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Posted by Brett Romero - 28 August, 2019

Manual Predictions VS Machine-Based Forecasting

If you are planning to launch a new product then forecasting its sales is one of the main tasks you should set out on right away. This is quite a challenge considering the many variables and unknown factors involved, yet a simple necessity for any business that wants to get the most out of its sales.

Sales forecasting will help you identify and plan your resources (inventory, staff and cash flow) required for meeting the actual demand. If carried out correctly, it will act as an important tool for measuring the performance of your sales, marketing and other relevant operations.

One of the important factors for successful sales forecasting is the accuracy. The data collection about your new product and all the required measurements should be done with the utmost precision and accuracy. If your demand predictions are overestimated, you will risk having excess inventory. In the opposite case, i.e. when underestimating the sales demand for your new product, you can expect a huge bill for expedited delivery or customers that are left empty-handed.

Below is a sales forecast example for a designated month:

forecasting methods(source)

Here is to prove you the significance of an accurate sales forecast: according to research by the Aberdeen Group, companies with accurate sales forecasts are 10% more likely to improve their bottom line and add up their budget and 7.3% more likely to hit quota.

Thus, no matter how uncertain you are about the above-mentioned factors, you should still give your product a go: it’s quite apropos to mention the following saying here: “Not taking risks is the riskiest move of all.”

To help you in your sales forecasting journey, we will dive deeper into the topic and see how you can make sales predictions for your new product in the most effective and fruitful way.

There are two main ways of sales forecasting:

  • The traditional one which implies a manual analysis of the market and similar products and drawing conclusions based on the acquired data.
  • The machine-based analysis - using reliable forecasting software.

Let’s now have a look at the essence, the advantages and disadvantages of these two sales forecasting ways.

Manual Sales Forecasting: What Do You Need to Know?

Manual sales forecasting means that you are going to carry out all the required forecasting processes yourself. Here is what you need to know on how to forecast sales manually:

  • Assess the Historical Trends: It’s always good to have statistical data regarding the sales of your past year at hand. Break down the numbers by price, product, sales period, etc. This way you might be able to project the past data into the future. This calculation can be done either by using certain corresponding tools or manually. The latter might be more advantageous, especially if it’s guided by analysis. Also, have a look at your past sales forecast examples if there are any, just to refresh your mind on where and how to start. Below is a graph that shows historical trends in a time series graph:

sales forecasting(source)

  • Develop Unit Sales Projection: Start by forecasting unit sales per month if it’s possible for your product. It’s not only product-oriented businesses that sell in units, many service businesses do that as well. The forecasting process is much easier if you are able to break things down into their components.
  • Use Factors for Your New Product: If your product is completely new with no history, an already existing similar product could work as a guide for your forecast.
  • Collaborate with Your Sales Team: Manual forecasting will be much more productive if you manage to ensure solid teamwork with your sales representatives and customer service staff. Sales representatives have a deeper knowledge of your market which also includes information about your competitors. Customer service team can also contribute to the estimation of the potential of your new product. Discussing your new product or project with them you’ll get more precise numbers: e.g., the number of units you can move in the initial months or, the possible ramp-up rate.
  • Talk to Other Professionals: Loyal customers, suppliers and sales partners (dealers or distributors) might be of great help in understanding the future success of your product.
  • Do Your Own Market Research: Conduct surveys, determine focus groups and observe your target audience. This way you’ll have a better idea of the potential customer demand for your new product. Find out any existing sales forecast examples of products similar to yours and learn about their sales development processes. This, however, will take a lot of time, unless you decide to trust a professional.
  • Choose Time Periods Wisely: Commonly, the sales and finance function may only be interested in monthly data. However, the first few days and weeks of the sales of your product are of crucial importance. Make sure to have detailed daily forecasts for at least the first quarter of your product sales in order to get more precise data and reach better results.
  • Keep Track of Your Results and Adjust: Keep in mind to adjust your sales forecast as soon as you have the actual sales results. Never let loose of disciplined sales monitoring on a monthly basis. Keep track of product reviews, media mentions and customer feedback and discuss with your team all the required changes.

As you can see, the manual execution of your new product forecasting is quite a long and complex process, however, if done correctly, it will surely pay you back with good results. Some of the main advantages of manual forecasting are as follows:

  • Free of Charge: Manual sales forecasting is technically free as you are doing it all on your own. However, this is not completely true as it will still require time investment from your employees whom you pay. They could be spending their time working on things that actually require human brain and cannot be substituted with a machine.
  • Detailed Analysis: Human common sense is one of the best “tools” when it comes to thoroughly analyzing the market and the possible future sales of your new product.

Manual product forecast comes with several drawbacks too:

  • Time-Consuming: Manual forecasting is quite a long process. The longer the time you spend working on sales forecasting, the higher the possibility of losing actual sales opportunities. Time is money!
  • Biased and Inaccurate: As a business owner, you might not carry out a really objective sales forecast for your own product. It will eventually end up being biased and inaccurate.
  • Erroneous Human Mind: Besides, the human mind can be erroneous and say, a single mistake in counting certain numbers will double your work.

Machine-Based Analysis: A Better Solution?

Machine-based sales forecasting is becoming one of the top trends in supply chain as it’s come to improve customer engagement and generate much more accurate demand forecasts without human interference.

If you are wondering whether or not machine-based forecasting is worth the investment, a list of its advantages displayed below will help you make the correct decision:

  • Unlimited Data: Machine-based forecasting combines big data, cloud computing and learning algorithms that enable the evaluation of millions of information using an unlimited amount of demand factors at once.
  • A Classier Approach: Machine learning forecasting uses the so-called pattern identification with a separate, broad array of algorithms that can become accustomed to all data and are suitable for numerous demand form categories. Below is an example of a time consuming algorithim if not used through machine learning.

machine learning algorithms(source)

  • Higher Accuracy Level: As machine-based analysis uses more data, it makes the forecast more precise and accurate. Such points as product elements, wrapping, raw material valuing, third-party fiscal data and other relevant information that can be counted will be included in the forecast. Besides, automated software is much less error-prone than the human mind and the probability of stumbling upon a mistake with it is drastically low.
  • Control of the Whole Product History: This automated method of sales forecasting is also able to control the history of all products which also includes sales advancements and estimated demand.

As it becomes clear from the above-listed advantages, machine-based analysis is pretty much the most effective method for your new product forecasting. All you need to do is choose the right software and let it predict the future of your new product sales.

Intuendi is here to narrow your search for the right machine-based forecasting software down. This highly responsive software will make your sales forecasting procedure much easier and faster. With Intuendi you will be able to predict how your margin will behave in the future. This way you will also have a better understanding of your business and of the right strategies to be implemented for increasing your profits.

Summary:

This blog talked about:

  • How to forecast your inventory, staff, and cash flow through forecasting by looking at historical trends to make great inferences for the future
  • What you need to know for manual sales forecasting by choosing the right software for you and your products
  • Why machine based learning is a great solution that combines big data, cloud computing and learning algorithms to help enable better business evaluations
  • How all of these systems prove time and time again that they are accurate and reliable

B2B Sales eBook to Increase Revenues

Topics: AI, machine based learning, forecasting

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