Re-thinking the "Driver-less" Revolution 

May be a decade ago, none of us would have ever imagined a car that can take us to places with the help of any driver. With the  increase  in  the needs and income levels of  the people  resulted  in high volume  of  sales  creating a  lucrative business opportunity. Despite the overall cool down of automotive demand globally, growth markets are expected to remain the main engine for volume 

growth in the automotive industry worldwide, driving an 18.8 million increase in vehicle assembly volumes from 2016 to 2023. Hence many major firms have started investing major chunk of their profits in the R&D department of their firms in their pursuit  for continuous improvement of the process and to improve the customer's experience.   

Autonomous car is one such innovation of the recent times. Experts perceive that it address the issues such as global gridlock and it's a leap in thinking for a viable future. Though many comprehend that it affects only automobile industry, in realty it has either direct or indirect influence on several other industries as well.

Cross-continental car trips don’t appear to be on the horizon anytime soon, but domestic and short-haul flights face a significant threat from self-driving cars. Once autonomous vehicles make car travel more convenient, many people will choose to take an on-demand car ride for shorter trips instead of going through the many hassles of air travel. Further, the average American drives 46 minutes each day, and without having to keep their eyes on the road, they’ll have plenty of time to consume news and entertainment. Broadcasters will compete to provide video content that travelers will be able to consume without risking their safety. For advertisers, it will also create a huge opportunity to present riders with location-based ads for nearby goods and services.

The need for long-term parking will decrease  as driver less car fleets move continuously between the various places. Owners of these spaces will reshape them in a way that creates value in a driver-less world.It’s not just parking garages — the ripple effects of self-driving cars will require the entire real estate industry to undergo a large-scale reimagination of how it allocates space.  A connected driver-less car network would theoretically be largely free 

from accidental collisions. As a result of decreased collisions, the healthcare industry could lose approximately $500B annually.

However, incase of any malfunction of the guiding system may result in an accident due to lack of human judgement. Also, what needs to be done incase of guiding system failure has to be taken care of. These sensitive issues need to be addressed.

So in future you can expect  that your car follows the smart parking system and talks to calendars  of everyone present in your office and helps you decide the best route to take home. We need to wait and see how it unfolds.

Cloud Computing in Supply Chain Management

Supply chain management typically involves supervising the transfer of products and goods, such as from a supplier, then to a manufacturer, a wholesaler, a retailer and finally to the consumer. Cloud computing refers to the practice of using a network of remote servers hosted on the Internet to store, manage and process data, rather than a local server or a personal computer.

Fig 1: Supply Chain Flowchart

The cloud architecture includes a pool of virtualized computers, storage and networking resources that get aggregated and launched as platforms to run workloads and satisfy their Service-Level Agreement (SLA).
Cloud services
The service provider provides the following main services to the service user. These are as follows:
• Software as a Service [SaaS]
• Platform as a Service [PaaS]
• Infrastructure as a Service [IaaS]

SaaS (Software as a service)
It features a complete application offered as a service on demand. A single instance of the software runs on the cloud and services multiple end users or client organizations. The most widely known example of SaaS is salesforce.com, Google Apps

PaaS (Platform as a service)
It encapsulates a layer of software and provides it as a service that can be used to build higher-level services. There are at least two perspectives on PaaS depending on the perspective of the producer or consumer of the services: Someone producing PaaS might produce a platform by integrating an OS, middleware, application software, and even a development environment that is then provided to a customer as a service. Someone using PaaS would see an encapsulated service that is presented to them through an API.

IaaS (Infrastructure as a service)
It provides basic storage and compute capabilities as standardized services over the network. Servers, storage systems, switches, routers, and other systems are pooled and made available to handle workloads that range from application components to high-performance computing applications.

