- Our supply chains depend on data.
There's data in our manufacturing processes,
data about our inventory and our shipments,
data about customers and data about suppliers.
As we focus on digital transformation of supply chains,
we need to look at two closely related trends
that are making data even more important:
the Internet of Things, and big data.
Most of our supply chain data right now comes
from the transactions in a system,
like an enterprise resource planning system,
a warehouse execution system
or a transportation management system.
These systems are essential for digital transformation.
But we're also starting to collect a lot
of additional data from automated devices,
like cameras, thermometers and location trackers.
We call these Internet of Things or IoT devices.
The growth of transaction systems combined
with the adoption of IoT devices
is fueling a trend called big data.
So we need to pay closer attention
to where and how we store data.
If we have a small amount of data,
we can store it on a single server.
When we have a lot of data,
then we need to group servers together
to create a data warehouse or a data lake.
And we house those servers in data centers
or server farms.
We also need to protect that data
so that it doesn't get lost or damaged
and no one gets unauthorized access.
That means we need to have backups of the data
and redundant hardware
and really good physical and cybersecurity.
It's also important to understand
that there are different kinds of data.
Some data is neatly organized,
like a spreadsheet that has numbers and rows and columns.
That's called structured data
but then there's unstructured data,
which is kind of messy.
Videos, audio files and social media posts
are all examples of unstructured data.
And we also need to think about the data
that describes the data, the metadata.
For example, when we store a digital photo,
we often store the date
and the location the picture was taken.
That metadata makes the underlying data more useful.
We need to have the right infrastructure in place
so that we can use big data to drive improvements
in the supply chain.
For example, analyzing large volumes of structured data
from transactions can help us create better production plans
and inventory forecasts
and looking at market data
can help us understand how much we should be paying
for the products and services that we purchase
and how much we should be charging our customers.
Unstructured data can be valuable
for supply chains too.
Analyzing social media is one
of the most powerful ways
to identify and fix problems in our supply chain.
For example, customer complaints can help us spot
inventory stock-outs in stores,
and many companies are starting to use unstructured data,
like pictures and videos
to monitor traffic through ports
and on highways around the world.
As we automate processes and implement IoT technologies,
the amount of data in our supply chains is growing quickly.
With digital transformation,
we're turning that big data into valuable business insights.