What Is Truth? Data Quality Takes on New Importance

Before the pandemic, I was planning on writing an article about Truth.  I was inspired by Johnny Cash and his song “What is Truth?”.   There was a interesting documentary about this song and when it was rebelliously performed in 1970 by the Man in Black for the President at the White House. The story of Nixon’s music requests and Johnny’s defiance struck a chord in me. johnny_cash

 

After 5 months of COVID-19 devastating health and economic impact on the entire globe, there is great attention and a need to know what the facts are so our leaders can make informed decisions about response, mitigation and reopening plans.

Knowledge is Power and Data is King but I continue to ask “What is Truth?”.

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Photo by cottonbro on Pexels.com

Everyone wants our local, state and federal officials to “follow science” and make data-driven decisions but not everyone agrees on the numbers, patterns and trends.  Not everyone agrees on what “settled science” is.

One expert proclaims one set of conclusions while another presents a compelling argument discounting it and supporting an opposite view.

Who is right?

Which set of data is the truth?

These profound, global questions are now front and center at my job where I am on a committee tasked with Improving Data Quality.  The main objective of this key 2020 initiative at my workplace is to ensure that the underlying information and data in our system of record (Remedy) is consistent and accurate.

As with the global heads of state, this quality data is crucial for the company’s leaders to identify gaps, patterns and trends so that they can make the best decisions for prevention and improved outcomes.

As I reflect upon my work team’s new mantra:  Restore, Prevent and Protect, I can’t help but think and reflect upon the world’s current challenge with COVID-19.

At my company, my role is to manage a team of Incident Commanders.  We are like digital firefighters and paramedics and work to restore service for our clients.  When a software or hardware system goes down, we mobilize support teams on a recovery call and facilitate the fixing of the problem.  We strive to “put out the fire” and revive the “patient” as quickly as possible.

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Recently my team expanded its role of Incident Management into the Problem Management space.  Once we resolve the issue, we help find out the Root Cause and focus on ways to prevent the outage from happening again. We restore, we prevent and we protect the production environment.  Production means live and customer facing systems (websites, stock trading platforms, etc).

To enable us to do the Prevention and Protection piece, we need to capture all of the information and data about what happened.  What caused the problem to occur?  Was it a result of a recent change?  All of this root cause analysis is captured in a centralized system of record that drives a crazy number of dashboards, charts and graphs.   The underlying quality of the data is so important because so many long reaching decisions are based on them.

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Photo by Lukas on Pexels.com

Every day for the past 4 months, I have been logging into my state’s Department of Health Dashboard to see what the current COVID  numbers are.  I look at the percentages and the rates per 100,000.  I look at the total deaths and the demographic breakdowns.

Most of all I care about the trends because I know that this is what my Governor is looking at when making decisions and executive orders about what businesses can be opened and when students will be permitted to have in-person instruction.

I was a bit confused and concerned the other day when I saw that the COVID dashboard had a -1 value in the daily death count box.  How could this be? What is a negative death?  What was the quality check on the data?  What this an automation mistake or a human error?

So many people are questioning the accuracy and validity of the numbers as it relates to the COVID-19 pandemic and I am afraid that the hyper-polarization in this US election year will only continue to make the situation difficult.

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In the end, all that I can do is focus on and improve what’s in my control. 

At work, I can help my team improve the data quality of our incidents and problems by providing clear guidance, standards and training.  We can enhance our processes to conduct frequency reviews and quality checks of the information we capture.  With an Agile mindset, we can focus on continuous improvement through experimenting inspecting and adapting.  We can work to have better accuracy and hit our targets.

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I wish I could have an influence on the quality of the health statistics at a local, state and federal levels but that is above my pay grade.  All I will continue to do is make the best personal decisions I can for myself and my family based on what I believe to be true.

But again, What is Truth?

Is there a way to guarantee the accuracy and consistency of the test results and confirmed causal deaths across 50 states and over 150 countries?

I’m not so sure that this is even possible, so why should I worry and fret about it?

In light of this, I’ll leave you with some quotes on statistics.

It is my hope that you are safe and well and are making the best possible decisions you can based on the data and information that our medical experts and government leaders are providing us.

“Facts are stubborn things, but statistics are pliable.” 

– Mark Twain

 

“We must be careful
not to confuse data
with the abstractions
we use to analyse them.”

– William James