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SAP Forecasting | All You Need to Know about SAP Forecasting

The world of business has begun changing since the previous decade. However, the so-called “change” became even more volatile after the COVID-19 pandemic hit us in 2020.

From then onwards, the scenario of consumer behaviour had changed entirely. 

There was a time when people used to focus more on quantity than quality. However, now the latter has become a more prominent theme of concern than the former.

That’s why, in a way, it has become difficult for businesses to understand how the demand of a product might be in the future. This is what’s affecting their business strategy as well.

So, how do you solve this issue?

Well, we, in our organisation have been trying to address this persistent problem through the integration of SAP Forecasting. Let us tell you what we have learned about it.

What is SAP Forecasting?

Technically speaking, SAP Forecasting is an integrated component of SAP IBP that is created and designed for two specific things –

  • Predict the demand of a product that you’ve been working on 
  • Anticipate how the market might change in the future

With SAP Forecasting, you can leverage advanced statistical algorithms and machine learning techniques in order to – 

  • Analyse historical data 
  • Find brand-new marketing trends 
  • Check other relevant factors to generate correct forecasts

Having such knowledge can enable you to make informed decisions accordingly. And it will also be easier to be decisive about inventory management, production planning, procurement, and supply chain management or optimisation.

By integrating with other modules within the SAP IBP suite, such as demand sensing, demand planning, and inventory optimisation, SAP Forecasting provides a comprehensive solution for organisations to align their –

  • Supply and demand planning processes, 
  • Improve forecast accuracy, 
  • Reduce inventory costs, and 
  • Enhance customer satisfaction.

SAP Forecasting can empower a business to predict future marketing demand while anticipating it accordingly. Optimising their supply chain operations will also be easier for the same reason. And the decisions you’re going to make will be data-driven too.

Types of SAP Forecasting Models

As a predictive tool, SAP Forecasting comes with different forecasting models altogether. We are going to talk about four of the most prominent ones here, so let’s get started with it.

Type – 1: The Constant Model

This type of model, as the name implies, assumes that the usage of a material is constant. But, being ‘constant’ in this context doesn’t mean that the use of the same will be similar to what it was in the previous month. Instead, this model works when there is minimal fluctuation.

This forecasting model can be applied, for instance, to the electricity consumption in an office. Yes, the amount of energy exhaustion will be high during the summer months due to the excessive usage of an air conditioner. However, considering winter months, the average consumption of electricity will not vary too much.

Type – 2: The Trend Model

A trend model is used when there is a noticeable and consistent increase or decrease in a particular material or variable over a period of time. 

Although there may be some deviations from the trend, the overall movement follows the established pattern. For instance, if the use of printer cartridges for popular printers declines steadily over time due to technological advancements, the trend would be a downward one.

Type – 3: Seasonal Model

The seasonal model is relevant to businesses affected by recurring patterns associated with weather, holidays, or vacations. 

This model involves patterns that repeat periodically, typically within a specific timeframe. For example, a company that manufactures patio furniture may experience higher demand during the summer months every year, creating a predictable seasonal pattern.

Type – 4: Seasonal Trend Model

The seasonal trend model shares similarities with the seasonal model but incorporates a trend component. Instead of a consistent pattern repeating in each period, the pattern gradually shifts away from the mean value, either in a positive or negative direction. 

For instance, California sparkling wine manufacturers may experience a positive seasonal trend as their sales consistently increase over time in response to seasonal demand. 

Conversely, beer manufacturers with a seasonal market might observe a negative seasonal trend, as their sales decline slightly each year despite the seasonal pattern.

There is also the IBP time series analysis with machine learning, where the system automatically analyses your products’ demand patterns and groups them into a constant, seasonal, sporadic trend, and so on. 

 

Time series analysis helps to understand the data; it also helps to optimise the forecasting process. 

 

The IBP system can automatically pick the ‘Best Fit’ forecast models for the different products according to their individual sales patterns as analysed by the time series analysis. 

 

FAQs – Frequently Asked Questions

Q: What types of forecasting scenarios does SAP Forecasting support?

A: SAP Forecasting supports various types of forecasting scenarios, including demand forecasting, sales forecasting, and financial forecasting, allowing organisations to align their supply and demand planning processes effectively.

Q: Can SAP Forecasting integrate with other modules within SAP IBP?

A: Yes, SAP Forecasting seamlessly integrates with other modules within the SAP IBP suite, such as demand sensing, demand planning, and inventory optimisation, providing a comprehensive solution for supply chain planning and optimisation.

Q: Does SAP Forecasting require specific expertise to use?

A: While SAP Forecasting leverages advanced algorithms and techniques, it is designed to be user-friendly and does not necessarily require extensive technical expertise. However, familiarity with forecasting concepts and training on the SAP IBP platform can be beneficial for effective utilisation.

Q: How does change management relate to SAP Forecasting implementation?

A: Change management is crucial during SAP Forecasting implementation to ensure successful adoption and utilisation of the forecasting system across the organisation. It involves managing cultural shifts, addressing user concerns, providing training, and engaging stakeholders to facilitate a smooth transition.

Q: Can SAP Forecasting be customised to specific business requirements?

A: Yes, SAP Forecasting can be customised to meet specific business requirements. It offers configuration options to define forecasting models, input parameters, and algorithms based on the unique needs of the organisation.

Q: What are the benefits of using SAP Forecasting?

A: The benefits of using SAP Forecasting include improved forecast accuracy, optimised supply chain operations, reduced inventory costs, enhanced customer satisfaction, and better decision-making based on data-driven insights.

Conclusion

So, now, we’ll be concluding this article. If there’s still something you are confused about, be sure to let us know through the comment section below.

We’ll try to help you out accordingly.