative was announced in March by the founding organizations ESOMAR, Insights Association, The Market Research Society (MRS), and SampleCon.

Angus Hunter, CEO of The Research Society said, “We are proud to contribute to this truly global campaign. Data quality is fundamental to the future of our research industry. Our work in this area will benefit our members in Australia and the international community.”

“Quality data is critical for our industry to deliver the insights businesses and organizations need to make the best decisions,” stated John Tabone, CEO of the Canadian Research Insights Council (CRIC). “CRIC is pleased to join this industry-wide initiative and support solutions that address the emerging risks to data quality.”

“The insights industry plays an instrumental role in our society, providing insights that serve as the basis for significant decisions. However, when low-quality data becomes rampant, it can have a devastating impact on our industry,” commented Florian Kögl, VMÖ Board Member, CEO of ReDem. “For this reason, it is paramount that we as an industry do everything in our power to ensure that only high-quality data is used.”

The organizations have pledged to coordinate efforts to fight fraud and address ongoing and emerging risks to data quality. Areas in which the organizations will focus include:

  • Fraud detection – tracking the prevalence of fraudulent survey completions by humans or bots and outlining best fraud detection and mitigation practices
  • Data quality in qualitative research, both in-person and online
  • Identification and mitigation of bias
  • Improvement of the research participant experience

Meetings are already underway in which experts are working collectively to formulate best practice guidelines and buildout, refine, and coordinate universal terms and definitions.

Research, including fielding a survey about fraud detection, is being discussed.

To learn more about this work and inquire about getting involved, please visit: Global Data Quality