- The people, processes and technologies that make
up a supply chain can interact
in ways that are hard to predict.
The good news is digital models give us a way
to analyze a complex supply chain virtually,
without many of the costs
and risks that we face when experimenting with things
in the real world.
Supply chain modeling expert,
Tony Grichnik says,
that a good model has to tell us two things.
First, it has to tell us something
that we know, that helps us gain confidence
that the model is accurate and the results are believable.
Second, the model has to tell us something
that we don't know.
That's what makes it useful and interesting.
Most supply chain models fall into three categories.
A digital twin is a file or a program
that describes the important attributes
of a physical product or process.
Simulation models show us how a supply chain process
will behave given a certain set of conditions,
and optimization models show us
how we should configure a supply chain
in order to achieve a particular result.
Let's look at each of those more closely.
We can create digital twins for a product, a facility,
or even an entire supply chain.
Imagine a digital twin
for an engine that can help us predict when
a part is likely to break.
So we can have a spare part ready or better yet,
so that we can make the repair before the part breaks
and avoid the risk of an unplanned shutdown.
While digital twins generally try to
capture what's happening right now,
simulation and optimization models help us predict
what could happen in the future.
With a simulation, we want to see what happens
under a certain set of conditions.
And with optimization, we want to see
how to change the conditions to achieve a better result.
Some of the simulation and optimization modeling techniques
that we use often in supply chains include discreet event
simulation modeling, Markoff chain models
and Monte Carlo simulations.
You can find a lot of information
about those techniques in textbooks and online,
but one of the most common techniques
is called system dynamics.
If you're going to start with simulation,
this is the one to start with.
We can use system dynamics to show how any
of the different parts of a supply chain interact.
For example,
system dynamics models can show how inventory moves
through a supply chain and how changes in supplier demand
at one place affect the whole rest of the chain.
Building supply chain models can be a challenge.
They use mathematical equations
and the complexity of the problem we're solving
determines the best tools for us to use.
I've built a lot
of simple models using spreadsheets like Excel,
but sometimes we need specialized modeling software
or we might even need to write our own code.
Interpreting models can be a challenge too.
A table full of numbers might be fine for an analyst,
but we generally need to use visualization tools
like graphs and charts to make it easier
for other people to understand the results
of our model.
Modeling can provide clarity
about what happened in the past, what's happening today
and what's likely to happen in the future.
So you can expect that digital twins, simulation
and optimization models will play a key role
in the digital transformation of your supply chain.