A growing number of companies are turning to technologies including big data analytics, the InternetRead More
How can big data help transform supply chain risk management?
One of the great benefits of big data analytics technology is that with the right skills and information available, the solutions can be applied to almost any aspect of a business. And one area where these tools are getting an increasing amount of attention is in supply chain risk management assessments.
This is a critical operation to many companies across a range of industries, from manufacturing to retail and food production. Any disruptions that may arise among suppliers can have a severe knock-on effect throughout the business, as the ripple effect stretches far beyond the initial incident.
However, for the majority of enterprises, their approach to managing this still revolves around relatively simplistic methods for assessing the likelihood of a problem. In many cases, this may come down to a gut feeling or guessing game, before buying what the company determines as an appropriate level of insurance.
Forbes contributor Kevin O'Marah wrote in a recent article for the publication that this is usually a reactive approach, with information derived from past experiences. This means businesses miss the chance to get ahead of threats in the first place and could leave them exposed to unforeseen risks.
This is where big data analytics can prove hugely valuable. Mr O'Marah explained: "The whole point of big data, and in fact its definition to some degree, is about seeing hidden meaning in a storm of information. As humans we naturally do this, but our behavioural ticks distort meaning and fool us into bad decisions."
Applying big data tools to traditional SWOT analysis can help ensure that risk management profiles are built on factual information rather than guesswork, as well as making sure that key principles are applied consistently throughout an organisation.
Mr O'Marah explained that risk management should be viewed as a constant cycle of preparing for trouble, spotting it as early as possible when it arrives, and then reacting accordingly.
"An analogy can be drawn with your home. In the event of a fire, which does you the most good? Insurance, a fire extinguisher or a smoke detector?" he continued. "Big data is your smoke detector."