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COVID disrupted healthcare industries and supply chains 

- from pharmaceuticals to services and manufacturing – at every level.


Healthcare system patient business model

  • USA: $200B hospital financial losses
    EU: Most vulnerable without healthcare; millions with no care.
  • APAC: 40-50% shifted to wellness of staff vs. providing care. South Korea, Thailand down 40-60% in procedure revenues.
  • LATAM: Shortfalls in funding causing inability to restart access.

Hospitals in the red and patients left without any place for emergent, semi-emergent or elective surgeries.


Healthcare adaptations and extensions

  • Backlog: Health systems create a backlog of surgeries with many health systems implementing a criterion to proceed.
  • Adaptation: Hospitals adapted the hospital to surgical areas and COVID areas to maintain surgical capacity but limited to emergent.
  • Expansion: More surgeries moved to ambulatory care and outpatient centers. Typical inpatient procedures were moved to an ambulatory or outpatient location.

Capacity re-direction is plug or bandage but not sufficient to sustain for future waves.



Next generation healthcare demand planning capabilities

  • Healthcare demand planning requires organizations to integrate multiple capabilities and resources, including forecasting, demand sensing, manufacturing, supply chain fulfillment and more.
  • Almost 90% of healthcare manufacturers depend on international distribution for 50 – 70% of their products, supplying only 25% of the world’s population.
  • This renders them particularly susceptible to sudden changes in the global supply chain caused by a pandemic like COVID-19.

When existing demand models are rendered ineffective, businesses and patients suffer as a consequence.


new data

New data standard for healthcare

  • To support, guide and help patients in need, we set out to establish a new standard for measuring global healthcare demand with a syndicated solution based on ML and AI.
  • Our next generation solution can be implemented in government and non-government organizations, manufacturers and healthcare providers as an input to their demand planning model, while integrating proprietary data which we assess for relative importance.
  • Through the use of the latest cloud-based technology, our demand planning solution provides cloud-based tools for flexible access to data reports from any device.

The resulting product provides demand planning capabilities for healthcare products integrating up-to-date and localized data.


ml demand case pic
Throughout the COVID pandemic, healthcare providers have faced unique supply chain disruptions which limit their ability to predict demand for supplies and procedures.
In this case study, we’ll consider the impact of COVID on supply demand from the perspective of patients awaiting orthopedic procedures due to decreased hospital capacity and availability of implants. Along the way, we will endeavor to show that next generation planning models driven by tenders data, artificial intelligence (AI) and machine learning (ML) can help healthcare providers to navigate the difficulties of a post-pandemic world.