2010-2011	2011-2012	2012-2013
Processes & providers characteristics & examples	Processes & providers characteristics & examples	Processes & providers characteristics & examples
In early pilots SCM using cloud needs innovation and continuous improvement. Testing attitude also needed. Support & administrative processes. These can easily be abstracted and isolated, and do not require complex integration. Examples: • Capability development/training delivery • Simple analytics	This era captures maturing phase, first providers disappears from the market and other invest to grow and improve service offering. Higher focus on core and rather complex processes. Examples: • Pricing optimization • Replenishment planning • Order processing • Transportation load building	Here consolidation phase starts and major player in each category of SCM defined. SCM accept well establish models for usage and payment of cloud based services. Also complex process covered in cloud e.g. requiring collaboration between many entities and tighter integration with other processes and perhaps involving physical capacity constraints. Examples: • Collaborative engineering • Warehousing and distribution of physical product • Reverse logistics/returns processing • Fleet management
User group interests	User group interests	User group interests
Companies with highest pressure for operational excellence and through competition, e.g. Products / Consumer Goods, High-Tech	Broader industry scope, companies with higher integration needs will start using cloud based services as part of their operating model	All industries applied cloud based processes

Table 1: Implementation process of SCM on cloud platforms

SCM Cloud
SCM Cloud offers - “a set of services that provide SCM functions to any cloud user in an efficient, scalable, reliable and secure way”. That is, Cloud masks all the heterogeneities involved in implementing various SCM functions and the tiers within each function and provides a purely functional view rather than having to deal with the inherent technologies. The view of the cloud makes us, the service providers the best ones to take the cudgel to implement the CLOUD. We must therefore prepare a pool of requirements and a pool of plausible technologies and create a layer of abstraction to free the user from choosing packages, best-of-breed solutions, databases, integration middleware, and infrastructure and think only about the required functionality and how much he can/should pay for it. Here is a simplified tiered-illustration of SCM cloud components.

Fig 2: SCM Cloud

Cloud computing is already making a significant impact on the supply chain management application market, and adoption is expected to continue to grow. Companies that provide SCM software applications – including e- procurement, warehouse management systems, transportation management systems, supply chain planning, and business intelligence & analytics – are either already offering ‘software as a service’ (cloud-based) solutions or are articulating a clear strategy to move to such solutions as more customers demand it. As this happens, look for the following supply chain processes to become particularly prominent venues for cloud computing:

Planning and forecasting:
Cloud-based tools are available for capturing itemized spends data, performing basic analytics; planning manufacturing runs and executing statistical demand forecasts. Applications focused solely on retail are also prevalent, with capabilities that include planning & allocation, assortment & space, pricing & promotion, and forecasting & replenishment. A primary reason is that planning and forecasting are rarely core components of companies’ ERP systems. Clients therefore can run on manufacturer’s ERP application, but leverage another’s best-of-breed planning/ forecasting application via the Internet.

Logistics:
Cloud computing applications for functions such as network strategy, inventory management, warehousing and transportation will appear with increasing regularity in the near future. Processes such as global trade compliance, replenishment planning, order processing, and transportation load building, fleet management and transportation route planning are likely candidates. Some basic warehouse- and transportation-management applications are already available online.

Sourcing and Procurement:
Cloud computing represents a great opportunity to reduce ‘total cost of ownership’: the most commonly cited success metric in sourcing and procurement. A key reason is that cloud-based tools are inherently collaborative and accessible – a significant boon to companies that may deal routinely with thousands of suppliers. Take contract management: cloud-based collaboration allows multiple parties to jointly develop supplier contracts. Myriad sourcing and procurement capabilities are rapidly coming online, including procurement report generation, database centralization and supply chain visibility.

