3 Ways to Think About Data Post-COVID-19
Understanding your customers, employees, and market might make the difference between flourishing and going out of business during a crisis.
- By Joe DosSantos
- July 9, 2020
It’s no secret that companies with superior data management and analytics skills have outpaced their competitors for years. However, in 2020, amidst a global pandemic with political and financial instability, understanding your customers, your employees, and your market might be the difference between positioning your company to flourish and grow in the new normal or being out of business. As the world continues to navigate the implications of COVID-19, it’s time to think about how to accelerate your company’s analytics strategy.
As a starting point, I present three questions that executives should be asking.
1. Is the data I need available when a crisis hits?
Data is everywhere, but the lingering paradox is that with all of this data, leaders still struggle to make sense of it and turn data to insights and action. Much of the data that can guide decisions and actions isn’t analytics-ready or accessible. Other data sets have vague or complex security rules that block access to key data exactly when it is most needed.
There are lots of abstract discussions around the power of analytics to make an impact in today’s world. However, a crisis is not the time to figure out that you don’t know where the data is and you don’t have a policy that governs how to distribute it in a way that is respectful of sensitive information.
Much like acquiring an insurance policy, it is essential to think carefully and protect yourself well in advance of the actual moment of crisis. For COVID-19, executives are looking at employee and real estate data to craft work-from-home policies, developing financial scenarios based on sales forecasts, and evaluating third-party financial and governmental policy data.
How did your company do at putting your fingers on information that perhaps only weeks before was not particularly useful? Are you ready for the next crisis? If not, focus on establishing a clear use-case-based catalog of data now. Be able to acquire, profile, describe, secure, and potentially prepare data quickly in anticipation of analytics needs. A key concept here is data on demand for analytics. Processes should be robust to put data on the shelves in advance of the analytics execution, which requires speed measured in hours rather than weeks for data integration and cataloging.
Data governance in this context is not about torturing data into truth, but rather clearly defining, classifying, and provisioning data assets to people authorized to see them at speed and scale. Doing this correctly will balance accessibility and security with clear rules that are ready when your company needs them most.
2. In my company, is data still only for nerds or is it a topic in the C-suite?
There have always been data experts who crunch numbers for organizations, but now we need a brand of data-literate executive who understands modern data and analytics concepts. Gone are the days of presenting simple, descriptive bar charts of last month’s performance in the same monthly format. Executives now crave a deeper understanding of data with predictive modeling to assist in making critical decisions.
Unfortunately, analytics is still trapped in many organizations because modern analytics approaches such as machine learning and artificial intelligence have been painted as too techy, leading executives to base their analytics strategy on technology alone. Executives must focus on connecting strategy to executable moments that can be enhanced through data and lead from the top down in instilling the use of data for decision making through analytics.
Organizations need to cultivate data-literate employees who will contribute more to their roles and help businesses sharpen their competitive edge in an aggressive global economy. It’s a strategy that can transform your business while building loyalty with a workforce that’s energized and empowered by your investment in their professional development.
It’s not just businesses that rely on data -- it’s the entire world. We’ve seen doctors, government officials, and business leaders make decisions using data during this crisis. New data maps and world meters are popping up all the time and we’re hearing phrases such as “bend the curve” at press conferences and in reports. Data literacy’s importance is clearer than ever, and creating an opportunity through both technology and training to increase data literacy will help drive efficiencies and uncover new opportunities that can fuel recovery.
3. Can my organization turn insights into actions quickly?
Certainly, deploying an effective analytics strategy requires data and analytics skills. One skill that often goes unnoticed is the ability to deploy analytics solutions to the processes and applications that need them at speed. DataOps is the emerging practice that takes a DevOps approach to data by addressing the people, process, and technology challenges to creating a data culture.
The organization needs to ask a number of questions: Is the analytics performant in real time? Is it clearly embedded in an application in a seamless way? Is the analytics having the desired impact? Should we change our approach? Is the challenge one of concept, analytics utility, or deployment option? This closed-loop process will provide a critical link back to the nontechnical community and allow for clear measurement.
Let’s keep it real -- this is not easy. There are significant cultural, procedural, political, and technical challenges in achieving this goal. However, having a clear vision of the goal line with language that's business-focused rather than technology-focused will most certainly accelerate this journey.
There has never been a better time to put your strategy into practice and empower your organization with data. Companies who will come out on top are the ones who embrace innovative approaches to this crisis. That will require you to think about data differently. Leaders will place more emphasis on understanding one of their biggest assets -- data -- and how they empower their other biggest asset -- people -- to work with and use data for better outcomes.
Joe is responsible for the alignment of business and technology to deploy the third generation of business intelligence at Qlik to enable meaningful data and analytics insights across the business. He is responsible for use case prioritization, DataOps methodology, and the deployment of information management systems, including all of Qlik’s data integration and data analytics products. He also provides thought leadership in modern data architecture, data governance, and data literacy, and serves as an evangelist at major conferences and events.
Prior to Qlik, Joe was the vice president of Enterprise Information Management Technology Services at TD Bank Group. In this capacity, he was responsible for enterprise technology required for the management, transformation, and analysis of information across the bank. He led the delivery of an enterprise data lake that included a metadata-driven catalog and data-as-a-service experience, Hadoop native ETL, and next generation reporting, analytics, and artificial intelligence solutions. He was also responsible for master data management, data governance, and data warehousing tooling.
Prior to joining TD Bank, Joe led the Big Data Consulting Practice for EMC Corporation’s Professional Services Organization, solving innovative client analytics challenges such as energy theft detection, geolocation analytics for telecommunications and gaming companies, as well as consumer analytics for financial services clients. He also developed the value engineering team for master data management solution provider Siperian (now Informatica) and spent the first decade of his career at Accenture, largely deploying ERP and data warehouse solutions to high-tech manufacturers.
Joe holds a BSBA in marketing/international business from Georgetown University.