5 Levels of Digital Government Maturity

November 06, 2017

Contributor: Rob van der Meulen

These levels help CIOs improve the quality of digital government services for citizens.

Choosing the direction of digital transformation, communicating that vision, and justifying the necessary budget requests are the biggest new challenges for modern CIOs. This applies equally to public sector CIOs. Overcoming these challenges requires a step-by-step strategy that is both affordable and sustainable.

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“ By level 5, the process of digital innovation using open data is embedded deeply across the entire government”

Speaking at Gartner Symposium/ITxpo in Barcelona, Andrea Di Maio managing vice president at Gartner, said that the vast majority of digital government strategies that Gartner evaluates are just modestly updated versions of a prior e-government strategy.

"We assess digital government maturity by examining the extent to which organizations use data effectively to redesign services and deliver new ones, as well as to transform and manage operations," said Di Maio. “Government leaders must replace their focus on services with a data-oriented mindset to truly transform government with new technologies such as artificial intelligence and the Internet of Things.”

Di Maio recommended that government CIOs use Gartner’s 5 level maturity model to help plot their digital business strategy and communicate it to key policymakers and stakeholders.

Level 1 — Initial (E-Government)

At this level, the focus is on moving services online for user convenience and cost savings, but data and its uses are siloed and extremely limited. “If the organizational view is that a high percentage of online services or mobile access represents a modern digital government, then more education and advocacy is needed to show what real digital government looks like, and its benefits,” said Di Maio. “To make the case for advancement, create case studies explaining how digital transformation will ease or remove high-priority pain points for the organization.”

Level 2 — Developing (Open)

Level 2 is not necessarily subsequent to level 1. E-government and open government programs often coexist, with different leadership and priorities. Open government often takes the form of public-facing programs intended to promote transparency, citizen engagement and the data economy. Examples we see today are nascent open data initiatives, often in the context of smart city programs such as the Copenhagen Data Exchange.

Level 3 — Defined (Data-Centric)

On this level the focus shifts from simply listening to citizen or user needs to proactively exploring the new possibilities inherent in strategically collecting and leveraging data. The key performance indicators here are “how much of our data is open?” and “how many of our applications are built on open data?” It’s tempting at this point to engage in vanity projects or skip ahead before the proper groundwork is laid; it’s paramount to remain focused on designing and implementing data-centric strategies and processes.

Level 4 — Managed (Fully Digital)

By this level, the organization, agency or department has fully committed to a data-centric approach to improving government, and the preferred approach to innovation is based on open data principles. Data flows regularly across organizational boundaries, leading to easier interactions and better services for constituents. It’s possible at this stage to encounter privacy-related backlashes, as citizens can be uncomfortable with how their data is being collected and used. Therefore, it is important to ensure that data is used within existing norms and regulations, and that this is clearly communicated.

Level 5 — Optimizing (Smart)

At this point, the process of digital innovation using open data is embedded deeply across the entire government, with buy in and leadership from the top tier of policymakers. The innovation process is predictable and repeatable, even in the face of disruptions or sudden events that require rapid responses.



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