Digital transformation involves the use of new technology to address business problems, and includes initiatives such as cloud computing, electronic data interchange, blockchain, artificial intelligence-powered technologies, and much more.
Gartner says the fundamental accelerator for digital transformation is a company’s competency and analytics, and by 2022, almost 90% of business strategies will explicitly treat information as an important asset and analytics is a robust competency.
Alarmingly, Forbes identifies that almost seven out of eight digital transformation initiatives fail. This blog post will help us identify reasons what they’re doing wrong – and what steps can be taken to get it right.
Business leaders around the world believe that companies need a well-executed data strategy to drive digital transformation initiates. In the absence of a robust data strategy, digital transformation efforts would go into vain.
Though for every company, the strategy can be different, there are some steps that are common.
Let’s know how each of the steps mentioned above can help you successfully execute your digital transformation.
As per Mckinsey, a lot of organizations begin their journey of analytics by finding out what data they have and where it can be applied in business.
But this school of thought is not scalable. Companies must get their resources ready to identify the decision-making processes they could enhance in order to produce additional value in the context of their overall strategy.
Data underpins all digital transformation initiatives. However, with big data revolution, using data to kick start transformation is not easy should a proper data integration platform is not in place. Companies need a next-gen integration solution to integrate large volumes of information in a unified database wherein, it can be used to make confident decisions through the extracted insights. With functionalities like pre-built templates, monitoring dashboard, application connectors etc., organizations can easily integrate data with speed and precision. In addition, some data integration solutions offer self-service functionalities that enable all business users collate data without IT support – to facilitate faster decision-making and ultimately make them easier to do business with.
When the data is integrated, users must be able to extract value out of it so that they can make accurate decisions. Self-service integration tools ease this analysis step as IT teams or developers become free to handle issues or cases that require more expertise, thus streamlining innovation.
Ergo, organizations can leverage these steps and align them with their existing data strategy to drive digital transformation.