2020 has been the year of the Supply chain, as all aspects of the function have been exposed and challenged and few businesses have emerged on affected. As we move through the myriad of 2020 supply disruptions, procurement has a supplier data problem, the side effects of which are costly and far-reaching.
As supply risk continues and effective suppliers’ relationship management and assurance becomes even more challenging, as can be seen by recent 2021 research findings:
So, what do we have to look forward and how can Supply chain and procurement executives prepare for success?
The solution might be found in investing time and resources to make sure that supply chain and procurement teams are empowered by a cleansed, harmonized and enriched big data foundation.
Big data is one of the most commonly discussed topics today, and many companies are attentively monitoring the evolution of this trend. Several studies have shown that managers are able to make the best decisions when armed with data and tools to gather insight. Researchers report that a 15-20% increase in ROI can be achieved by introducing big data to enterprises’ business analytics.
Traditionally, purchasing and supply management (PSM) has strongly relied on data management, as procurement managers need to dispose of, clean and update data of different natures to compare suppliers’ performance and 20-50% of working time in procurement is related to searching for information accordingly.
Big data analytics have obvious applications and represents a new era in the PSM field as they link and aggregate all relevant information, thereby facilitating and speeding up strategic and operational procurement activities significantly and are a critical source of meaningful information that can help supply chain stakeholders to gain improved insights and gain a competitive advantage and maximizing speed and visibility, improving supply chain relationships and enhancing supply chain agility.
However, despite the relevance of data management, the PSM field has been relatively slow to identify the potential role of new technologies and businesses have been less quick to implement big data analytics in PSM than in other areas, such as marketing or manufacturing.
Few companies, however, have been able to apply the "big analytics" techniques that could transform the way they define and manage their supply chains. The full impact of big data is restrained by two major challenges. First, there is a lack of capabilities. Supply chain managers—even those with a high degree of technical skill—have little or no experience with the data analysis techniques used by data scientists. As a result, they often lack the vision to see what might be possible with big data analytics. Second (and perhaps more significantly), most companies lack a structured process to explore, evaluate and capture big data opportunities in their supply chains.
But, once applying these technologies, high performers are 4-5 times more likely to have fully deployed advanced analytics/visualization, have fully deployed predictive analytics capabilities (12% vs. 0% for others) and are 18 times more likely to have fully deployed artificial intelligence (AI)/cognitive capabilities. Strong digital capabilities can help procurement organizations improve data visibility and the ability to collaborate/synchronize with suppliers, enabling greater agility both within these organizations and across the extended supply networks. CPOs can work toward building use cases for the Internet of Things, 5G, blockchain, control towers and collaborative workflows enabled by AI/machine learning to up their digital game in these areas.