The future
Cloud computing in supply chain management is a paradigm that is still in its early stages. Thus it is likely to develop at different paces in different process areas, industry sectors, and markets:
Process areas: supply chains ‘in the cloud’ are likely to initially take hold in those areas that are on the fringe of what many people consider core capabilities. Processes like global trade compliance, transportation route planning, freight bill audit and payment, and even basic product design engineering are all likely candidates.
Industry sectors: early adopters will likely be industries with products
Markets: since supply chains in the cloud will be characterized by a more efficient way to use services, the most likely early services could emerge in countries with less developed infrastructures.
This could be a big boon to companies in Asia as well as to developing economies in areas such as the Arabian Peninsula and parts of Africa, where companies look for ways to leapfrog development cycles and have minimal access to capital

References:

1. Analysis of Supply Chain Management in Cloud Computing by Animesh Tiwari, Megha Jain.
2. Cloud Computing For Supply Chain Management by Harshala Bhoir and Ranjana Patil Principal
3.http://www.forbes.com/sites/louiscolumbus/2014/02/12/where-cloud-computing-is-improving-supply-chain-performance-lessons-learned-from-scm-world/

About Author:
D.Santosh is a PGP second year student at IIM Raipur. He completed his graduation in Automobile Engineering from PSG College of Technology, Coimbatore. He has 22 months of work experience with Mahindra & Mahindra Ltd. He can be reached at 15pgp013.santosh@iimraipur.ac.in. 

Role of Supply Chain Management in Make in India initiative

India is a country blessed by nature in terms of natural resources. It is a source for large number of significant minerals and substances like coal, iron ore, mica, bauxite, natural gas, diamonds, limestone and thorium. India not only has these resources but also tops the ranking list in the world for these mineral reserves. For coal, India has 4^th largest reserves, for bauxite 5^th largest and for manganese ore 7^th largest. Hence as far as raw material strength is concerned, our country has sufficient of it. But still it lags behind a number of countries in utilizing these resources and thus manufacturing.

One of the major reasons being its inability to harness these resources. The factors that make India lag behind other countries include legal rules of licensing, control pricing, currency controlling, labor laws, land rules, environment regulations, poor infrastructure, political barriers and corruption that is prevalent. Although India has a good demographic dividend now but it is expected that population of workers aged 15 to 24 will reduce by 61 million by 2030 in India and other BRIC nations. This again poses a serious threat to manufacturing industry.

INDIA: A Manufacturing Hub?

Make in India, a whimsical step taken by our Prime Minister Mr. Narendra Modi is an initiative taken towards boosting manufacturing in India and increase the contribution of manufacturing to GDP from 15% to 30%. Manufacturing is a very important sector for any country and acts to strengthen the backbone of economy. Encouraging manufacturing in our own country will reduce costs and give employment to our people. Creating more employment opportunities will prevent brain drain as well. Effective supply chain will play a huge role in making this a reality.

Supply chain involves the whole process of converting raw materials into finished product. Each stage requires inputs in various forms and value is being added at each stage and so it is known as Value chain. The value addition incurs costs that result in overall effect on final price. Now if the cost at the very beginning stage i.e. raw material cost is high, the ultimate product costs will automatically rise. The reason for high cost of raw materials is that they are imported from foreign countries instead of being extracted from our own country. Now imagine that not only the raw materials are imported but also the manufactured parts and finished products are imported. Imagine the amount of money that is being flown out of the country for no reason.

Now to “Make in India” there have to be facilities and opportunities equivalent to other developed countries so that the dream of making India a self-sufficient country comes true. In addition to that India also has to overcome the barriers present.

The most important part of excellent manufacturing is well maintained supply chains, but as of now India does not witness a good level of operations management. In India a huge portion of gross domestic product equal to 14% is spent on logistics. 22 % of total sales is caught up in inventories of all the supply chains. Due to inefficient logistic network there is a wastage of 20% in cold supply chains. It is agreed that making development in supply chain in a country like India which is seventh largest according to area, is not that easy but it is not impossible too.

The reason for poor logistics network are numerous and they have been effecting production since ages. There are some geographical disadvantages also. As compared to China, India lags behind by two weeks in shipping line from United States. Indian infrastructure which denotes roads, railways, airports, seaports, information technology (IT) and telecommunications is very deprived as compared with other developed and developing countries. Indian infrastructure is rated 54th among 59 countries in comparison to other developing countries (World Economic Forum, 2000). Only 48% of all villages present in India are connected by roads. Indian railways are rated 25th among 59 nations, World Economic Forum and the quality of airport infrastructure is rated 40th among 59 countries. All these figures tell us that infrastructure of India is not up to the mark of handling efficient supply chains. This results in grave disadvantages in acquiring of necessary materials required especially when companies are planning to get global. Make in India will promote the up-gradation of supply chains in India by strengthening freight network. This is a cycle of improvement that will take place. Due to Make in India campaign freight network will improve and the improvement leads to achieving better results for Make in India. To make this possible government has kept funds for increasing freight capacity by 50%.

