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The generic approach to Digital Maturity

Digital maturity is a measure of how well companies can identify how their digital assets can help them. The digital assets not only include the data held by the company but also covers the technological assets and staff.

The NESTA datavores program seeks to explore how local authorities can use data to drive better value for local people and communities. It is driven by the need for local councils to save money based on the tightening budgets as a result of the austerity drive from central government. The concept is simple. The framework gives guidelines on how to move from a simplistic digital presence, such as a website and a separate social media presence, to an all-encompassing holistic view of the customer in both the online and offline world.

The Forrester Data Maturity Model, which could form part of the digital transformation, stresses the importance of the foundation aspect of buy in from management. Senior management needs to support the incentive – giving resources in ensure the project is successful. The road map from unaware or basic to fully mastered and engaged requires the project plan to aid with understanding the challenges that will be faced, the skills required and the tools needed.

There are a number of maturity models which provide some form of framework enabling companies to rank the quality and automation of data. This can be attractive to businesses as the measure can reassure management that progress is being made to a perceived data nirvana. The measurements of digital maturity are defined below:
Unaware – Not interested and do not invest in data and analytics.
Nascent – Some awareness with little investment in data. Use data for historic analysis.
Learning – Know data is important but small investment.
Developing – Becoming engaged and supportive.
Mastering – Bridging online and offline views of customer.

A social sector data maturity model was developed by Data Orchard and Data Kind. This model was designed purely for the social sector with the aim of helping organisations gain more from the data they hold.

The concept backing up all digital maturity models is to allow for the data which is collected to be trusted, cleaned and relevant. Once complete the data can then be used for predictive analytics allowing the organisation to become more proactive rather than reactive. The idea is that with good data going into the model good results will come out.

Blog post by Richard Skeggs (Senior Research Data Manager at the Business and Local Government Data Research Centre), please email us if you have any questions about the contents of this post.

Published 26 July 2017