The failure to accurately predict the outcome of the elections has caused some backlash against big data and algorithms. This is misguided. The real issue is failure to build unbiased models that will identify trends that do not fit neatly into our present understanding. This is one of the most urgent challenges for big data, advanced analytics and algorithms. When speaking with retailers on this subject I focus on two important considerations. The first is that convergence of what we believe to be true and what is actually true is getting smaller.
This is because people, consumers, have more personal control than ever before. They source opinions from the web, social media, groups and associations that in the past where not available to them. For retailers this is critical because the historical view that the merchandising or marketing group holds about consumers is likely growing increasingly out of date. Yet well meaning business people performing these tasks continue to disregard indicators and repeat the same actions. Before consumers had so many options this was not a huge problem since change happened more slowly. Today if you fail to catch a trend there are tens or hundreds of other companies out there ready to capitalize on the opportunity. While it is difficult to accept, business people must learn a new skill, leveraging analytics to improve their instincts.