Small and medium enterprises hold a very important space in Indian industrial sector as they have been able to perform efficient process of assembling goods in less costs and also maintained the quality standards. There is enough scope of cost reduction due to number of available factors, the only need being to employ them successfully. The reduced cost of logistics will decrease price of goods not only in India but also globally in turn making them more competitive. This will ultimately affect the economy and give us fruitful results being aspired by Make in India. In situations where it is inevitable to import machinery and components there the suppliers should also be asked to import certain minimum amount of components or raw materials from India so that the exchange remains same.

Hence improvements can be done in number of areas to come up with better supply chains which play a major role in Make in India. The focus should be on improving all zones including inventory management, operations and manufacturing. Utilization of latest technologies like radio frequency identification will lead to matching the pace of demand and reducing errors. Information technology and analytics should be utilized vigorously to standardize processes and keep a track of all activities. Internet of Things (IoT) and big data analytics will definitely help in making India’s supply chain competent.

The article is written by Akanksha Rajput. She is a second year PGP student at Indian Institute of Management Raipur

Disruptions in Supply Chain Management – Learning it the Hard Way

In the light of ever diminishing profit margins, over-whelming demand for shortest possible time delivery and minimum inventory holding, presence of a responsive and resilient supply chain is a necessity. External factors like natural disasters, fire accident at supplier end and government restrictions that are not under control of the company also pose a significant risk to smooth functioning of the supply chain. To address these issues let us have a look at some of the companies that had to deal the issues that arise due to supply chain disruption.

In March 2011, Japan was hit by earthquake and tsunami which caused huge loss of lives and also affected the production facilities of major automotive companies namely Toyota, Nissan and Honda. The effect was of such magnitude that it took Toyota over six months to restore production to pre-calamity levels, resulted in a production loss of 140,000 cars and 30% decrease in company profits.

Not all disruptions are man-made. Closer home, labour strike at Maruti Suzuki India’s Manesar plant in June 2012 led to the shutdown of the plant for a month. The resulting effect was a daily loss of INR 900 million and significant drop in sales and market value. This led to long waiting period and cancellation of bookings of its top selling cars. 

Supply chain disruption is an unplanned event that adversely affects a firm’s normal operations. It can be a sudden increase or decrease, in demand or supply that leads to imbalance between the two. 

A convenient solution for such an unplanned situation can be, building Inventory. But holding excess inventory can be a costly affair. Reasons behind it – the inventory carrying costs are incurred continually and also the inventory is meant to be used only in a rare events of disruption. So, the company may end up paying for resources that remain untapped forever! There are also concerns for obsolescence of the products. At the same time, holding excess inventory is reasonable in case of commodity products that are associated with low holding cost and low risk of obsolescence. For example, large amount emergency fuel reserves are maintained by United States as Strategic Petroleum Reserves (SPR). It is one of the largest emergency supplies in the world.

For products showcasing high inventory carrying cost and risk of obsolescence, having limited but multiple suppliers is a better approach. Controlled decentralization, hedges the risk possessed by a centralized or pooled (single) supplier in case of untoward situations. As in case of technology companies like Samsung Electronics  which always aim to have at least two suppliers, even if the second one provides only a fraction of the total volume.This approach helps the company to lower risk of disruption in the supply chain.

