Integrating Human Intuition into planning is a problem tailor made for AI

AI has transformed planning. It’s not a case of replacing humans, more so leveraging expertise. As AI takes on more of the planning load, the challenge for leading manufacturers or retailers is to blend advanced technology with the intuition and experience —unlocking agility, consensus, and the competitive advantage which served you so well in the past.

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The Evolution of Planning: From Chaos to Consensus

Traditional Planning where excel dominates the landscape

  • Manual, error-prone processes: Teams struggle to reconcile multiple, often conflicting forecasts, leading to unstructured S&OP/IBP meetings.
  • Low engagement: Planning meetings become a source of frustration rather than insight, causing participation to wane.
  • Reactive, not strategic: Teams spend more time firefighting than innovating.

Modern Planning where AI-based systems are used by everyone

  • Structured, data-led meetings: Weekly or monthly S&OP/IBP meetings begin with AI-generated baseline forecasts. These forecasts span multiple variables so all business units operate from a single, unified forecast.
  • Automation at scale: Up to 90% of forecasts require no manual intervention, freeing up time to focus on gaining market share.
  • Systemic replenishment actions using dynamic Min/Max levels.
  • Many-to-many attribute logic for more accurate New Product Introduction (NPI).
  • Demand-led procurement using real-time demand data.
  • External demand signals inform and accelerate New Product Development (NPD).
  • Human oversight: Planners manually adjust the remaining ~10% of forecasts to respond to supply disruptions, market nuances, or strategic shifts. This acts as an essential safeguard and a source of agility.

The Next Frontier: AI as a Collaborative Partner

Rather than viewing AI as just a planning tool, think of it as a collaborative team member—one that listens, learns, and responds in real time. Imagine this:

Your planning tool actively participates in S&OP/IBP meetings—not as a passive observer, but as a real contributor. It consumes meeting transcripts, understands context, and automatically adjusts forecasts based on nuanced discussions that only humans can provide. This isn’t science fiction—it’s the logical next step, building on transcription and contextual AI tools already embedded in today’s meetings.

Why this matters:

  • Unified data and agentic AI: Leading retailers already use unified data and autonomous AI to drive automated decision-making. The competitive edge comes when these are combined with human insights for category management, promotions, and demand forecasts.
  • Shopper insights at speed: AI accelerates the discovery and application of shopper insights, but it’s human planners who interpret trends and craft strategies around loyalty, basket size, and trip frequency.
  • Operational excellence: AI-powered analytics identify exceptions, but it’s human teams who define the tolerances and prioritise the most critical actions.

Practical Steps for CXOs

  • Empower planners as AI collaborators: Ensure automated tasks are balanced with your organization's risk tolerance and available resources.
  • Integrate AI into planning rhythms: Use AI not just for forecasting, but also to summarize meetings, suggest actions, and capture the “why” behind manual overrides—and then feed that back into the system.
  • Work from a single forecast: Align finance, customers, sales channels, and operations behind one unified forecast. Different department perspectives shouldn’t mean different forecasts.
  • Foster a culture of hypothesis testing: Encourage teams to test AI tools in real-time scenarios, focusing on business outcomes and continuous learning.

The Future - Human-in-the loop AI

 

The future of retail planning isn’t about replacing humans with AI—it’s about forming a symbiotic relationship where each complements the other. AI handles the heavy lifting, while human intuition and experience guide strategy, interpret anomalies, and drive innovation. Crucially, any changes must be captured and coded into historical data, enabling the AI engine to learn and further automate over time.

Rethink your planning process—not as “AI as a tool,” but as “AI as a team member.” We’re already building this future. Let us show you how to make it a reality for your business.