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Half Day | Max. 16 Participants
Workshop Outcomes
- Quantify the true cost of manual, repetitive and duplicated work in your own teams
- Build a defensible business case for an AI or automation initiative using standard financial measures
- Prioritise a list of competing opportunities against effort, risk and payback period
- Define the measures that will prove whether an initiative actually delivered
- Recognise the cost patterns that make a proposed AI project a poor investment
Topics Covered
- The Friction Ledger: putting a dollar figure on repetitive, manual and low value work
- Costing an initiative properly: licences, integration, training, change effort and ongoing maintenance
- Payback, benefit realisation and total cost of ownership applied to AI initiatives
- Prioritisation: scoring opportunities against value, effort, risk and readiness
- Choosing measures that survive scrutiny; avoiding vanity metrics such as tool logins
- Presenting the case: what executives, boards and finance functions actually want to see
Location
- Willing to work remote
- Willing to work interstate
- Willing to work internationally
How can this workshop be delivered?
- Face to Face
- Virtual
Overview
Most organisations are being asked to invest in AI without any agreed method for deciding what to fund, what to defer and what to walk away from. The result is a scatter of pilots that nobody can defend at budget time.
This workshop applies conventional financial and project disciplines to AI and automation decisions. Participants learn to put a real cost on the friction inside their own operations, build a business case that finance will accept, prioritise competing opportunities, and define the measures that will demonstrate return. The focus is on solving business problems first and selecting technology second.
Delivered by a former CPA and accredited PRINCE2 project manager with over 30 years of experience in business transformation, this session brings investment rigour to a field that is currently long on enthusiasm and short on evidence.
Workshop Outcomes
- Quantify the true cost of manual, repetitive and duplicated work in your own teams
- Build a defensible business case for an AI or automation initiative using standard financial measures
- Prioritise a list of competing opportunities against effort, risk and payback period
- Define the measures that will prove whether an initiative actually delivered
- Recognise the cost patterns that make a proposed AI project a poor investment
Topics Covered
- The Friction Ledger: putting a dollar figure on repetitive, manual and low value work
- Costing an initiative properly: licences, integration, training, change effort and ongoing maintenance
- Payback, benefit realisation and total cost of ownership applied to AI initiatives
- Prioritisation: scoring opportunities against value, effort, risk and readiness
- Choosing measures that survive scrutiny; avoiding vanity metrics such as tool logins
- Presenting the case: what executives, boards and finance functions actually want to see
Who is this workshop for
Executives, finance leaders, transformation leads, operations managers and anyone required to approve, sponsor or justify AI and automation spending.
Handouts/materials provided
Friction Ledger costing template (XLSX), AI business case template (DOCX), opportunity prioritisation matrix, benefit measurement framework.
What to bring
A laptop and, if possible, indicative headcount and salary cost data for one team, plus two or three processes you suspect are consuming more time than they should.
Facilitator
About the facilitator
Over more than 30 years, Razz has helped organisations improve performance through technology, marketing and business transformation, working with IBM, Westpac, The Salvation Army, Jefferies and Company, Computer Based Solutions and Kenneth Cole, alongside thousands of Australian small and medium businesses.
His focus is not AI for its own sake. It is workflow automation, business systems, productivity and process improvement, with AI applied where it genuinely improves the outcome. The method is deliberately problem-first: identify the repetitive, manual and low-value work, quantify what it costs, then select the technology.
That approach is grounded in commercial and delivery discipline. Razz is a former CPA, an accredited PRINCE2 project manager, a member of the Australian Marketing Institute and holds a Master of Teaching, so sessions carry the financial rigour of a finance function, the delivery structure of a project office and the instructional design of a qualified teacher.
His facilitation style is practical and hands-on. Participants work on their own processes, their own numbers and their own documents, and leave with working examples and measurable outcomes rather than theory.
His philosophy is straightforward: AI should remove friction, improve decision-making, and let people spend their time on work that is actually worth their attention.
Key Expertise
- AI Strategy and Business Transformation
- AI WorkflowAutomation and Process Improvement
- Marketing Strategy and Customer Growth
- Business Systems Design
- Digital Transformation
- Prompt Engineering and AI Adoption
Industry Focus
- Financial Services
- Government
- Professional Services
- Retail
- Not for Profit
- Technology
- Small and Medium Business
Based in:
About the facilitator
Over more than 30 years, Razz has helped organisations improve performance through technology, marketing and business transformation, working with IBM, Westpac, The Salvation Army, Jefferies and Company, Computer Based Solutions and Kenneth Cole, alongside thousands of Australian small and medium businesses.
His focus is not AI for its own sake. It is workflow automation, business systems, productivity and process improvement, with AI applied where it genuinely improves the outcome. The method is deliberately problem-first: identify the repetitive, manual and low-value work, quantify what it costs, then select the technology.
That approach is grounded in commercial and delivery discipline. Razz is a former CPA, an accredited PRINCE2 project manager, a member of the Australian Marketing Institute and holds a Master of Teaching, so sessions carry the financial rigour of a finance function, the delivery structure of a project office and the instructional design of a qualified teacher.
His facilitation style is practical and hands-on. Participants work on their own processes, their own numbers and their own documents, and leave with working examples and measurable outcomes rather than theory.
His philosophy is straightforward: AI should remove friction, improve decision-making, and let people spend their time on work that is actually worth their attention.
Key Expertise
- AI Strategy and Business Transformation
- AI WorkflowAutomation and Process Improvement
- Marketing Strategy and Customer Growth
- Business Systems Design
- Digital Transformation
- Prompt Engineering and AI Adoption
Industry Focus
- Financial Services
- Government
- Professional Services
- Retail
- Not for Profit
- Technology
- Small and Medium Business
Based in:
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