Big Data Analytics in Supply Chain Management

Big Data Analytics In Supply Chain Management What is “Big Data” anyway? Gigabytes? Terabytes? Petabytes? The first personal computer that I’d had touted a storage space of 100 GB, a rare feature in 2004. But with the advancements in technology and the advent of Internet of Things (IoT), 100 GB has been rendered insufficient. Although 100 GB is not trivially small yet but to put the “bigness” of big data into perspective, just imagine that Google handles 100 billion searches per month, Wal-Mart requires 2.5 PB (petabytes) to store its transactional data while eBay requires an almost unimaginable 90 PB.1 Handling and analysing this amount of data is no duck soup, it requires an infrastructure aptly described by Adam Jacobs as “massively parallel software running on tens, hundreds, or even thousands of servers”2. This kind of infrastructure has its own costs. So why do companies maintain big data? Why do they need it? What benefits do they see in it? As supply chains for companies are becoming more complex with time, spanning multiple continents, involving external suppliers and customer demands are becoming more complex, BDA is becoming more important to reduce inventory, lower costs, enhance customer responsiveness, and improve agility. As more and more companies are adopting BDA for managing their supply chain. Big data has different characteristics by which it is classified. These characteristics are Volume, Variety, Velocity, Variability, Veracity and Complexity. Further to these, it can be structured, semi-structured and unstructured.

Abhinav Srivastava (15P181)

Big Data Analytics In Supply Chain Management This graphic provides a quick snapshot of 52 sources of data that are available throughout the supply chain3. A glance through this graph also indicates that majority of data being generated is outside an enterprise which is practically outside its control. This makes the data extraction with authenticity a bit difficult. Big Data analytics has revolutionized the supply chain management by deriving insights that were unimaginable before. It is because of this that many companies are adopting it at an accelerating pace. The Boston Consultancy Group provides insights into how big data is being put to use in supply chain management in its article. One of the examples provided is how a merger of two large consumer products companies was facilitated efficiently by employing geoanalytics. The following graphic is from one of their reports.4

BDA is also helping companies in real time delivery tracking. The data is composed of inputs from bar-codes, radio frequency identification (RFID) tags, global positioning systems (GPS) devices, among others. By using the data collected from these systems a logistics manager can optimize delivery scheduling as she has the traffic data, road network data, and vehicle data, in real-time. She can track packages and vehicles in real-time no matter where they are. BDA is also helping firms in optimizing their supplier management (by forecasting margins if different mix of suppliers is chosen); product pricing (forecasting profit margins at different price points by anticipating consumer behaviour) among many other things. After

its

patent

for

“automated product sourcing” Amazon has taken

the

BDA

one

notch up by patenting its “Anticipatory Shipping” in December, 2013.5 It will use predictive analysis to forecast future sales at different locations and ship its products pre-packaged to the nearest fulfilment centre.

Abhinav Srivastava (15P181)

Big Data Analytics In Supply Chain Management Although the success of this model remains to be seen, this feat provides insights into the prowess of big data in today’s world.

Shortened order-to-delivery cycle time

14%

Better customer and supplier relationships

28%

Improved cost to serve

28%

More effective S&OP process and decision making

32%

Optimization of inventory and asset productivity

33%

Greater integration across supply chain

36%

Increase in supply chain efficiency

36%

Faster and more effective reaction time to supply chain issues

Improvement in customer service and demand fulfillment of 10% or greater

41% 46%

The exponential growth of digital technologies has enabled collection of massive amounts of data which also require even more sophisticated techniques to extract meaning out of them. This requires huge investment in the existing supply chain infrastructure of companies which is proving to be a big deterrent. However, given the benefits that many companies have already extracted out of BDA, this investment is strategic in nature. According to the Accenture Global Operations Megatrends Study the results achieved by companies from BDA are as shown in the graph. 6 These results only indicate the possibilities that BDA holds in terms of improvements in every aspect of supply chain. It is therefore very important for every supply chain manager to understand the various possibilities that her area of business holds and leverage it to the best extent possible to extract the maximum benefits.

Abhinav Srivastava (15P181)

Big Data Analytics In Supply Chain Management

Sources 1. Inside eBay’s 90PB data warehouse, http://www.itnews.com.au/News/342615,insideebay8217s-90pb-data-warehouse.aspx, Accessed on 26th July, 2015 2. The Pathologies of Big Data, Adam Jacobs, http://queue.acm.org/detail.cfm? id=1563874, Accessed on 25th July, 2015 3. Big Data Analytics in Supply Chain Management: Trends and Related Research. Presented at 6th International Conference on Operations and Supply Chain Management, Bali, 2014 (http://www.researchgate.net/publication/270506965_Big_Data_Analytics_in_Supply _Chain_Management_Trends_and_Related_Research) 4. Making Big Data Work: Supply Chain Management (https://www.bcgperspectives.com/content/articles/technology_making_big_data_wor k_supply_chain_management/) 5. Amazon Patents “Anticipatory” Shipping — To Start Sending Stuff Before You’ve Bought It (http://techcrunch.com/2014/01/18/amazon-pre-ships/) 6. Big Data Analytics in Supply Chain: Hype or Here to Stay, https://acnprod.accenture.com/_acnmedia/Accenture/ConversionAssets/DotCom/Documents/Global/PDF/Dualpub_2/Accenture-Global-OperationsMegatrends-Study-Big-Data-Analytics.pdf#zoom=50, Accessed on 26th July, 2015

Abhinav Srivastava (15P181)