While disruptive environments are hard to avoid, whether a company mitigates or fails in that situation depends lot on the company. A classic example for the case is a major fire that broke out in a plant in Philips electronics in March 2000. It was a major supplier of semiconductors to Nokia and Ericsson and the fire destroyed chips meant for millions of phones. Nokia was quick to respond to this by sourcing chips from other plants of Philips and also procured from other suppliers. This multi-supplier strategy along with timeliness, led to little effect of the situation on Nokia’s demand supply capabilities. The other major customer of Philips, Ericsson was confined to single supplier strategy. The single source of chips led to disruption in mobile phone production by Ericsson. As a result, Ericsson ended up losing significant market share to Nokia and a drop in net profits.

The contrasting outcomes to a single event showcases that a responsive and resilient supply chain can alter the fortunes of a company. Breakdowns at a point in the supply chain can have consequences, which are not limited to that region rather, on a global scale.

Thus as a supply chain manager, one should take an informed decision in designing the Supply Chain, by taking into consideration all the factors and risks involved; past industry practices and experiences; and whether it is sustainable for the company and the specific product.

References:

1. WIPRO Consulting Services, “Supply Chain Vulnerability in Times of Disaster”   http://www.wipro.com/documents/resource/ Supply_Chain_Vulnerability_in_Times_of_Disaster.pdf

2. Sanjeev Prashar; Harvinder Singh; AnshuKatiyar, “MarutiSuzuki India Limited: Marketing,” Ivey Publishing, Feb 6, 2013

3. Sunil Chopra and ManMohan S. Sodhi, “Managing Risk to Avoid Supply-Chain Breakdown.” 

http://sloanreview.mit.edu/article/managing-risk-to-avoid-supplychain-breakdown/

4. William Schmidt Ananth Raman, “When Supply-Chain Disruptions Matter.” http://www.hbs.edu/faculty/Publication%20Files/13-006_cff75cd2-952d-493d-89e7-d7043385eb64.pdf

5. https://en.wikipedia.org/wiki/Strategic_Petroleum_Reserve_(United_States)

6. M. Sodhi and S. Lee, “An Analysis of Sources of Risk in the Consumer Electronics Industry,” Journal of the Operational Research Society 58, no. 11 (November 2007): 1430-1439.

The article is written by Aditya Pratap. He is PGP first year student at Indian Institute of Management Raipur. 

Supply Chain Management in India : Challenges and Opportunities

Greater and more intense competition between global value chains are leading to a substantial shift in the expectations from supply chains. India's complex operational challenges and increasing expectations make the job of a supply chain professional extremely difficult. In this article, we shall try to analyze the Indian scenario and provide some suggestions to chart the best way possible to create robust supply chains. Finally, we would conclude with a concise look at the initiatives being taken by the government, the industry and allied sectors to augment the supply chain infrastructure in India. 

Fig 1: The competition today is between value chains

The competition today is primarily between value chains. This makes it imperative to collaborate within the organization across following three levels,

•          Functional areas
•          Value chain 
•          Beyond the value chain

     With organizations being more diverse than ever, it is important to follow a tailored approach rather than a one size fits all approach. This differentiated approach will enable organizations to take care of different market and product needs. 

     Supply chain managers must be ambidextrous, able to see the bigger picture while also focusing on the details. In this regard, the single demand forecast for the entire organization can be the chief enabler with total cost optimization for capacity planning and scenario analysis for risk assessment. To take care of all stakeholders in the value chain from customers to vendors, supply chain professionals proactively need to apply pull replenishment strategies. This will invariably involve a solid information infrastructure, regular inventory calibration and removal of artificial demand distortions.

     The supply chains are becoming increasingly complex due to

•                       Broader product portfolios
•                      Shorter product life cycles 
•                      Increasing customer expectations 

      So it is important to actively manage supply chains. Going forward, it will be important to prune the non value added activities and capitalize the value added activities.

  

   We further look at the real-time problems faced by supply chain professionals and the unique characteristics in the Indian context. In India, the biggest bottleneck is the lack of proper logistics’ infrastructure. A lot more can be accomplished if there is better infrastructure and the ability to scale up to get products to far flung areas, especially small towns and villages. There is a huge opportunity once infrastructure bottlenecks are removed. The country has the potential to emerge as a supply chain centre of excellence for the world. The corporations need to build larger distribution centers in the interiors to consolidate access. The use of larger, efficient and appropriate vehicles is equally important. Another issue is the cost of movement in India due to long routes.

