Key to Supply Chain Change Management Success: Scenario Analysis

Supply chain network models are powerful tools that help organizations make critical decisions. These decisions have a significant impact on growth plans, customer service and overall cost to serve. Therefore, the analytical process to develop and run these models is rigorous and very data intensive. This analytical rigor brings a level of confidence to the results of the model and should make accepting the results a logical step. In theory, this is true. But in practice, supply chain change management doesn’t quite work out that way.

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Supply Chain Change Management: The Supply Chain Network Model

The best way I have come to understand why supply chain change management often breaks down is due to the way most organizations think about models. When we refer to models, we often refer to something that we build physically or virtually within a computer. It could be an architectural model of a building, or a supply chain network model for an organization.

For this blog post I will focus on mathematical optimization-based supply chain network models and simply refer to it as the “network model”. What we often fail to consider is the mental model that is internal to the thoughts of each person that is using the network model. When mental models collide with network models, you have started to leave the world of analytical thinking and entered the world of supply chain change management.

Mental models of experienced professionals can be incredibly strong. They are often deep-seated beliefs based on years of experience. This is not a bad thing. They help people make quick decisions when there is no time to build, run and understand results of large complex mathematical models. But when the result of a network model conflict with a strong mental model, it creates an opportunity for some of the most powerful “AH-HA! moments”.

The AH-HA moment: Merging Supply Chain Models with Mental Models

Getting to that AH-HA! can be difficult because it requires changing mental models. One of the most powerful methods to do this is through the power of example or stories. This helps the model users understand the difference between the two models in conflict. Initially, it forces the network model to be better as it is tested against hypotheses from mental models by uncovering data or logic errors.

But once the network model reaches a point of maturity and completeness, it starts to force model users to challenge their mental models if differences still exist. This takes some time, but it is well worth the slog. It gets people to go beyond the WHAT the model says to get to WHY the model says what it says. The model now has given a voice to the data – not just a voice that suggests what to do, but also why it makes sense. This is when mental models learn and improve and, ultimately, get stronger.

Supply Chain Change Management: Psychology Matters

Designing an agile supply chain network may rely more on psychology than technology, however, technology can be a very useful friend in the process. Technology that enables network model users to run scenarios easily and quickly is a huge help. To be able to clone a scenario in a few clicks, change some inputs based on a mental model driven hypothesis, run the scenario, and compare the difference is the first step to technology helping the process. To then be able to take a scenario, parameterize multiple changes and run multiple scenarios is even better. Instead of simple cloning (i.e., 2x) you have scaled up an order of magnitude (i.e., 10x) in terms of scenarios to explore. Now layer in cloud computing technology and relatively inexpensive compute capacity and you can parallelize these scenario runs across additional compute nodes and go up another order of magnitude (i.e., 100x).

Today, we have an unprecedented opportunity to leverage technology for large scale scenario analyses. This, in turn, makes our ability to learn from network models unprecedented. Learning is the act of changing our mental models. When our mental models change, our beliefs change. This changes our actions, making the hurdle of supply chain change management just a little bit lower, and enabling our organizations to evolve faster and keep pace in an ever-changing world.

If you enjoyed this post on supply chain change management, view our webinar recording, Designing Your Supply Chain Network for 2021 & Beyond, featuring executive speakers from both FICO and Profit Point.

About Zahir Balaporia, CAP®

Joining the FICO team in 2015, Zahir helps clients design solutions for their advanced analytics needs with a focus on analytics deployment and change management. Prior to joining FICO, Zahir spent 20 years building and deploying models in manufacturing, transportation and logistics, leading various advanced analytics teams delivering impactful solutions. His work is profiled in the book Only Humans Need Apply – Winners and Losers in the Age of Smart Machines by Tom Davenport and Julia Kirby.

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