If you are truly passionate to run a thriving business, demand planning and forecasting simply cannot be overlooked. Time and time again, we have seen evidence of volatile markets and evolving demands that continue to shake the business world. Having a robust system to predict and plan for such demands can mean a huge difference between thriving and surviving.

In this article, we will discuss the basics of demand and forecasting, explore processes and tools, and show how OneCart can help you with your day to day business.

Table of Contents

1. What is Demand Planning?
2. What is Demand Forecasting?
3. Demand Planning vs. Forecasting
4. Why Are Demand Planning and Forecasting Crucial?
5. Understanding Demand Planning Models
6. The Demand Forecasting and Planning Process
7. Demand Forecasting Models
8. Key Metrics for Measuring Success
9. Common Pitfalls and How to Avoid Them
10. How OneCart Can Transform Your Demand Planning and Forecasting
11. FAQs about Demand Planning and Forecasting
12. Summary

What is Demand Planning?

Demand Planning Definition

Demand planning is a strategic process of predicting and managing future customer demand for products or services. When demand planning, your main goal is to balance supply with demand in order to minimize waste and maximize customer satisfaction through order fulfillment. When inventory levels and stock purchases are aligned correctly, businesses will see a significant improvement in operational efficiency.

The Role of a Demand Planner

A demand planner is a professional responsible for creating and managing accurate demand forecasts. The roles of a demand planner include analyzing data, market trends, and customer behavior to identify demand patterns. Demand planners play a big part in procurement, production, and inventory decisions.

Example: If a company sells seasonal products like winter coats, without proper demand planning, they might overstock, leading to extra inventory costs, or understock, resulting in lost sales during the most important sales period.

What is Demand Forecasting?

Demand Forecasting Definition

Demand forecasting is the practice of predicting future customer demand using historical data, market analysis, and statistical methods. Forecasting activities are actually the foundation of demand planning by providing actionable insights into future demand.

Types of Demand Forecasting

1. Qualitative Forecasting: Based on market research, surveys, and expert opinions. Suitable for new products or markets with little historical data.
2. Quantitative Forecasting: Based on historical data and statistical models, such as time series analysis and regression techniques.

Demand Planning vs. Forecasting

Key Differences

• Demand Forecasting is about predicting what might happen in the future. For example, you estimate how many customers might want a product next month based on past sales and market trends.
• Demand Planning is about taking action based on those predictions. It involves deciding how much inventory to order, how to schedule production, and how to manage the supply chain to meet the predicted demand.

Think of forecasting as seeing into the future and planning as preparing for it.

How They Work Together

We can explain things in the simplest way with an example:

1. Forecasting provides the numbers: For example, it predicts that 1,000 units of a product will be needed next month.
2. Planning makes the decisions: Based on the forecast, you decide how many units to procure, where to store them, and how to deliver them to customers.

When demand planning and forecasting are done correctly together, it allows a business to be proactive rather than to scramble at the last minute to fix any demand issues that come up.

Why Are Demand Planning and Forecasting Crucial?

Benefits in Supply Chain Management

• Optimized Inventory Levels: Prevent overstocking or stockouts.
• Cost Efficiency: Reduce holding and production costs.
• Improved Customer Satisfaction: Ensure timely product availability.

Common Challenges and Their Impact

• Inaccurate data: Leads to poor decisions and inefficiencies.
• Lack of Technology: Makes it difficult to analyze large datasets effectively.

OneCart offers real-time analytics and automated insights to overcome these challenges, ensuring a better operations plan for your business

Understanding Demand Planning Models

Statistical Models

There are machine learning models available as well, but for our discussion today, we shall focus on statistical models. These mathematics-based models analyze historical data to identify trends and patterns. Two key examples are:

1. Moving averages

• Definition: This method calculates the average demand over a specified number of past periods. As new data becomes available, the oldest data point is dropped, and the average is recalculated.
• Advantages: – Simple to calculate and implement – Helps reduce the impact of random variability in demand data.
• Limitations: – Lag in responsiveness to sudden demand changes. – Limited capability to handle seasonality or complex trends.

2. Exponential Smoothing

• Definition: A forecasting technique that applies decreasing weights to older data points, giving more importance to recent observations. Variants include simple, double, and triple exponential smoothing.

• Usage: – Simple exponential smoothing: For data without trend or seasonality. – Double exponential smoothing: For data with trends. – Triple exponential smoothing: For data with both trends and seasonality.

• Advantages: – More responsive to recent changes compared to moving averages. – Adjustable smoothing factor for customization based on data characteristics.

• Limitations: – Less effective in cases of sudden, unpredictable demand shifts. – Requires parameter tuning for optimal performance.

