Course blog for Digital Analytics course at the University of Utah
Tuesday, February 18, 2014
Analytics in Supply Chain
use advanced data analytics in supply chain?
The reason I am interested in Supply Chain
analytics is because the Director of the MBA program that I am in strongly
suggested that I take a digital analytics class because I would use it in any supply
chain internship that I do. The
internship that I accepted was in supply
chain and since I have little experience in analytics and how it is used in
supply chain I thought it would be beneficial to do some research on the topic
and hopefully it will prove to be beneficial during the internship.
Companies are trying to use the data that they already
have to improve their supply chain forecasting, but it is a relatively
and these companies are still trying to figure out how to do it better and more
cost effectively. When companies
their data effectively it pays off in a big way especially in supply chain
since that is typically their biggest expense and
ultimately affects the bottom
Today there are many factors affecting supply chain such as shifts
in technology, social signals, increases in weather
sensing, shortages of
talent, and the evolution of new forms of analytics. Supply chain leaders are transforming their
view of the data they collect, and how they analyze it. The work is not about
inside-out and the deployment of traditional technologies. The problem is that
supply chains today catch orders and shipments and assume that they are representative of the market. They do not allow for systems to manage the
channel from the outside in. The analytics and traditional systems are not able
to effectively use channel data. 
One thing that I have learned in my Digital (web) Analytics class is
that many people confuse analytics with reporting. Analytics is much more than that. Reporting is only a small part of it, you
have to take the data and translate it into actionable insights.
”Analytics is much more than reporting. The evolution of analytics
for visualization, pattern recognition, unstructured text mining and parallel
processing are converging to drive a new form of supply chain. It is one
that combines digital with cognitive reasoning to sense, think and act.” 
Some of the questions they bring up are very interesting. What if we could test and learn in-market,
reading market impacts in real-time through analytics, based on matching
customer attributes to product attributes to build customized products for
regions around the world? This new approach allows test and learn capabilities
to answer the questions that we do not know to ask to build unique insights. And, what if we could mine unstructured data
and combine it with transactional data to mitigate supplier risk? 
Is it possible to take the capabilities that we currently have further? Think of what we could do if we could sense upcoming risks before they happen. In
the past supply chains responded, but they did not sense. It sounds like the next generation of
analytics will be able to sense what is going to happen and adjust
accordingly. This is getting me more
excited about my internship in supply chain and the capabilities that analytics
will be opening up.
Is it worth the cost?
Can advanced analytics extract additional
value from your supply chain?
Companies already using ERP systems find that they have large
amounts of data. Turning that data into
actionable insights is where some companies struggle. It is easy to spend a lot of money on these
programs without seeing the results.
First of all you have to ask yourself if you can afford the initial
plunge to get started, and then whether you can keep it going so you can always
have updated feedback. Many companies
deem advanced analytics in supply chain as too expensive while others are using it effectively and it is really paying off.
Supply chain is an area of many companies’ biggest expenses, which
ultimately affects their bottom line. So
if you are capable of using advanced analytics in cutting your supply chain costs
it could pay off big for you. 
Using data to predict rather
There are many factors affecting supply chain including recent
economic impacts such as rising fuel costs, the global
bases that have shrunk or moved off-shore, as well as increased competition
outsourcers. All of these
challenges potentially create waste in your supply chain. That’s where data analytics comes in.
The supply chain is a great place to use analytic tools to
look for a competitive advantage, because of its complexity.
Remember to keep in mind that the purpose of
using advanced analytics is to predict not react. If you can use your data
to do this successfully
then you will see your investment pay off for your company.