We are all biased – whether towards our family, friends, company, nation or culture.
Bias means we select what we know and like and avoid what we dislike or that is too hard to understand. Yet for effective competitive intelligence identifying and avoiding bias is crucial to correctly evaluate our competitors and competitive environment. Avoiding a biased view means we see things as they are – not as we would like them to be. As such, we are better placed to create winning strategies. There are numerous examples of companies failing due to biases that led to failures to see reality.
Around 175 different types of bias have been described, many of which are similar. In fact, these can be simplified and grouped into 4 broad categories: This session will explore and explain the key biases that can impact competitive intelligence processes – from collection to analysis to communicating results needed for business decision making.
This session will explore and explain the key biases that can impact competitive intelligence processes – from collection to analysis to communicating results needed
for business decision making.
Arthur Weiss is the CEO of AWARE, specialising in CI analysis, research and training. He has worked in CI since the 1980s, initially with Dun & Bradstreet and now with AWARE, established in 1995.
Arthur is well known as a competitive / marketing intelligence expert and has taught hundreds of CI professionals on a range of topics. He led the world’s first workshop on finding CI using the Internet at the 1997 International Online Conference and has carried out social media (SOCMINT) research for clients since 1999.
Arthur was the General Editor of Croner’s Marketing – A Practical Management Guide (1996) contributing chapters on competitor analysis and marketing planning. He wrote the corporate intelligence chapter in The Palgrave Handbook of Security, Risk and Intelligence (2017). He is the module leader for ICI’s secondary research (OSINT) and counter-intelligence workshops and is also a member of AIIP and SLA.
GICI Institute for Competitive Intelligence GmbH
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