Companies often spend millions on digital-transformation initiatives without seeing any return on the investment. In fact, 70 percent of digital-transformation projects are expected to fail. Effective digital transformation is dynamic and includes people, IoT machines, , and a lot of IT systems cleanup. Once “transformed,” continuous monitoring and intervention are typically necessary to keep data clean and usable.
But, at the end of the day, did your digital transformation make you more customer centric? Are you able to see a clear view of all of your data in one place? Can you trust the data? Are you willing to make bet-the-company decisions based on what your dashboards display?
Successful digital transformation must drive operational efficiency and boost customer engagement. But legacy data management systems are not equipped to manage new types of data, such as IoT data, along with traditional ERP and CRM data. Because of that, data remains in silos and overall analytics views of a company’s data are not available. Selecting the wrong technology is a root cause of this failure.
Digital transformation must include a nimble solution to manage the data effectively. “Nimble” means
- no infrastructure change or investment required;
- deployment in days;
- connection to everything, with all sources, systems, data ( both traditional and new types) managed together;
- a single centralized view of data health updated in real time.
Data management must begin with data accuracy, because without accuracy, data cannot be trusted. Data must be accurate in each source and then combined into a consistent record available to the entire business, so that everyone operates from the same set of facts. Data health must be readily viewable for all data globally across an enterprise, so that trust is established. Only then can management trust that bet-the-company decisions are based on accurate real-time data.