In the past, supply chain analytics was limited mostly to statistical analysis and quantifiable performance indicators for demand planning and forecasting. Data was stored in spreadsheets that came from different participants within the supply chain.
By the 1990s, companies were adopting Electronic Data Interchange (EDI) and Enterprise Resource Planning (ERP) systems to connect and exchange information among supply chain partners. These systems provided easier access to data for analysis, along with assisting businesses in their designing, planning and forecasting.
In the 2000s, businesses began turning to business intelligence and predictive analytic software solutions. These solutions helped companies gain a more in-depth knowledge of how their supply chain networks were performing, how to make better decisions and how to optimize their networks.
The challenge today concerns how companies can best use the huge amounts of data generated in their supply chain networks. As recently as 2017, a typical supply chain accessed 50 times more data than just five years earlier.² However, less than a quarter of this data was being analyzed. Further, while approximately 20% of all supply chain data is structured and can be easily analyzed, 80% of supply chain data is unstructured or dark data.³ Today’s organizations are looking for ways to best analyze this dark data.
Studies are pointing to cognitive technologies or artificial intelligence as the next frontier in supply chain analytics. AI solutions go beyond information retention and process automation. AI software can think, reason and learn in a human-like manner. AI can also process tremendous amounts of data and information — both structured and unstructured data — and provide summaries and analyses of that information in an instant.
IDC estimates that by 2020, 50% of all business software will incorporate some cognitive computing functions.⁴ AI not only provides a platform for powerfully correlating and interpreting data from across systems and sources — it also allows organizations to analyze supply chain data and intelligence in real time. Coupled with emerging blockchain technologies, companies in the future will be able to proactively forecast and predict events.