Artificial intelligence (AI) is discussed, referenced, dissected, and applied to almost every situation in modern technology news. One aspect of AI that could provide immediate practical benefit to your business today is natural language processing (NLP).
NLP translates unstructured data into “signals” of upstream supply-chain activity based on highly sophisticated human-computer interactions. Examples of expert systems that interpret and analyze written language using NLP include iPhone’s Siri and Window’s Cortana.
As part of the forecasting process, raw data must be cleaned before it is imported into any solution. This data could include unstructured data from news feeds, social media, weather trends, etc. The process of cleaning and normalizing data takes far longer than necessary, absorbing the majority of a demand planner or forecaster’s time, which takes them away from crucial planning activities. NLP can help solve this issue.
That said, applying NLP is not enough. Precision is also important, which is why Vanguard Predictive Planning is the top choice for many industry-leading companies.
Benefits of NLP
With daily advances in data mining and NLP, the range of content and depth of understanding will only become more sophisticated over time, allowing you to scan, pinpoint, and manage potential supplier disruptions before they occur. With these self-learning algorithms in place, supply chains become significantly more intelligent.
This knowledge is layers deep, providing additional insights and analysis to the existing historical time-series framework, which most organizations use to forecast various aspects of their supply chain.
Start leveraging the benefits of NLP and text analytics to monitor signs of instability in your supply chain. Set alerts to notify you of potential changes that may impact the efficiency of your supply chain. The goal is to gain as much insight as you can regarding the health of your supply chain in order to better serve your customers. Reach out to see what Vanguard can do for you.