Data and evaluation in Government services, Part IV:
Data Training and Culture Uplift

This article is Part IV of a four-part series on data and evaluation in government services – see Part I, Part II and Part III for additional information on this topic.

In Part III of this series of articles we discussed the process of data and digital uplift to meet the commitments made by the Australian Government in the Data and Digital Government Strategy (DDGS) and Implementation Plan. Full data and digital uplift also requires parallel uplift in training and “data culture” to ensure that staff have the skills and cultural mindset required to “deliver simple, secure and connected public services, for all people and business, through world class data and digital capabilities.”¹

Data training and culture uplift

Irrespective of the particulars of the data and digital uplift, it will also be necessary to ensure that staff skills and work practices maintain pace with uplifted service needs. To ensure this, Australian Government entities should conduct training and culture uplift to update and improve data and digital training for staff, and put practices in place for the development and maintenance of an innovative and data-savvy culture. Focus should be on the development and maintenance of in-house capabilities to rely less on outside consultants in the long-term. Some aspects of data training and data culture are direct requirements under the mission outcomes in the DDGS (e.g., building a data and digital-capable APS and growing APS maturity²) but other aspects are secondary requirements that will be needed to aid in the implementation of other missions and initiatives.

In some organisations, the required uplift of data and digital systems is not the largest impediment to improved use of data. In some cases it may be a greater hurdle to impart data skills to staff and to foster an environment where staff habitually seek out and use data for insight and decision-making. Having a data-driven culture means that there is a general ethos that prioritises the sourcing and use of relevant information (systematically collected as data) to aid in insight and decision-making wherever possible. This ethos is supported by training and skill uplift that allow staff to develop their data capabilities and have a long-term pathway to the successful use of data in their work role.

Data training and culture uplift is the third part of the overall process of implementing the DDGS, as described in Part I of this series of articles. Depending on the operational requirements of a particular Australian government entity, data training and culture uplift will usually occur after the uplift of data and digital systems and processes. This is so that the underlying systems and processes are more stable once the training and cultural uplift begins, to minimise disruption and supplanting of training topics and processes. (In some cases it is possible to do parts of the data training and cultural uplift in parallel with data and digital uplift, and this may have benefits in some cases.) Since organisations typically have some existing data and digital training in place, the training and culture uplift will typically build on existing systems and processes.

Data and digital training

Following (or in parallel with) a data and digital uplift, Australian Government entities should conduct data and digital training to uplift the skills of their staff to ensure that they are able to make appropriate use of data and digital systems and processes to allow them to consistently implement each of the commitments of the Australian Government in the DDGS. Depending on the existing skills and training processes in the organisation, this might require uplift of a range of data and digital training programs and processes:

• training in data governance and management;
• training in data stewardship;
• training in processes for sourcing data;
• training in processes for creating and maintaining reference and master data;
• training in processes for recording and tracking metadata;
• training in processes for document and content management;
• training in data quality and quality assurance processes;
• training in privacy and ethics processes for data systems/processes;
• training in data security and review processes for data access;
• training in data extraction, validation, wrangling and, transformation;
• training in research design and data sampling;
• training in data modelling and analysis;
• training in statistical methods and machine learning/AI;
• training in data visualisation and business intelligence;
• training in using for economic valuation of programs and services; and
• training in specific internal or public-facing data and digital platforms.

Specific areas for data and digital training will need to be informed by the DDGS mapping that examines the application of DDGS requirements to the operations of the entity at issue. It may also be informed by training practices and materials used in educational institutions and other relevant organisations.

Data culture uplift

Data culture uplift goes beyond the skills/training of staff in an organisation. It refers to the broader ethos of data usage in ordinary business operations and decision-making. By systematically sourcing relevant information, reducing it to useable data, and prioritising use of data in processes and decisions, an organisation can foster a data-driven culture that improves decisions and realises value from available information. A data-driven culture also supports staff with a long-term pathway to the successful use of data in their work role.

ACIL Allen has developed a data culture approach based on four key pillars: leadership and change management, empowering users (internal and external); fostering data-oriented communication; and evaluation and value realisation. These four pillars of good data and digital culture are illustrated below in Figure 1. The pillars provide overarching objectives that augment specific data and digital training; these objectives should inform and be built into training on specific data and digital issues.

 Figure 1: ACIL Allen data culture pillars

Data training should be based on educational best-practice

Data training in business and government organisations is oriented towards developing practical skills that will aid the realisation of value in the organisation. This differs from comprehensive scholarly and professional education and training conducted through university degree programs. Nevertheless, applied data training in Australian government organisations should be based on a sound understanding of underlying theory, including the foundations and mechanisms for data science, and relevant statistical theory and computational theory. Modern data science and corresponding evaluation processes involve the intersection of several highly complex areas of scientific practice (computer science, mathematics, statistics, probability, economics, etc.). Consequently, training will often have multidisciplinary inputs and may involve integration and synthesis of ideas across multiple domains.

Delivery of training should be conducted by data experts with comprehensive knowledge of data science and underlying statistical theory. This ensures that practical data skills are based on sound statistical practice and that any data modelling is undergirded by a proper understanding of the internal model dynamics and theory. The best experts for delivery of data training will typically be professional statisticians, data scientists, or economists (in some cases also practitioners of other sciences that use statistics and data heavily).

Organisations have a range of options available both for curriculum development and provision of training. Organisations may develop bespoke internal curricula designed to be optimal to organisation needs, or they may use external curricula for a more general training program. Similarly, organisations may provide their own internal training, or they may refer staff to external training providers (e.g., universities, online providers, external consultants who deliver in-house training, etc.). Often organisations will adopt a mixture of these methods, involving some internal curricula and training provision and some external curricula and training provision. In making these decisions organisations must consider their own needs but they must also be cognisant of employee incentives based on transferability of skills.³

In Figure 2 below we illustrate our training and culture services. These include a range of training areas, program and curriculum development and education/training review. Our services are augmented by our approach to data culture based on our four pillars.

Figure 2: ACIL Allen data training and culture service

Summary

Data training and culture uplift based on an initial DDGS mapping provides support for data and digital uplift to comply with the missions and initiatives in the DDGS. Australian government entities will need to uplift their training processes and data culture to support substantive changes to their data and digital systems and processes. Some aspects of this training and culture uplift are direct requirements for mission outcomes in the DDGS and others are needed as support for other missions. In either case, proper training for staff and a data-driven culture will be important requirements to meet the vision set out in the DDGS.

Data training and culture uplift should be based on educational best practice and be performed by appropriate subject-matter experts. Curriculum development and training can be done internally or externally (or using a mixture of internal and external programs) and it should be adapted to organisational needs and professional incentives of staff. Culture uplift can be focused around four key pillars of a healthy data-driven culture, involving leadership and change management, empowering data users, fostering data-oriented communication, and evaluation and value realisation.

Data training and culture uplift is the final step in the ACIL Allen approach to services for DDGS described in Part I of this article series. We hope you have enjoyed this series and found it helpful in understanding the DDGS and approaches to compliance. As previously noted, all Australian government entities should be implementing the DDGS with a view to full compliance with its vision by 2030.

¹ Australian Government (2023) Data and Digital Government Strategy, p. 5.
² Ibid, pp. 27-28.
³ For general career development, employees are typically incentivised to prefer external training provision by recognised providers that can provide a recognised qualification (e.g., universities, accredited training providers, etc.) rather than in-house training in an organisation. This may cut against organisational goals and it may affect employee engagement with training programs.