It seems that everyone is talking about Procurement these days. A Google search for cognitive procurement returns about 650,000 results that include news sites, analyst firms, and vendors ranging in size from Old St. Labs to SAP Ariba to IBM.
Definitions are varied as well. Quora defines cognitive procurement as the application of self-learning systems that use data mining, pattern recognition and natural language process (NLP) to mimic the human brain to around the processes of acquiring, buying goods, services or works from an external source. IBM’s Vice President of Global Procurement defines cognitive procurement as the use of systems and approaches that are able to learn behaviour, manage structured and unstructured data, and unlock new insights to enable optimized outcomes. Vodafone defines cognitive procurement as augmented intelligence capabilities that allow a category manager to make faster and smarter data driven decisions that deliver competitive advantage.
But what does this all mean? First of all, the only commonality is using systems to do a task better. Which systems? Which tasks? Who gets the benefits? And what precisely are the benefits?
To figure this out, we have to go back and define what makes for better Procurement. The first step is good Sourcing. What are the keys to good Sourcing?
There are a number of keys to good Sourcing. Some of the most important include:
Visibility. Who are your potential suppliers? What do they provide? Where are they? What do you know about quality, reliability, delivery, etc? What are the risk factors with dealing with them? What data can you get on finances and sustainability? You need good information.
Analytics. Once you get the information, you need to make sense of it. Roll up component and material costs across bill of materials. Amalgamate risk ratings into meaningful scorecards. Aggregate demand across categories. Determine what you need, when, in what quantities, and how much it should cost before you start a negotiation.
Modelling. The ability to define detailed should cost models based on components or materials, production costs that include energy and labour and overhead, and other relevant cost factors. To define how those costs change with market data or production volumes. And so on.
Optimization. Once you get the data, you need to figure out the baseline costs and what the optimal awards are assuming nothing changes. Then how those change as costs change as bids change. Also, what are the optimal logistics strategies and costs. How does logistics impact the award decision? How should the logistics supply chain be designed?
Negotiation Support. At some point, the analysis needs to turn to negotiation, because the goal of sourcing is to acquire the products and services the organization needs to support its operations and satisfy its customers. All of this capability needs to be brought to bear in a cohesive, assistive, fashion that can help a buyer make the right decision.
That’s what cognitive procurement is — presenting a user with the information they need when they need it to make the right decision. Not automated buying. Not artificial intelligence which doesn’t exist. Not trying to mimic the human brain, as we don’t even fully understand how that works now.
So, does any application meet these requirements?