Stuck in Second Gear: Why Productivity Stalls

Australia’s productivity debate has returned to the front page.

In The Australian Financial Review recently, NAB CEO Andrew Irvine warned that living standards will stagnate unless productivity improves, arguing that without reform, “this may be as good as it gets.” Treasury is reportedly preparing to prioritise productivity in the May budget after what has been described as a 30-year slump.

The macro message is clear: economic growth without productivity growth is unsustainable.

But while the national conversation focuses on policy settings, industrial relations and fiscal levers, a more immediate constraint sits inside large enterprises.

The bottleneck isn’t effort.

Organisations are busier than ever – investing in transformation, deploying AI pilots, hiring specialists, running compliance programs. Yet when executives examine performance through a capital lens, they see the same pattern: rising cost-to-serve, slower decision cycles, constrained return on invested capital, and marginal improvements in time-to-market.

In enterprise terms, productivity is the system-level ability to convert capital, talent, and technology investment into measurable throughput, faster decision cycles, and stronger transformation ROI. By that definition, many organisations are not under-investing – they are under-performing. Despite significant digital spend and ambitions around scaling AI across the organisation, enterprise agility remains limited.

Most enterprises have mistaken activity for productivity. Effort has increased. System performance has not.

The Problem: More Input, Same Output

1. Three data points leaders report consistently:
2. Costs are rising faster than output. Technology investment is significant, but cycle times haven’t materially improved.
3. Teams are stretched despite record headcount. New hires manage complexity instead of reducing it.Decision cycles are slowing. Multiple steering committees, escalation-heavy governance, and risk-averse approval processes create latency that stalls value delivery.

This is the productivity trap: increasing inputs without improving system performance.

At a national level, productivity stagnation erodes living standards. Inside enterprises, it erodes return on capital and competitive position. The dynamics are structurally similar: rising inputs, constrained output, and systems that resist adaptation.

Why Technology Alone Doesn’t Fix It

Over the past decade, enterprises have migrated to cloud platforms, deployed automation, and launched AI initiatives. The tools are modern. The operating models are not.

The pattern is consistent:

• Legacy governance layered over modern platforms - Agile frameworks implemented without structural change
• Automation deployed into broken processes - AI pilots that never integrate into decision loops prevent scaling AI across the organisation

Digital tools sitting inside analogue organisations don’t create enterprise agility. They create expensive inefficiency.

Where Enterprise Productivity and Transformation ROI Break Down

1. Decision Latency

The constraint isn’t poor decisions – it’s slow decisions. When approval pathways are fragmented and accountability is diffuse, projects extend, opportunity windows close, and teams disengage.

Reducing decision latency unlocks more productivity than most process optimisation efforts.

2. Organisational Design Misaligned to Value

Most enterprises are structured around functional silos, not customer value streams. This creates handovers instead of ownership, competing KPIs, budget fragmentation, and duplicated effort.

The customer experiences one organisation. Internally, work is fragmented across boundaries. That fragmentation is one of the largest systemic productivity drains in large enterprises.

3. Capital Shallowing at the Team Level

Rapid hiring without workflow redesign creates the organisational equivalent of capital shallowing: more people managing the same inefficient system. Instead of simplifying, organisations add headcount to compensate. Cost increases. Throughput doesn’t.

What High-Performing Organisations Do Differently

The shift required is from effort to flow, designing systems where value moves with minimal friction.

Three patterns distinguish high performers:

Clear decision rights and accountability Teams operate with clear ownership, funded as persistent units rather than temporary projects. Leaders enable rather than control. Governance is simplified, not layered.

Operating models aligned to value delivery Structure follows customer journeys or product lines, not functional domains. Cross-functional teams own outcomes. Funding, KPIs, and incentives align to the same objectives.

Technology deployed as an amplifier, not a fix Workflows are redesigned before automation. AI is embedded into decision loops, not bolted onto legacy processes. Digital literacy is built alongside platform deployment.

When these elements align, execution accelerates without heroic effort. Productivity becomes a system outcome, not an HR metric.

Enterprise Operating Model Design Is the Leadership Lever

Productivity stalls are not technology problems. They are not workforce problems. They are leadership design problems.

Leaders set the conditions under which productivity either flourishes or stalls:

• What behaviours are rewarded?
• How quickly can decisions be made?
• Is experimentation safe, or punished?
• Are structures aligned to value, or optimised for control?

In organisations that unlock productivity, leadership mindset shifts precede system redesign.

What Leading Organisations Are Measuring

Forward-thinking executives have shifted focus from transformation theatre to operational performance.

They measure:

• Flow efficiency (time value-adding vs. time waiting)
• Decision cycle time (approval to execution)
• Cost-to-serve trends; and
• Return on invested capital, not just revenue growth.

And they act on what they measure:

• Reducing governance layers
• Simplifying funding models
• Prioritising capability uplift over short-term cost cutting; and
• Redesigning end-to-end workflows.

The impact is tangible: faster cycle times, lower cost-to-serve, higher engagement, and stronger capital efficiency.

Moving Out of Second Gear

National productivity reform will take years. Enterprise productivity redesign can begin now.

While policymakers debate structural reform, executive teams control a more immediate lever: operating model design. The organisations that will outperform over the next decade will not simply work harder – they will work differently.

The productivity ceiling in most enterprises is significantly higher than current performance suggests. Unlocking it requires intentional redesign of operating models, decision rights, workflows, and culture.

The constraint is not talent, ambition or technology design.

It is system design. And system design is a choice.