The 5 biggest demand forecasting challenges in supply chains – and how to fix them
Unbalanced inventory levels can have big consequences on both sides: Hold onto too much, and you end up paying for discounts and storage. Keep too little, and your customers will find what they’re looking for somewhere else. Each side carries its own associated challenges and costs, but they both stem from an inability to accurately predict demand and adjust inventory to meet it.
To streamline costs and make the most of sales opportunities, demand forecasting combines sales, inventory and advanced modeling so 3PLs can determine how much stock they should have on hand at any time. But common challenges can make inventory forecasting difficult, inaccurate or unreliable, leading to even more lost time and money.
Here, we’ll take a look at five of the top challenges that stand in the way of better demand forecasting and planning in supply chains, and how logistics leaders are overcoming these problems with better control over their data.
1. Limited data availability
Problem: Incomplete data affects accuracy
Having siloed inventory data can lead to inaccurate forecasting because it provides an incomplete picture of the market. When you base your inventory levels on incomplete data, it can lead to downstream challenges that can be hard to fix later—including some of the other challenges on this list. To gain value from your demand forecasts, ensure your inventory and sales data is clean, accessible and reliable.
Solution: Integrate data into a unified platform
To get a more accurate view of your business and the buying landscape, centralize your business data into a single platform that helps you stay in sync. By having all the key data available in one place, you can create a more complete picture of the market and capitalize on new opportunities while fine-tuning stock levels for peaks and valleys in demand.
2. Inaccurate forecasts
Problem: Leads to overstocking or stockouts
Incomplete data leads to inaccurate inventory forecasts, and inaccurate forecasts can bring down your bottom line by leading to either overstock or stockouts. Inaccuracy can also stem from adhering to manual processes, experiencing rapid growth or a shift in personnel, but despite the root cause, there are advanced tools that can help businesses dial up their forecasting accuracy.
Solution: Use advanced models with historical data, machine learning and AI
Advances in machine learning and AI can help companies clean and apply market data quickly, unlocking a level of accuracy that can’t be matched by older, more conventional methods. Combining these innovations with verified historical business data can help you plan accurately for swings in demand across your entire footprint by applying complex logic to your sales patterns.
3. Demand fluctuations
Problem: Sudden changes disrupt forecasts
When products become popular or get overshadowed by a newer offering, it can be difficult for everyone along the supply chain to keep up. The overnight changes in demand can throw off your forecasts, leading to backups and out-of-stock challenges. Disruptions in transportation and weather can also cause breakages along the supply chain that defy current modeling and planning.
Solution: Use demand sensing tools and predictive analytics
Demand sensing tools and predictive analytics use AI and machine learning to look at your data and offer insights that help you forecast demand. New analytics tools can help you see around the corner and calibrate for market changes before they land on your doorstep.
4. Long lead times & supplier variability
Problem: Hard to align supply with demand
While it’s difficult to adjust for buyer demand, it can be equally challenging to flex for long supplier lead times. Extended lead times or disruptions on the manufacturer’s side can generate a mismatch between the rhythm of supply and demand that can leave you with too much—or too little—product on the shelf.
Solution: Collaborate & communicate with suppliers
Streamlined communication between you and your supplier can help you bridge the gap and gain visibility into disruptions on their side before they become a problem on yours. Solutions that offer easier channels for collaboration boost forecasting accuracy by keeping you in touch with individual suppliers, allowing your business to adjust instantly to challenges that might be developing on the other side of the world.
5. Departmental misalignment
Problem: Poor collaboration causes inaccurate forecasts
A collaborative approach isn’t just key for you and your external partners; it’s critical for the effectiveness of your internal departments, too. Using siloed departmental data can cause your forecasts to be inaccurate, and misalignment on goals and initiatives can cause forecasts to be ineffective. Solutions that bring stakeholders together to work toward a common goal should be prioritized.
Solution: Implement Sales and Operations Planning (S&OP)
Focus on business management process by implementing Sales and Operations Planning (S&OP), which usually takes the form of a monthly sync between marketing, production, inventory management and sales. Assign leaders and set up a strategy for meetings, handoffs and changes to the S&OP as you coordinate business areas for more effective forecasting.
Inventory and demand forecasting in supply chains will look different for each business, but by adopting these proven best practices, you can ensure your stock levels are balanced and your forecasts are accurate.
Curious about how SPS can help? See how we help 3PLs everywhere stay in sync with the rest of the supply chain.
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