Sharpen Focus Across a Global Portfolio 🧭

Set Fewer, Clearer Priorities for 2026

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Hey there, CFOs! 💼

CFOs are using sharper portfolio discipline and a data-driven operating rhythm to create focus and agility. Nestlé’s example shows how a global scale can still move fast.

Are your capital bets as intentional as your growth goals?

📰 Upcoming in this issue

  • 📊 How Nestlé’s CFO Sharpens Focus Across a Global Portfolio

  • 🧮 CFOs Urged to Build AI Data Audit Discipline

  • 🤖 Agentic AI in Finance: What You Need to Know

📊 How Nestlé’s CFO Sharpens Focus Across a Global Portfolio

McKinsey interviews Nestlé’s finance chief on pruning to core strengths, doubling down on winners, and building a faster, data-driven operating rhythm.

Key Takeaways:

  • 🧭 Portfolio Discipline: Systematic reviews back divest, fix, or grow decisions, concentrating capital in categories and markets with a durable advantage.

  • 💸 Sharper Capital Allocation: Stage-gated investments link funding to milestones and returns, improving payout quality and reducing the spread across pet projects.

  • ⚙️ Speed and Simplicity: Leaner governance, clear decision rights, and standard metrics help country teams move faster while staying aligned with strategy.

  • 🤖 Data to Decisions: Digital dashboards and AI-enhanced forecasting raise visibility into pricing, mix, and productivity, turning insights into timely actions.

🧮 CFOs Urged to Build AI Data Audit Discipline

CFO Dive explains why finance must hardwire consent, lineage, and auditability before scaling AI. Usercentrics warns that weak data controls sabotage value and compliance.

Key Takeaways:

  • 🧭 Governance First: Map data inventories and lineage, set access controls, and define retention so AI projects start on solid, auditable ground.

  • 🔐 Consent at the Core: Capture, store, and enforce user permissions across systems, ensuring models use only compliant, purpose-limited data.

  • 🧾 Prove and Trace: Maintain logs, model versions, and source records, enabling regulators and auditors to trace every decision back to its data.

  • 🤝 Finance as Orchestrator: CFOs align legal, IT, and business owners, tie controls to risk and ROI, and set metrics that reward compliant growth.

🤖 Agentic AI in Finance: What You Need to Know

Agentic AI can streamline close, forecasting, and controls, but only with strong governance and clean data. Gartner maps where to start and how to scale.

Key Takeaways:

  • 🧭 Outcome First: Tie agent projects to cash, margin, or risk metrics, with owners and payback windows.

  • 🔐 Governance and Control: Enforce access, approvals, and audit trails, keeping decisions explainable and documented for regulators and boards.

  • 🧱 Data Foundations: Standardize master data and lineage, integrate ERP, CRM, and planning systems, so agents act on reliable, real-time context.

  • 🚀 Prove Then Scale: Pilot narrow tasks like reconciliations or variance analysis, measure lift, and expand with playbooks and training.

📊 Take This Edition’s Poll:

This or that: which risk feels harder to manage in AI adoption?

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Why It Matters

Clear portfolio choices and clean data convert complexity into strategic speed. Start by linking funding to measurable milestones and real-time dashboards.

Governance and audit-ready AI keep finance both accountable and adaptive.

Wishing you continued success,

Vanessa Carter
Editor-in-Chief
CFO Executive Insights

P.S. Interested in sponsoring a future issue? Just reply to this email and I’ll send packages!

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