How the pandemic has underscored the value of external data

Editor's note: This article originally appeared in Forbes.

Whether your organization’s goal is to delight customers or improve healthcare outcomes, one of the biggest challenges is finding the right data to answer your questions.

Data insights can be the difference between timely treatment and hospital capacity issues, or understanding consumer trends and losing sales to competitors.

Saving time, increasing efficiency or arriving in the nick of time for the right opportunity often requires data resources beyond what any individual or organization can process alone.

That’s why there’s growing interest in data partnerships and data sharing—to give organizations the breadth and depth of insight needed to solve difficult problems when there’s little margin for error.

The City of New York entered the eye of the storm when the Covid-19 pandemic hit the United States. Yet one of the bright spots of 2020 has been a cooperative effort around data that’s been guiding the city’s response to the pandemic.

As New York City became the epicenter of the virus in March, city analysts who typically deliver data insights to policymakers pivoted to focus on the health crisis. Most critically, they analyzed data to assess ICU capacity and relayed this information to emergency medical services staff across the city. The timely information led first responders to divert the most acute patients from overburdened facilities to those with available beds.

In July, the city launched the NYC Recovery Data Partnership, an initiative to facilitate data sharing among community, nonprofit and private organizations to aid response and recovery efforts. The partnership allows analysts to tap into a wide range of data from more than a dozen member groups to not only help leaders understand various impacts of the virus, but also empower innovative responses. 

In scenarios that necessitate prompt insights and swift action like the pandemic, this type of data partnership offers a comprehensive view of available data so people can come together to quickly solve complex problems.  

At its foundation, a data partnership involves sharing between two or more parties in pursuit of a broader goal, often with a long-term strategic horizon or a big-picture reward in mind. “A data partnership usually delivers a missing piece of the puzzle for each side of the agreement. When utilized correctly, it enables better service-delivery or more informed decision making,” said Anthony Young, a senior manager of solution engineering at Tableau. 

In the city, those benefits may include less crowded hospitals, accelerated care delivery and better outcomes for Covid-19 patients. 

With data on Covid-19 test results, insights into neighborhood foot traffic and up-to-date information on business operating hours, the partnership is also well positioned to help authorities determine which targeted control measures might contain outbreaks.

The data partnerships forged to fight the pandemic offer models for forward-thinking businesses that see the value in sharing data to build resilience amid uncertainty and discover new revenue opportunities. 

When the pandemic disrupted supply chains, for example, brands looked to fill gaps in their knowledge by augmenting internal data sets with public data sets, as well as with data from business partners. By combining data to create a fuller picture, brands looked for ways to source materials from alternative locations, move products across consumer locations to fill gaps downstream and sell products in new markets when intended markets could not be accessed.

The pandemic shifted business norms and made existing performance measurement unreliable. This propelled leaders who once relied primarily on internal data for strategic decision making to look outside of their own four walls. As Covid-19 surged, leaders were keen to monitor the competitive landscape to learn from reopened markets and companies that had launched successful e-commerce alternatives, adapting their own responses based on new insights. 

“Clients who would normally ask for a data engineer to blend their product and customer data for a report started asking for ways to monetize the insights they have and for recommendations on good datasets to shop for to augment those in-house insights,” said Amer Numan, director of data and analytics at Slalom, a global consulting firm focused on business transformation. “Decisions enabled by sharing and blending external data are more specific and impactful than ever because they are based on more context than ever before.”

The value of data sharing is especially high for retailers and consumer goods manufacturers, said Numan. A reopened region could inform closed regions about how consumer behavior and traffic are changing, for example, while an e-commerce marketplace could offer insights on new trends, seasonality and specific metrics like conversion and basket size across different product categories.

“One example of a game-changing data provider would be a luxury department store with a strong online presence,” said Numan. “Combining data from foot traffic sensors, web visits, sales, social media posts and promotions and product attributes can be an enormous win for a brand that is on those shelves and websites. It can tell a brand which varieties are selling, how many people who see the product opt to buy it and even what is being purchased alongside it.”

“Imagine the possibilities when you know, with a very high degree of confidence, that you should present a specific type of product, at an exact price point, for a particular ZIP code, in a defined timeframe, to achieve a guaranteed sale. It’s the holy grail in data-driven business planning,” said Numan. 

Of course there are challenges that accompany data sharing, says Numan. “The chief concern in executing this has been data security—the ability to obtain and share specific data elements without compromising intellectual property and highly proprietary information,” he said. “This is why a shared cloud repository for data to be presented and accessed is imperative, and why secure virtual data platforms have dominated the data marketplace this year.”

Data partnerships operate best when fueled by data from a wide range of partners. Here are examples of the kinds of insights retailers, suppliers and other collaborators can contribute in a data sharing scenario:

• Retailers: Data on which products are selling and how sales are being made—not just color, quantity and location, but also product placement, foot traffic, conversion rates, promotions and discounting.
• Suppliers: Data on raw material stock levels and lead times, downstream distribution alternatives, warehoused products that can quickly be moved to a higher-performing region and options for new formulations.
• Media partners: Insights on competitive purchases, web searches for fashion trends and engagement with fashion influencers on social media, along with sentiment analysis on consumer engagement and which factors are likely to convert to sales. 
• Other commercial partners: Demographic data on purchases and spending habits, such as insights into whether the buyer ever flies first-class, drinks alcohol or wears a sports team’s colors.

For data sharing initiatives to thrive, senior leaders need to play an active role. While the concept may be new and somewhat unfamiliar to organizations that typically rely on internal or proprietary data, the potential benefits of data sharing are significant, and worth exploring.

1. Practice good governance.

   Data partnerships must come with boundaries. Even if a data partnership is built around crisis response, parties should hold each other accountable for using data for mutually agreed upon goals, including maintaining proper governance and controls. “You need to define what data is shared with which entity and how long they have access,” said Sunil Rao, global head of the consumer goods go-to-market team at Salesforce.

2. Strike plain-language agreements.

   Data privacy and licensing can be complicated. Whenever possible, data partnership agreements should focus on clear language and avoid unnecessary obstacles, without sacrificing security of the information. The reason is more of a practical matter than one of principle: Shorter, simpler agreements are easier to consummate. And they’re simpler to amend later if need be.

3. Share insights and context.

   Data partnerships will underachieve if they only provide one-time static, or even periodic data reports. Make sure your stakeholders understand that sharing data is only the beginning of the collaboration. The real work is done when people converge on a shared topic and shared goals and then create analytical insights and explanations that are valuable to everyone in the partnership.

4. Reduce friction for faster results.

   Even modest time savings can pay significant dividends. “Hopefully, people will have learned from the pandemic that even a slightly more rapid response that's supported by data makes all the difference,” Young said. Rao adds: “Partnerships should enable access to data that’s clean, normalized and ready to use,” in order to minimize redundancy.

5. Emphasize new-economy challenges.

   Don’t limit the scope of your partnership to rearview-mirror analyses. Use your new collaboration to test strategies, implement solutions and solve challenges that may have seemed insurmountable. And don’t expect the data partnership to help restore the pre-Covid status quo. “Things will never be the same. Seasonality as we know it in retail is completely gone,” said Numan, assessing the impact of the pandemic. “Is there a weekend anymore? Are there holidays anymore? You need to tackle and explore those questions with your partners.”

Data sharing and data partnerships will help organizations address significant humanitarian and logistical challenges in the months and years ahead by focusing the best minds on challenges too difficult and pressing to solve alone. 

To learn more about how organizations are using data during the pandemic, visit the All Hands on Data webpage.