Omnichannel Commerce & Retail in Pharma/MedTech

Our Consulting Services & Enagement Models:

1) Models for Omnichannel Commerce & Retail for Pharma&MedTech
2) Diagnostics (current level of Omnichannel & Optimized Retail capability)
3) Strategy & RoadMap (for target capability level)
4) Assessment for Omnichannel Commerce Capability (at defined intervals)

Sample Models:

1) A model for optimal inventory policy parameters for the Pharma/MedTech supply chain that result in minimum cost and minimum waiting times
2) A model for systemic effects and which introduces the need for supply chain and network management. Goal is to minimize the cost
3) An Agent-based Model for Consumer Experience and Marketing in Retail
Expected: vast ranges of products (much larger assortment), lower prices, inspiring customer experiences (more useful reviews), personalization (personalized recommendations), ever faster delivery, better service (quick returns)

A) Agent Type: Consumers – WHO is shopping WHERE?

  • How to improve consumer engagement and access that data
  • We need deep understanding customer preferences, habits, and motivations
  • Insights from emerging data sources (e-commerce websites, social media)
    • Consumer-flow analysis (insights into consumer preferences)
  • How data from consumer experience, marketing can aid in
    • Improving consumer experience
    • Marketing improvement
    • dynamic pricing, demand shaping, or demand sensing
  • How to measure ROI on consumer experience improvement efforts?
  • How to measure ROI on marketing improvement efforts?
  • How to do Buyer Behavior Analysis and use it to our advantage in Retail?
  • Consumer and product-flow analytics includes basic elements, such as understanding cost-to-serve expenses for different service levels combined with an estimation of the benefits. It also includes demand shaping through dynamic pricing and a deep understanding of the underlying drivers of consumer behavior.

B) Agent Type: Omnichannel Store Manager
Segment – channel, customer group, product category, location

Operations: Demand Forecasting, Inventory Mgmt, Assortment, Pricing Inventory policies, Order management processes


  • Real-time inventory visibility (inventory across channels, and potentially across companies)
  • Strong DOM – Determine the optimum node from which each order should be fulfilled
  • Planning and Inventory Management – advanced analytics and machine learning to predict point-of-sale demand per SKU for specific stores, or specific zip codes, by day and sometimes even by hour. Combined with quick, smart replenishment processes for stores and DCs, this reduces the stock required for individual nodes by enabling a sort of just-in-time delivery.
  • Efficient and rapid node and store operations