Digital transformation is a 20th century phenomena. As an early adopter of new technologies – and the digital age – I quickly embraced digital data structures and tend to think in data matrices, looking for the data keys to join data and discover new patterns.
When I look to create a new product or insight, my mind asks the following questions: What information is required to provide the signal that an individual or company needs to make a decision or provide insights? How is that unit of information integrated with other information? How quickly can I get that piece of data from collection to derive insights? What are the keys that allow us to tell a story?
Computers, smartphones, sensors, the internet, networks, and edge computing are just some of the technologies that enable our digital life. More significantly, they provide access to data – good and bad. But just because data seems ubiquitous and BIG does not mean it is easy to innovate or disrupt. With this much data and the ability to use more advanced technology to derive value, we often assume that our jobs get easier. However, figuring out what data matters or how to capture its value gets more challenging.
Digital innovation within your organization or industry can be smoother if you keep a few things in mind as you develop your strategy:
- Think and behave digitally: Take the extra time to ensure that you provide context when generating data, ensure it is digitally accessible to others, and key data is retained.
- Define the use case: What are you trying to solve? People often ask you to innovate and tell you what they want you to do without telling you what they are trying to achieve.
- Find and/or create the smart data: Just because you have the data doesn’t mean it can provide value. You may need to clean, standardize, and connect it to other data before creating value.
- Don’t boil the ocean: Start simply. You don’t need to create an ensemble of ML models if simple regressions suffice. Live by the adage of ‘crawl, walk, run.’ Crawl with a proof of concept that may not be digitized but can be repeated. Walk with a digitized, repeatable solution that may require a manual start or manually changing parameters. Run when you have proven the use case and want to scale and improve.
Lauren S. Moores is a serial startup data innovator, advisor, and strategist. A Digital Innovation Leader, Teaching Fellow at Harvard Business Analytics Program, and USA for UNHCR Hive Advisory Board, Lauren also has over 25 years of experience creating strategy and data platforms for many companies using data, multi-media, and emerging technology to create and capture value.
