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SigmaWay Blog

SigmaWay Blog tries to aggregate original and third party content for the site users. It caters to articles on Process Improvement, Lean Six Sigma, Analytics, Market Intelligence, Training ,IT Services and industries which SigmaWay caters to

Love to play with Big Data and Analytics, pursuing MBA from IBS,Kolkata, currently doing internship under Sigmaway LLC.

Big data boom leads to the rise of the Chief Data Officer

Analyst, Gartner thinks that the growth in big data and its related technologies will increase the demand of Chief Data Officer (CDO) along with Chief Information Officer (CIO) by the end of the year 2014. 17% of organizations will hire CDO. Big data has made the role of CDO very significant and it is as important as the role of CIO. To know more on the importance of CDO in any organization, go through the following article written by Colin Barker, senior reporter at ZDNet in London:

http://www.zdnet.com/big-data-boom-leads-to-the-rise-of-the-chief-data-officer-7000025795/

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Skills necessary for big data team

Most companies are trying to figure out how to use big data more efficiently. They are also in search of the skills which can be helpful in extracting proper business insight from piles of data. A survey of senior managers revealed that along with technical skills, some other skills are also necessary. To know more about these skills, follow the article by Colin Barker, senior reporter at ZDNet in London:

http://www.zdnet.com/what-skills-do-companies-really-want-on-their-big-data-team-7000025945/

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Big data: What to trust – data science or the boss's sixth sense?

Guy Cuthbert, managing director at visual analytics firm Atheon Analytics, says that many of the firms selectively choose data to back up currently held views, which is just opinion based decision-making. The firms usually prefer to take decisions using untested opinions rather than data science. By applying data science, firms can deliver insights which are intrinsically more valuable than what they have today.To know more on data science, go through the article of Toby Wolpe, senior reporter at ZDNet in London:

http://www.zdnet.com/big-data-what-to-trust-data-science-or-the-bosss-sixth-sense-7000026550/

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Mongo DB 2.6 hits general availability - so what's in it?

Mongo DB announces its latest open source NoSQL database release 2.6. This release introduces greater automation features like incremental backup, point-in-time recovery, monitoring, visualization and alerts on more than 100 parameters in order to improve provisioning and management. Users can access network resources more efficiently along with an integrated text search in 15 languages with the help of Mongo DB query language. To know more about the features and efficiency of this release, follow the article of Toby Wolpe, senior reporter at ZDNet in London:

http://www.zdnet.com/mongodb-2-6-hits-general-availability-so-whats-in-it-7000028148/

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Different quality standards

“Quality means doing it right when no one is looking.”
― Henry Ford
The quality of your product or service defines the success measure of your efforts. Now this leads to several questions like - What is ‘quality’? Why it is so important? To get answers to these questions we have to ask ourselves what is the level of standard we would like to achieve? ‘Quality’ is nothing but the final performance criteria which affects a company with respect to its customers, clients or consumers. For each product and service, requirements are specified which are known as ‘Quality Control’ parameters. The article deals with the details of different quality standards.

http://creative.sulekha.com/chapter-22-introduction-to-iso-six-sigma-tqm-lean-manufacturing-cmm-pcmm-cmmi-etc_273495_blog

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ISO 9000: Quality management

ISO 9000 family addresses various aspects of quality management. It provides guidelines to organisations ensuring that their services and products consistently meet customer requirements. To know more about the latest version of ISO 9000 (ISO 9001: 2008), follow:

http://www.iso.org/iso/home/standards/management-standards/iso_9000.htm

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Total Quality Management tools

 Total quality management (TQM) tools help organizations to identify, analyze and assess qualitative and quantitative data that is relevant to their business. Each of these tools can be examined and used to enhance the effectiveness, efficiency, standardization and overall quality of procedures, products or work environment, in accordance with ISO 9000 standards (SQ, 2004). Read more about the TQM tools from the following link:

http://totalqualitymanagement.weebly.com/tqm-tools.html

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What is Total Quality Management?

“Quality in a service or product is not what you put into it. It is what the client or customer gets out of it.” – Peter Drucker. Total quality management describes a management approach to long term success through customer satisfaction. The primary elements of TQM are: Customer focus, Total employee involvement, Process centered, Integrated system, Strategic and systematic approach, Continual improvement, Fact based decision making, Communications. To know more on this aspect, please go through the following link:

http://asq.org/learn-about-quality/total-quality-management/overview/overview.html

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Six Sigma improving survey methods

What is Six Sigma? 'Sigma' is a statistical term for measuring how far a product differs from perfection. 'Six Sigma' means six standard deviations between mean and nearest specific limit. The main goal for applying Six Sigma is to reach as close to zero defect as possible. Six Sigma can be approached on three levels: Metrics, Methodology, Philosophy

Read more at http://www.surveymethods.com/glossary/article_six_sigma_seg_l.aspx

 

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Six Sigma application in construction industry

Taiwan is in a seismically active zone as it is situated on the earthquake prone Pacific ring of Fire. The cracks in the lightweight partition walls cause customer dissatisfaction as repairing cost is higher. To increase customer satisfaction, American Society of Civil Engineers (ASCE) is applying Six Sigma in construction technology. Application of C&A (Cause and Effect) and FMEA (Failure Modes and Effect Analysis) is being used to determine the reason of cracks. To know more on this please go through the following link.

