A vademecum to understand (and manage) procurement in the next twelve months

The voices that continue to fuel the state of uncertainty and instability on a global scale are well known, from the Red Sea crisis to consumer caution and the impacts of climate change. Companies are therefore called upon to be aware that they have to operate in an economic environment characterised by market volatility, regionalised supply chains and the increasing pervasiveness of algorithm technologies in business processes. Those involved in procurement, in particular, will have to come to terms with the fact that (as a recent McKinsey study states) the world of procurement is - and will be - among the segments most impacted by the challenges of the period in terms of skills and talent shortages, increasingly sustainable procurement policies and greater local interconnectedness.

The experts at IUNGO, a cloud-based supply chain collaboration platform founded in 2001 as a spin-off of the Faculty of Engineering of the University of Modena and Reggio Emilia, have tried to outline some procurement trends to look out for over the next twelve months with a view to anticipating the effects of predictable fluctuations. Artificial intelligence will certainly be a factor, especially with regard to the analysis of data in procurement processes: its use makes it possible to speed up decisions, reduce risks and enable a more agile and informed management of the supply chain, providing the necessary tools to improve efficiency through demand forecasting, stock optimisation, supplier selection and real-time monitoring of the supply chain.

The use of AI in procurement, however, requires knowledge and skills that are not always available or updated adequately and that risk hindering the adoption of innovative solutions in procurement models. According to Micaela Valent, former Head of Purchasing and now Chief Operation Officer Solutions at IUNGO, "to facilitate the deployment of technologies such as artificial intelligence and predictive analytics tools in companies, it is crucial to carefully assess the specific needs and objectives associated with such technologies, reducing the risk of investing in solutions that are too complex, overly expensive and difficult to implement. It is therefore advisable to start with a pilot project, possibly scalable, following an approach that integrates a training path for users and reduces barriers to entry'.

Predictive analytics, not surprisingly, is one of the other trends that will mark procurement during 2024, precisely because the ability to interpret and process historical data and data collected in real time (a capability ensured by the work of algorithms) makes it possible to obtain more accurate forecasts of demand and consequently optimise the management of loads and stocks, reducing the level of risk. Predictive analysis, in other words, can help buyers define strategies starting from real data and achieve better results faster. "However, we have to consider," recalls Valent, "that the introduction of these technologies affects both business processes and people, changing the organisation and the way of working. It is therefore essential to develop analytical skills in order to correctly use the available information, assess its accuracy and effectively communicate the results of the analyses performed'.

A further aspect to be considered, according to the COO of IUNGO, is the generational transition taking place in corporate functions, a change that should be read as both an advantage and a challenge. An advantage because the new generations are generally more at ease with advanced technologies and possess more developed analytical skills, and a challenge because knowledge and 'know-how' are often not corporate assets but remain tied to individuals, increasing the risk that crucial information for correctly interpreting the analyses provided by predictive tools may be lost.