By now, several of us are beginning to hear about Lean Six Sigma and are wondering what this is all about? Lean Six Sigma (LSS) is a unique analytical business process available to facilitate continuous process improvement (CPI) which includes Champions, Black Belts and Green Belts that enables companies to drastically improve their profitability by monitoring everyday business activities minimizing waste and inefficiencies. CPI program tends to improve the operational, administrative and support functions of the company. Many successful companies, such as Motorola, use Six Sigma. Ranging from customers, stockholders, employees to suppliers all benefit from this business process. The following factors make LSS achieve its success: 1) Leadership commitment 2) Focused resources. 3) Common tools and language 4) Disciplined project approach 5) Bottom-line business measures. Improvements are made by working to reduce waste through a five-step process: 1) Identifying customer value  2)Mapping the value stream  3)Creating flow 4)Seeking perfection 5)Pulling based on demand. Read more about this aspect at George Aslinger's article link: 

http://www.processexcellencenetwork.com/lean-six-sigma-business-transformation/articles/continuous-improvement-with-lean-six-sigma-for-beg/

Big data gives governments tools to discover more effective and innovative ideas on how to decrease poverty across the world. Proper application of big data and technology advancement can improve the circumstance of people currently impoverished. Before, collecting reliable data from all corners of a country can pose as a hindrance in the complete elimination of poverty but now this problem is solved by the advances in mobile technology. Reportedly, more than 85% people in the world have access to mobile phones, even if some of them are the poorest people which lead to greater data collection on the poor and availability of big data acts as a catalyst to help the poor people prosper. Data collected from cell phone call data records and an individual's bill payment history banks and other financial institutions can effectively evaluate a person's ability to pay back loans and determine their risk attitude. This helps the institutions to give credit to the required people through micro financing. Read more at:

http://www.bigdata-startups.com/5-applications-big-data-in-government/

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There exists price war among major cloud providers. Amazon Web Services announced to lower the prices of a number of its cloud services, soon after Google cut down its prices. According to the vice president of Amazon Web Services, cost slashing is aggressive in nature. Slashing prices is a regular process. Whenever it is possible to reduce costs, they lower the prices for the customers.As soon as Google announced to reduce its  Google Compute Engine (GCE) by 32 percent, Google Storage  by 68 percent Amazon Web Services decided to cut its price of AWS' Simple Storage Service (S3) by 51 percent, Elastic Cloud Compute (EC2) by 30 percent to 40 percent, AWS' Relational Database Service (RDS) by 28 percent, ElastiCache service  by 34 percent on average.The repeated cloud price cuts make it hard  to run in-house operations, which would create both hardware costs and preservation costs costly. Read more at:

http://www.computerworld.com/s/article/9247216/Price_war_Amazon_cuts_cloud_costs_to_counter_Google

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Three ways analytics can change customer service: (1)Barriers to the organizations are to be broken down as encouraged by Analytics: The multi-channel analytics is causing many brands to call their customer service technologies and processes frequently to break down data vaults and multi-channel support and reaction is centralized to avoid repetition of customer information. say of the customer, a 360-degree vision of the customer, makes analytics more convenient and insightful. (2) Changing awareness of chief Measurements by Analytics: Organizations are deviating from old methods such as rapidity to answer and quantity of calls handled per hour, and moving towards more important methods such as overall client pleasure, first call decision. (3) Allowance of analytics to   move ahead: Once the right analytical reports are collected organizations use them to improve their services and support. Using analytics an organizations can estimates what customers are wanting and expecting from their services. Read more at:

http://www.parature.com/customerservice-analytics/

Enhanced e-commerce is a trending reason nowadays for the uprising online retail shopping. It includes tracking code updates, data model changes, and new end-user reports that address many ecommerce-specific use cases. Together they help online retailers see farther and understand customer behaviors better than ever before. According to reports, online retail grew above 30% in year 2013. Digital data has played an essential role in that growth offering deep insights into online shopping behavior and letting retailers make smarter moves. But needs are rapidly increasing and retailers are requiring more sophisticated and comprehensive analysis tools to understand shoppers and improve product-level performance. We should analyze how far shoppers get in the shopping bag and understand which products are viewed most and which are frequently abandoned in cart. We should also create product lists for onsite merchandising rules, product landing pages to see which lists and products are best at driving customer engagement and analyze how internal promotions impact sales and act immediately on the results. Read more at: 

