Recently I had the privilege of being interviewed for an article for Strategic Risk, a leading publication on risk and corporate governance intelligence. The article [paywall] explores two trending technological developments that allow supply chain businesses to improve how they manage and respond to risk. The first development that we are seeing is the growth in predictive and prescriptive capabilities in analytics; the second is the growth of collaborative networks, also known as crowdsourcing.
Predictive and prescriptive analytics enable companies to plan and respond to unexpected events. For example, when a recent monsoon in India wrought havoc on sugar cane crops, many food production companies struggled. One chocolate factory, however, used analytics to choose a secondary sugar supplier – halfway across the world in South America. The company located and sourced the sugar using data collected from satellite imagery and soil level sensors, which they analyzed to predict the growth rates and health of sugar crops across the globe. This was not possible 10-15 years ago.
Data like this can be very difficult to gather. However, crowdsourcing can reduce the burden. One important factor customers consider when purchasing materials, for example, is knowing that they are child labor and conflict free. However, as I stated in the article, “that is a significant amount of data to gather for any single company, but many other buyers in the market use that exact same supplier and all of its contract manufacturers. So rather than regenerating all this information, we’re starting to see collaborative networks where, when you are using one of these products in your production, you can save that information to the cloud, it can be validated and standardized, and then it can be leveraged by others to understand pricing and market trends.”
These improvements aren’t seamless however, and organizations must keep in mind that this kind of data “...isn’t easy to come by. Often when companies are using these tools, it’s the company’s internal data that is the hardest to integrate.”
For any subscribers out there you can check the full article text here.