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Demand Forecasting: 5 Steps to Improve Your Skills Now

Learn how businesses of all sizes can access accurate demand forecasting to scale challenges and make well-informed decisions for their business strategy. Let’s cut to

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Learn how businesses of all sizes can access accurate demand forecasting to scale challenges and make well-informed decisions for their business strategy.

Let’s cut to the chase โ€” you’re here to learn how to forecast demand effectively. One out of 2 sales leaders arenโ€™t confident about the accuracy of their demand forecast. But this guide will save you from guessing if youโ€™re going about it correctly.

Check out Ware2Goโ€™s latest eBook to discover how accurate forecasting and effective fulfillment strategies enhance customer satisfaction and grow your business.

You probably constantly wonder if you’re ordering too much or too little, or perhaps you notice your profits slip away as sales donโ€™t come in as planned.ย 

Predicting demand doesn’t have to feel like shooting in the dark.

This article will help you understand the ebb and flow of your consumer demand and confidently make each business decision, helping turn business data into demand forecasts.

What Is Demand Forecasting?

Demand forecasting is the process of estimating the level of consumer demand for a product.

Merchants decide how much inventory to buy based on demand forecasting models, and strategic businesses even determine the location of their inventory distribution based on geographic demand.ย 

Accurate demand forecasting is important for avoiding stockouts (which result in missed sales opportunities) and slow inventory turns (which lead to inventory obsolescence and high inventory carry costs).

5 Steps to Simplify Your Demand Forecasting Skillsย 

The Demand Forecasting Process

The demand forecasting process involves choosing effective methods and tools, and knowing what the market needs by analyzing data carefully and using insights wisely. Knowing this will help you optimize operating costs and improve customer experience.ย 

Hereโ€™s a breakdown of these steps and tips for each to help you implement a solid demand forecasting strategy.

1. Select a Forecasting Method & Technique

Carefully consider the nuances of your business and industry, and choose a method that optimizes resource allocation. Some important factors to consider are the amount of historical sales data you have available, access to general industry data, and the skill set of your team.

2. Identify Factors Influencing Demand

Understand factors that influence demand, such as your consumer preferences and competition. Itโ€™s important to think on both a micro-scale (your marketing budget and seasonal sales patterns, for example) and a macro one (like the general economic climate and state of the supply chain).

3. Collect & Analyze Data

Any demand forecast is only as accurate as the data itโ€™s based on. The larger data set you have, the more accurate your forecast will be, and a healthy mix of first-party and third-party data adds diversity to your data set.

4. Implement Forecasting Results

Use your forecasting insights to make practical changes in how you manage your inventory and resources. By aligning your business operations with expected demand, you can ensure you have the right resources available at the right time, improving efficiency and meeting customer needs effectively. Itโ€™s important to share your demand forecast with all of your partners, including fulfillment and marketing partners, to set them up for success.

5. Continually Optimizeย 

Assess the effectiveness of your forecasting efforts by comparing your forecast to actual sales. Refine your forecasting strategies by using feedback from your suppliers, distributors, and other stakeholders. Explore customer surveys, regular market research, and input from your sales team to stay agile in dynamic market environments.

Types of Demand Forecastingย 

There are several methodologies for forecasting demand and planning. The method your business employs will be determined by the sales history available, the length of your sales cycles, and your business goals. Below are a few common demand forecasting methods:

  1. Passive Demand Forecasting is best for very small or hyper-local businesses. Itโ€™s based on limited historical data and makes broad assumptions. This method isnโ€™t likely to support aggressive growth goals.ย 
  2. Active Demand Forecasting considers historical sales data and external market forces and trends. Itโ€™s best to employ active demand forecasting before major changes to marketing tactics or expanding into a new market.ย 
  3. Short-Term Projections are only meant to forecast demand for the next business quarter to business year. Businesses use this method primarily to manage just-in-time supply chains. Itโ€™s best suited for businesses with a higher risk tolerance.ย 
  4. Long-Term Projections are best for high-growth businesses with aggressive growth goals. They take into account increased market share over time and determine capital expenditures and long-term marketing plans.ย ย ย 

Demand forecasting techniques

Demand Forecasting Techniquesย 

For each of the types of demand forecasting above, there are many techniques to accompany them. Choosing the right technique can make all the difference in how effective your process of demand forecasting is.

Here are some commonly used demand forecasting techniques for purposes such as making informed inventory decisions, mitigating risks, and seizing growth opportunities.

1. Time Series Analysis

Time series analysis looks at past data, like previous sales, to spot patterns that repeat over time. Understanding these patterns helps businesses predict busy times and plan better, making sure they have enough products and setting prices wisely to meet customer needs and boost profits.