The two important ways to redirect a user agent client-side are meta refresh and JavaScript redirect. Either method of client-side redirection has potential for causing significant issues with both analytics and SEO in spite of having flexibility in choosing whether or not to redirect after the page is rendered and portability in having code. Essentially there are two issues of client-side redirection with Analytics: 1) page view bloat 2) unclean referrer. The first issue occurs when the client-side redirect fires after the analytics code has already discovered the page view. The second issue, unclean referrer, refers that the final result has an unclear referrer. Regarding SEO, the problems are more extreme. There are at least two key issues: 1) page rank devaluation 2) content mismatch. The use of a meta in short explains that most crawlers support a meta refresh of 0 and treat it as a redirection of server-side, and a JavaScript redirect is simply ignored as crawlers don't read JavaScript.Read more at: 

http://thesimplesynthesis.com/post/effect-of-client-side-redirects-on-analytics-and-seo-meta-refresh-and-javascript

Disruptive technologies are technologies that will transform existence, commerce, and the worldwide economy. According to a report, there are twelve technologies that could bring massive economic alterations and disturbances in the coming years. The report also states how these technologies could modify our world, their profit and confront, and propose rule to help leaders’ .Business leaders should update their organizational strategy continuously with the developing technologies, and use technologies to progress inner presentation. Disruptive technologies can change the strategy for businesses, create completely fresh yields and services, and changing team of value between creators or from producers to customers. Organizations use business model improvement to arrest that value. Leaders need to presume from where risks are coming from and should look further than confirmed models. Organizations also need to make sure to keep their workers’ abilities advanced.Read more at:

http://www.mckinsey.com/insights/business_technology/disruptive_technologies

Big data is a popular term used to describe the exponential growth of structured and unstructured data. Despite of such an understanding by business organizations, according to a survey, second annual analytic usage, trends, and future initiatives report, 75 percent of businesses have yet to reach big data production. However, just 12.6 percent of respondents said their company has completed several big data projects that are now in production. Drew Rockwell (Lavastorm CEO)said “It’s organizations that go the next level by removing complexities from the analytics process and empowering others in the organization, namely business analysts, who are going to be able to turn data insights into actionable business enhancements for long-term success.” According to another survey, one concern for executives who are experimenting with big data is a shortage of expertise in that field. With a lack of big data skills, organizations are reluctant to take the plunge since a clear ROI immediately available. Without being open to a little disruption, organizations will have a much more difficult time adapting to changing consumer mindsets. Businesses should conduct their own research and see what options best fit their needs. Read more at: 

http://www.pymnts.com/in-depth/2014/is-big-data-just-a-big-problem/#.U6KBPZS1Yn7

An investment banking firm  has developed a ‘stochastic model’ its predictions to generate distribution of results for the each of the 64 matches to be played during WC.The predictive model is part of the the World Cup and Economics 2014. Stochastic modeling is used to forecast outcomes, even in the field of sports. This mathematical model predicts the probability of outcomes. According to the model, predicting the outcome of the WC is based on predictions for each match on “regression analysis”. This analysis used 14,000 observations to approximate the coefficients of its model. The dependent variable is the number of goals attained by each team during a match. Based on this analysis Brazil fares as the winning team. The next are Argentina and Germany, but these two teams have inferior probability. Read more at:

http://blog.arekibo.com/world-cup-2014-the-use-of-analytics-to-predict-the-winning-team/

