Today, companies have access to unprecedented amounts of data. The potential to derive value from data is huge, but so are the investments. In order to maximize the return on investments, companies need to have a data strategy in place.
A data strategy defines how data is acquired, stored, processed and eventually used for various business objectives. It involves identifying opportunities for leveraging data for business benefits, building data architectures and a realistic roadmap to take the company from its current state to a data driven state. It also details out the cost considerations, target operating model, and a strategy to onboard distinct business units to collaborate for mutual benefits.
A good data strategy takes into account key considerations like..
- Are we aware of business opportunities that can be tapped using data?
- Are we utilising our data to its maximum potential?
- Are we serving the right business goals and in the right sequence of priority?
- Are we ensuring that the data is secure and trustworthy?
- Are we able to extract the truth from our data?
- Are we adhering to the ethical and regulatory compliances?
- Are we getting the maximum returns on our investments?
The biggest challenge that an enterprise wide data strategy can potentially solve is that of creating awareness among fragmented businesses within the organization about the potential use-cases of data and getting them onboarded towards building a truly data-driven organization.