IBM's Watson: Creating Healthier Supply Chains

The readings this week show how the internet is radically changing SCM, by bringing about such innovations as mass customization (McKinsey) or the creation of B2B exchanges (Vance).  At the heart of all recent innovations is companies’ ability to collect and manage data to make critical decisions. As companies gain access to more information, making sense of it all—separating the signal from the noise—becomes more and more of a challenge. This is where IBM’s Watson comes in.  

After its debut on Jeopardy, Watson has been developed to be used for more practical applications, such as healthcare decision-making. While information technology that helps doctors and patients make decisions has been around for a long time, Watson provides something different. According to IBM, Watson can process information and make recommendations much more quickly, and more intelligently, than any machine before it—processing up to 60 million pages of text per second, even when that text is in the form of natural language. 

This is huge, given that (per IBM) 80 percent of all information is unstructured. In medicine, unstructured information consists of things like physician notes dictated into medical records or complicated sentences in academic journals. In theory, Watson can make sense of it all, and over time it is able to learn. The Atlantic explains: 

As Watson got better at Jeopardy the longer it played, so it gets better at figuring out medical problems and ways of treating them the more it comes into contact with actual cases. Watson even has the ability to convey doubt. When it makes diagnoses and recommends treatments, it usually issues a series of possibilities, each with its own level of confidence attached.

 

Global supply chains have a level of complexity similar to that of healthcare, and Watson may prove to be a useful tool in helping companies manage that complexity. Per Waller and Fawcett, data science applications for SCM require both domain knowledge and quantitative skill, and Watson is a machine that holds the potential to maximize both.  Watson demonstrates just how advanced analytics can be applied in creative new ways  to deliver faster, deeper insights into unstructured information while continuously learning over time.

Watson’s capabilities may go a long way in helping companies address current and future supply chain challenges. According to IBM's most recent study on supply chain management, some of the biggest challenges companies face are: 

• Cost Volatility – global complexities, market shifts, and fluctuations in customer demand
• Visibility -lack of access to timely, global information from partners to make decisions quickly
• Customer Engagement—including customer preferences and feedback into product and SCM decisions 

Watson has the potential to help companies face all of these challenges by enabling decision-makers to separate the most important information from a deluge of data coming from multiple areas, including planning, forecasting, sourcing, transportation, manufacturing, distribution on the supply side and advanced analytics/customer feedback on the demand side. With additional development, Watson can act as a doctor for a given company's supply chains, as it diagnoses bottlenecks and enables supply chains to become more healthy and resilient.
  
How would Watson contribute to SCM strategy, such as lean manufacturing, sourcing and sustainability decisions? What are Watson’s SCM limitations? 
 

References: 

How Technology Can Drive the Next Wave of Mass Customization. McKinsey Quarterly. February 2014. 

For an Online Marketplace, It’s Better Late than Never. Vance, Ashlee. New York Times. Novemeber 20, 2010. 

Data Science, Predictive Analytics, and Big Data: A Revolution that Will Transform Supply Chain Design and Management. Waller, Matthew and Fawcett, Stanley. Journal of Business Logistics, Vol. 34[2]. 2013.