Fake Data

Dr. Scott Shemwell

Even a casual observer of the American political discourse may be taken aback by the unending stream of seemingly undocumented allegations and in some cases, outright incorrect statements.

Volume 6 Number 5—March 10, 2017

Even a casual observer of the American political discourse may be taken aback by the unending stream of seemingly undocumented allegations and in some cases, outright incorrect statements.  Dubbed “fake news,” the flood of these stories can confuse many as well as possibly weaken some institutional reputations.[i]

Most of us develop an opinion based on media reports about a variety of subjects.  Some of us make decisions based on this information, i.e., write our congressman or woman.  Others are more action oriented and may get involved in civil disobedience (possibly based on an erroneous news story).

In such an environment, it is important that all of us become better consumers of information.  For example, when shopping for “big ticket” consumer goods we look for sales, do our homework and often seek out references before making that decision.  We must now vet information in the same manner.

As executives, we are facing a similar quandary regarding the data used to make decisions.  This is true whether the decision maker is human or machine.

Is the data of good quality or is it poor or even inaccurate?  Poor quality data has long been an issue but now we must add “fake data” to that mix.

There are two primary types of fake data.  First data that is wrong—neither valid or reliable.  An example, might be the output of sensor errors.[ii]  The other source is data that is deliberately and maliciously manipulated, i.e. hacking SCADA systems.

In either case, decisions based on these data can be disastrous, including the loss of life.  There are several technologies available to help assure data integrity and interested readers are invited to do their own research.[iii]

Our purpose herein is to suggest that as better consumers of data, we develop a “sense” of what is valid and reliable as opposed to data streams that do not meet that test.  In other words, does the data we see pass the so-called smell test?

We have all been in a situation where something just did not feel right, i.e., we pick up a bag on the airline carousel that is the same make, model and color but we know instantly it is not ours.  This happens even subconsciously.

You know your business.  Does the data feel right or is something (even if you can’t put your finger on it) amiss?  Healthy skepticism is useful when consuming the news these days.  It is for data as well!

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About the Author

Dr. Scott M. Shemwell has over 30 years technical and executive management experience primarily in the energy sector.  He is the author of six books and has written extensively about the field of operations.  Shemwell is the Managing Director of The Rapid Response Institute, a firm that focuses on providing its customers with solutions enabling Operational Excellence and regulatory compliance management.  He has studied cultural interactions for more than 30 years—his dissertation; Cross Cultural Negotiations Between Japanese and American Businessmen: A Systems Analysis (Exploratory Study) is an early peer reviewed manuscript addressing the systemic structure of social relationships.

End Notes

[i]  https://www.theguardian.com/media/2016/dec/18/what-is-fake-news-pizzagate

[ii]  http://www.pennenergy.com/articles/blogs/governing-energy/2017/01/self-decision.html

[iii]  https://en.wikipedia.org/wiki/Data_integrity

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