Skills and capabilities

Team skill set for automation excellence

Developing human capabilities is pivotal in the transformation of service and product delivery. This is particularly true when implementing automation. Success in automation requires skills across business, technology, and specialist expertise areas to enable discovery, build, run, and maintain stages of the lifecycle. Organisational capabilities and skills also need to increase in alignment with automation maturation. Government organisations must prioritise up-skilling their teams in alignment with their automation ambition to achieve optimal results.

Teams that yield high success rates embrace and are structured upon:

Agile, collaborative ways of working
Product-based teams comprised of business and technical professionals with multi-disciplinary skill rather than individual roles
Appointing relevant business owners.

Multidisciplinary teams bring diverse and domain experience essential to automation initiatives. These teams possess domain expertise in business, technology, legal and compliance, and governance. The key domain areas include:

Business expertise:

Domain experts or business process owner
Business analysis.

Technology expertise:

Automation technology and architecture expertise
Artificial intelligence and data engineering
Software development, quality assurance and user experience (UX) expertise
IT infrastructure and operational expertise.

Risk, legal and compliance expertise:

Data and ethics governance
Procurement, compliance, and auditing
Privacy and cybersecurity experience
Administrative law and policy knowledge.

Governance experience:

Program and project management framework i.e., waterfall/agile.
Change management experience.

The skill sets of automation team members can be categorised into core, valuable, and specialist.³³ The level of skill required depends on your automation maturity ambition, lifecycle phase, and chosen technology solution. The skill sets identified below are assessed based on their degree of impact, learning curve, and impedance. Impedance refers to the difficulty of adopting and implementing the skills or technologies, considering the associated learning curve.

Learn about the core, valuable, and specialist automation skills required to pilot and scale beyond RPA below.

Core automation skills

Fundamental skills to achieve production readiness.

Core skill	Description
Basic bot development	Create straight forward automation scenarios using graphical user interfaces or pre-integrated templates. Positive impact: High Learning curve: Moderate Impedance: Light
Advanced bot development	Create automations that integrate with external systems, comply with regulatory requirements, handle complex decision logic and manage repetitive tasks. Positive Impact: High Learning Curve: Difficult Impedance: Moderate
Document and data processing	Extract and prepare data from business applications and documents. Positive Impact: High Learning Curve: Moderate Impedance: Moderate
SDLC management	Software development lifecycle (SDLC) management applies practices such as documentation, testing, and change management to ensure code security and reliability. Positive Impact: High Learning Curve: Moderate Impedance: Moderate
Platform operation	Maintain and operate automation platform to ensure reliability of automation environments. Positive Impact: Significant Learning Curve: Basic Impedance: Light
Enterprise applications	Apply root cause analysis (RCA) during any phase of the automation lifecycle. Positive Impact: High Learning Curve: Moderate Impedance: Moderate
Automation testing	Define and execute user and functional tests to ensure business and technical requirements are met. Positive Impact: Significant Learning Curve: Moderate Impedance: Moderate

Valuable automation skills

Skills valuable in automation adoption vary by use-case. These skills extend automation within the organisation through new use cases or optimisation. Your organisation should prioritise them based on the use case and operational requirements.

Skill	Description
Automation architecture	Ability to identify the optimal approach amongst available options. Positive impact: Significant Learning curve: Moderate Impedance: Moderate
API integration	Integrating external systems with different types of APIs and handling their programmatic responses. Positive Impact: High Learning Curve: Difficult Impedance: Heavy
Development languages	Develop objects and scripts in different software languages. Positive Impact: Significant Learning Curve: Difficult Impedance: Heavy
Troubleshooting and debugging	Understanding enterprise applications use and architecture for business rules enforcement and integration optimisation. Positive Impact: High Learning Curve: Basic Impedance: Light

Specialised automation skills

Skills that extend automation value in limited cases. Investing in them must be justified.

