Data-first modernisation requires hardware, software, and service changes to process and analyse data, but these are only a few links in the chain.

True modernisation depends on cultural change – changes in attitudes towards data and a deep understanding of the value of data. This starts from the top down and usually requires changes to the Chief Data Officer (CDO) role. These changes won’t happen overnight, but there are four main steps you can take to put your enterprise on the right track.

  1. Create a CXO-driven data strategy

The Chief Experience Officer’s primary role is to refine customer experiences using deep analytics and data. In other words – to create value from data. This makes their role in data-driven transformation critical to operational success.

Your data strategy should focus on experience and value, considering how to quantify the value of different types of information and leverage the skills of data officers. People with expertise in data analytics, data management, information security, and algorithms should be on a governance committee to oversee the strategy.

  1. Embrace data truths

Here are some truths about data:

  • Data is valuable
  • Data is a core asset
  • Data has gravity
  • Data has rights
  • Data fuels operating models
  • Criminals target data (and the people who manage it)

These fundamental points are critical to your data-first modernisation, defining how you approach data (extracting value, verification), manage data (security, processing), store data (security, access), and use data (business objectives).

  1. Determine the ideal level of data-first maturity

It isn’t enough to identify where you are in your data-first modernisation – you also need to determine where you can go.

There are five levels of maturity:

  • Ad-hoc – no or minimal data standards and management
  • Adapting – governance and management policies; some standardisation
  • Cloud-enabled – data lifecycle management
  • Optimised – data is fully accessible, portable, and secure
  • Maximised – enterprise-wide AI, automation; no manual intervention.

Which stage can you get to? Cloud-enabled is a realistic goal for most enterprises, but most should aim for Optimised.

  1. Prioritise your investments

Data-first modernisation requires significant technological investment to shift skills, processes, and practices to the machine. It’s easy to sink money into the wrong avenue and waste time in areas that deliver no value.

Here are the investments we recommend (in order)

  • Data and governance strategy
  • Data knowledge and awareness training
  • Data lifecycle management (technologies that manage, retain, and protect data)
  • Data security (authenticating, verifying, encrypting, and securing server-level data)

Take these four steps to data-first modernisation, and you will be ahead of most enterprises in your industry.