Tuesday, June 04, 2013

Real-Time Big Data is the Next Big Thing for Supply Chains


The vast majority of supply chain managers are itching to adopt Big Data solutions. These managers believe that getting a handle on Big Data will make the supply chain more efficient, that it will reduce costs, and perhaps most importantly – that it will enable real-time analytics for better business decision-making, as opposed to relying on historical data. The ROI of Big Data will be found in visibility, demand planning and risk management. But in many cases these executives also say that they fear integration of a Big Data solution with their current systems can be too complex, and be a barrier to getting that ROI.
Hadoop addresses Big Data challenges
So let’s take a look at both these issues: First – is there a real benefit to the supply chain in being able to effectively process data at extremely large volumes and speed? And second – is there a way around the challenge of integrating shiny new Big Data systems with legacy IT architecture.
Here are a few real-life logistics use cases that illustrate the challenges posed in today’s technical environment. The examples refer to package delivery, but the issues are valid for fleets as well:
1.   Can you track individual packages (or vehicles) in real time, no matter where they are, or how many packages your system is handling at any given time?
2.   Can you get useful information about the individual packages? How quickly and effectively can you act upon that information? For example, if a package delivery leg is delayed due to weather, can you notify the end recipient? Can you accurately calculate the new delivery time?
3.   With multimodal transport, do you have real time visibility into package status? Can you accurately get package status from each carrier and show it to your users and customers?
4.   With vast streams of data flowing into your management system from the field, can you sort the useful information from data that you don’t need right away? And can you perform real-time analytics on the data to generate reports that will help you make decisions that save your company money?
An in-memory computing platform, such as XAP and Cloudify from GigaSpaces Technologies , a provider of application and cloud-enabling platforms for mission-critical applications, adds extreme processing capabilities to any Big Data application stack, such as one based on IBM BigInsights
IBM InfoSphere BigInsights brings the power of  Hadoop  to your management system, in order to handle and store your data, no matter how much data you generate. The GigaSpaces XAP adds the ability to sort, process, and act upon that data in real time. GigaSpaces Cloudify makes orchestration of application infrastructure and managing your applications easy and efficient.
Here is how GigaSpaces XAP and Cloudify can help with the challenges described above:
1.   When individual package movements are tracked as events, supply applications generate lot of events. XAP provides a scalable and resilient infrastructure that can be used to store and process these events.
2.   Package movement events provide a lot of valuable information which can in turn be used for real-time shipment tracking, proactively identifying delays and dynamic route generation and re-routing.
3.   In multimodal transport, integration of information between various carriers is important to give the end users visibility into the location of their shipments. XAP easily integrates multiple, disparate applications and exchange information across these applications, which provides visibility into the shipment location information to any interested parties.
4.   When all this data is stored in IBM BigInsights, it can be used to provide additional business insights from your data. With the Hadoop infrastructure that is at the heart of BigInsights, you are able to run analytics on this data and generate useful business metrics and trends.
So you can see that there are clearly benefits to supply chain management with Big Data systems – you can make better decisions in less time, to save money, and optimize operations.
The good news about both XAP and Cloudify is that they are easy to use with any framework or programming language. You do not need to change your applications, or buy new system management tools. XAP and Cloudify are already integrated with BigInsights, so if you are moving to adopt a big data system, it can be a truly worry-free process. 
The result? Let’s go back to our real-world example: You can track millions of packages in multiple geographic zones, and then get exact information of which packages will be delayed, get new delivery time information, and send emails to end customers notifying them of the schedule changes. You can track trucks and airplanes that are not in your network – and even weather – to determine how they’ll affect your supply chain. And then you can move any relevant data right into your operational and back office systems, so that all your business operations are always in sync.
See a logistics management system demo to see how this works and read more about logistics and Big Data.
This is a contributed blog post by Tsipi Erann, marketing communications manager at GigaSpaces.


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G. Dalby said...

Well said Chris. Today’s omnichannel world means retailers need real-time intelligence to ensure they have the right product, in the right location, at the right time. Big data has a wide range of potential applications for the retail supply chain. It can help companies track profitability, on-time delivery, and customer feedback – real-time. We recently wrote about how retailers can benefit from big data. http://www.gtnexus.com/blog/cloud-supply-chain/big-data-a-big-question-for-retail-supply-chains/

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