How We Can Fight Coronavirus with Data

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How We Can Fight Coronavirus with Data

By Kerry Young - 03/31/2020

COVID-19 continues its rapid spread. As the world looks on, a massive response is underway across industries and regions. Perhaps for the first time, we are seeing how the interconnectivity of our world creates problems with containment that weren’t present with previous widespread health crises.

Early on, the signs were evident that COVID-19 would challenge retailers. However, the resulting disruption has been astounding. According to FMI, “A pandemic, if it develops, will necessitate engagement across a host of areas, including health care, store operations, supply chain, food safety, workforce, emergency management and media.” 1

Thankfully, one asset our world possesses today is the presence of a massive network of data. Master data management (MDM) in particular becomes an even more critical platform for meeting the needs of retailers and ultimately, consumers.

When harnessed effectively across sectors, data can be the tool that determines current and future success in retail, as the world continues to combat this dangerous outbreak and whatever comes our way in the future.

As retailers scramble to stock their shelves with everything from the very basic staples like toilet paper, hand sanitizer, bleach and wipes to newly sought-after items like gloves and masks, the role of data in this crisis stands out as both savior and learning curve.

The Current Situation  

Store shelves are empty across the world as consumers rush to buy supplies. According to StoreBrands and a Nielson report, hand sanitizer sales were up 73% over the prior-year period in February. 

Additionally, despite Surgeon General Jerome Adams urging the public to stop buying face masks, sales for medical masks saw a 319% percent boost. Canned goods, medical gloves, water, and supplies like toilet paper have also been flying off the shelf. Certain products and medicines made in the coronavirus-epicenter of China are increasingly unavailable.

On the flip side, more consumers are staying away from crowded shopping areas, lowering the demand for other goods. For example, NBC News reports that areas in Seattle are like a “ghost town,” with shops in the iconic Pike Place Market nearly empty.

In times of crisis, retailers need to know not only how much inventory they have, and which products are selling the fastest in which areas, but also what type of demand to anticipate and where they can source products from.

Predictive analytics, applied to the pandemic, could have foreseen the havoc COVID-19 would bring.

Take, for example, the challenge in inventory management for items a retailer might generally not stock in bulk, but currently considered essential personal protective equipment (PPE) for consumers. Previously, this PPE might have only been purchased at retail by those caring for an elderly parent or a sick child. 

In order to ramp up stock of such items it’s important for the retailer to really understand if a specific type of PPE is fit for purpose. This requires detailed information about that product in terms of product specs, certifications, etc. Having this data also helps retailers relay information to consumers helping them make the most informed decision about what they are purchasing. 

Leveraging Data to Identify Emergent Needs with Predictive Analytics/AI

Another potential area to apply data and technology is to use AI and predictive analytics to help us try to predict and measure the impact a pandemic might have, as it emerges. Analyzing the spike in sales of items like hand sanitizer and anti-bacterial wipes in Europe would have offered  data to trigger retailers to procure and stock more of these – and other – high demand products, ahead of the curve. 

According to Datanami, “While the possibility of a global pandemic is real, people can take some solace in the fact that public health officials have at their disposal an array of powerful data collection and analytics techniques that previous generations lacked.” 

Predictive analytics, applied to the pandemic, could have foreseen the havoc COVID-19 would bring. Leveraging a wide array of data – like IoT devices, field reports, flight manifests, social media and news sites – health organizations rushed to trace where the infection may have been spread and build predictive models around where the virus will take hold next. 

With access to a similar level of data regarding what was being purchased in the first global hot spots, retailers could have had shelves stocked for the inevitable rush by consumers to stock up on the items that are in such high demand as the virus continues to spread in the U.S.

The ideal supply chain uses a just in-time model. While JIT succeeds in managing costs, it doesn’t work well in special cases, like the current coronavirus emergency. Applying data on the emergent pandemic would have triggered points along the supply to increase production and distribution which in turn would have helped retailers to more quickly increase inventory and manage sell through to consumers of such an unprecedented amount of hand sanitizer, gloves, masks, etc. 

