Introduction

What is the primary reason for supply chain analytics? With every passing minute of every day, packages and shipments are moved all around the world within a huge unending flow of supply chains.

These supply chains shape the world’s economy and keep the world moving. An ideal tagline to understand this is DHL’s- We move the world.

With that being said, think of the amount of data required to make these supply chains function as effectively as they do.

The end goal of the supply chains is to move a product from A to B really fast and efficiently.

However, there’s a whole lot more going on behind the scenes to make all this work.

In today’s world of growing technology, data is what drives a company. Be it a big company or small company, to make the right decisions, the company should have access to data.

However, it does not end with that, they need to understand and make sense of this data for the data to be useful.

Injecting Analytics!

For the best insights and effective decisions, procurement functions turn to big data and advanced analytics.

The best logistic and supply chain companies of the world have the most sophisticated data architecture in place to aid in their decision making.

Agility is lost without advanced information management capability.

Sensory systems monitoring external conditions and analytical capabilities that make sense of this data in the business context are required for agile operations. Business decision making depends on this flow of feedback information.

Data analysis is the catalyst to enhanced procurement. Having the right information at the right time and being able to act on it is extremely crucial during procurement.

This actionable data is revolutionizing the transportation industry which hasn’t seen much change over the past few decades.

How big data and analytics can help is by giving you a full measure of your business and provides a plan for improvement by identifying key metrics.

The Rise of Big Data

Big data analytics is the most powerful thing today and it’s quite interesting that it picked up only from 2010.

Big data analytics grew to the level that it is at today with the flourish of mobile and cloud computing technologies.

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The buildup to the adoption of big data and advanced analytics has been slow but the boom is finally here.

When it comes to supply chain, companies need to harness the power of big data in the right way.

Why Supply Chain Analytics?

Globalization and the internet are the reasons for an increase in complexity. There are more products, multiple locations, various channels and many more markets as part of the mix. This leads to new challenges and new tools.

The amount of data available is vast. This data is from ERP systems and other sources. Today, computing speed has increased. Even database technologies that speed up access to data are really fast. This makes analytics a lot more practical and deployable.

The world of supply chain also presents analytics with an opportunity to develop new methods and techniques. Supply chain analytics play a huge role in the operations of a supply chain like – demand forecasting, transportation routing, inventory optimization, RFID tracing and network designing.

Recently, advanced analytics services have been benefiting supply chains around the world in areas like – supply chain segmentation, risk management, manufacturing flexibility and complexity reduction as well.

The C level managers today are tired of working through excel sheets and want big data, advanced analytics and data visualization to be embedded in their long term strategies.

A Few Challenges!

Big data is a very powerful tool and may prove to be overwhelming if not implemented correctly.

Trying to analyze huge data streams without the right support is like trying to find a needle in a haystack.

The data is just too vast and the company may have to go through tons of data to hit what they are looking for.

In a survey conducted in 2017 by American Shipper, it was very astounding that only 5% of the respondents claimed to have accurate data and 35% claimed to have “somewhat accurate” data.

This in itself provides an opportunity for supply chain analytics.

This is dangerous for companies in this space as being armed with the wrong data will lead to decisions based on wrong data points and this will do a lot of harm to the company.

Outsourcing a data science team or having an in-house data science team is the best way to analyze your data and make informed decisions.

The Supply Chain Analytics Arsenal!

Decoding the data is important and so are the tools used to gather it. Advanced analytics has Machine Learning and Artificial Intelligence in its arsenal.

These tools are algorithmic in nature. AI leans towards predictive models that are very crucial for companies in the supply chain industry.

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Another widely used technology is the IoT. The Internet of Things is used to gather data from virtually any link in the supply chain.

The supply chain industry is a pot of gold for the analytics industry. Both these industries are mutually beneficial and will require each other to sustain and grow.