It’s no secret that the global healthcare industry is undergoing a profound and fundamental shift from rewarding volume of sales, procedures performed, and patients treated towards a focus on improving overall health, patient outcomes and value for the health system. But what does this mean to today’s supply chain? Recently, I had the opportunity to pose this question to a select group of life sciences supply chain executives at Logipharma 2016 in Princeton, New Jersey.
The group, comprised of executives from companies within the Biotech and Pharma value chain, were of diverse size and at various stages of transformation within their own companies. The overarching theme that emerged in the discussion was the need for digital supply "network" capabilities to support the varied business models, while navigating a rapidly changing landscape. More specifically, we discussed the characteristics of what a "digital supply network" is. This led to a discussion on the four key characteristics that define a digital supply network:
Rapid – enhanced responsiveness, proactive prevention, last mile postponement
Scalable – maximum efficiency, organizational flexibility, highly evolved operating models
Intelligent – analytics, actionable insights, automated execution, enhanced, accelerated innovation
Connected – real time visibility, seamless collaboration, personalized experience
The added challenge of assembling the right team with a diverse range of specialized skills is a common stumbling block. In order to broaden our sights beyond traditional sources and categories of talent, supply chain leaders need to deepen the talent bench and explore new roles. The supply chain team of the future builds upon the traditional skillset of a Business Analyst, and supplements this with a Data Scientist, Systems Architect, Data Engineer and Predictive Modeler.
Our group was particularly intrigued by the role of the Data Scientist. The seamless integration of the characteristics and skills of the Business Analyst, with the technological know-how of the Systems Architect needs to be underpinned by the modeling of the Data Engineer. Resulting in, a Business Analyst who works with the Data Scientist and Predictive Modeler to proactively determine business insights- a dynamic that would not happen with a traditional approach. This organizational approach enables a more effective outcomes-based, and business value focused mindset versus the traditional approach of simply keeping the operations running and understanding what has happened in the past.
Ultimately, the roadmap must be defined and executed to meet the business objectives for each company. There are a number of ways to transform from the traditional supply chain to a truly integrated digital supply network. But the time is now. Taking no action is not an option.