Introduction. Modern organizations may utilize thousands of suppliers. Suppliers with poor or inefficient processes or inadequate compliance may directly impact production and revenue targets. Furthermore, suppliers with poor social responsibility practices may expose an organization to brand and legal risks. As such, an organization must regularly audit the products and services provided by its suppliers. In particular, an organization must evaluate suppliers based upon quality management procedures, supplier corrective action request (SCARs) responses, documentation, requirements and specifications, programming, testing, installation, change control, support and maintenance, security and electronic records compliance as well as review legal, ethical and regulatory aspects and for a large organization this process will take two weeks on average. Supplier audits are a necessary, but time and cost prohibitive, aspect supply chain governance. One widely used solution is to automate complex tasks such as audit planning, checklist preparation, audit schedule, data collection, record findings, and supplier ranking and incorporate the results as part of an enterprise-wide audit management system. While these systems may be highly useful, the biggest drawback is that they are often implemented as a static solution predicated on individuals having the time to complete assessments and analyze data. 
What is cognitive procurement? Cognitive procurement, the application of cognitive computing to procurement, is the act of accessing structured and unstructured data and dynamically investigating spend categories, suppliers, and external risk factors. A cognitive procurement system enables one to systematically analyze data and subsequently generate meaningful results. A well designed cognitive procurement system may be self-learning. If this is the case, then it incorporates current information into future analyses.Cognitive procurement allows us to transition from a cross-sectional view of our suppliers to a time-evolving view. Furthermore, it shifts the role of technology from that of enabler to adviser. Some specific tasks where cognitive procurement may be highly useful include 
- Quickly sorting through very large amounts of structured or unstructured data
- Providing detailed supplier assessments
- Providing in-depth risk assessments, identifying hidden risks, and calculating risks
- Supporting and validating decision-making
- Uncovering new opportunities
Risk management example. A good supply chain governance system not only allows one to rank the risk of their suppliers, but it also allows them to rank them in a timely manner. As the world is ever-changing this means that we would like to be able to reduce our list of thousands of suppliers down to a manageable subset of those suppliers (for the more technically inclined readers we would like to reduce the dimensionality of our data set). This can be accomplished via cognitive procurement. Sentiment analysis studies the expression of mood, opinions and attitudes. In essence it attempts to determine whether a communication suggests a positive, negative or neutral sentiment. Some public sources that are commonly mined with sentiment analysis include Twitter, Facebook, news articles and feeds. However, it is becoming increasingly common that companies are starting to mine internal communications such as emails, phone calls, wiki, and chat rooms. According to Vasant Dhar, a data scientist and professor at New York University’s Stern School of Business and the Center for Data Science, “Sentiment analysis has become a form of risk management and is emerging as a useful risk control tool for a variety of businesses.”  By constructing a system using a procurement-specific sentiment dictionary, similar to the JP Morgan dictionary that was recently published at , one could cost-effectively develop a flagging system. News-related analysis would allow one to proactively identify good suppliers that may run into problems due to external risk factors. Alternatively, using internal communications allows one to cost-effectively identify problematic suppliers or even fraud related to those suppliers.
Conclusion. Cognitive procurement is a burgeoning field. According to Jeff Jarvis, director of the Tow-Knight Center for Entrepreneurial Journalism at the City University of New York, “By 2025, artificial intelligence [a technique considered to be part of cognitive procurement] will be built into the algorithmic architecture of countless functions of business and communication, increasing relevance, reducing noise, increasing efficiency and reducing risk across everything from finding information to making transactions.” By adopting cognitive procurement, a company shifts itself from a reactive company to a proactive one. Early adoption ensures that one is able to identify and take advantage of arbitrage opportunities in the marketplace. 
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