How you should classify your demand series

Executives today take forecasts into account in almost every move they make. Demand forecasting is the practice of estimating what the future demand for products will be. It predicts what products, both existing and potential customers, will wish to purchase and instructs manufacturing facilities on what to manufacture.

Therefore, it involves not just guessing about future demand but also using several methodologies to do so in a way that is both objective and scientific.

Many forecasting strategies have been created recently to tackle the growing diversity and complexity of managerial forecasting problems. In this article, we will cover demand classification, how you should classify your demand by using the various demand forecasting techniques that are available, and the benefits of demand classification.

With our experience at Growth Jockey, we will demonstrate how to use the various strategies. We'll next discuss issues in demand series categorization to wrap up.

Common Methods of Demand Series Classification

According to a Technavio analysis, from 2020 to 2024, the global demand planning software market is anticipated to expand at a compound annual growth rate (CAGR) of over 8%.

To increase the accuracy of forecasts, demand classification examines demand patterns. Based on synchronized internal and external time series data, it applies analytical and statistical approaches to categorize demand patterns. Demand patterns, pattern grouping, and volume grouping are all categorized as part of the demand classification process.

Manufacturing businesses can learn more about the needs of their customers by using demand classification and forecasting. Forecasting your future demand is challenging. To effectively predict future demand for your business, excellent judgment, and appropriate scientific formulas are needed.

A McKinsey & Company study found that businesses can increase revenue by up to 10% and cut inventory holding costs by up to 20% by efficiently using demand sensing and shaping tactics.

Here are the top demand forecasting techniques Growth Jockey uses to classify your demand for better forecasting.

1. Market Research

Customer survey data is the foundation for market research demand forecasting. Here, consumer-specific survey forms are distributed to gather data in a tabular manner.

In an RSR Research survey of retailers, 63% of those polled cited poor forecasting as their largest inventory management difficulty.

This approach offers insightful information that internal sales data cannot. It provides more detailed information on the types of clients and demographic information that can be used to target new markets. It helps in how you classify demand by knowing your customer base better.

2. Delphi Method

An organization employs a team of outside specialists to use the Delphi Method. Each expert creates a forecast based on their understanding of the market. Utilizing the knowledge of individuals with diverse areas of expertise is possible with this demand forecasting technique.

Each participant can give honest responses because the responses are anonymous. You can have panelists from all around the world because there will be no in-person discussion. The procedure is set up to let the group capitalize on one another's insights and viewpoints. The outcome is a well-informed consensus.

3. Trend Projection

The simplest and most popular method of demand forecasting is this one. Growth Jockey uses your historical sales data in trend projection to forecast your future sales.

For instance, you might have seen a brief increase in sales the year before because of a month-long viral article about your product or you might have experienced a temporary decline in sales because of a hack into your eCommerce website. Both occurrences are unlikely to occur again, hence they shouldn't be considered when predicting a pattern.

4. Sale Force Opinion

Data from sales groups are used in the Sales Force Opinion approach to forecast demand for your business.

The individuals in your sales team who interact most frequently with your clients. They listen to criticism and fulfill requests. They are thus a fantastic source of information about consumer preferences, product trends, and what your rivals are doing.

5. Econometric

This method develops a mathematical formula to classify demand series to improve forecast by fusing historical sales data with the factors affecting demand.

Relationships between economic elements are considered by the econometric demand forecasting method. For instance, a rise in personal debt levels may be accompanied by a rise in the need for house repair services.

Benefits of Accurate Demand Series Classification

Accurate classification of demand series to forecast can provide several benefits, including:

• Improved forecasting accuracy: Accurately classifying demand series can lead to more accurate forecasts. This can help businesses better plan their inventory levels and production schedules.

• Better inventory management: With accurate demand series classification, Growth Jockey can help businesses optimize their inventory management processes. This will also ensure that they have the right products in the right quantities at the right time.

• Enhanced customer satisfaction: Accurate demand series classification can help businesses ensure that they have the right products available to meet customer demand. This in turn will lead to higher levels of customer satisfaction.

• Increased revenue and profitability: By helping organizations better understand demand patterns and effectively manage inventory levels, Growth Jockey helps businesses increase their revenue and profitability. We do this by helping you avoid stockouts and minimizing waste.

• Improved decision-making: Accurate demand series classification provides businesses with better insights into customer behavior and demand patterns. This can help them make more informed and strategic business decisions.

Challenges in Demand Series Classification

You need precise data before you can forecast demand effectively. Many businesses experience problems with demand forecasting due to missing data. Here are a few things that could prevent you from classifying your demand series for improved forecasting.

• Lack of historical data: For businesses with little prior experience, this is a concern. Even well-established companies, nevertheless, occasionally face difficulties. To combat this, Growth Jockey uses a user-friendly structure by compiling and organizing sales data from previous years.

• Data quality: Demand series data can be incomplete or contain outliers, which can make accurate classification difficult.

• Unpredictable events: Unpredictable events such as natural disasters, pandemics, or economic downturns can disrupt demand patterns and make accurate classification challenging.

• Lack of inventory control: Good demand planning is built on good inventory management. You run the risk of overproducing or under producing if you don't know what's in the warehouse. Fortunately, Growth Jockey can help you with that by providing innovative solutions for inventory management.

• Lack of domain expertise: Demand series classification requires domain expertise to identify and extract meaningful features from the data and to interpret the results of the classification. Growth Jockey offers such expertise, which makes developing accurate models less challenging.

• Dynamic demand patterns: Demand patterns can change over time, which can make it difficult to develop accurate classification models that remain effective over the long term.

• Multiple demand signals: Demand series data can come from multiple sources. These include sales data, web traffic, and social media. This can make it difficult to integrate and classify the data effectively.

Overall, demand series classification can be a complex and challenging task. With the help of Growth Jockey’s combination of technical expertise and domain knowledge, you can effectively classify your demand for better forecasting.

To Sum Up

Demand forecasting assists companies in making well-informed decisions that impact everything from supply chain management to inventory planning. In a poll of supply chain professionals by APQC, 64% of participants responded that their firms' top objective was to improve demand forecasting.

Businesses want a strategy to accurately estimate demand because client expectations are changing more quickly than ever.

According to a Gartner report, cloud-based demand planning and forecasting solutions will become more and more prevalent by 2024, accounting for 50% of new midsize WMS deployments and 30% of new big and worldwide deployments.

Demand forecasting supports wise business choices. It makes no difference whether you select straightforward or intricate methods. Your company will remain strong with demand planning based on sales data, market analysis, and economic variables.

Demand forecasting done correctly can make or kill a business. ECommerce companies can keep track of their inventory coming in and leaving out by analyzing demand. Growth Jockey can assist you in creating the most effictive demand generation strategy for your business.

We think that what is needed right now is improved implementation of the available approaches rather than better-predicting methodologies. We help you construct the forecasting problem correctly and, as a result, you will have more confidence in the forecasts offered and be able to use them more effectively.

At Growth Jockey, we are dedicated to generating demand for your business through tailored strategies that effectively address the crucial challenges faced by our clients across diverse industries. Regardless of the size of your company, whether it's a small-scale enterprise or a large corporation, you can now tap into the advantages of advanced demand generation techniques. Take the decisive step towards unlocking the next level of growth for your brand by contacting us today!