Modern supply chains, or demand forecasting and planning based on data

Developments: focus on data and artificial intelligence

Companies open to technological innovation, working at the forefront of digitisation have started to incorporate new generation solutions into their operational processes, such as artificial intelligence, machine learning, or data analytics, that accelerate decision-making and can also "pave the way" for the automation of the supply chain. It is an encouraging sign that 90% of the supply chain managers surveyed expect the advent of new IT solutions in the next 5 years, and 4 out of 5 would like to enjoy, or are already enjoying the benefits of artificial intelligence and machine learning in the design process.

Why is it so difficult to upgrade supply chain planning support systems?

Despite the advantages offered by modern technology, many people still stick to manual, old-fashioned procedures. For example, three-quarters of supply chain processes are still based on the simplest method: spreadsheets (Excel). Furthermore, half of the respondents questioned replied that they used the SAP APO planning system, with support purportedly discontinued by the software company in 2027. Although the innovations would bring several benefits, in general, the majority of companies are concerned about the costs and the lengthy time period of migration to the new system, and therefore are stuck with the old status quo.

Of course, the duration of the process also depends on the complexity of the company's supply chain. However, it can be stated that implementing a new system can take up to 3 years from the selection of the supplier to commissioning.

Nevertheless, almost everyone is well aware that innovation is essential, with 90% of respondents planning to introduce new IT solutions - not surprisingly, artificial intelligence and machine learning ranked first -, and 23% have already done so.

How to bridge the problems that arise during the implementation of new supply chain planning support software?

So, there is no doubt that state-of-the-art systems can make the supply chain more efficient and better prepared, but the necessary IT implementations are in many cases more time and money and time-consuming than originally planned, and the achievement of business objectives is not always carried out to the extent expected. To avoid this, here are 3 important factors that every company should keep in mind when picking supply chain planning support software:

1. Rethinking processes

Of course, automation is not the solution to all problems. Companies should therefore first define the goals they want to achieve and then take the time to discuss how the transition to new software would help them realise them. They also need to decide which parts of the supply chain they intend to improve.

2. Selecting the supplier

• Definition of the requirements imposed on the system,

• Detailed development of the evaluation criteria for the new software,

• Demonstration of 2-3 key study cases by the supplier.

3. Developing an implementation roadmap

According to a pertinent McKinsey survey, one of the biggest problems is the lengthy, dragging implementation of the software. Thus, it is essential to have a detailed roadmap in advance to help prioritise the implementation of each function.

Digesting the above, the introduction of a new supply chain planning support software may seem a little daunting. But with the right attitude, the process can be a success, and the potential benefits speak for themselves: Better planning ability, systems that meet the needs of the business, and ultimately a more receptive and efficient supply chain.

Having read these lines, would you like to start out on the road to improvement? With our data analytics solutions, you can easily realise your ideas, so contact us! In our next article, we will present our machine learning-based solution for demand forecasting.

Source: McKinsey & Company.