What the 2016 Elections and Business Misinformation have in Common
~Written by Marc Jaffrey
In the 2016 presidential election, the final polling average by polling data aggregator, Real Clear Politics, estimated Hilary Clinton’s lead over Donald Trump was 3.3%. However, that prediction and many other pollsters’ predictions were dead wrong.
Public Opinion Strategies noted that in the nine swing states, the polls were all wrong in the same direction. This miscalculation caused many Americans to wonder why the pollsters’ predictions were so skewed.
Clinton was wildly predicted to win; but on November 9th, Trump was named the 45th US President Elect. Some people in the nation were surprised. A yawning gap exists between what was expected and what actually happened, leading to social disruptions.
How can your business sidestep these same blind spots that plagued this election’s polling predictions and avoid potential business disruption in the aftermath?
Knowing what your information risks are before moving into a strategy is key. These risks come in three essential flavors:
Misuse of information
When we turn data into information, such as analyzing polling results for election predictions, the risk of failure due to incorrect information increases. This risk increases tenfold when you mistakenly think your information is giving you a crystal-ball gaze into the future.
Misinformation is the first risk. The idea of a “secret Trump vote,” or that voters didn’t want to disclose to a stranger what their vote would be, are perfect examples of misinformation. This behavior stems from the idea that voters give polling responses that they think will reflect well upon them instead of answering truthfully.
In business, misinformation occurs from using incorrect information, such as an improperly built data analysis program. When that happens, money leaks out of the company via holes that could have been stopped.
Inaccurate data analysis leads to bad information and poor decisions. In the 2016 elections, misinformation ran rampant with misleading or fake news stories. Readers were led astray into bad decisions or impressions by this misinformation.
Missed information is the second risk. This risk happens when pollsters call but people don’t answer the phone. Claudia Deane, vice president of research at the Pew Research Center, theorizes that it’s possible some pollsters managed to miss Trump supporters in a big way. This missed information skewed their polling results in Clinton’s favor.
It’s hard to know what information you’re missing until afterward.
In business, an example of missed information happens when a company begins selling its products internationally, but doesn’t research what their marketing or product images mean in the new countries. Each culture has different cultural stories to explain ideas like Santa Claus, where babies come from or the story of Easter. As a result, their revenue is directly impacted with poor or failed sales.
The third information risk is misuse of information. It happens when information is used inefficiently or when that information is used contrary to the information’s value and incorrectly analyzed. In the election, both camps misused information: Clinton blamed the Russians for the WikiLeaks, but ignored that her internal emails contained pay-for play, racist, and derogatory comments about voters; Trump used information about Bill Clinton’s extramarital affairs to deflect Trump’s recorded sexist comments against women.
In business when the data is misused, an overly optimistic or skewed future could be seen.
How can you manage the missed information, misused information and misinformation to prevent business disruption and failed strategies?
Here are three tips:
Risk analysis: Ensure you understand the limits of information and present it in the right context with financial risk analysis.
Right infrastructure: Guide corporate data into the right place and time to create information. When data technology architecture is managed correctly, you help avoid the 3M’s of Information.
Financial based decisions: Analyze your corporate data in the context of financial consequences to business. Given the revenue value in your data, do you have all the available information on your customers? Are you doing all the analysis possible?
As the potential for increased business disruption is a direct consequence of the 3M’s of Information, strategic planning is more complicated with advanced information analytics. Manage these three information risks to your corporate data, so they are disruptive to your competitors.
Contact infoedge today for a complimentary consultation to manage your information risks, so we can help you minimize business disruption and maximize market potential.