Rethinking Data in the COVID-19 Era

Notes from the July “Leading the Way Forward” Roundtable, hosted by Stanton Chase’s North American Technology Practice

execunetselect-general-dataIn the COVID-19-era marketplace, there are winners and losers. The stakes are high, but companies with responsive and intelligent data practices are adapting, thriving, and — even in a context of great uncertainty — maintaining their growth trajectory. Stanton Chase’s North American Technology Practice is constantly engaged in conversations with experts that keep us on the forefront of advances in AI, machine learning, and data analytics. Last month, five data-savvy executives were invited to join in a virtual roundtable to discuss how their relationships to data are evolving as they rise to the challenges of a global pandemic. Here are three insights from this fascinating and wide-ranging conversation.

1. Our Data Problems Aren’t New … They’re Just Getting Harder to Ignore

These days, every business leader wants to know the future, but COVID-19 has made it next to impossible to predict long-term trends using traditional data. One of the most head-turning insights of the afternoon came from John Parkinson, Founder and Partner at Parkwood Advisors.

Parkinson is a leader in providing elevated data solutions and building fast, predictive models for private equity and enterprise customers. He previously served as CTO for TransUnion LLC and Capgemini and as a Senior Vice President for Axis Capital. In Parkinson’s view, the data problems facing companies today aren’t new at all; they’ve just become more visible due to COVID-related disruptions.

“It turns out that the data we always relied on were no good anyway,” says Parkinson.

Instead of relying on limited sets of internal data, he suggests that those hoping to adapt should focus on mining the enormous troves of external data available. With the help of sophisticated machine learning and AI, companies can gain actionable insights at lightning speed. Machine-learning techniques “point us to new kinds of data that enrich the models in ways that you wouldn’t have guessed” and, while we still can’t predict the future, Parkinson says this kind of ‘elevated’ data can help companies weather uncertainty by revealing “what has to be true for a given set of scenarios to play out.”

Rather than looking to the past, Parkinson’s approach works backward from a range of desired future outcomes; he uses machine models to map out the trajectory of various what-ifs. “We’re not trying to predict what’s going to happen. We’re trying to predict what you have to believe in to invest in a future scenario,” he says. This approach is particularly useful when decisions need to be made quickly. For instance, in the past six months companies have rushed to address unprecedented challenges to their supply chains. When deciding where in the world to build a new factory, these businesses must account for many variables such as manufacturing capacity, energy availability, and port capacity. These decisions need to be made quickly, and companies can’t afford to be wrong. To guide these choices, Parkinson has seen the business world turn more than ever to external, AI, and machine-learning data solutions. One lesson COVID-19 seems to have taught us is that historical data is not a crystal ball. Therefore, it’s time to upgrade our data practices.

2. The private and Public Sector Need to Work Together

In the wake of the pandemic, government agencies are scrambling to launch new initiatives and expand existing programs. These efforts have been hindered by outmoded data practices. Gloria Parker is the CEO of Parker Group Consulting, which specializes in helping clients market more effectively to the federal government. The question she posed to the group was: “How can the government catch up?”

What if the government took a ‘customer experience’ approach toward serving its citizens?”

As former CIO of the U.S. Department of Housing and Urban Development and the U.S. Department of Education, Parker has a deep understanding of the obstacles and opportunities that exist in the public sector today. She noted the stark contrast between the highly coordinated and precise ways that private companies use data to identify and understand customers, and the slowness of governments to adopt similar models for public good. For example, by accessing and leveraging data, Target knows its consumers and their habits. They then work to optimize and personalize their customers’ experiences. In contrast, government agencies, schools, shelters, and hospitals are not nearly as responsive to people’s needs or histories. A significant barrier is that, in comparison to consumer-oriented retail companies, these institutions do not have the ability to collect the same level of data about individuals who are the intended recipients of their services. Additionally, due to a siloed mentality and culture, government agencies do not share data consistently with one another.

As the government rolls out ambitious new public health initiatives like contact tracing, a smarter, more coordinated data framework could save lives. Effectively carrying out data-driven programs without infringing on the privacy of individuals is an incredible challenge. In Parker’s view, the government has much to learn from the private sector. She believes just as retailers focus on improving the customer experience, governments need to adopt a ‘citizen experience’ framework as they move forward in the post-COVID-19 era.

3. Understanding the Customer Has Never Mattered More

As the business world rushes to innovate, companies are turning to new data sources and techniques to help them keep pace. Jonathan Silver, CEO of Affinity Solutions, has seen an emerging trend: customer data has taken center stage in guiding change.

According to Silver, it is no longer just marketing teams who are interested in using external customer data to optimize decisions. “In the retail space, historically it’s been the marketing group that argues that the customer should be at the center of the business. The rest of the enterprise hasn’t always lined up. That’s changing.”

Silver is a pioneer in the world of data optimization, but his company, Affinity Solutions, didn’t start off as a data company. In the early 2000s, Affinity originated the concept of ‘merchant-funded’ offers — credit-card rewards programs funded by retailers rather than banks. This became an industry standard and earned Affinity access to an incredibly rich and versatile blend of data from banks and retailers. Now Affinity leverages these unique data sources to provide clients with machine-powered insights about their customers.

For example, Silver told a story about a large grocery client that had viewed other grocery chains as its main competitors. A machine-learning analysis of customer data revealed another source of competition: fast-food restaurants. The company was able act on this insight by expanding their selection of prepared foods. In a way, what Silver delivers is the connective tissue of data, a high-level view that clients can use to guide decisions. Specifically, companies today are faced with burning questions: What new products should they offer? What safety protocols should they follow? Where and when should they reopen stores? As leaders navigate the way forward, Silver is seeing a greater reliance than ever on insights derived from external customer data.

“With COVID, companies have had a hole punched in their own data,” he says. “A focus on external data has become critical.”

These three insights represent a necessary shift in thinking to better develop actionable data to drive growth and facilitate more rapid change in companies, governments, and the world: (1) Instead of using just your existing data to determine conclusions, envision your ideal outcome and work backward to determine the data needed to deliver that outcome; (2) The public sector needs to mimic the best practices of the private sector by developing, sharing and leveraging data, viewing citizens as customers, resulting in more responsive services and better outcomes, and (3) Obtaining data about your customer/potential customer’s interactions outside of your own data will deliver a more comprehensive and robust dataset, illuminating heretofore unknown connections across all facets of your business and the marketplace. The insights you derive from understanding these connections can be the impetus for taking actions that drive different and better results.

Written by Greg Selker, Stanton Chase’s North American Sector Leader, Software, and a Director at the Baltimore office. Originally published by Stanton Chase.

Stanton Chase

Stanton Chase

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