Tuesday, February 18, 2014

Analytics in Supply Chain

Why 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
new idea and these companies are still trying to figure out how to do it better and more cost effectively.  When companies
use 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 line. 
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. [1]

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.” [1]

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? [1]

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. [2]

Using data to predict rather than react

There are many factors affecting supply chain including recent economic impacts such as rising fuel costs, the global
recession, supplier bases that have shrunk or moved off-shore, as well as increased competition from low-cost
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. [3]

[2]  http://www.deloitte.com/view/en_us/us/cefe46d054aaa210VgnVCM3000001c56f00aRCRD.htm