The Best Practices for Demand Forecasting

September, 2021
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Forecasting is the practice of predicting future events. Demand forecasting is the process of estimating demand for products and services to help in supply chain management. It’s used by industries as diverse as e-commerce, wholesale, manufacturing, and retail. 

The inputs to forecasting are from data sources like sales history, supplier lead times, market research data, seasonality and business intelligence insights. Understanding what makes an effective forecast can make all the difference in your company’s success.

Forecasting Basics

Basic forecasting techniques rely on historical information about historical activity and industry norms. These techniques work well for predicting daily and monthly trends. The challenge is to predict the next 30-day period. The “unknown unknowns” (e.g., seasonality, supply chain interruptions) can sometimes make this prediction process less reliable. 

When forecasting, businesses must understand how their activities affect their own business and others. Demand forecasting is one of the most important practices for businesses.

There are three key questions to consider during the demand process: 

  1. What should be done to create demand?
    This is considered Demand Planning.
    Demand planning is a process that helps businesses meet the customer demand for a particular product. During demand planning requires you to analyse your sales, trends, historical data and seasonality data to optimise the ability to meet the demand. 

    Consider the 4P’s during the Demand Planning period.

    • Product & Packaging
    • Promotions
    • Pricing
    • Place
  2. With the demand plan in place, what will the demand be?
    This is when the Demand Forecasting is done.
    Demand forecasting is the process of making estimations about the future customer demand over a defined period, by using historical data and other information.

    Take the following into account:

    • Strategic, Tactical, Operational plans
    • Consider the internal and external factors
    • Baseline, unbiased and unconstrained data
  3. How do we prepare for and act on the demand?
    This is Demand Management.

    Demand management is the process of preparing and acting on the supply and demand.
    Things to consider:
  • Balance demand & supply
  • Sales & Operations Planning (S&OP)

 

The Data Behind Demand Forecasting

This can be a daunting task, especially with an unpredictable future awaiting businesses. Businesses can develop forecasts using proprietary data that captures how customers behave in response to products and services. 

Supply chain managers could use this data to see how supplies will be delivered on time and within budget. The data will also show the impact a delay or disruption has on the customer experience. 

Businesses use a combination of the following types of data: 

  • Historical sales data
  • Sales forecasts
  • Market plans
  • Market research 
  • Competitor trends
  • Economic trends
  • Growth projections
  • Operational data
  • Supplier lead times
  • POS data
  • Internal data
  • Geographical patterns
  • Category, health and ingredient trends
  • Search engine data
  • Social media data
  • Weather patterns
  • Seasonality


It’s essential to know which datasets are vital to sales and inventory predictions.

Types of demand forecasting

There are different types of demand forecasting based on the model you use. The best practice is to do multiple forecasts to give you a more accurate picture of future sales. Different models will highlight differences in the predictions. 

The differences between the forecasts can indicate more research or better data. These are the different forecasting types: 

    1. Passive demand forecasting
      Use historical sales data to predict future sales. This is a great model when the aim is stability. It assumes that the upcoming sales will be the same as the current year’s sales. 
    2. Active demand forecasting
      This is great for businesses that are starting or are growing. This model looks at market research, marketing campaigns, growth plans and economic factors. 
    3. Short-term projections
      This looks at a period of 3 – 12 months. This helps to manage the just-in-time supply chain. This allows you to adjust your projections based on real-time sales data and respond quickly to changes in demand. 
    4. Long-term projections
      This forecast offers projections for one – four years into the future. This will help to shape the business growth. The data will be a mix of historical sales data, market research and aspirational growth projections. 
    5. External macro forecasting
      This brings in the trends of the broader economy and how those trends will affect your business. For example, it may look at the availability of raw materials, and other factors that may affect the supply chain. 
    6. Internal business forecasting
      Internal factors could limit your business growth. For example, if you expect demand to double – do you have the capacity internally to meet that demand? This can help to uncover limitations that may limit your business growth. Conversely, it can also highlight opportunities within your business.

 

How to Build an Effective Forecast

Making predictions can be tricky because there are too many variables and many of them are beyond a company’s control. 

The 5 best practices for demand forecasting: 

  1. Understand the external factors
    You need to understand what is impacting the daily lives of people, down to the most basic of levels economically, socially, professionally and personally. Consumer behaviour and demand patterns are volatile and change quickly.
  2. Examine current forecasting processes
    Run an internal assessment of your processes and ask the following questions: 

    • How long does the process take and how frequently does it happen? 
    • Who is involved in the process, and what resources are required to align the forecast? 
    • What tools are being used? Are they still effective? 
    • What methods are you using to calculate demand forecasts? 
    • Is data siloed between teams? 
    • What data is being used? Sales? POS? 
    • What datasets need to be included in the forecasting? 
    • Are you calculating forecasts at the SKU-, customer-, and warehouse- levels?
    • How consistent are your predictions? 
    • Are your forecasts dynamic and insightful? 
  3. Identify your needs
    Once you’ve examined your processes, it’s time to identify the areas that need attention and what those solutions could look like. 
  4. Data
    The foundation of all of your forecasts starts with data. If your data isn’t clean, take time to fix the errors. If the wrong data is put into your calculations, you’re likely to get a result that doesn’t help you. Clean data is complete, accurate, up-to-date and without mistakes. 
  5. Automation
    Embracing automation allows the process to work in the background. The technology does the work for you.

The Best Demand Planning Tools

There is a lot that goes into accurate demand forecasting. Doing forecasting manually is incredibly time-consuming which isn’t practical for a modern business. This is where software becomes invaluable. 

Many inventory management systems have built-in inventory forecast components which take the guesswork out of demand forecasting by using past sales history to calculate how much inventory is needed. This allows you to work out how much stock is required to cover a variety of upcoming periods. 

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Without demand, there is no business. Without an understanding of demand, businesses are not able to make smart business decisions.  Effective demand forecasting is the foundation of good sales management. You are going to make the most of your budget and thus your team’s time and resources.

An effective demand forecast will improve your forecasting ability, business operations, and marketing. Achieving demand forecasting success will help you to succeed in sales.

Are you ready to bring that perfect system in your head to life?

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