In a recent piece on digital transformation initiatives, eWEEK’s Chris Preimesberger writes, “As in any important undertaking, caution should be observed [and] there are some easy-to-overlook missteps that should be avoided during that journey.”
Read on to learn more about four common digital transformation mistakes that companies make, and tips on how they can be circumvented:
- Moving to the cloud without a clear plan. Preimesberger states, “Simply migrating your infrastructure to the cloud won’t make your legacy applications agile, scalable, and intelligent. Once you move to the cloud, the meter is always running.” It’s important to have a clear objective, a roadmap for achieving it, and an understanding of the resources involved before taking any action.
- Rewriting your legacy apps from scratch. Rather than starting from zero with updating legacy applications for the digital world, Preimesberger urges companies to keep the app intact and place it in a modern foundation. By doing so, “you preserve the interface and business logic that is the secret sauce of your company and prevent embarking on an expensive, lengthy, and risky project.”
- Abandoning SQL applications in favor of the NoSQL database. Replacing a SQL database with a NoSQL one can easily cause a project’s scope to snowball and also increases its rate of risk. Because NoSQL databases lack full SQL support, organizations need to rewrite a large amount of code, and it can be difficult to find talented NoSQL developers. In addition, Preimesberger cautions, “NoSQL systems typically excel at short-running operational queries, but their performance on analytical queries can be poor and not up to par to meet the application’s needs.”
- Relegating data science to a backroom activity. The APEX of Innovation offers numerous examples of why this is a huge digital transformation no-no. One reason, as noted by Preimesberger, is that in order to build an intelligent application capable of delivering actionable business insight, it’s essential that domain experts are included in the development process. As he puts it, “Data science is a team sport that needs representation from [data science, data engineering and application development teams] working side by side with people who have a solid understanding of the business.”
If you recognize your company in any of the mistakes outlined above, don’t panic. Digital transformation is the ultimate endurance race, in which the most important thing is the ability to quickly course correct should you get off track.