Skill	Description
Process and task mining	The ability to leverage mining tools to analyse and generate process flow diagrams detailing every step, decision path, and step duration. Positive impact: Significant Learning curve: Moderate Impedance: Moderate
AI and ML	Incorporate external ML systems to tackle specific use cases that require classification, prediction, or pattern detection. Positive Impact: High Learning Curve: Difficult Impedance: Heavy
Reporting	Extending monitoring capabilities to report and measure automation impact on business. Positive Impact: Significant Learning Curve: Moderate Impedance: Moderate
Ethics	Ensure that automation solutions align with ethical standards and guidelines to prevent biases and promote fairness, transparency & accountability. Positive Impact: High Learning Curve: Moderate Impedance: High
Governance, risk, and compliance	Implement policies and procedures to ensure that automation solutions comply with regulatory requirements and manage associated risks. Positive Impact: Significant Learning Curve: Moderate Impedance: Moderate
Data governance	Establish and maintain data management practices to ensure data quality, consistency, and security across automation processes. Positive Impact: High Learning Curve: Moderate Impedance: Moderate

Building an automation centre of excellence

A Centre of Excellence (CoE) is an organisational team designed to promote best practices, enhance expertise, and foster innovation in automation.³⁴ Establishing a CoE ensures your organisation achieves scaled automation excellence. It fosters collaboration and sustains automation across all maturity stages, maximising value and impact scaling appropriate to the organisation automation maturity.

A CoE follows a structured approach to achieve operational excellence, ensuring the automation lifecycle is followed to realise benefits. They govern automation operations to deliver consistent quality from ideation to deployment.

In the pilot level, the CoE identifies and assesses initial automation initiatives. During implement level, they establish best practices and governance frameworks. As automation expands, the CoE enables broader adoption, knowledge sharing, and training. At the scaling level, the CoE leads strategic planning to align automation initiatives with organisational goals, driving innovation and continuous process optimisation.

Operational excellence in automation CoE

Discover: identify and evaluate

Process discovery and mining
Requirement gathering.

Build: design and build

Process design document
Solution development.

Run: test and deploy

Deployment strategy
Acceptance testing
Business continuity plan.

Monitor: measure and monitor

Performance monitoring
Change management
Break and fix management
Security and operational management.

CoE roadmap aligned to automation maturity

The expansion of the CoE should align with the automation initiatives and organisational automation maturity.³⁹ Justified by scope, scale, and business KPIs, the COE expands with a mix of full-time and part-time resources comprised of business, technology, and domain specialist expertise. The goal is for the CoE to scale from pure technology-based roles into multi-disciplinary capabilities. The CoE should collaborate with business process owners at early stages, leveraging low code no code developing practices where possible, so that both business and technology-based roles are employed to build multidisciplinary teams.

	Early stage	Intermediate stage	Mature stage
Scope	Organisation charters a CoE team: build team charter define CoE services.	Pilot and implement early automation deliverables: define KPIs build automation strategy.	Organisation expands and scales automation initiatives: enterprise orchestration mature governance model AI/Emerging technology integration.
Skills	process design solution architecture automation tool knowledge.	development testing integration infrastructure security.	process modelling and mining platform engineering DevSecOps practices data science, advanced analytics AI, ML, NLP ethics and data governance.
Process and engagements	delivery team technology review vendor selection.	pipeline creation pipeline evaluation criteria.	automation portfolio business technologist practices automation architecture automation roadmap community of practice (CoP).
Technology	Robotic process automation (RPA) Data integration.	Automation platform ecosystem: robotic process automation (RPA) business process automation (BPA) APIs and iPaaS intelligent document processing (IDP).	Fully integrated platform: conversational AI/prompt engineering analytics platform process mining ML/LLM/testing automation.

CoE team composition through maturity

Team composition through maturity | Digital NSW

Empower business technologists

Empowering employees to become business technologists is essential to achieve automation excellence. Upskilling your team in essential automation skills will progress your organisation towards self-sufficiency. Fostering a culture where employees are encouraged to become developers will also accelerate the adoption of innovation and automation in your organisation. It will cultivate your workforce's ability to effectively identify and address business challenges.

Empowering employees to become business technologists allows your organisation to tap into the collective knowledge and creativity of your workforce. Employees will be motivated to identify automation opportunities, develop solutions, and address business challenges more effectively. Your organisation should provide education, training, resources, and rewards so that employees are enabled to achieve their full potential as business technologists.

The following table describes the investment in employees needed by organisations to achieve business value:

Business value	Investment in employees required
Faster time-to-benefit	Education and training in automation and associated skills.
Accelerated innovation	Establish communities that share knowledge and collaborate.
Increased return on investment	Provide the tools, guidelines and resources to business technologists.
Employee engagement	Training in pipeline contribution and ideation skills.

Scaling skills for automation

The figure below shows the necessary skills for business technologists (non-IT) as the organisation matures from pilot to scale. Scaling skills relative to maturity, ensures the appropriate skills and capabilities are in place when required.