Demand Planning in the Digital Age
Demand planning has come a long way from spreadsheets and gut feel. Today’s digital tools enable unprecedented accuracy, speed, and insight—but only if implemented thoughtfully.
Let’s explore how leading FMCG companies are transforming their demand planning processes for the digital age.
The Evolution of Demand Planning
Traditional Approach
- Monthly planning cycles
- Statistical forecasting on aggregate data
- Manual adjustments based on planner judgment
- Limited ability to handle complexity
- Weeks to produce forecasts
Digital Age Approach
- Continuous planning with regular updates
- AI-powered forecasting at granular levels
- Augmented intelligence combining algorithms and human insight
- Handles millions of SKU-location-time combinations
- Real-time forecast generation
Key Digital Capabilities
1. Granular Forecasting
Digital systems can forecast at levels previously impossible:
- SKU-location-week level for thousands of combinations
- Channel-specific demand patterns
- Customer-specific forecasts for key accounts
- Time-of-day predictions for fast-moving items
2. Multi-Dimensional Analytics
Understanding demand requires looking at it from multiple angles:
- Product hierarchies - Category, brand, SKU
- Location hierarchies - Region, territory, store
- Time dimensions - Season, month, week, day
- Customer segments - Demographics, behaviors, preferences
3. Causal Factor Integration
Modern demand planning incorporates external factors:
- Promotions - Type, depth, duration, merchandising
- Pricing - Own price and competitive pricing
- Distribution - Weighted distribution and store count
- Events - Holidays, sporting events, local activities
- Weather - Temperature, precipitation, seasonal patterns
- Economic indicators - Consumer confidence, unemployment
4. Real-Time Demand Sensing
Short-term forecasts benefit from up-to-the-minute data:
- POS data showing actual consumer demand
- Inventory positions and flow-through
- Order patterns and fill rates
- Social media sentiment
- Search trends and online traffic
The Human + Machine Advantage
The best results come from combining AI and human expertise:
What AI Does Best
- Process massive datasets quickly
- Identify complex patterns
- Maintain consistency across thousands of forecasts
- Continuously learn and adapt
- Handle routine updates efficiently
What Humans Do Best
- Incorporate qualitative insights
- Understand market context
- Navigate unique situations
- Make strategic decisions
- Build relationships with stakeholders
The Sweet Spot
Systems that put AI recommendations in front of planners, with:
- Clear explanations of the logic
- Easy override capabilities
- Collaboration tools for sharing insights
- Feedback loops that improve the algorithms
Best Practices for Digital Demand Planning
Start with Data Quality
No algorithm can overcome bad data:
- Master data management - Accurate product hierarchies and attributes
- Historical cleansing - Remove anomalies and correct errors
- Promotion taxonomy - Consistent classification of promotional activities
- Regular audits - Ongoing validation and correction
Implement Gradually
Don’t try to boil the ocean:
- Pilot with key categories - Prove value before expanding
- Start with statistical forecasts - Get the foundation right
- Add AI capabilities - Layer on machine learning gradually
- Expand causal factors - Incorporate additional inputs over time
- Scale across portfolio - Extend to more products and locations
Build Organizational Capability
Technology alone isn’t enough:
- Training programs - Help planners use new tools effectively
- Change management - Address concerns and resistance
- Clear processes - Define workflows and decision rights
- Performance metrics - Measure and reward improvement
- Continuous learning - Share best practices and insights
Integrate with S&OP/IBP
Demand planning doesn’t exist in isolation:
- Supply planning integration - Ensure feasibility of demand plans
- Financial planning alignment - Connect volume plans to revenue forecasts
- Commercial collaboration - Incorporate marketing and sales input
- Executive review - Present demand assumptions in monthly IBP cycles
Measuring Success
Track both accuracy and business impact:
Accuracy Metrics
- Forecast bias - Are you consistently over or under?
- Mean Absolute Percentage Error (MAPE) - Overall accuracy level
- Weighted MAPE - Accuracy on important items
- Forecast value added - Does each step improve the forecast?
Business Metrics
- Inventory levels - Days of inventory and carrying costs
- Service levels - In-stock rates and fill rates
- Waste/obsolescence - Write-offs due to poor forecasts
- Production efficiency - Stability of manufacturing plans
- Cash flow - Working capital improvements
Common Pitfalls to Avoid
Over-Reliance on Technology
- Algorithms aren’t magic
- Context and judgment still matter
- Build human capability alongside systems
Under-Investment in Data
- Garbage in, garbage out
- Data quality requires ongoing attention
- Integration across systems is critical
Lack of Collaboration
- Demand planning isn’t just a supply chain function
- Commercial input is essential
- Finance needs to be aligned
Unrealistic Expectations
- Accuracy improvements take time
- Quick wins are possible, but transformation is a journey
- Continuous improvement is better than perfection
The Future of Demand Planning
Where is the field heading?
More Autonomous Systems
- AI handling routine updates automatically
- Planners focusing on exceptions and strategy
- Self-learning algorithms that improve continuously
Greater Integration
- Real-time links between demand planning and execution
- Tighter connection to consumer behavior data
- Integration with external market intelligence
Enhanced Collaboration
- Cloud-based platforms enabling global collaboration
- Mobile access for anywhere, anytime planning
- Social planning with crowdsourced insights
Prescriptive Analytics
- Moving beyond “what will happen” to “what should we do”
- Optimization recommendations for inventory, pricing, promotions
- Closed-loop planning with automated actions
Getting Started with Digital Demand Planning
Ready to modernize your demand planning?
- Assess current state - Where are the biggest gaps?
- Define the vision - What capabilities do you need?
- Build the roadmap - Phased approach to transformation
- Choose the right partner - Technology + implementation expertise
- Start the journey - Pilot, learn, scale
How Blueshift Can Help
Our demand planning solution combines:
- Best-in-class AI - Proven algorithms that deliver results
- FMCG expertise - Built specifically for consumer goods
- Easy integration - Works with your existing systems
- Implementation support - We guide you through the journey
- Continuous innovation - Regular updates with new capabilities
The digital age demands better planning. We can help you get there.
Schedule a demo to see our demand planning platform in action.