With regard to a range of other consumer goods, while it may have been difficult to anticipate the actual hoarding of toilet paper, it would have been quite evident that a need would exist to increase retail availability of all the basics that people stock up on during emergencies – including paper products – as well as non-perishable food items. With consumers using their smart devices to fill all of their retail needs, there is also a strong case to be made for the importance of IoT. 

Sharing Data

Much of the current chaos being experienced by retailers could have been mitigated by sharing data from the outset. A lot of solutions exist to manage staffing needs. However, there is not a good way of sharing or managing this information on a universal level. Solutions exist that could help potentially provide for shortage of stock managers and delivery workers that would help retailers more effectively manage the crisis.

Interestingly, the EnterWorks PIM/MDM platform actually began with the original role of serving classified government intelligence agencies. In 1998, EnterWorks launched as a Virtual Data Base platform known as “Pangaea.” The platform applied the “Pangaea” hypothesis of the globe – the idea of a singular supercontinent – to a central and singular view of global and unstructured data.  

At that time, the mission was to bring together physical and digital intelligence assets and information from a variety of national level command, control, communications and intelligence sources.

The “Pangaea Effect” could also benefit retailers in much the same way during a global pandemic by allowing those entities serving the consumer to access essential public health data and respond with greater stock of necessary goods.

In order to successfully make what in “normal times” is a huge leap, the key to success is having accurate product information. 

Data to Drive Business Pivots

In the retail sector, right now many businesses are pivoting to delivery models like curbside delivery – that they’d never considered before. Overnight, traditional brick and mortar stores have become digital businesses. In order to successfully make what in “normal times” is a huge leap, the key to success is having accurate product information. 

From grocery and hardware stores to clothing retailers and restaurants, everything flipped a switch and went “to go” immediately. Where data has not been available and accurate, the pain points became obvious quickly.  

To support a digital model – at any scale – data is mandatory. Inventory, asset tracking and location are essential, and available through a Multi-Domain Data Management platform. It goes without saying that knowledge in this case is power – knowing where your products are is the only way to manage a retail environment where supply and demand become out of balance, as they have during the coronavirus pandemic.

With demand by consumers for hand sanitizers, commercial grade cleansers, gloves and masks for personal use, multiplying by each upward swing of the COVID-19 curve, retailers are retooling what they need to restock inventory, at scale. Data management plays an important role in the ability to get these products to market faster. It’s necessary to set up the new data in ERP systems faster in order to quickly manufacture and deliver essential products.

Learning for the Future

COVID-19 is forcing retailers to become much more efficient by the day. Days were lost by not applying predictive analytics that would have triggered retailers to get more of necessary items into inventory.

U.S. retailers could have leveraged information from global companies who faced the same challenge earlier, triggering appropriate responses across supply chains. Applying predictive analytics and managing data accurately and efficiently also speaks to preparing for hurricanes and other future natural and economic disasters.  

More accurate and connected information will be key for health care organizations – along with retailers, manufacturers, and distributors – to analyze trends, manage product and supply inventories, locations, employees, and physical assets. An MDM solution can play a significant role in bringing this vision to fruition.

Kerry Young is VP, general manager at EnterWorks. Young joined EnterWorks in 2006 when Ennovative, Inc., the multi-channel publishing software company he co-founded, was acquired by EnterWorks. He brings more than 25 years of technology and business management experience to Winshuttle, having served as CTO for a subsidiary of the Dow Chemical Company, and earlier as VP, Information Technology for Marshall Industries, a $1.7 billion industrial electronics distributor. He previously managed information systems for a subsidiary of McDonnell Douglas Corporation. Young holds a B.S. degree in Computer Science from Cal Poly, San Luis Obispo and an M.B.A. from California State University Fullerton.

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