2. Moving Averages

Moving Averages smooth out the ups and downs in data, helping you focus on the main trends. Here’s how you do it:

  • Pick a time frame, like each week or month
  • Calculate the average for each time frame
  • Draw these averages on a graph

This method helps clear up the clutter in the data, making the important trends easier to see.

3. Exponential Smoothing

Exponential smoothing is similar to moving averages but gives more importance to recent data. This method adjusts more quickly to recent changes, helping businesses stay responsive to current trends and demand shifts.

4. Regression Analysis

Regression analysis helps forecast future demand by examining how different factors relate to each other. For example, it can show how changes in marketing spend influence sales. This analysis helps businesses understand and predict how changes in one area can affect outcomes in another.

5. Delphi Method

The Delphi method involves gathering insights from experts through structured discussions. This technique pools diverse perspectives to challenge existing assumptions and develop more accurate forecasts by collectively addressing uncertainties and blind spots.

6. Simulation Models

By exploring various ‘what if’ situations and analyzing their potential impacts, companies can better anticipate risks and opportunities, leading to more informed decision-making under uncertainty.

These forecasting techniques allow you to foresee market changes, manage your resources effectively, and keep your business competitive, ensuring you’re always one step ahead.

important factors in demand forecasting

Factors to Consider in Demand Forecastingย 

Understanding the factors influencing demand forecasting can help you succeed with your chosen forecasting techniques. Here are some considerations for sustained growth.ย 

1. Economic Conditions

Keeping a finger on the pulse of economic indicators is critical to anticipating shifts in consumer spending patterns. These economic indicators include unemployment rates, Gross Domestic Product (GDP) growth, inflation rate, interest rates, and income levels. With these indicators, you can gain insights into consumer sentiment. Their perception of the economy and their financial outlook helps you gauge their ability and willingness to buy your products.

2. Competition

Understanding competitive dynamics, such as your competitorsโ€™ pricing strategy, product assortment, market share, and marketing strategy also helps you assess the level of demand to expect for your products.ย 

3. Demand Forecasting Software

Demand forecasting software streamlines data analysis and improves forecast accuracy. You can use it to analyze historical sales data, identify trends, and automate repetitive tasks. Advanced analytics and visualization features can help you gain deeper insights into demand patterns.ย 

4. New Product Introductions

Demand forecasting for a new product launch is a tricky process. With no historical sales data to measure against, you must have a deep understanding of your current customer base and the competitive market. You should also decide which outcome is more favorable to your business long-term: under-ordering and selling out or over-ordering and being left with a product to further market or liquidate.ย ย 

5. Consumer Trends

Tracking consumer trends, such as on-demand shopping, customization needs, fast shipping, and eco-conscious shopping, provides businesses with insights into evolving preferences and behaviors.ย ย ย ย ย ย ย 

6. Price

Fluctuations in pricing directly impact consumer purchasing behavior and demand levels. Considering your pricing strategies when forecasting demand equips you to optimize your revenue and profitability.

7. Availability

Ensuring product availability through effective supply chain management is crucial for meeting customer demand, maximizing sales, and providing customer satisfaction and loyalty. However, itโ€™s important to balance the risk of stocking out against the risk of carrying too much inventory.

8. Geography

Geographic factors, such as location, climate, and demographics, play a pivotal role in demand forecasting. Businesses must tailor their forecasting strategies to specific regions or markets to optimize sales and customer satisfaction.

benefits of accurate demand forecasting

The Benefits of Accurate Demand Forecasting

Accurate demand forecasting can benefit businesses in several ways, including:ย 

1. Control Shipping Costs with a Distributed Fulfillment Network

Understanding where your customers are located and accurately forecasting demand enables you to stock the right SKUs in the right quantity in the most optimal location in anticipation of purchases. This level of forecasting helps you meet your customersโ€™ demands for 1- to 2-day shipping without depleting margins with costly solutions like next-day air.ย 

2. Alignment Between Marketing and SKU-Readinessย 

Poor demand forecasting leads to poor supply chain performance. A marketing campaign should geo-target audiences based on available inventory at the SKU level. Otherwise, customers will encounter stockouts and shipping delays, ultimately leading to lost revenue.

Sales arenโ€™t the only measure of success for a marketing campaign. Emphasizing sales over customer experience or SKU-level profitability might lead to back orders piling up while a replenishment order is still coming from the supplier. This results in a frustrating experience for customers, who may not return for a repeat purchase.