I    We compare the Indian scenario with the United States of America, the highway network in the US enables inter-state commerce system. It allows long-distance travel efficiently. In the US, for instance, a barge system for non time sensitive goods like copper or steel are moved in large quantities at low cost.  Similarly, India has a huge road structure but the same is not integrated to provide a strategic advantage. But if we can eliminate barriers and the congestion, and create a road or rail system allowing long-distance travel, then it helps in getting foreign investments in manufacturing. Retailers and Supply Chain Management companies would develop infrastructure and distribution centers. This will lead to consolidation and scaling up of distribution at lower costs.

    

     The cold supply chain in India is almost non-existent.The wastage of perishables that happens because there is no proper infrastructure for temperature control and refrigeration of goods is substantial. We have an to look at water, rail and road systems and connect them with ports. 

Fig 2: The cold chain logistics  

Now, we shall provide an overview of the initiatives presently underway to improve the supply chain system in India.

The Dedicated Freight Corridor Corporation of India Limited (DFCCIL) was registered as a company under the Companies Act 1956 in 2006. This company under Ministry of Railways was conceived and formed to undertake planning & development, mobilisation of financial resources and construction, maintenance and operation of the Dedicated Freight Corridors. The construction of the Western Dedicated Freight Corridor from Dadri to Nava Sheva (total length 1483km) and the Eastern Dedicated Freight Corridor from Ludhiana to Dankuni (total length 1839km) is already underway. The construction of East-West Dedicated Freight Corridor , the North-South Dedicated Freight Corridor, the East Coast Dedicated Freight Corridor and the South-West Dedicated Freight Corridor is in the planning stage.

The mission of this major infrastructure push spearheaded by the government is to build a corridor with appropriate technology that enables Indian railways to regain its market share of freight transport by creating additional capacity, to set up Multi-modal logistic parks along the DFC to provide complete transport solution to customers and to support the government's initiatives toward ecological sustainability by encouraging users to adopt railways as the most environment friendly mode for their transport requirements. This would occur in tandem with the industrial corridors to be setup in India. 

An industrial corridor is a package of infrastructure spending allocated to a specific geographical area, with the intent to stimulate industrial development. An industrial corridor aims to crease an area with a cluster of manufacturing or other industry. Naturally, such corridors are often created in areas that have pre-existing infrastructure, such as ports, highways and railroads. The vision is to have a holistic network of high quality infrastructure, connectivity via all modes of transport accompanied by industrial clusters. These modalities are arranged such that an "arterial" modality, such as a highway or railroad, receives "feeder" roads or railways. Concerns when creating corridors including correctly assessing demand and viability, transport options for goods and workers, land values, and economic incentives for companies. Examples include the Delhi Mumbai Industrial Corridor Project and Chennai Bangalore Industrial Corridor.

Fig 3: The proposed Dedicated Freight Corridors 

All the major steps taken by government to improve infrastructure will ensure smooth transportation of goods with less bottlenecks. That will allow India to be a global player in field of supply chain management. It will also help in getting investment in manufacturing. The policy reforms are being overhauled through introduction of initiatives like Make in India, Skill India and digital India. 

About the Author:

The article is written by Gulshan Prakash. He is  PGP first year student at Indian Institute of Management Raipur.
 

OPERTUNE - 2015 :

OPEP_Operation and supply chain club , IIM Raipur congratulates the winners.

Thanks all for such an overwhelming participation

Big Data Analytics

Big data is collection of large and complex data that cannot be processed by using normal data processing systems. Analytics refers to getting meaningful patterns from an unstructured or semi-structured data. Now Big Data Analytics is processing large data (Unstructured, semi-structured and structured) to discover unknown correlations, hidden data patterns, consumer preferences, market trends and other useful business information.

