One number forecast
n this video, we will discuss the importance of one number forecasting and how to achieve it. We will explore the following topics:
- The challenges of traditional forecasting
- The benefits of one number forecasting
- How to achieve one number forecasting
One number forecasting is a best practice in demand planning. It refers to the process of creating a single forecast that is shared by all stakeholders in the organization. This ensures that everyone is working from the same data and that decisions are made in a coordinated manner.
There are many benefits to one number forecasting. It can help to improve accuracy, reduce costs, and increase agility. It can also help to improve communication and collaboration between different departments.
However, achieving one number forecasting can be challenging. There are a number of factors that can contribute to forecast inaccuracy, including:
- Lack of data
- Inconsistent data
- Biased data
- Poor forecasting methods
To achieve one number forecasting, it is important to address these challenges. This can be done by:
- Collecting and cleaning data
- Standardizing data
- Using unbiased forecasting methods
- Ensuring that everyone is involved in the forecasting process
So Chakri, the modern best practice is to try and get to one number forecasting. Well, what does that mean? That's a great question. It's a very often repeated mantra, one number forecast.
So what it actually is referring to is the fact that there are different stakeholders in the company for the forecast. There are different forecasts in the company: For example, there is a sales forecast, there's a supply chain forecast and there's a finance forecast. Often these forecasts are completely misaligned, causing sales and supply chain decisions to be disconnected. And eventually that has impacts on the P&L.
So the question is, how do we create a one number forecast that aligns sales, supply chain and finance? But to understand the complexity of the problem. Let's first understand why there are different forecasts. Sales is using the forecast to drive commercial decisions, i.e. investments in marketing and sales investments by product line, by brand, by market by account.
Supply chain is using the forecast to drive supply chain decisions, which are at a different level of detail. It's by supply chain location Its by potentially by SKU stock keeping unit that you're building to a forecast. The financial forecast is at a different level. What they're required is what they need to report to the external stakeholders, and that's at a different level by product line and business unit, by brand, by market, etc.
So they are different stakeholders. Each have a need for a forecast to support their decisions. But all these forecasts are at different levels of detail for different purposes. And what has happened historically is because of the functional silos and technology limitations, each one has developed their own forecast and they never get connected.
And as a result, supply chain and financial decisions and sales decisions are often at odds with each other. And when they try to reconcile those decisions, if there is a big war between the different stakeholders. So the idea is to get to a one number forecast. And what that really is talking about is the need to get to one view of what the market forecast is at some common level between sales, supply chain and finance, agreed to that number as the plan or the forecast at the common level.
But then the process and the technology needs to have the ability to then enable the supply chain to have its own lens of that forecast or disaggregated to what it requires for the down supply chain decisions. And take that one number, a common forecast that technology needs to have the ability to enable the sales team to take that view of the forecast as they're required by market and by account and by product line and similarly, finance. So the one number is really referring to the collaboration and consensus that we need to arrive at a common level between the sales supply chain and finance organisation.
But the technology needs to enable the different lenses of the forecast at different levels of detail that these different stakeholders need to have. And that's really the challenge in creating a one number process and one number system.
How industry leaders improved their forecast accuracy with AI/ML Forecasting
Learn in these use cases how industry leaders can vastly improved their planning and decision-making with AI/ML forecasting