Maturity assessment

A maturity assessment provides stakeholders with a good understanding of the current digitalization landscape providing clarity to identify strengths and opportunities for improvement. Based on that assessment, governments are better positioned to establish policy priorities to reach higher maturity levels.

This section provides references to different maturity assessment approaches stemming from the public sector, the private sector and academia.

1. Government

The Digital Maturity Assessment is designed to help governments worldwide assess their readiness to undertake digital transformation. It defines five maturity levels:

  1. Digitally Nascent

  2. Digitally Emerging

  3. Digitally Agile and Integrated

  4. Digitally transformed

  5. Digitally Innovative

The UNDP Digital Maturity Assessment can be used to evaluate the current potential for digital government across six key pillars that include: Technology and Solutions, Policy and Regulations, Skills and Capacity Building, User Centricity, Service Definition and Delivery, Institutional Framework, and Collaboration.

As in the case of Lao PDR, it was used to evaluate how ICT solutions in government can continue to improve operational efficiency and user satisfaction.

2. Private Sector

Gartner (2017) assesses 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.

Gartner’s 5 level maturity model includes:

Level 1: Initial (E-Government)

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)

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)

Defined (Data-Centric)

At 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)

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.

Stage 5: Optimizing (Smart)

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.

3. Academia

Comparing and Contrasting e-Government Maturity Models: A Qualitative-Meta Synthesis (Almuftah, Weerakkody, and Sivarajah 2016) article compares 17 different e-government models. It emphasizes that most models have three main stages that capture the following dimensions: presence, communication, and integration. The table below shows the mapping of each model’s stage to the three proposed main stages (presence, communication, and integration).

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