Online social networks give vital information. If someone posts something on Twitter, Facebook, they generate a digital footprint. If someone reads it, or watches a YouTube video, they add to the data trail. We can analyze it to take business decisions. The information that we look for depends on business goals. Some companies use social media to increase sales, some concentrate on brand consciousness, others are focused on brand trust, or increasing customer satisfaction. An analyst records keywords which customers are discussing, use them into status updates or tweets to be more relevant to customers. They check which messages attract readers most so that they can reach new customers. There are different social media analytics tools. Some are Hoot Suite; span multiple channels, Twitter etc. Some tools include workflow; they allow social media managers to connect information to others. Customer feedback raises sentiment analysis. Read more at: 

http://www.theguardian.com/technology/2013/jun/10/effective-social-media-analytics

In financial markets, the ability to take risk while investing indicates risk profile. This is an important variable considered by a financial planner before advancing a product to an investor. Risk profile classifies the individuals in conservative, moderate or aggressive. Wealth management services suppliers use psychometric surveys to estimates the risk profile of a customer. Generally, the individual taking the test is asked to choose that option that best describes his response to the position out of the many options provided. The responses help the financial planners and wealth managers to insight how the person will react in a given situation. That is the basis of the individual's capacity to take risks. The survey minimizes the probability of wealth managers from being biased in the financial-planning process. An individual taking the test should be honest enough to select that option which best explains him.Read more about this aspect at: 

http://articles.economictimes.indiatimes.com/2011-04-21/news/29459327_1_wealth-managers-risk-profile-financial-planner

Big-data analytics impacts any organization economically, but often data scientists hope for benefits.The reality of where and how data analytics can improve performance varies across industries. Customer-facing activities- the greatest opportunities lie in telecommunications. Here, companies benefit by focusing on analytics models which optimize pricing of services, maximize marketing spending by predicting on where product promotions will be most effective, and identify ways for withholding customers. Internal applications- In industries, like transportation services, models focus on process efficiencies-optimizing routes. Hybrid applications- Some industries need both. Retailers use data to influence next-product-to-buy decisions and to choose the best location for new stores or to catch flows of products through supply chains. Companies operate along two horizons: capturing quick wins to build momentum while keeping sight of longer-term. Open data- swelling reservoirs of external data. Models are often improved combining these data with the existing ones for better business outcomes.. Read more at: 

http://www.mckinsey.com/insights/business_technology/views_from_the_front_lines_of_the_data_analytics_revolution

There are significant opportunities to make use of big data techniques. Unlike technology and consumer retail sectors in which advanced analytics has been implemented, it can also be used in other industries like insurance, health care, banking and public sector. In insurance, data can be aggregated from public sources and specialist data providers, allowing companies to better target customers and frame policies accordingly. Banks are increasingly using big data to generate a much deeper view of their customers, combining the information collected from all of customer's interactions with bank with selective third-party data like paying patterns for mobile phone bills, tracking trends on social media platforms such as Twitter. Read more about this aspect in Dominic Barton (global managing director at McKinsey & Co.)'s article link:http://blogs.wsj.com/experts/2014/03/28/sectors-where-big-data-could-make-an-impact/?KEYWORDS=analytics 

For the very first time in this computing era, it is made possible for machines to learn from experience and penetrate through the complexity of the data and identify associations between them, collectively known as cognitive analytics. This innovation works in a similar manner as of human brains. It processes information, draws conclusion and codifies behaviour and experience into learning. Cognitive analytics has the ability to process and understand exploding volumes of data in real time including data that may contain wide variations of format, structure, and quality. Instead of depending on predefined rules and structured queries to mine answers, cognitive analytics relies on systems that draw from a wide variety of potentially relevant information and connections to generate hypotheses. This process differs from traditional analysis in the way that more data is fed into a machine learning system, the system learns, which results in higher-quality insights and more accurate hypotheses. Read more at:http://deloitte.wsj.com/cio/2014/05/13/human-brain-inspires-new-cognitive-analytics/?KEYWORDS=analytics

Service level, abandoned calls, productivity indicators, quality indicators, customer service are some of the key metrics typically used by a call center to measure data for customer complaints. For many businesses, retaining existing customers are cheaper than acquiring new customers. Customers become repeat purchasers usually because they believe that the services they buy are good value for money and the service they receive when contacting the firm is of optimal standard. Read more at:http://www.lieberandassociates.com/800_Number_Measurement_Metrics_Inbound_Customer_Service_Orders_Sales_Statistics.shtml 

