A Demand-Driven Supply Chain - 4 Pillars for Success (Part 1)

By Sophie Rutherford

April 29, 2017

What does it mean to become a more demand-driven supply chain? I recently saw a good definition and adjusted it to apply it to healthcare - “A system of coordinated processes and technologies that senses and reacts to real-time demand signals across a network of suppliers, employees and patients.”  The crux is this: we need an infrastructure that enables demand signals to be shared up and down the supply chain.

So how we can best align and leverage data, optimize workflow and integrate systems? There are four pillars that tee up the framework for alignment and integration, foundational pieces of shifting to demand:

1. Visibility - Transparent demand and inventory levels across supply chain require an organization to:

  • Have a technology to support real-time visibility
  • Work closely with your suppliers
  • Share information rapidly and frequently
  • Take action promptly

Many healthcare organizations suffer from a lack of visibility, especially when there are multiple ERP systems in place. So many data sources, so many variables. Look for a technology platform that can support your data across your entire infrastructure. This is a critical component because the availability of that data in a real-time exchange is mandatory to becoming demand-driven.

2. Infrastructure - Support a robust infrastructure to quickly adjust to changes in supply and demand:

  • Includes People, Process & Technology
    • Technology should support seasonality, demand forecasting and variability
    • The people in your organization should have the capacity and flexibility to implement and support change
    • Processes should be evaluated routinely to optimize the technology that can forecast change

While infrastructure can be broadly used to describe many things, in this case, let’s refer simply to the people engaged in the data standardization efforts, the processes that are in place to support the efforts and the technology which is the curator of the “Supply Chain DNA,” your data. Your technology must have the flexibility to support variability across your infrastructure and provide you with actionable data; the people in your organization need the skills and knowledge to translate and take action on the data.

3. Coordination - Tight coordination across players to execute flawlessly and cost-effectively:

  • Set a common goal
  • Define the team roles
  • Plan and communicate…and communicate again
  • Measure effectiveness, and adjust

The fastest way to fail is a lack of communication. Build understanding of common goals, so everyone is moving in the same direction. Know who your stakeholders are – and then regularly engage with them.  COMMUNICATION IS KEY. I can’t say this enough…I have teenagers, I know this is true! 

Communicate key performance indicators (KPIs) to your team so everyone understand what “good” looks like. Make sure everyone knows how to adjust, if KPIs aren’t yet at “good.”

Finally, your processes should be ever-changing to support the constant change in healthcare. You should routinely evaluate your process (standard with a six sigma approach) to determine where there are opportunities to further optimize, change and measure to continuously improve.

4. Optimization - Set sights on optimizing performance - not just reducing costs - to deliver the best service and solution and achieve major financial benefits:

  • Assess the problem and measure performance before change
  • Identify what is critical for improving the performance
  • Measure the performance of the system after change
  • Practice gaining consensus

Scorecards or performance reports are a great way to measure, assess, change and measure again. Just like we saw in “Coordination,” it’s a cyclical process.  Without data, you can’t measure and assess. Having data standards in place to optimize is critical to the process.

These four pillars help build the foundation to shift toward a demand-driven supply chain. Next, we’ll talk about the challenges of standardizing your data, especially across disparate systems.