The results of analysis can be used for improving operational efficiency, better targeting of potential customer, new avenues for revenue generation, gaining competitive edge over rival firms and better customer service. The main aim of big data analytics is to help various firms to take more informed business decisions by enabling analytics professionals and data scientists  to analyze and interpret huge volumes of data  which is untapped by traditional business intelligence programs.

                

Big data encompasses internet clicks information, server logs, Content in Social media,various Social network reports, ,mobile phone call records, customer survey responses and market research data etc. Usually only unstructured and semi-structured data is associated with big data, but consulting companies like Forrester and Gartner consider structured data also as a valid component of big data.

Technologies in Big Data Analytics

Some software tools that are used to analyze big data are based on predictive analytics .There are new class of technologies such as Hadoop and related tools such as MapReduce, YARN, Spark, Pig and NoSQL databases which can process Big data. These technologies form crucial part of an open source software that supports the processing of large and diverse data.

Hadoop

Hadoop is a open source Java-based programming framework that supports the processing of huge data sets in a distributed computing environment. It is part of Apache Software Foundation. It was inspired by Google's MapReduce, a software framework in which any application is divided into numerous small parts. These parts (also called fragments or blocks) can be run on any node (a connection point in a network) in the cluster.

Illustration of Big Data Analytics

         

                                       Big Data Analytics solution by LogicMatter

        Let us now illustrate how big data analytics solution is implemented using Hadoop. LogicMatter is a low cost Big Data Analytics solution provider.  Here traditional (e.g. ODS, EDW) and emerging (Hadoop MapReduce) analytical tools are combined to operate on big data. The data platform is built on the powerful and flexible Amazon Web Services Cloud platform. To capture, process, store and transform data, Hadoop is used with the LogicMatter-designed Analytical Data Store (ADS). File-based storage service of Hadoop is used by platform for flexible and fast data processing .This big data analytics platform enables the continuous delivery of both real-time and historical analytics via the popular Tableau.

The Analytics platform and solutions is built specifically to solve some complex customer problems such as clickstream analytics, video analytics, sales performance analysis, fraud detection and financial analytics.

Data Sources

This platform enables to collect, process, store, and transform both unstructured and structured data exclusively for analytical purposes. It can quickly process various varieties of unstructured data including  text, documents, weblogs, XML files, Excel, audio & video, call logs), clickstream, and event data. It can also simultaneously process structured data from familiar enterprise data sources such as CRM, ERP and SQL Databases.

The data collection process is separated from transformation and analysis. It allows us to easily add data sources of unknown and known kind without impacting the analysis, a huge challenge with present analytics solutions. Transformation of data is delayed till you need to do the analysis wastage and reducing upfront costs.

Data Platform

The AWS data platform consists of two primary components:

 -Hadoop Cluster.

 -LogicMatter-designed ADS (Analytical Data Service).

The flexible and scalable Hadoop technology is used to collect both structured and unstructured data. The data collected is integrated, pre-processed and stored in ADS. The flat file-based storage system of Hadoop allows you to scale quickly as well as handle large amounts of known and unknown data. Hadoop is an integrated and intermediate data source and acts as a feeder to the ADS.The data from Hadoop is mapped and transformed to develop a data model. The model built iteratively and stored in the ADS forms the basis for a powerful analytics. ADS uses traditional data warehouse technology – Cubes, and OLAP. Hence, it supports all the powerful and traditional analytical techniques that you are used to (dashboards ,reports, scorecards etc.).     

Visualization

One of the unique design features of LogicMatter’s Big Data Analytics services is to enable continuous analytics both real-time and historical .As there is an integrated data discovery platform ,the visualization tool is directly connected to either Hadoop or ADS for development the analytics. Ad-hoc queries can be run against Hadoop for exploratory analytics and instant  data access . For the standard, canned reports and dashboards, you connect to the ADS to gain a historical perspective.

The data platform is so flexible that you can easily connect any of your favorite visualization tools (such as Qlikview ,Excel,).

