Editing Anchoring effect (section)

=== Business intelligence ===
A peer-reviewed study<ref>{{Cite journal|last1=Ni|first1=Feng|last2=Arnott|first2=David|last3=Gao|first3=Shijia|date=2019-04-03|title=The anchoring effect in business intelligence supported decision-making|url=https://www.tandfonline.com/doi/full/10.1080/12460125.2019.1620573|journal=Journal of Decision Systems|language=en|volume=28|issue=2|pages=67–81|doi=10.1080/12460125.2019.1620573|s2cid=182259743|issn=1246-0125|url-access=subscription}}</ref> sought to investigate the effect of [[business intelligence]] (BI) systems on the anchoring effect. Business intelligence denotes an array of software and services used by businesses to gather valuable insights into an organisation's performance.<ref>{{Cite web|last=Fruhlinger|first=Mary K. Pratt and Josh|date=2019-10-16|title=What is business intelligence? Turning data into business insights|url=https://www.cio.com/article/2439504/business-intelligence-definition-and-solutions.html|access-date=2021-04-26|website=CIO|language=en}}</ref> The extent to which cognitive bias is mitigated by using such systems was the overarching question in this study. While the independent variable was the use of the BI system, the dependent variable was the outcome of the decision-making process. The subjects were presented with a 'plausible' anchor and a 'spurious' anchor in a forecasting decision. It was found that, while the BI system mitigated the negative effects of the spurious anchor, it had no influence on the effects of the plausible anchor. This is important in a business context, because it shows that humans are still susceptible to cognitive biases, even when using sophisticated technological systems. One of the subsequent recommendations from the experimenters was to implement a forewarning into BI systems as to the anchoring effect.