Demand forecasting with a Stratis solution

The role of demand forecasting

Demand planning with suitable accuracy can be the starting point to answer many commercial issues. We can already make better decisions if we know only approximately how our sales figures will look like in the period ahead. We can organise supply processes seamlessly and more cost-efficiently starting from procurement to delivery. We can avoid the inconvenience of stock-outs and minimise the warehousing and transportation costs associated with goods pile-up. Of course, there are other benefits to being adequately informed about the level of demand. This way we can adjust our prices and plan our future marketing activities.

The criteria for demand forecasting

When forecasting demand, it is worth thinking in terms of types and factors. On this basis, we distinguish between short- and long-term forecasts, as well as macro- and micro-level forecasts, which are influenced by factors such as seasonality, competition, and product types. By considering these parameters together, you can provide continuously updated performance figures with weekly or daily degree of detail, broken down by article number, region, or store. By integrating this data into your procurement, logistics, and manufacturing systems, you can introduce efficiency into your day-to-day operations and improve your business performance.

An easy-to-integrate solution 

At Stratis, we believe that the demand forecasting model created should be a solution that integrates well with the company's operations from the angles of business and technology. Let's look at the characteristics of the solution we provide:

• REFINED: The diversity of input variables ensures the accuracy of the model and the ability to take into account different effects together. The model provides insight into the impact of each factor on demand, which can then be modelled independently, disregarding other effects.

• ROBUST: One model provides forecasts for multiple article (item) numbers.

• SELF-LEARNING: The model continuously absorbs and learns new patterns and trends, providing increasingly accurate forecasts.

• MEASURABLE: Model performance can be measured and monitored. Models are easy to operate and maintain.

Technical implementation

Implementation may proceed along two lines. The first option is to insert the demand forecasting model into the existing BI (Business Intelligence) & ML (Machine Learning) environment, and the other is to create a stand-alone analytical environment. In the following, we show what tasks we carry out in both:

• Develop a data market to structure input data

• Store results, create an interface to operational systems

• Data visualisation, dashboard development

• Develop an operational framework for the continuous learning, running, and monitoring of models.

Of course, Stratis always offers customised, individual solutions for its clients. We assess the BI maturity of your company on demand, create a BI strategy, and propose technology, process and organisational improvements. Then comes implementation, so that the data can start generating real business value in the real world.

If you want to raise your company's demand forecasting solution to a new, advanced level, assign the task to expert hands to make it happen! Contact us!