What Data Taught Us in 2020 and How It Should Shape 2021

In 2020, companies across every industry were impacted by the COVID-19 pandemic. As a result, many new business models emerged, including curbside deliveries, contactless-service, and virtual fitness training, to name a few. We also saw people further their education, pick up new hobbies, and learn to cook—all from the safety of their own homes. With 2021 well underway, let's take a look at the new habits that we can expect to endure even after the pandemic is over.

Although 2020 needs much more in-depth analysis, here are the top data-related learnings from the past year: 

  • Responsiveness Equaled Survival. Businesses always talk about agility and flexibility. Last year was the one to prove it. Businesses were forced to think about retaining and serving their customers in new ways, and time was of the essence. Organizations with the right data strategy were able to make quick data-driven decisions to adjust their organization, systems, and processes for new needs and customer expectations.
  • Sales and Marketing Were Put to the Test. So you said you were data-driven? Again, 2020 was the year to prove it. Sales teams had no physical access to their customers. Office phone numbers were no longer in use. Marketing groups had budgets cut and had to rely on the data to optimize their spending and connect with buyers in new ways. Teams had to move from Visual Flying to Instrument Flying techniques. Companies with a higher quality of data—consistent, clean, and consolidated—had competitive advantage.
  • Digital Came to the Forefront. In-person access to customers became limited; retailers could not offer store samples or tester products. Data innovators found ways to shift to digital. Online interaction by representatives and coaches to serve the customers became a norm. 
  • Data Became the Pulse of Healthcare. Access to data is the driving force in life sciences. Organizing clinical information, selecting sites, subjects, and investigators, and ultimately finding cures and vaccines for COVID, is all about data management. Similarly, healthcare providers relied on data to manage increasing admittance rates by analyzing their capacities, ordering the right supplies, scheduling equipment, prioritizing patients, and using telemedicine. 
  • Data Privacy and Ownership Were Still a Concern. Although we have made data privacy progress, consumers are asking for more. We saw many state measures on the ballot this year, including California’s Consumer Personal Information law and Agency Initiative augmenting CCPA, Michigan’s protection against unlawful searches, and Massachusetts “Right to Repair."
  • The Power of Cloud Became Evident. If there was any doubt, 2020 confirmed that enterprises’ survival depends on their cloud strategy. Cloud-first businesses thrived, and businesses with cloud strategies pivoted faster than their peers. And I hope we all realize that having the right cloud strategy is not about cost optimizations. It is about agility and speed.

So, what can we expect in the coming months? Moving to the cloud and access to data will remain crucial and determine an organization’s ability to succeed in the coming years. Here are a few things that we can expect in the next twelve to eighteen months.

  • Cutting the Data Shackles. Data is not for collecting or reporting. Data is for making decisions, fueling innovation, and a currency to determine any product or service value. We will see organizations making more concerted efforts to make data available across functional groups to bring consistency in operations. We’ll see companies opening their data to partners in data exchanges, and making their data available to other companies via Data as a Service. Why shouldn’t Novartis, Clorox, and Estee Lauder exchange information on biomarkers for skin allergies? Why can’t Comcast, Best Buy, and Kaiser Permanente share information to foster human wellness?
  • Data Privacy Awareness. Your right to your data will strengthen. Technology will support that. As data moves across departments, across companies, across international borders, we’ll have mechanisms in place to ensure privacy. Businesses will need to consider tools for data anonymization, tokenization, PII identification, masking, generalization, randomization, and perturbation. Maintaining the data lineage and traceability back to the exact source and point in time will be critical.
  • Data for Artificial Intelligence and Machine Learning. The past 12 months produced more data scientists than the last 5 years. LinkedIn proiles are constantly being updated with information about individuals completing classes and certificates on ML and its business applications. This is fantastic news. The more people realize the value of AI and ML, the faster the innovation will be.

To take this one step further, could AI/ML on its own be a business’ unique differentiator? AI platforms and ML algorithms are commodities today. Available for free! So, who will have the advantage? People who have the data and the domain expertise of using that data. Read that again. It’s time to take data science out of the science lab and into the real world.

  • Leveraging Data in Motion.  If your data operations look something like: Collect the data >, organize the data > analyze the data > generate the reports > make decisions, then you are already behind and destined for failure. Your competition is moving much faster. They are not doing weekly syncs of master data and producing quarterly reports. They are capturing, organizing, and moving data at high speeds to make business decisions in any instance. They are impacting the customer experience at the point of engagement. Think high-speed algorithmic trading but happening at Amazon.com or Walmart marketplaces. Data must enable real-time operations.
  • Understanding Data Quality for Fast Data. When the data is moving fast, your data quality tools should catch up as well. After all, garbage in garbage out. Quality of data determines the effectiveness of decisions. Technology must adjust to the data in motion. You can no longer rely on tools that clean up and dedupe static data. Your system must identify issues, anomalies, and risks for the data in motion. Data observability for anomaly detection and instantaneous root cause identification will become critical. Fraud, revenue leakages, poor customer service, inventory stockouts, bots clicking on your emails, all benefit from early detection.
  • Data to Demonstrate Values: Values-driven customers have been on the rise. Customers will reward the organizations that align with their beliefs and values. Lip service will not be enough; customers will ask for the data. Organic, Vegan, Fair Trade, Diverse, Socially Responsible, Charitable, Inclusive—companies will no longer be able to use these words casually. They will have to demonstrate values with data. Organizations that can demonstrate data lineage that traces supply chains or show data on inclusive and diverse recruitments and enrollments will have a competitive advantage.

With several successful vaccines now being administered, let’s look at how companies leading in data management strategies came to the forefront and did things like restocking retail shelves or pivoting to produce sanitizers rather than cosmetics. Let’s acknowledge how businesses adapted from in-store to online, from sit-down to curbside. Let’s applaud that they were able to expedite the clinical trials and coordinate efforts across the globe. Data will continue to be a competitive advantage, a driver of customer experience as we move forward. An agile, responsive data strategy will determine success.

May the data be with you!


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