How can the framework help you?

How to find the resources you need to improve data maturity.

Provide clarity and structure

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Demystify concepts surrounding this topic by using clear language, visualisation and providing structure.

Approach

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Link the topics covered to your strategic goals and encourage the view of managing data as an asset.

People before technology

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Encourage the view of technology as an enabler focusing on strategic vision and the role of people first.

Baseline

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Help you understand what a foundation level for data maturity is and why this is important to achieve.

Asssessment and roadmap

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Support an honest appraisal of data maturity through self-assessment and five levels of maturity.

Culture

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Encourage you to understand your organisation before you try to improve it.

Risks

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Help you engage your colleagues in recognising the risks related to low data maturity.

Key points

Ideally, developing maturity would be a sequential activity and this is how the framework is presented.

However, the world is imperfect, and it is rarely possible to make progress in this way. While an overarching sense of direction is important, delivery is likely to be about taking opportunities where and when you can, but within the context of an overall plan.

  • Doing is generally more impactful than talking. Try to find a way to demonstrate value, preferably in a high priority area like student experience, to make the argument and gain engagement from colleagues.
  • Ad hoc activity allows you to test ideas, and it can appear agile in responsiveness to demand. However, it rarely delivers consistency and can be time intensive and inefficient, particularly at scale. Enterprise thinking can be challenging, but considering what will work across business areas will help you find solutions that will create standards and structure, rather than compounding siloed working practices.
  • Embedding good practices using a framework or defining individual roles can provide a structure for initiatives but be wary of mistaking process for progress
  • Domain activity is a challenging concept as it often sits across several functional areas, particularly in larger institutions. Clear requirements, driven by strategic priorities, or by an area that feels achievable, ensure you can focus on the data that is needed for a specific issue and start to build your data model from there.

Well-considered data architecture is critical.

  • Do you know what your fields mean?
  • Have you agreed what a student or an employee is?
  • Is your data stored at the most granular level, so that it can be mapped and aggregated or grouped for multiple purposes, both strategic and operational?

Bringing people with you

Embedding new processes, driving accountability and realising the benefits of good data management is difficult. The biggest challenge is likely to be defining, implementing and embedding a structure to ensure accountability for data as an asset. This is a slow evolution and all about organisational change.

Other priorities are likely to be:

  • Developing customer focused reporting provision by helping people think about what they need (information) rather than what they want (data).
  • Demystifying concepts and processes most notably translating between technical and business or customer facing functions.
  • Understanding and accepting different personas so that you can manage their expectations effectively.
ChampionsFind your allies
Early adoptersDeliver what you say you will and get their input.
Move graduallyBe patient, consistent and manage your communications.
Never changeAccept but manage misinformation.

Investment

It may be possible to make progress with existing teams and structures but you may need investment to develop roles or a function or you may need to find time for individuals away from business as usual. Getting support for data management activities is typically challenging and may need carrot, stick and a bit of opportunism.

Defensive levers (risk and compliance)Offensive levers (opportunity and value)
StatutoryData as an asset
Information governance and auditEfficiencies
Opportunism - new systems (will things break?)Opportunism - student wellbeing (a critical driver)

Quick wins can help make your case – and there may be pressure to deliver them. But be mindful - they should support your vision, not undermine foundational work.

Stakeholders

Each element of data maturity is owned by an area of the university, college or provider. Consultation, communication and support are essential to deliver effective services. Establishing responsibilities that work for your organisation is a crucial part of data management.

Next section: stakeholders