For the past 20 years, businesses have been weathering what could be described as a “data explosion.” This explosion has rippled through supply chain and sourcing as access to useable data sources has increased. This data has the potential to revolutionize the way continuous sourcing is conducted.

With proper analysis, organizations can get unprecedented insight into their larger operating environments, allowing them to reduce risks and improve margins. Opportunities that would have been all but invisible before are now revealed.

Unfortunately, lean teams and limited resources mean a lot of sourcing teams struggle to manage this data effectively and so don’t reap the benefits of their digital bounty as a result.

Increasing Agility With Cognitive Sourcing

Being able to react quickly to changing circumstances is an important factor in determining whether an organization is competitive or not. That puts a lot of pressure on sourcing teams. To make use of the data available to them, organizations have to invest in the right analytical platforms and software applications. They need applications that can integrate data and analyze it immediately.

This would help them in sensing real threats, comprehending them and quickly taking appropriate action.  This always on, data-driven approach, designed to enable professionals is what is known as cognitive computing.

This is more than a software iteration, it’s a paradigm shift. One can only expect to achieve a continuous sourcing process through intelligent automation of the underlying monitoring, sensing and action steps. Innovation in direct materials sourcing starts with a recognition that direct sourcing talent must be redeployed in a constant sensing paradigm.

So that means cognitive computing-born intelligent agents must be deployed in parallel. Solving for uncertainty must mirror efforts to identify and act on opportunities (i.e., continuous assessment of market drivers, not just potential threats).

These solutions should have the ability to:

  • Manage and analyze both structured and unstructured data
  • Simultaneously apply objective and preference-based reasoning
  • Learn as they encounter feedback (more data, preferred scenarios)
  • Take action (self configure market interventions, sourcing events, etc.)
  • Communicate with their human counterparts in natural ways.

What this means is that they must not only understand but think, learn and stay dedicated to answering the questions and achieving the objectives presented by sourcing professionals.

Direct materials sourcing professionals needed a way to move past prescriptive, reactionary approaches based on warehoused data histories. They have have taken a path where their actions can be modeled on real-time information. Cognitive sourcing has demonstrated that path.