Supply Chain Management Leading in Revenue Through 2018

The year 2013 witnessed the rise and reign of big data and predictive analytics. However, in the past, supply chains didn't seem to embrace big data as much as they should have done. That needs to change.

Supply chain leaders need to pay more attention to big data and predictive analytics to stay on top of the game from 2014 onwards. Both will be critical components of smoothly navigating toward global revenue predictions created using Supply Chain Management (SCM).

For this, supply chain leaders must plan a thorough strategy based on the analysis and evaluation of results of technologies adopted in the past. Out of that effort arises an important question: What is there in the horizon of big data to better help supply chain management? Let's see some general figures: According to detailed research conducted by IndustryARC, the global big-data market was around $6.93 billion in 2012 and this doubled to around $12.21 billion in 2013. The market is expected to reach $40.4 billion by 2018, growing at a CAGR of 27% from 2013 to 2018.

Learn from yesterday, look to tomorrow
Traditional business analytics were good in the past, but they don't work for the demands of the new supply chain. Today, supply chain leaders need to know how to ask the important questions. This is precisely where big-data predictive analytics comes into play helping to recognize and mitigate issues quickly, saving both time and money.

IndustryARC, an industry market research and analysis company, explored this topic in particular detail in the global “Big Data Market in Supply Chain Management” report. The 110-page report published in October 2013 includes key trends, competitive landscape, geographic, and end-user segment analysis comprising the years 2012 to 2018. (The full report can be downloaded here and the table of contents can be seen here.)

Big data in supply chain management
Big-data technologies have captured everybody's attention in the last year. The different varieties of data have become regulars in everybody's vocabulary: Structured data, unstructured data, clean data, dirty data, and real-time data. All big data that, if used well, can provide the SCM with great answers and valuable help in doing faster and better business in today's data driven world. IndustryARC found in its research that the global big data in supply chain market is expected to increase from around $0.43 billion in 2012 to around $3.7 billion in 2018 growing at a CAGR of around 31.4% from 2013 to 2018.

Predictive analytics brings opportunity of growth to supply chains
As supply chains get more and more complex they need to adopt better tools to maximize their data in a fast and efficient way. There are plenty of supply chain opportunities in big data and predictive analytics. For example, the anticipation of problems brings solutions before problems manifest and it's too late prevent a business disaster. With this in mind I asked Rahul Mistry, senior consultant ICT of IndustryARC and author of the report “Big Data Market in Supply Chain Management” about his advice to SCM leaders. This is what he told me in an email:

The manufacturing segment collects massive amounts of data from its supply chain channels and also from the instrumentation or sensor networks on the production floor. Tighter integration and analysis of these databases using big data can be helpful to improve efficiencies of inventory management, sales and distribution process and continuous monitoring of devices. For the manufacturing segment to grow, companies need to realize the cost benefits accrued due to usage of big data. Predictive maintenance of equipment is an immediate segment in this sector ripe for growth.

Big-data tools implementation in the supply chain
With so many vendors out there sometimes it's difficult to choose the one that suits best the interest of a particular supply chain. The best way to impress a client is to offer something unique, standing out from the crowd. Mistry went on telling me about implementation advice for SCM:

A range of big-data software tools from vendors like IBM, HP, Teradata, Oracle, SAP, EMC and Amazon are available for clients to explore currently. These offerings are highly integratable with the existing ERP, SAP and MES solutions as the original vendors for these tools are essentially the same. The costs are also significantly less due to less usage of legacy software, cloudification of data analysis and decreased number of licenses, personnel. Big-data providers, however, need to showcase the cost and time-saving benefits of their tools to potential clients and impress the client with implementation of their service with one division and ramp up to include the whole organization .

The manufacturing sector will lead in revenues for big data
The promising $40.4 billion in revenue for the supply chain market between 2013 and 2018 is certainly a big motivator. Rahul Mistry and IndustryARC kindly shared with EBN the following segment of the report. Click on the image below to view a slideshow that demonstrates the growth and revenue of big data in SCM:

Global big data in SCM market share, by industry segments (%), 2012

'The figure above shows the market share breakdown by the industries that are using big data in their SCM strategies. The services, manufacturing, and retail segments together have around 68 percent revenue share due to their higher dependency on SCM and the need for big data in analyzing big data sets,' IndustryArc said.

“The figure above shows the market share breakdown by the industries that are using big data in their SCM strategies. The services, manufacturing, and retail segments together have around 68 percent revenue share due to their higher dependency on SCM and the need for big data in analyzing big data sets,” IndustryArc said.

9 comments on “Supply Chain Management Leading in Revenue Through 2018

  1. Ariella
    March 4, 2014

    Certainly the big data field is big with major implicatons for the supply chain. Certainly, $40.4 billion in revenue for the supply chain market between 2013 and 2018 is quite an incentive for companies to get their data on track.

  2. Susan Fourtané
    March 5, 2014


    Indeed. And the slideshow is quite interesting as well. 🙂 Good times are coming for the suppli chains. 


  3. Hailey Lynne McKeefry
    March 5, 2014

    I just saw this and thought it was worth sharing…great data here:

    March 7, 2014

    I am excited for the day that the medical industry really conquers the big data initiative as there must be great gains for all to be had.  If we can seamlessly share and analyze data from all over the world it must be a real boon for healthcare.

  5. Susan Fourtané
    March 8, 2014


    That's a great infographic. 🙂 Thanks for posting it here to add to the topic. And everything matches. Supply chains must be super happy. 😀


  6. Susan Fourtané
    March 8, 2014


    Well, the healthcare sector is also seeing the benefits of big data analytics. You can start being excited already. 😀  

    Do you have something in particular in mind about the applications of big data in healthcare? 


  7. Hailey Lynne McKeefry
    March 9, 2014

    @Susan, yes… it seems like we all agree that greater efficiency, lower cost, and greater nimbleness are the must haves that big data can support. Does anyone have an examples to share of big data initiaves in your supply chain organization? If you aren't doing it, what's holding you back?

  8. Hailey Lynne McKeefry
    March 13, 2014

    @Susan, the stat in that chart that suprised me as that 75 percent said that internal data is more important than external data. I think that's going to shift. Data from across the global supply chain is going to be increasingly important to staying competitive. Internal information will always be important, but i'm betting that external information may start to be at least as important.

    Did anything particularly catch anyone elses attention?

  9. Susan Fourtané
    March 18, 2014


    Big data is growing in all directions. As we see changes take place within the supply chain more will balance the importance between internal and external data. 


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