Target operating model
How the capability is organised, funded, staffed and sourced, including the split between central platform and embedded business teams.
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Capability decays without structure. This is the work that decides whether an investment compounds or quietly reverts.
The approach
Every organisation that has run a serious data or AI programme knows the pattern. The build lands, the team disperses, ownership blurs, the standards drift, and eighteen months later someone proposes rebuilding the same capability from scratch.
That is an operating model failure, not a technology failure. It happens when nobody holds clear accountability, when decision rights are ambiguous, when risk and assurance were consulted too late to be useful, and when the funding stopped at go live.
We design the structure that prevents it: the target operating model, the decision rights, the governance forums that are actually worth attending, and the assurance approach that satisfies risk, audit and regulators without smothering delivery.
On the AI side specifically, that means a responsible AI framework with real teeth, aligned to ISO 42001 and to Australian regulatory expectations: documented model decisions, bias and fairness testing where decisions affect people, human oversight, escalation paths, and evidence you can produce on request rather than reconstruct under pressure.
Business outcome
Lower total cost of ownership and faster approval cycles, with regulatory exposure reduced and benefits still measurable twelve months after go live.
What is included
Engagements are scoped to what you actually need. Very few clients take all of this at once, and we will say so when a component is not worth funding yet.
How the capability is organised, funded, staffed and sourced, including the split between central platform and embedded business teams.
Who decides what, who is consulted, and who carries the outcome, documented at a level that survives a change of personnel.
Standards, policies and forums that are proportionate to the risk, designed so that compliance is the path of least resistance.
An AI management system aligned to ISO 42001, covering transparency, bias testing, human oversight and audit evidence.
A funded, sequenced plan with a named owner per outcome and a business case that finance and risk will both sign.
Benefit measurement that continues past go live, plus the assurance and audit readiness work that keeps regulators satisfied.
The other services
Most engagements touch more than one of these. The sequence matters more than the labels.
Bring a process that frustrates you, a decision you cannot evidence, or an AI idea you are not sure is real. Thirty minutes, no pitch deck. You will leave with a straight read on whether it is worth doing.
Prefer email? Write to fabian.abacum@decisionworks.com.au or connect on LinkedIn.