Testimonials Of Big Data Analytics

There are several examples of how bigger, better, faster, stronger applications, analytics, sensors, and networks are creating results with big data today across various industries.

1. The Financial Services Industry

The financial services industry uses big data to make better financial decisions. Banking gaint Morgan Stanley ran into issues doing portfolio analysis on some traditional databases and now uses Hadoop to analyze investments on a larger scale and with better results. Hadoop is also used in the industry for sentiment analysis, financial trades and predictive analytics.

2. The Automotive Industry 

Ford’s modern hybrid Fusion model generates up to 25 GB of data per hour. Data obtained can be used to understand driving behaviors, reduce accidents, understand wear and tear to identify issues that lower maintenance costs, avoid accidents, and even confirm travelling arrangements.

3. Supply Chain And Logistics

Companies like Union Pacific Railroad use thermometers and ultrasound to capture data about their engines and send it for analysis to identify equipment at risk for failure if any. The world’s largest  multi-carrier network for the ocean shipping industry-INTTRA uses it’s OceanMetricsapplication to allow shippers and carriers to measure their own performance. Companies are also using telematics and big data to streamline trucking fleets . GE believes these types new capabilities can contribute $15 trillion to the global GDP by 2030 by using systematic and data-driven analysis.

4. Retail

Walmart is using big data from 10 different websites to feed shoppers transaction data into analytical devices. Sears and Kmart are trying to improve the personalization of marketing campaigns and offers with big data to compete better with Wal-Mart and Target.

Practical Big Data Benefits

Develop Target Markets

By analyzing the various customers purchasing orders, companies can now know better about customers who are buying their products. Companies can accordingly target on those customers.

Customize your website in real time

Thorough big data analytics companies can personalize their websites and portals based on gender, location and nationality of customers and offer them tailored recommendations .The best example for this is Amazon’s use  item-based, collaborative filtering (IBCF).Amazon uses

Features such as “Customers who bought this item also bought” and “frequently bought together” to reach more customers. Amazon could generate more revenue through these methods.

Create new revenue streams

The insights that a company obtain from analyzing market and consumers with Big Data are not just valuable to that company. Firms could sell them as non-personalized trend data to large industry players operating in the same segment and create a whole new revenue stream.

There are many companies like Bloomberg and Analytics Quotient which sell the analyzed information to other companies and generate revenues.

Reducing maintenance costs

Factories estimate that a certain type of equipment is likely to wear out after some years. So, they replace every piece of that technology within that many years. Big Data tools do away with such unpractical and costly practices. Massive amounts of data that they access and use and their unequalled speed can spot failing devices and predict the depreciation time. This results in a much more cost-effective replacement strategy for the utility as faulty devices are tracked a lot faster now.

Offering enterprise-wide insights

Previously when business users needed to analyze large amounts of varied data, they had to ask their IT colleagues for help as they themselves lacked the technical expertise. But by the time they received the requested information, it was no longer useful or even correct. Now With Big Data tools, the technical teams can do the groundwork and then build  algorithms for faster searches. They can develop systems and install interactive and dynamic visualization tools that allow business users to analyze, view and benefit from the crucial data.

Making Smart Cities

To deal with the consequences of their fast expansion, more  number of smart cities are indeed leveraging Big Data tools for the benefit of their citizens. Oslo in Norway, for instance, reduced street lighting energy consumption by 62% with a smart solution. The Memphis Police Department started using predictive software in 2006 and has been able to reduce serious crime by 30 %. Portland city in Oregon, used technology to optimize the timing of its traffic signals and was able to eliminate more CO2 emissions in just six years.

References:

http://searchbusinessanalytics.techtarget.com/definition/big-data-analytics

http://dermatological/big-data-analytics-services-solutions/

http://blog.pivotal.io/pivotal/news-2/20-examples-of-getting-results-with-big-data

http://en.wikipedia.org/wiki/Apache_Hadoop

 The article is written by B.kiran kumar.He is currently a PGP first year student of IIM Raipur.He has 3.9 years of experience at virtusa.