When Kolkata Knight Riders (KKR) clinched their IPL victory, they must have been thanking the technology that powered some of the decisions right from team selection strategy to competitive analysis. The SAP Game Analytics solution helped KKR to analyze the strengths and weaknesses of each player competing in the IPL, and also helped KKR increase team readiness and performance against their opponents. SAP HANA based platforms - SAP Auction Analytics, SAP Game Analytics, and SAP Lumira enabled KKR to evaluate players during the auction, derive post-game analytics following each of the team's games, and drive fan engagement respectively. Read more about this aspect at:http://www.informationweek.in/informationweek/news-analysis/296068/analytics-helped-kolkata-knight-riders-win-ipl-2014

In today's era of competitive world, it is less expensive to provide "great" service over "good service". The customer service company relies upon listening, analyzing and acting on it. Many organizations underestimate the impact and damage of various customer issues. This usually occurs because they are using data only from a single customer channel or taking into account their vocal customers only, limiting data to a single customer channel. If your organization works in silos, you may not have the complete picture especially if customers complain across multiple channels. This means if a company only counts the cases that complain on a specific channel, your view is limited to a small subset. Even if your organization counts all the complaints across all channels on a specific issue, it is likely that you'll still see a small percentage of the cases where customers are encountering these issues, because   majority of customers affected don't complain to the organization directly. In order to estimate more accurately and prioritize the impact of each customer concern organizations follows the following process. To know more:

http://www.informationweek.in/informationweek/news-analysis/271903/steps-measure-impact-silent-customers/

Unlike other retailers, Nordstrom (a fashion speciality retailer), wanted to learn more about its customers like how many came through the doors, how many were repeat visitors. The company started testing new technology that allowed it to track customers' movements by following the Wi-Fi signals from their smart phones. Nordstrom's experiment is part of a movement by retailers to gather data about in-store shoppers' behavior and moods, using video surveillance and signals from their cell phones and apps to get information as varied as their gender, how many minutes they spend in the candy aisle and how long they look at merchandise before buying it. If a consumer looks for Wi-Fi network, a store that offers Wi-Fi can pinpoint where that particular shopper can go and get Wi-Fi connection within a 10-foot radius. Stores can also recognize returning shoppers as mobile devices send unique identification codes when they search for networks. This means stores can now tell how repeat customers behave and the average time between visits. Read more at-http://www.nytimes.com/2013/07/15/business/attention-shopper-stores-are-tracking-your-cell.html?pagewanted=all&_r=0/

To transform the customer experience from traditional methods to better and newer methods, business authorities are relying on agile technology development. When Capital One started using agile development in 2011, Rudy Wolfs, Senior VP of Card IT at Capital One said, it amounted to only 1% of software that was delivered. Today, 85% of software’s are delivered by the agile development method. Also with agile, Capital One now also releases approximately 400 products a month, which has reduced the delivery times to three to six months while "cutting costs significantly," and finds 95% of products meet expectations on the first release. Presently, Capital One has more than 3,000 developers and business users trained on the agile methodology to get a better product. To know more kindly refer to the below mentioned link: http://www.banktech.com/channels/capital-one-delivers-85-of-software-thro/240166887?_mc=MP_IW_EDT_STUB

A recent research report shows that Medicare ACOs are facing difficulty to control and manage patient care because most beneficiaries have unrestricted choice over choosing healthcare providers. Much of the specialty care received was provided outside the patients' assigned ACO. The potential challenges in outpatient care are: the proportion of patients assigned to an ACO in 1 year who remained assigned the next year

• The proportion of office visits outside a patient's contracting organization

• The proportion of Medicare outpatient spending billed by a contracting organization that is devoted to assigned patients.

For more details please visit Mark Crane’s article in this link: http://www.medscape.com/viewarticle/823951