http://ascelibrary.org/doi/abs/10.1061/(ASCE)ME.1943-5479.0000155

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Six Sigma in managing operational risk

Different financial services suffer high operational risks when there is market failure and industry transformation. In order to reduce the cost of risk management operations, financial organizations are seeking new models and methodologies. FMEA (Failure Mode and Effect Analysis) and Control charts are two very powerful Six Sigma tools which not only help to identify and prioritize risks but also monitor the risks. To know how FMEA and Control charts help in risk management, please go through the following article written by Abhishek Soni, a certified Six Sigma Black Belt and Project Management Professional.

http://www.isixsigma.com/industries/financial-services/leverage-six-sigma-to-manage-operational-risk-in-financial-services/

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Six Sigma at Citibank

In order to become premier international financial company in the next millennium, Citibank, a Citigroup company, implemented quality initiatives to provide quick customer service anywhere in the world. They took the challenge of implementing Six Sigma to improve customer satisfaction by using methodologies like cycle time reduction (CTR), coupled with detection of defects using Six Sigma methods which resulted in significant improvements in process timeline, cash management and customer loyalty and satisfaction. To read more about this aspect please visit Rochelle Rucker’s (a freelance writer and publicist for Motivators Inc) article link as given below.

http://www.qualitydigest.com/dec99/html/citibank.html

 

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Effective utilisation of data in BFSI sector

Data analysis is an important part of BFSI organisations. It helps to manage huge customer database of the organisations. It also automates the day-to-day transaction process. An article by Mohan Jayaraman, Managing Director of Experian Credit Information Company of India Pvt. Ltd. and Country Manager of Experian India describes that it is necessary to bridge the gap between information and its effective usage. For this, data analytics solution requires ability to manage and draw interferences from large amounts of data.

 For more information, please go through: http://www.informationweek.in/informationweek/perspective/287791/indian-banks-improve-customer-lifecycle-analytics?utm_source=rss&utm_medium=rss&utm_campaign=how-indian-banks-can-improve-the-customer-lifecycle-by-using-data-analytics

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Job opportunities in BFSI sector

With the advancement of new technologies, big data and internet, young professionals are getting opportunities for new career options. With the growth of facebook and twitter, different organisations of BFSI sector require more professionals for their work like collecting data, prediction and forecasting revenue. So doors for new jobs are being opened in front of the young pool of talents.

For more information, please go through: http://economictimes.indiatimes.com/news/news-by-industry/jobs/rise-in-demand-for-social-media-experts-in-fmcg-bfsi-pharma-companies/articleshow/29500508.cms

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SOHAM SRIMANI
sOUTRIK, THIS ONE IS AWESOME
Monday, 24 March 2014 10:57
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Stabilisation of the banking industry

The main cause of 2007-2009 recession was bursting of real estate bubble. But it was the banking crisis which led the U.S. economy to a far worst situation. Now the key question is whether banking industry is able to solve their problems. Losses suffered by banks created a number of fundamental problems in the industry. An article by Michael Sivy, a chartered financial analyst and a former securities analyst for an independent stock research firm, speaks about the needs to be addressed to get financial system back to full strength.

For more information, please go through: http://business.time.com/2013/02/05/has-the-banking-industry-really-been-fixed/

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Consequences of mergers and acquisitions in banking sector

The international banking and financial sector had gone through a major turmoil in terms of mergers and acquisitions. Deregulation has been the main driver, through three major routes - breakage of interest rate controls, removal of barriers between banks and other financial institutions and lowering of entry barriers. The article by Srinivasan R., an associate professor in the Corporate Strategy and Policy Area at IIM Bangalore, speaks about the benefits and disadvantages of post 2000 mergers and acquisitions in India.

For more information, please go through: http://tejas.iimb.ac.in/articles/01.php

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Frequent insurance alerts

FICO, a predictive analytics and decision management software company, has done a global survey which revealed that 55% of customers want insurance renewal reminder more frequently through mail and Smartphone.

For more information, please go through: http://online.wsj.com/article/PR-CO-20140312-906735.html

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Analytics: facilitating insurance organisations

Insurance organisations face problems in storing information. With the increase of information, innovations are required to handle information to detect risk properly. With the help of analytics in distribution channel, market products have improved. It also helps in taking decisions and reduces customer retention.

For more information, please go through: http://www.youtube.com/watch?v=KN-KgCgZdTE

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Hybrid Approach: Detecting insurance frauds more effectively

The main threat of any insurance organisation is to detect fraud. To prevent fraud effectively, SAS has taken a Hybrid Approach, which enables detection of fraud 10times more effectively. The technologies in this Hybrid Approach are: Business rules, Anomaly Detection, Predictive Models and Social Network Analysis.

For more information, please go through: http://www.youtube.com/watch?v=HbJmJ_jK7gU

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Effective use of big data in insurance

The biggest challenge for any insurance company is  to capture, store, search, share, analyze and visualize big data. Moreover, handling these data is also very challenging for the insurers. Étienne Castonguay, partner and co-founder of InEdge, suggests that Predictive Modelling in insurance can help them in solving the problems.

For more information, please go through: http://tdwi.org/Articles/2013/02/26/Insurance-Analytics-Trends.aspx?Page=1

 

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