Instead, marrying your demand forecasting with your marketing efforts will enable you to squeeze the most ROI out of your marketing dollars without sacrificing customer experience. By closely monitoring SKU-level performance, youโ€™ll know which campaigns to turn off and which ones to ramp up.

3. Lower Inventory Carry Costs

Inventory turns really shouldnโ€™t be longer than 1 months. Otherwise, your inventory carry costs will drag down your profitability, eventually leading to inventory obsolescence.

Some merchants focus only on supplier discounts to create margin. They order more inventory than they can sell in a quarter to get the steepest volume discount. Then, they let inventory sit on the shelves of a costly storage facility for 6โ€“12 months. By the time the inventory sells, the storage costs have exceeded the amount saved through the supplier discount.

An outsourced fulfillment partner with a technology-first approach to logistics can provide an accurate demand forecast. Using custom forecasting models, you can strike the perfect balance between getting the best supplier discount possible without over-indexing on storage costs.

4. Profitable Seasonality

Some seasonal demand spikes are virtually industry-agnostic. Most merchants expect seasonal spikes around the holidays and Amazon Prime Day. Sometimes, stocking for these seasonal demands can feel like an educated guess. Merchants may reach the end of a holiday season feeling confident about sales velocity only to find that their SKU-level profitability was down.

There is also an element of risk that youโ€™ll have to determine for your business. Businesses with a higher tolerance for the risk of running out of inventory can fine-tune their inventory levels for the least amount of capital expenditure. Taking the high-risk approach yields the highest profits and frees up capital to invest in other areas of your business.

If your business has a lower risk tolerance, you can optimize inventory levels to insure against stockouts. This low-risk approach requires greater capital expenditures but ensures a seamless customer experience. Once you determine your risk appetite, you can choose the inventory level that will yield either the most profitable or the most satisfying season for your customers.

Other businesses, however, may be surprised by seasonal patterns in their business. Whether due to weather, sporting events, or back-to-school, your customers may find more need for your product at different times of the year.ย 

Analyzing your sales cycles will help you identify seasonal trends, stock up accordingly, and align your marketing strategy with seasonal demand to double down on profitability.

Demand Forecasting Examples

To accurately forecast demand, businesses with highly seasonal demands like winter weather gear will want to look at historical sales data, such as exactly when demand began to spike in years past. They may also look at the average temperatures and weather patterns during demand spikes and compare those to long-term forecasts for the coming year.

Long-term forecasts clearly work on many assumptions and donโ€™t guarantee accuracy but can help make general predictions. The forecast should also consider regional weather patterns to have inventory ready at the right time and place to best service their end customers.

A business thatโ€™s less seasonal, like supplements and nutraceuticals, will want to forecast demand based on historical sales data and marketing strategy and growth plans. Past marketing campaigns can determine how much sales will grow with incremental marketing spend.

FAQs

For more clarity and insights into the demand forecasting process, here areย  some questions that commonly surround demand forecasting:ย 

How do I choose the right demand forecasting technique for my business?

To determine the right forecasting technique, consider factors such as the nature of your products or services, the availability and quality of historical data, and the accuracy and complexity levels required. Also, assess the technique’s scalability and adaptability to accommodate future business needs.

What data do I need for demand forecasting?

You’ll need historical sales data, market trends, customer demographics, promotional activities, economic indicators, and any other relevant factors that may impact demand.

How often should I update my demand forecasts?

The frequency of updates depends on factors like market volatility, seasonality, and the speed of demand changes.ย 

Update forecasts regularly to ensure accuracy and relevance. Fast-moving goods might demand weekly or even daily forecasts. For industries with fairly stable demand patterns, you can opt for monthly or quarterly updates.

What are the limitations of demand forecasting?

Demand forecasting is subject to uncertainties such as unexpected market shifts, changes in consumer behavior, and inaccurate data inputs.ย ย ย 

It’s essential to acknowledge and mitigate these limitations through robust forecasting methodologies.

Demand Forecasting for Fast-Growing Brands

Demand forecasting is no longer a function reserved for enterprise-level businesses. In fact, by partnering with a tech-focused 3PL or on-demand warehousing partner like Ware2Go, fast-growing brands can access custom reporting and analytics to make smarter decisions about their business.

The benefit that fast-growing brands have over large enterprises is their agility and ability to pivot in response to market changes. When that flexibility is paired with best-in-class demand forecasting, high-growth brands will have a distinct advantage to grow their market share and compete in todayโ€™s quickly-changing marketplace.

Looking for robust demand forecasting capabilities for your business? Reach out to our in-house experts.

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