In days when suppliers of companies were located close-by, relationships were based on trust and perception. Times have changed. All enterprises source goods or services from far-flung suppliers—separated by time zones, cultures and regulations.
As the radius of supplier universe grows, so do the risks that suppliers carry. In some cases, the losses caused by supply chain disruption can go up to millions of dollars. In 2014, a huge controversy on food safety broke out when a China-based supplier of Walmart was found to have contaminated donkey meat with fox meat. A year before, BMW had to recall 220,000 vehicles due to a faulty airbag sourced from one of its suppliers.
BI and predictive analytics
Organizations now have to be vigilant and predict supplier risks in order to prevent them. The proactive approach to continuously monitor suppliers by gathering information from a variety of sources can be made possible by analytics. All in all, supplier risk is also required to be computed on a global scale.
Investing in basic business intelligence (BI), however, is only half the job done. BI can trace noteworthy patterns by mining and interpret historical data. This can surely help assess supplier risk and take decisions. It cannot, however, provide an warning about the specific potential risks that loom in the future.
As the world has become complicated with a variety of risks, there is a need to brace for the unforeseen risks. The primary need for analytics in supplier risk management is to anticipate a possible disruption. If it cannot be predicted, it should give the fastest possible alert for the company to take necessary action and cushion the fall.
Predictive analytics can arrive at worst case scenarios that may potentially lead to crisis. It analyses a large volume of data sourced from across the business by applying hundreds of variables. With simulation, predictive modeling, and resource optimization the procurement office can take suitable decisions based on the potential scenarios offered by analytics. With a regular flow of such insights, chief procurement officers (CPOs) can ensure that their supplier ecosystem stays healthy—at all times.
Future and prediction of risk
Companies generally classify their suppliers tier-wise. Each of these supplier tiers needs different levels and extent of surveillance which can be linked to analytics. Analytics improves the quality and usability of enterprise data.
Risk assessments which do not involve automation tend to use old or outdated data and tend to make faulty assumptions potentially leading to risky conclusions. With automation, supplier risk mitigation becomes a dynamic process where every change including the latest financial data of suppliers to external factors such as weather, the stock market, economic and political developments, etc. are factored in and updated.
It takes a lot to predict future, especially in uncertain times. Analytics can provide a much-needed view for organizations to stay alert and ready!