  

Moving averages and exponential smoothing are both great models to use for planning. However, for a start, moving averages would be the best to start out with as this would allow a business to have a better overall insight over its sales. Any needed adjustments can be made later on, as demand planning is a continuous process.

The Demand Forecasting and Planning Process

Step 1: Data Collection and Cleaning

Gather accurate and relevant data from multiple sources, such as sales records, customer feedback, and market trends, to build a comprehensive dataset. Ensure the data is cleaned to eliminate outliers, duplicates, or errors that could distort the forecasting process.

Step 2: Forecast Demand

Use demand forecasting tools, such as statistical models or machine learning, to analyze historical patterns and predict future trends. Consider external factors like seasonality, market conditions, and competitor activity to refine accuracy.

OneCart uses a simple moving average model to better calculate possible stockouts. This feature is a perfect complement for demand planning as it provides more relevant and recent data based on historical sales.

Step 3: Plan Execution and Review

Implement the demand plan by aligning inventory and procurement efforts with the forecasted demand. Continuously monitor performance metrics to identify variances between actual and predicted outcomes.

Demand Forecasting Models

Step 1: Causal Models

Identify relationships between demand and external factors, such as prices changes, marketing campaigns, or economic conditions. By understanding these relationships, businesses can make proactive decisions to respond to demand fluctuations effectively.

Step 2: Time Series Analysis

Analyze historical data to identify patterns and make forecasts. This approach is best for stable markets where historical trends are likely to continue. By analyzing the timing and magnitude of demand, businesses can create close-to-perfect forecasts for inventory and resource planning.

Step 3: Judgment-Based Approaches

Use expert opinions and market insights for situations with limited data. These methods are most appropriate for forecasting new products or entering unfamiliar markets. With the combination of expert insight with available market intelligence, businesses are able to generate informed estimates to guide their decisions. While some may be critical of such methods, it is definitely better than doing nothing at all like jumping into the water without any preparation.

Key Metrics for Measuring Success

• Forecast Accuracy: Measure the percentage of accurate predictions. High accuracy indicates better alignment between demand predictions and real-world outcomes, reducing risk of overstocking or stockouts.
• Inventory Turnover: Track how often inventory is sold and replaced. A high turnover rate indicates efficient inventory use, while a low rate may signal overstocking or slow-moving products.
• Order Fulfillment Rate: Assess the percentage of orders fulfilled on time. A high rate demonstrates the business’s ability to meet customer expectations, improving satisfaction and loyalty.

Common Pitfalls and How to Avoid Them

Over-Reliance on Historical Data

Avoid relying solely on past data. Doing this can lead to inaccurate forecasts when market conditions shift unexpectedly. For instance, unforeseen disruptions like economic shifts, supply chain interruptions, or sudden demand spikes leaves any historical data to be of no use and irrelevant. Thus, go the extra mile and incorporate market trends and real-time insights. The need for the human element cannot be understated in this case.

Ignoring Market Trends

Stay updated with changing customer preferences and external factors. It is important to monitor market trends and leverage tools like OneCart that provide actionable, real-time data. Failing to account for such external factors can lead to outdated and ineffective demand forecasts.

How OneCart Can Transform Your Demand Planning and Forecasting

OneCart is a one stop tool for many of your business activities, which include inventory tracking, order processing and listings management. Such features allow you to have a better overview of your business operations and plan accordingly to avoid any disruptions that could impact your business negatively. The result is high efficiency, better customer satisfaction, and significant cost savings.

FAQs about Demand Planning and Forecasting

1) What is Demand Planning?

Demand planning is the strategic process of predicting and managing future customer demand to align inventory, production, and resources, ensuring efficiency and customer satisfaction.

2) What is Demand Forecasting?

Demand forecasting is the practice of predicting future customer demand using historical data, market analysis, and statistical methods to provide actionable insights.

3) What is the difference between Demand Planning and Demand Forecasting?

Demand forecasting predicts what might happen in the future, while demand planning uses these predictions to take actionable steps.

4) What are the benefits of Forecasting and Demand Management?

Forecasting and demand management help optimize inventory levels, reduce costs, and improve customer satisfaction by ensuring product availability.

Summary

Demand planning and forecasting are vital for businesses that wish to keep up with changing market conditions. However, it is very important to note that a business should not fully rely on automation to plan future demands. Such tools should be a complement to the human mind. By adopting effective techniques and leveraging automated tools like OneCart, one can focus on other aspects of the business that needs to be handled to maintain and grow operations.

Take the next step in mastering demand planning. Try OneCart today for a free trial and experience automation at its best!