Written by Srini Vasan CEO of eShipGlobal
The big data revolution is here. Enormous quantities of digital data are produced every day. “The world’s leading commercial information providers deal with more than 200 million business records, refreshing them more than 1.5 million times a day to provide accurate information to a host of businesses and consumers,” writes Cognizant’s Sethuraman M.S. in a 2012 paper, Big Data’s Impact on the Data Supply Chain.“They source data from various organizations in over 250 countries, 100 languages and cover around 200 currencies. Their databases are updated every four to five seconds.”
And the pace of data production is picking up. The International Data Corporation (IDC) predicts that digital data will grow from 2.8 trillion gigabytes in 2012 to 40 trillion gigabytes by 2020. Though this unprecedented volume of information may seem overwhelming, it offers unparalleled opportunities for companies willing to invest the time and money to analyze and utilize the data available.
The Benefits of Big Data in Supply Chain Execution
Companies wanting to increase efficiency and profitability in supply chain execution should take note of big data. According to Ramesh Sethuraman and Satya Krishna Kunadharaju, senior solutions principals for HCL Retail and CPG Consulting Practice,the information provided by big data can:
A Practical Application
Efficiency and expediency is the lifeblood of FedEx, which handles nine million shipments a day and all the accompanying data. But FedEx isn’t just familiar with big data, it recognizes the potential behind it. The company recently decided to apply that data to physical items by creatinga next generation, first-of-its-kind information service that combines a GPS sensor device and a web-based collaboration platform: SenseAware. Originally used by the healthcare and life sciences industries as a means to track high value and/or extremely time sensitive shipments (and now available to all industries), SenseAware attaches digital information topackages, providing:
Since the device is equipped with a radio that constantly broadcasts information back to FedEx, an enormous amount of data is generated—information that must be acted on in real-time. Analysis of the data is critical.
Analyzing Big Data
But big data, which is not only big, but unstructured by nature, requires a new, different type of analysis. “New” and “different” often translate to “new and different costs.” In terms of supply chain execution, is the expense worth the result?
Yes, says Sanjay Agarwal, principal of Deloitte Consulting LLP. “Supply chain analysis is an untapped opportunity for many organizations that have data at their disposal but lack either the tools or the knowledge to exploit it,” notes Agarwal. “Our experience shows that manufacturing companies can realize a margin improvement of 2 to 4 percent by applying more analysis to the data they already have.” Big data, properly analyzed, says Agarwal, can help companies to employ parametric pricing, predict commodities volatility, and mediate any issues that arise from merger and acquisition integration.
Advanced analytics can be utilized in every aspect of the supply chain, agrees Agarwal’s Deloitte Consultingcolleague, Jerry O’Dwyer. It can improve forecasts, demand planning, sourcing, production and distribution, though it’s best used when looking at the big picture. “If you’re performing analytics in different areas of the supply chain – for example, spend analytics or demand planning,” says O’Dwyer, “you may be missing opportunities that a comprehensive approach can yield. For example, some companies have adopted the use of advanced analytics to develop a predictive asset maintenance strategy or to improve manufacturing operational performance.”
The impact of business analytics on supply chain performance, a 2010 study by Decision Support Systems, examined analysis efforts in four areas of the Supply Chain Operations Reference (SCOR) Model: plan, source, make and deliver. The study noted several potential uses of Business Analytics (BA) in these areas, including:
Plan:Data may be analyzed to predict market trends.
Source:An agent-based procurement system with a procurement model, search, negotiation and evaluation agents may improve supplier selection, price negotiation and supplier evaluation and the approach for supplier selection/evaluation.
Make:Information may be used to ensure the correct production of each inventory item in terms of time, production belt, and batch.
Deliver:Various applications of BA may aid in delivery efforts, but since many decisions about delivery are usually made at the end of the decision cycle, the impact of BA may not be as great in delivery.
The study’s finding may be of special interest to companies that are not yet able to invest in a comprehensive analysis: The authors found “a preliminary indication that an investment in BA in the Make area may bring the most significant improvement.”
The findings from the Decision Support Systems study, which considered a large sample of companies from different industries and countries, “reinforced the importance of a company's use of its databases, explicative and predictive models and fact-based management to drive its decisions and actions. The analytical capabilities can better guide the exclusively human decisions and provide automated decisions in some tasks in organizations.”
Right now, companies have an opportunity to get in on the ground floor of this big data revolution. By proactively using big data and its corresponding business analytics, they can make better decisions, create a more efficient supply chain, and increase profits. Big data is here. Use it.
About the author
Srini Vasan is the CEO of eShipGlobal, an on demand transportation management solution provider, which prides itself on bringing business applications to the market quickly and helping customers manage their transportation effectively. Vasan is currently involved in business development and oversees technology infrastructure and software development.