The future of S&OP: How AI is revolutionising supply chain planning for paper & packaging Jari Kaukiainen, Advisor Integrated Business Planning and SCP, I Plan

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Best practices include:
• Tracking MAE/MAPE and FVA in parallel
• Making FVA results transparent to planners
•
Limiting manual overrides to low-volume or highly
variable items
• Requiring real market insight for any adjustments
Over time, this creates a feedback loop that boosts trust
in system-generated forecasts and enhances collaboration across
functions. At I-Plan, we see forecast accuracy not just as a technical
metric—but as a strategic lever that enables smarter, faster
decisionmaking.
Aligning forecasting with the planning hierarchy is
essential across:
1. Strategic Planning (12–36 months) – Capacity and
CAPEX
2. Tactical Planning (3–18 months) – Procurement and
production
3. Operational Planning (0–12 weeks) – Execution and
S&OE
I-Plan helps organisations ensure forecasts support each
horizon consistently connecting insights to action across the
business.
A global paper packaging business improved forecast accuracy
by 20% and significantly reduced working capital
A global packaging paper operator applied I-Plan across
its operations focusing first in improving monthly forecasting and
second phase in improving supply planning and demand/supply
balancing based on profitability (advanced S&OP), achieving:
• 20% improvement in SKU-level forecast accuracy
• Reduced safety stock and working capital
• Substantially improved service levels and delivery
reliability
Similarly a northern European paper group producing
graphic fine paper based products implemented I-Plan to combat
variability in niche market demand. Results included:
• Significantly reduced forecast error
• Better alignment between sales and production/operations
• Faster responsiveness to short term customer changes
Conclusion The future of supply chain planning and S&OP in the paper
and packaging industry is intelligent, integrated, and data-driven. As
customer examples show, AI no longer just supports forecasting—
it’s reshaping how businesses plan and respond.
AI is becoming deeply embedded across the planning
process: from sourcing and capacity decisions to risk evaluation and
execution.
Recent trends driving this transformation include:
• Real-time forecasting via IoT and cloud data
• Demand sensing from unstructured signals (e.g. social,
news)
• Sustainability-aware planning (e.g. emissions, waste)
• Explainable AI to increase transparency and trust
In many recent supplychain planning focused conferences,
it has become clear that leading manufacturers are moving beyond
static scenarios toward continuous, simulation-based decisionmaking. Instead of planning for fixed outcomes, today’s simulation
engines run persistently—digesting real-time data, modelling
disruptions, and guiding adaptive responses. Paper and packaging
companies need to follow the rhythm to keep their positions.
Rather than relying on predefined best-case or worst-case
models, simulation engines are now expected to run continuously.
These engines ingest real-time data, model disruptions across
functions, and recommend adaptive actions. This marks a structural
evolution in the way planning is conducted.
Generative AI (GenAI) offers further promise
through agents that can autonomously generate
forecasts, explore what-if scenarios, and propose plans
using near real-time inputs. This unlocks proactive
planning across all horizons—from strategic to
operational. Yet, traditional AI techniques (like statistical
models and optimisers) still outperform GenAI in
accuracy-critical, constraint-heavy use cases.
Crucially, GenAI excels at collaborative
intelligence—making insights more accessible across
departments. This empowers commercial, financial,
and operational teams to engage with data in ways
previously limited to technical planners.
The companies thriving today understand that
resilience is no longer just a process—it’s an outcome
of smart, AI-enabled planning systems designed to
sense, anticipate, and act.
At I-Plan, we help organisations turn AI into a
strategic S&OP advantage—combining machine-driven
insight with human expertise.
Ready to explore your AI potential? Visit
[www.iplanworld.com] or contact us to start your journey.
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