Advanced Sourcing and Procurement Technologies: Natural Language Processing

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Ardent Partners’ recent research report, Sourcing and Procurement: The 2016-2017 Technology and Innovation Outlook Report, chronicles the evolution of sourcing and procurement technologies over the last two decades to where they are today and poised to go tomorrow. This report, which is chock full of great insights on many advanced, distinct sourcing and procurement technologies, has spawned a series here on CPO Rising that looks in depth at each of the innovative solutions coming onto the market today and in the near future. Today’s installment: Natural Language Processing.

Natural Language Processing

Another derivative of machine learning, natural language processing (NLP) has been in development since at least 1950 when Alan Turing, the famed British mathematician and cryptologist whose computer cracked the Nazi enigma encryption device, began developing the technology as a proof of concept. Since then, NLP has advanced to the point where developers have combined it with machine learning, artificial intelligence (AI), and advanced algorithms to make human-computer interfacing seamless and instantaneous. Its implications for future business practices in general and procurement and supply management in particular are meaningful, and perhaps not fully understood.

For starters, NLP can serve as a practitioner’s very own personal, digital assistant that can take orders and questions and provide solutions and answers with a moment’s notice. Practitioners can simply verbalize their question or request and a NLP-enabled solution will provide the answer or the status update in return. Likewise, users can type their questions or requests into a search field and the system will perform the task or answer the query. The capability already exists in several common, recognizable forms, such as Amazon’s Echo or Alexa, Apple’s Siri, and Microsoft’s Cortana. Consumers are using them in their personal lives – why not their professional lives, too?

Consider the efficiency gains for process workflows wherein a user, on a whim, calls out to their personal assistant to search for the market price for light sweet crude, or the direction in which the New York Stock Exchange is trending, or the status of labor disputes in a major port town. Although the user may be performing a related task, like a sourcing event, searching for this information on their own may interrupt their process workflow and result in efficiency losses. But tapping a virtual assistant via NLP technologies allows the user to remain “on target” while pulling in vital market intelligence to support the project.

Another added value of NLP occurs when the “voice” moves from reactive to proactive – when it learns from previous transactions, anticipates user needs in the context of a particular scenario (for example, a sourcing event involving crude oil and seaports), retrieves the pertinent information, and provides it to the user in the context of their application or workflow. Here, the confluence of NLP, machine learning, Big Data, and AI can produce a sum of value that is greater than the whole of its parts.

Final Thoughts

Natural language processing has been an exciting and promising innovation for more than 65 years, and it has shown significant potential to aid the business world. If procurement and supply management practitioners can incorporate widely available technologies and capabilities into their process workflows, they have the potential to add significant value to their day-to-day transactions and offload random queries to a personal digital assistant that is standing by to take questions and orders and deliver answers and results.

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Tagged in: Ardent Partners Research, Innovation, Matthew York, Process, Strategy, Technology