It is axiomatic that a thriving business needs to embrace a robust de-risking strategy. Spend intelligence is increasingly playing a critical role in helping maintain business continuity. As we traversed through the pillars of modern Spend Management, we saw how each pillar added value and laid the foundation for the next pillar.
The fifth pillar of spend intelligence is all about predicting and mitigating risks. Organizations usually have a better handle on managing internal risks as compared to external ones. The unforeseen threats emanating from the external environment are more severe as they can arise from triggers seemingly unrelated to the business, factors such as natural disasters, political upheavals, global calamities, and supply chain disruptions. Internal factors are better understood, and companies have developed better control over those.
The environmental threats have the potential to cause significant business interruptions and can strike from any direction unexpectedly, and organizations are hamstrung in formulating effective mitigation plans. Preparing for these necessitates digging into the data to identify potential risks and develop a well-defined approach to achieve a higher level of preparedness and prevent business disruptions.
Pillar Five: Getting the right balance – a delicate matter!
An ML-based spend solution gives you actionable recommendations allowing you to be in a better position to de-risk your supply chain challenges. For example, take the use-case of your supplier base - being able to see your tier-one and tier-two suppliers across a unified supply chain network allows you to reduce the risk in that area. For instance, if all your suppliers are in tier-one, the solution might recommend expanding and covering your base better by including a few tier-two suppliers, essentially spreading the eggs in different baskets.
If you have too many suppliers for some categories or too few in others – the solution helps you get the right balance. All these work towards reducing the impact of disruptions. You build resiliency in your supply chain with insights harnessed from historical data.
Today ML techniques have the potential to mitigate supplier risks by predicting supplier reliability, supplier non-compliance, and capability using pattern recognition and harnessing the historical data for trends.
The details of the other pillars are located at Pillar One, Pillar Two, Pillar Three, and Pillar Four (add link).
ElectrifAi’s SpendAi: 2-4% savings in 6-8 weeks
ElectrifAi is one of the US’ leading ML solutions providers with a large library of pre-built solutions enabling our clients to capture tangible benefits quickly. We work with the C-suite to understand and then solve business problems through data and machine learning. The insights generated from SpendAi help our clients realize 2-4% savings in 6-8 weeks. In addition, it provides specific recommendations to mitigate supply chain risks. All this is done with zero data quality requirements and zero need for a data science team.
Our solution does not require investment in a new platform or infrastructure or a data science team. Instead, we leverage the data existing in your system to power the ML models to deliver business outcomes.
We are the last mile solution that sits on the top to solve specific business problems and bring about savings.