Data maturity: The 4 stages of becoming a data-driven organisation

One significant challenge today’s organisations are facing is that the rate of growth in data is outpacing the rise in value their teams can extract from it.
In almost every industry, we are collecting more information than ever before—90% of the data in existence was created in the last two years—so it should follow that more insights are being gained as a result.
This, however, is not the case for an increasing number of organisations, despite sitting on vast amounts of data and, in some cases, having the tools and technologies available to unlock it.
The crux of the challenge is in the preparedness of the people and processes within the organisation.
If they are not optimised to extract real value from data as when they need to, they can’t be part of an efficient, data-driven operation.
If they are optimised in such a way, though, they can start exhibiting the power of a data maturity model that enables sustainable business growth.
It is, by no means, an easy task to achieve data maturity as a business, but it’s certainly not impossible.
It’s a process that can be broken down into four distinct stages of data transformation:
Each step must be carefully orchestrated to move a business away from restrictive data silos and towards embracing a Data-as-a-Product (DaaP) mindset at every level.
Discover more about applying a product-first mindset to data
Let’s take a look at each stage in more detail to help you pinpoint where you might be as an organisation and determine what steps you can take next on your path to data maturity.
This is the stage at which the enormity of the opportunity becomes clear.
You may be sitting on an accumulating amount of data, but it’s difficult for your people to access it or your processes to unlock it.
You may still be working with siloed spreadsheets or self-service tools that are slow and cumbersome, thus restricting the value you could get from your data.
You may only be allowing access to your data for a small number of employees, thus denying yourself the outcomes that can come from interdepartmental collaboration.
The most important aspect of this stage is that there is a mandate to become data-driven somewhere within your organisation.
Even if your data strategy isn’t clear, there’s no data governance or the prospect of cloud is a pipedream, both the realisation of the opportunity and the desire to take action are crucial.
The next step is to install a Chief Data Officer (CDO) to transform your organisation’s relationship with data and ensure closer collaboration between business and engineering teams.
You’ll recall that the crux of the challenge lies in transforming the ways people and processes treat data, so this stage must be built on creating a change management programme to instil a data-driven culture with a product-first mindset.
This way, you can start piloting tightly-scoped data products that address user needs and begin the transition to a modern cloud data stack.
The desired outcome here is:
Once a robust data strategy has been established, an organisation can move into carving out market differentiation as a data leader.
It will have a data-driven decisioning culture at every level, enabling cross-functional product and data teams to thrive.
Each new data product will be subject to a product/market fit approach and monetisation will be on the horizon, turning data product creation into a possible revenue stream.
This stage is also where Product Owners (POs) come in and a data marketplace is established to allow ease of discovery for every team, every department and even every brand within larger organisations.
It’s when data CX reaches the levels of the digital natives and true innovation is within reach.
The last stage of the data maturity model is when a Data-as-a-Product mindset has been fully adopted and the challenges around people and processes have been overcome. Data is accessible for everyone and data products are generating profit.
By this point, the organisation has advanced to such a state that it is recognised as an innovator; its data strategy embraces AI and ML across business domains and its operational and analytical systems are fully integrated and modernised to the cloud.
It’s the optimal state, boasting a CX that’s reached the levels of the true digital natives.
Turning a mandate to become data-driven into an achievable action plan and timeline looks different for every business.
You’ll have various operational obstacles to overcome, from skills gaps to legacy platforms, but the benefits of adopting a DaaP mindset are endless.
They can be the difference between evolving into a digital leader and stagnating as a digital laggard in your industry.
To transform your relationship with data, get in touch today to discuss how our DaaP experts can help you take the next steps towards data maturity