Having compared digital transformation in the private and public sector over many years, a number of lessons can be drawn from the experience of commercial businesses. These can be applied as best practice to the needs of public sector bodies undergoing business change often with poor legacy systems, deep organizational silos and a lack of effective cloud strategy and infrastructure.

First, define and understand the problem. 

Digital transformation – the use of digital technology to solve problems – is now more relevant than ever in the public sector given continued resource constraints and the impact of the coronavirus pandemic on public service provision. However, many organizations fail to appreciate that data transformation underpins most business and digital change.

Second, ensure clarity and decisiveness in digital transformation.

 The data maturity model charts the stages of data utilization within an organization as it moves through digital transformation.  Organizations begin at the “no data stage”, with very little known or useful data for information-based insights and decision making. However, as we live in a digital age, almost as soon as they start exploring their data they are inundated with it. At this point they almost immediately find themselves in the “big data stage”, which is a double edged sword for most organizations. They need to make the most of data sources, data silos and scripted transfers, which can be challenging, so decision making continues to be based on little or no useful information. Once organizations begin to create standardized sets of data, interfaces and reporting, and corporate taxonomy and metadata, they move into the “quality data stage”. In this phase, decision making can begin to be based on explainable data. There follows the “predictive stage”, when data is used to make all critical business decisions,​ and predictive and retroactive analysis can be performed, and finally the “strategic stage”, when data is fully embedded in all processes and all decision making is based on analytic data.

Once public sector bodies define the problem and understand the implications of the digital maturity model, they can take the third and final step – plan their approach and implement the program. Agile approaches to software development are particularly powerful in managing digital transformation.  They involve a continuous assessment and adaptation of work, and the division of tasks into short phases of work, to identify and achieve quick wins while planning and implementing longer term data transformation. This pragmatic and iterative process ensures that outcomes are defined and executed â€śas you go”, rather than committing huge amounts of time and resources without delivery â€“ or worse still waiting until the end to deliver something which may not be the right solution. Agile is well suited to managing intractable public sector technology and organization challenges, such as workflow continuity, skyrocketing quantities of data and the governance and security concerns that arise as government expands cloud adoption â€“ and moves data across a wide range of public and private clouds and on-premise infrastructure.

Public sector bodies can adopt this digital transformation framework to effectively manage business change in an increasingly complex, unpredictable and cost constrained environment

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