In response to the COVID-19 pandemic, several global epidemiological data collection and harmonisation efforts were initiated to provide guidance on data definitions, data formatting, and data sharing. Although it took a long time to ramp up, what was achieved in such a short period of time, on a global basis was remarkable. The pandemic has shone a light on the many lessons to be learned around data management in the sphere of public health, but it also serves as a ‘case study’ for business in the way that organisations manage novel datasets and large data volumes.
Here are some of the key takeaways.
Lesson 1. Quickly assess the availability of data.
It was nothing short of a miracle, that hospitals, local governments, pharmaceutical companies, scientists, data modellers and public health advisors were able to gather and share data on a global basis. It didn’t happen overnight, and mistakes were made on the way. According to the medical journal the Lancet1, the media played a crucial role in gathering data about outbreaks in the early stages of the pandemic.
The main lesson (reminder) is that new information requirements are often difficult to supply, they are not always immediately available in operational systems, and it can take a long time to implement dependable processes that can serve up timely and accurate data.
If organisations are changing their chart of accounts, for example, or rushing in some new information requirements for the Board, it is vital to consider upfront, the availability and trustworthiness of the new data and allow plenty of time for rolling it into regular reporting.
Lesson 2. Set crisply defined data definitions from day one
From the early stages of the pandemic, there was confusion about what data was needed, little agreement on data definitions and what quality management and validation steps were required to support the reliability of the new data being gathered.
The USA National Library of Medicine says multiple organisations attempted to standardise the compilation of disparate data from multiple sources during the COVID-19 pandemic. However, each composite data source used a different approach to compile data and address data issues with varying results1.
Turning to business, if one looks across the reporting landscape from financial reporting to financial forecasting, FSN’s research finds that data quality remains a persistent concern. We must spend more time on data quality. It all starts with an agreed data model and global data dictionary.
Lesson 3. Avoid changing information requirements ‘on the fly’
The progress of the pandemic, with numerous Covid variants and responses, required additional information and insights as the disease spread. Symptoms changed, different types of antigen tests were required, new drugs were needed and new players, such as schools had to become involved, in testing, data capture and reporting. All these changes increased complexity of data capture and reporting, with staff in different settings, stretched to the limit. From the public health point of view, much of this was unavoidable. Nobody had faced a public health threat on this scale before.
In business terms, changing information requirements during a project, is fraught with difficulty. It can easily knock a project off course, as well as causing numerous delays and errors. The key take-away is to resist changing information requirements ‘on the hoof’, it is much better to save up all the changes, so that they can be implemented in one go.
Lesson 4. Beware information overload
The pandemic illustrates how quickly data can become overwhelming and confusing. It started with flattening the curve of hospitalisations but quickly developed into large variety of KPIs, for example, hospital admissions, ICU admissions, ventilator occupancy, ‘normal’ operations postponed, vaccinated versus and unvaccinated, stages of vaccination administered, age groups, gender, nationality, local geography and many more. The most important statistic appeared to be the number of deaths “because of Covid” as opposed to “with Covid”
In business we often talk about “one version of the truth”, but the pandemic illustrated how quickly “one version of the truth” can fall apart, even on a country level. This underlines the crucial importance of having a single authority that is responsible for data governance, conformity, and analytics.
“Businesses face a constant stream of new management information or regulatory requirements.”
Lesson 5. Keep reporting appropriate and consistent
Regrettably, daily reporting of the pandemic became highly variable and confusing, even when aimed at the same type of audience. Politics inevitably crept into the presentations and, when not convenient, certain news channels, politicians, advisors (add your own list) suppressed some information and amplified other parts.
In business, the number of different audiences is more limited, but nevertheless reporting has to be sympathetic to the skills, experience and knowledge of the recipient. Regardless of the way the information is presented, it must be consistent, so that “revenue” reported in a financial statement, is the same as revenue in an analyst’s report, or shareholders’ statement. Business has its own problems with culture and bias. It is impossible to eliminate even unconscious bias in reporting, but all reporting should be under the control of one ‘owner’ to ensure that information is reported in an accurate, relevant, and even-handed way.
Lesson 6. Centralise strategic decision-making
Ostensibly there was one dataset, but wildly different recommendations and public health actions emerged. No two people seemed to agree on what the data meant and what actions were appropriate. Decision-making appeared to become more haphazard as time moved on.
The lesson is that, for all its faults, strategic decision-making must be made by a centralised function, for example, the executive team, so that there is clear and consistent communication of decisions across the enterprise.
Businesses face a constant stream of new management information or regulatory requirements. Covid offers a fascinating insight into the challenges of data management, reporting and decision-making in a rapidly changing environment. When so many businesses are beset by data problems, the pandemic offers a timely reminder of our need to rededicate ourselves to data quality management and governance if we are to remain agile in the face of extreme volatility and change.
By Gary Simon, BSc, FCA, FBCS, CITP
Chief Executive of FSN & Leader of the Modern Finance Forum on LinkedIn
Note1 The Lancet; Data journalism and the COVID-19 pandemic: opportunities and challenges
Note2 US National Library of Medicine; Challenges in reported COVID-19 data: best practices and recommendations for future epidemics