How do you measure data maturity?

For large financial services firms, good data management is critical. But how do you know you’re on the right track? In this blog post, we highlight some of the pitfalls facing organisations trying to do data management better – and how they can overcome them.


The data challenge

There is no longer a knowledge problem when it comes to data but not everyone understands that data needs to be proactively managed which is why we see varying levels of maturity – across many industries – when it comes to data management and achieving the necessary stakeholder buy-in for data management programmes. 

The sheer volume of data accumulated by financial services organisations can seem overwhelming. IBM estimates that we create 2.5 quintillion bytes of data every day and that 90% of the data in the world today has been created in the last 2 years. Aggregating, managing and monetising that data is the name of the game, but it’s frankly impossible without solid data management capabilities.

Frameworks such as the EDM Council affiliated DCAM can be used both for justification of buy-in as well as for your data maturity assessment itself. 


Be proactive, not reactive

Rather than getting on the front foot and being proactive with data management, some firms fall into the trap of reacting to situations. As the volume and complexity of datasets grow, this reactive approach simply isn’t sustainable, and problems begin to snowball.

The root cause might be operational. It’s certainly true that many organisations lack robust infrastructure and internal processes to manage data effectively. But the problem can also be cultural, with a lack of clear leadership at the C-Suite level and concomitant buy-in from teams.

Organisations need to take control of their data. Otherwise, they risk undermining confidence amongst those who rely on it to make key decisions. This pervasive self-doubt can inhibit effective strategy-making. It can also hurt growth. To stop this from happening, firms should think long-term about their data management capabilities and how a more structured and comprehensive approach can unlock value for stakeholders.


How to build your data roadmap

Enter data management maturity frameworks. 

These frameworks are designed to give organisations a clear overview of where their data maturity sits and give a good indication of what ‘good’ looks like based upon pre-existing benchmarks.

One such framework is the EDM Council-led Data Management Capability Assessment Model (DCAM) which is popular across the industry.


Deep-dive on DCAM

DCAM is an industry-standard guideline on the practice of data management, providing a standardised mechanism to measure progress in building capability. It provides a way for financial services organisations to measure their data maturity and act upon it. In other words, it helps you to understand where you are now, and where you want to be.

Here at Mudano, our data management assessments are developed and grounded in industry standards and enhanced by experience. As a DCAM accredited partner, we are able to incorporate this framework as part of our approach as we work to help clients to build their data management roadmap and accelerate their transformation in an informed, balanced and pragmatic way.

We use the DCAM framework model (as well as other frameworks) to assess data maturity for clients. We then ensure to deliver added value by recommending actions and implementing them to ensure that our clients are where they need to be in terms of their data management programmes. 


Our approach to measuring – and improving – data maturity

Our approach is simple, yet comprehensive:

  1. Assess – we partner our DCAM accredited experts with your team to perform an independent assessment through workshops and interviews.
  2. Analyse – we provide a comprehensive report containing key findings, consolidated DCAM score and recommendations, and benchmark performance against your peers.
  3. Plan – following a data-driven approach, we provide support for you to define achievable, measurable goals and a roadmap for continuous improvement.
  4. Execute – we support you to embed a consistent framework and foster a data culture across your organisation through iterative review cycles and learnings.

This multi-layered approach helps organisations to gain a deeper understanding of their data capabilities – both shortcomings and strengths. And it enables decision-makers to understand the opportunities that come with a more progressive approach to data. 


Embrace the opportunity

DCAM translates data management into a quantifiable science, introducing metrics and benchmarks that enable organisations to track and improve performance. The importance of adopting this quantitative approach to data cannot be overstated. It means organisations are able to compare their capabilities with peers and align with industry recognised practices. 

DCAM is a powerful tool for financial services organisations, enabling alignment of interests between front-line teams, management, business stakeholders, senior executives, and regulators. But it goes beyond adhering to industry best practices. DCAM helps organisations to unlock the power of their data and start seeing data management as an opportunity to drive growth, rather than an operational and reputational risk. 

It’s a hugely empowering process – perhaps it’s time you embraced it?


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