Five Key Elements to Driving a Data-Driven Strategy in the Enterprise

Harnessing the power of data has been a challenge for some of Australia’s largest companies over the last decade. As the digital footprint of the individual customer increases, the data captured by some industries has increased by ten-fold.

So how does an organisation look to build a strategy to take advantage of this? And what are some of the critical elements in getting a data strategy right? In partnership with Commvault and Hitachi Vantara, Innovatus Media hosted a recent roundtable that looked into this, here were the five key takeaways.

1. Data: Less Numbers, More Culture

Data strategy is more about building the right culture inside a business than getting the right technologies and Australia’s best data scientist. If there is not an inherent drive for organisations to be data-driven, data strategies will eventually become siloed.

2. Advocacy and Stewardship is Critical

Organisations need to identify the right leader for their data strategy. Too often the traditional siloes of an enterprise weigh in on data strategy as “the business” and “the technologists” look to take ownership. A steward that sits in between the business and the technologists can be a valuable tool for building momentum behind data projects.

3. Customer Trust is Critical

If your organisation is going to analyse customer data for future benefit, you have to build trust between the customer and the business. Without trust, a data-driven strategy can be perceived in a negative light by your customer base. Identifying a value-exchange, proving your data management credentials as well as being open and transparent, were identified as crucial task points to consider.

4. Don’t Start with the “Shiny Toy” Technologies

New technologies that leverage from IoT inputs and artificial intelligence have been lauded as the “next big thing” for business. However, to take advantage of the shiny new toys, you need to ensure your back of the house is in order concerning data management. Simple steps like creating a holistic data platform, ensuring correct governance, as well as knowing where all your data points are, are often more critical that leveraging the latest data science brain or SaaS AI application.

5. Take a Top-Down Approach

If your CEO is not bought in on your data management blueprint, you may already be on the backward foot. Many executives in the room linked the success of a data management project to executive sponsorship. Organisations of size need the motivation to change, and this has to come from the top of an organisation. This point opens up the question to whether C-Suite executives should be incentivised to change by their board also. The trickle effect must start from the top.