Every year, organisations invest billions in strategy formulation. Leadership teams retreat, consultants synthesise, and polished presentations are delivered to boards. And yet, McKinsey's own research suggests that fewer than 30% of strategic initiatives deliver the value projected at inception. The slide deck was excellent. The execution was not.

The Knowing–Doing Gap

The challenge is rarely one of intelligence. Leadership teams generally know what needs to be done. The failure is almost always structural: strategy is formed by one group, communicated through another, and executed by a third — with decreasing specificity and ownership at each handoff point.

We call this the "last mile" problem. The strategy travels 90% of the way through the organisation with reasonable fidelity. It is the final 10% — where abstract objectives must become specific daily decisions — that destroys value.

Three Root Causes

• Ambiguity at the operating level. Strategic pillars like "accelerate digital capability" or "deepen customer relationships" rarely translate into actionable guidance for a department head managing quarterly targets.
• Misaligned incentives. Bonus structures, performance reviews, and budget cycles typically reward short-term operational metrics that may actively conflict with long-term strategic objectives.
• Insufficient middle management capability. Senior leaders set strategy. Frontline staff execute. Middle managers must do both simultaneously — and are rarely given adequate support for the translation role they play.

A Framework for the Final Mile

At Volume, we've developed what we term the "Strategic Activation Model" — a structured approach to translating board-level strategy into team-level operating rhythms. The model comprises three components: Decomposition (breaking strategic themes into specific, measurable outcomes by function), Alignment (linking those outcomes to existing performance management infrastructure), and Cadence (establishing review rhythms that create accountability without bureaucracy).

The Consultant's Responsibility

We should be candid: consulting firms bear partial responsibility for this problem. An engagement that concludes with a pristine strategy document and no implementation roadmap has delivered an incomplete service. At Volume, we do not consider our work complete until the client organisation can credibly articulate how the strategy will be executed at the team level. Anything short of this is strategy theatre.

Marcus Lim is Managing Partner at Volume. He has led over 60 strategy engagements across financial services, technology, and consumer sectors in Asia-Pacific.

In the eighteen months since large language models became genuinely capable research and synthesis tools, every major consulting firm has been forced to confront a fundamental question: if AI can conduct market research, synthesise competitor intelligence, and draft initial frameworks in hours rather than weeks, what exactly is the consultant's value proposition?

What AI Does Well in Strategy Work

Let's be honest about the capabilities. AI tools are now genuinely useful for: rapid secondary research synthesis across large corpora; first-draft hypothesis generation from structured inputs; pattern recognition across financial and operational datasets; and communication drafting at all levels of detail. These tasks previously consumed a material portion of junior consultant time.

Where Human Judgement Remains Irreplaceable

The value of experienced consultants has always resided in areas that resist systematisation. These include: the ability to read organisational dynamics and political realities that never appear in documents; the credibility to deliver uncomfortable truths to senior leadership; the contextual judgement to know which frameworks apply to a given situation versus which are inappropriate; and the facilitation capability required to build genuine alignment across senior teams.

• AI cannot attend the working dinner where the real constraints are revealed.
• AI cannot read the CFO's body language when the revenue projection is presented.
• AI cannot bear accountability for a recommendation that shapes a company's future.

The New Engagement Model

Forward-thinking consulting teams are restructuring their engagement models accordingly. The AI-augmented team reallocates human hours away from information gathering and toward synthesis, challenge, and co-creation with the client. Engagements become more intensive but more compressed. The analyst layer shrinks; the senior advisory layer grows. Cost structures must adapt accordingly.

The Risk No One Is Discussing Loudly Enough

The strategic risk we see most frequently is over-reliance on AI-generated analysis that appears authoritative but lacks the contextual grounding that comes from primary research. AI synthesises what is publicly known. Strategic advantage is typically built on what is not publicly known — proprietary customer data, internal capabilities assessments, and primary channel research. Firms that mistake AI fluency for strategic intelligence will make confident decisions based on structurally incomplete information.

Dr. Priya Nair leads Volume's Digital Strategy practice. She holds a PhD in Operations Research from NUS and previously led digital transformation programmes at two Fortune 500 companies.

The era of seamless global supply chains optimised purely for cost efficiency is over. The confluence of US-China technology decoupling, shifting tariff regimes, regional security dynamics, and post-pandemic resilience priorities has made supply chain strategy one of the most consequential boardroom topics of this decade.

The New Geopolitical Realities

Asia-Pacific CEOs are navigating a fundamentally more complex operating environment than even five years ago. Three forces dominate the current landscape:

• Technology bifurcation. The separation of US and Chinese technology ecosystems — in semiconductors, cloud infrastructure, communications hardware, and increasingly software — is creating parallel supply chains with incompatible standards and compliance requirements.
• Friend-shoring pressure. Policy incentives from multiple governments are actively encouraging organisations to restructure supply chains along geopolitical alliance lines, creating both risk and opportunity depending on where existing operations are located.
• Climate and ESG compliance. Emerging regulatory requirements — particularly from the EU's supply chain due diligence frameworks — are adding a sustainability dimension to network design decisions that was largely absent a decade ago.

A Framework for Strategic Response

We recommend that leadership teams approach supply chain strategy through four analytical lenses simultaneously:

• Exposure mapping. Systematically identifying where current supply networks intersect with geopolitical fault lines — by geography, supplier nationality, technology category, and regulatory jurisdiction.
• Scenario stress-testing. Modelling the financial and operational impact of specific geopolitical scenarios — tariff escalation, market access restrictions, export controls — on current network configurations.
• Optionality building. Investing selectively in supply chain flexibility before it is needed, treating dual-sourcing and geographic diversification as strategic insurance rather than pure cost.
• Stakeholder positioning. Actively managing relationships with government bodies, industry associations, and multilateral organisations to ensure early visibility of regulatory change.

The Strategic Opportunity

Disruption at scale always creates competitive divergence. Organisations that have invested in supply chain intelligence and strategic flexibility over the past three years are now able to move into markets and categories that less-prepared competitors cannot reach. Geopolitical complexity, when navigated well, is a source of durable competitive advantage.

James Okafor is a Partner at Volume leading the Growth & Markets practice. He has advised CEOs and boards across 14 countries on market entry, M&A, and strategic positioning.