Harnessing messy data for future improvements

By Rhonda McDeigan-Eldridge, CPA, CA

Founder & Impactioneer

Harness All Possibilities Inc

Data does not rest. It is everywhere, created by everyone for anything and everything. Silently, it has grown exponentially over the past few years, especially most recently, with the attention on COVID-19. We are obsessed with the moment-to-moment updates. While data is messy, I believe it is the most significant contributor to our emotional discomfort and mistrust, as well as disinformation – which are all at unprecedented levels. We would like to believe what the data says but do not trust it.

Three reasons why data and I struggle with its message

  1. Data’s story is as good as the storyteller

On its own, data is messy, random and disorganised. One cannot take it at face value because its source may have its own agenda or perspective. The data may have some hidden facts that are like needles in a haystack. The storyteller may have an agenda - a call to action or a desire to appease, oppress, suppress or depress others. Let us assume the source is an expert, a respected leader, or a trusted friend. One would immediately lean towards believing the storyteller versus the messy data, no matter what may be revealed – even if it is misinformation. The details we see in the data trigger our emotions, ranging from ‘comforting stories’ to ‘unpleasant realities'. When it comes to human survival in the COVID-19 environment, one must weigh economic and emotional conclusions against the source that provides interpretation or perspective on the data.

  1. The data, the expert and personal experience

When it comes to basic human needs, survival beats data. My experience during the 2008 financial crisis proved this assumption. I worked for a European bank and was awoken at 4am by a call from the head office. The conversation confirmed what the data had been showing for months. We were facing a precipitous decline in the company’s stock price, a trend for many of the major global banks at the time.

The data was messy and forewarned of a domino effect, potential bank failures, or significant losses spread from one to the next in the banking world. The global financial tsunami was underway. There was nowhere to run or hide. Our primal human instincts of survival kicked in; a Fear of Not Acting (FONA) mindset left many frozen. The media, economists and every subject matter expert chimed in with their angle on the data.

However, I was able to take a different, regional perspective with access to other data. My team and I recognised something the media had yet to cover. I did not believe the 'doom and gloom' scenario. There was something in the data telling me to read the data from a fresh angle. I was insistent and unwavering in the quest for a gold nugget, digging into and through a plethora of liquidity and 'what if' scenarios to see what the data was saying.

My team and I switched to survival mode. Using our instincts, experience, and teamwork, honed by doing unusual deals, we scoured the data to sort facts from conjecture and took a different path. The experts knew what they knew, and we saw the data from a different angle. We ignored them and went against the tide with our version of our truth and harnessed opportunities. This united my tribe.

  1. Do the numbers lie? Well, yes!

Numbers can and do lie because people who gather the data misstate, overestimate or underestimate their expectations. We may not be aware of our biases and ingrained actions. People have an agenda, tell lies, misunderstand the purpose of data, or manipulate the system or data at the source.

The book and movie of The Big Short relates the story of individuals who found the nuggets of data highlighting the subprime home loan problems, resulting in the 2008 financial crisis. They showed that the underlying data was poor and not verified. The entire subprime lending model was based on lies. These observations, and a deep dive into the data, predicted the housing market collapse, setting off a global financial crisis that impacted every major bank.

The Big Short was the realisation of a big data opportunity. The nugget: People lie about their income on their mortgage applications. Human nature often supports fudging inputs to achieve the desired outcome. In this case, those little lies were the trigger that ignited a global crisis. The cumulative data told the story of a catastrophic financial disaster. It was messy. Maybe no one wanted to understand or dig into it until it was too late. No one likes messy.

So what? Why does this matter? Why is data relevant to The Bahamas? There are many reasons. However, I shall touch on three areas.

COVID-19 is an airborne pathogen. We breathe it as we do oxygen, except it triggers a technical glitch in humans for which there is no technical solution. Yuval Noah Harari describes our human condition in Homo Deus: “Humans always die due to some technical glitch." Humans spread COVID-19 to varying degrees. The data tells the truth about capacity to care for those with the disease (caregivers and hospitals reach capacity), potential risks of super spreader events across age, sex and pre-existing technical glitches (diabetes, weight, immune, heart or lung). People have died. The data tells how many did. That is past tense. It tells at any point in time the potential risks of not trusting these past observations to predict future occurrences.

Elections are another area where data is important for truth-telling. Bahamians laser focus on them, and observations of past elections tell a story of what happened. However, data is omnipresent within the context of the election period in showing the number of persons at a rally, persons registering and, at polling day, who is predicted to win or lose. Are there any predictive models for what candidates have said before an election to predict their likelihood of delivering the outcomes once elected. How can data help with accountability and transparency reporting? Can data also speak to credibility, trust, being held accountable? How does this data help move a country forward in making decisions about candidates? What did the candidate do to have a measurable impact on socio-economic well-being and the community’s growth? Data can provide some insights on the intangibles and tangible outcomes of the electoral process.

Finally, skills. Data has some truth-telling about human skills in The Bahamas. The efforts to upskill and reskill , and to close gaps, have been thwarted by COVID-19, and pressing the pause and reset buttons post-Dorian. A 2019-2020 collaboration by five private sector summer technology programmes found little reliable publicly available data on the national skills portfolio; breakdown of the student population; reliable learning trackers or other variables to get and tell a skills story.

Data is the common language to tell this story and solve people, planet and profit problems. It is an engine for economic recovery for small island nations like The Bahamas. Data highlights business, education, health, government and innovation pain-points, work-skill gaps and laser focuses efforts to accelerate, target, track and scale human capital programmes to close multiple divides. The absence of data is the absence of knowledge, resulting in operating in a vacuum versus having a catalyst to thrive, strive and harness work opportunities that match local and global workforce needs.

Using data’s predictive qualities would provide valuable insights on the present value impact on the country’s GDP, and in almost real time, given the feedback loops and data harvesting tools now available. The predictive model from our research for one summer STEM programme, for example, showed an approximate present value to GDP of $54m. Now imagine the predictive story of the data on all national skills programmes. Imagine telling that story to ignite the power of data analytics. Think STEManalytics, LEARNanalytics, BAHAMIANMADEAnalytics, JUNKANOOAnalytics, FISHAnalytics, EXPERIENCEAnalytics offered to the world? Massive remote work opportunities with imagination and creative passion.

So while data is messy, it may be an untapped source that has the potential to unite a nation in understanding what has happened and is happening, through the 'what-if-then' scenarios, ways to pivot or anticipating obstacles. But, most importantly, a plan must be developed to harness that messy data which will tell evidence-based stories. That plan will become a tool for, and of, infinite possibilities.


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