According to KPMG research, as many as 92% of the surveyed managers believe that improper use of data analytics can damage a company's reputation…

 

KPMG survey results

61% of CEOs taking part in the KPMG survey admitted that building trust among customers and business partners is a priority for their companies.

35% of respondents admitted that they fully trust the results of the data analytics they use, while 19% have limited trust in it. Interestingly, 6% of managers completely distrust the results of analyses.

How can trust in data and analyses be increased?

How can trust in data and analyses be increased?

Respondents say that companies wanting to increase trust in the data and analyses they use should focus, among other things, on:

  • Increasing the transparency of algorithms and methodologies
  • Strengthening internal and external quality assurance mechanisms
  • Oversight of artificial intelligence
  • Developing standards for the safeguards used

 

“Data analytics has been used in enterprises for many years, but now, due to the ongoing digitalization of internal processes and relations with the external environment, as well as the growing number of available sources, the value that can be gained from high-quality analyses is incomparably greater. Still, in most organizations the fundamental challenge remains ensuring the quality of analysis results. Our experience shows that it is not only about algorithms, but above all about a consistent understanding among the various participants in the process of what specific data categories mean, and thus a consistent understanding of what the result calculated on their basis means.” - says Krzysztof Radziwon, partner in the advisory services department, head of the risk management team at KPMG in Poland.

Summary

The KPMG survey shows that only 35% of managers fully trust the results of data analytics, and 6% completely distrust them. A priority for 61% of CEOs is building trust among customers and partners. Key actions include increasing the transparency of algorithms and strengthening quality mechanisms.

Krzysztof Radziwon of KPMG emphasizes that the main challenge is not algorithms, but a consistent understanding of data categories by process participants. For 92% of respondents, improper use of analytics can damage a company's reputation.