A pilot project using predictive analytics and applied natural language processing identified 8,500 patients of Carilion Clinic who are at risk of congestive heart failure. Discrete data points, such as weight and medications, can be found in structured EMR (electronic medical record) fields. Unstructured data includes physicians' notes that are typed or read into a patient's EMR or discharge papers.  The natural language processing technology searched for key words or phrases within the unstructured data as well as in structured data. In all, 20 million documents were analyzed. Because approximately half of all patients who develop heart failure die within five years, according to the “Centre for Disease Control and Prevention”, early identification is essential. About 3,500 of the 8,500 patients Carilion identified as at-risk would not have been found if the project had analyzed only the structured data, according to Steve Morgan, MD and chief medical information officer at Carilion Clinic.

To know more, please visit famous author & reporter Maggie O'Neill’s article by clicking on the following link:

http://www.baselinemag.com/analytics-big-data/analytics-ids-patients-at-risk-for-heart-failure.html/

The world’s music habits were once relatively private. Record companies were aware about which radio station played their songs and where their CDs were popular, but that information painted an incomplete picture at best in reality. Who knew what music people were sharing on tapes and CDs burnt in the privacy of their own bedrooms? The sales figure notifies companies about the number of records or CDs sold, but no information can be tracked after that. With the time, the music industry is changing, thinking is changing, market is changing. The explosion of data from sources like torrents, music streaming sites and social media platforms has offered the music industry a huge opportunity to track sales, monitor post selling behaviour, understand their fans and spot upcoming artists like never before. Music analytics is now worth an estimated £ 1.8 billion per year. While internet is taking power away from record labels, it is also giving them the ability to predict future hits. Universal Music UK’s director of digital, Paul Smernicki, thinks that ultimately the music industry will always be focused on content, no matter what analytical tools are available. According to him,“It’s important to remember that it's just a set of tools to help inform us. The data doesn't make the decisions, that's an un-replicable part of what we do.” But with robots replacing humans in every sphere of work, who knows how long it will be before music- the most successful talent scout in the industry is defined by an algorithm!

To read more, visit: 

http://www.theguardian.com/technology/2014/apr/09/music-analytics-is-helping-the-music-industry-see-into-the-future

Most banks nowadays implement Analytics intensively to gain insights from their customers’ data. By generating reports with the help of queries and analytical tools, questions are answered for better decision makings. But still formulating and testing the hypotheses, tuning the model and tweaking the data structures are being done manually. Though much of the work is done by computers, the main part, which is thinking requires human intervention.

But, all these are set to change with the help of Cognitive Computing and Analytics. So, what is cognitive computing? Cognitive computing is the ability to master natural language processing and draw deductions that are not typically possible.

To provide impetus to the growth of its products and services, Global financial services firm DBS Bank has redefined its financial operations with the power of Cognitive Computing and Analytics and they are bearing fruits from it. Read more at http://www.baselinemag.com/analytics-big-data/bank-turns-to-cognitive-computing-and-analytics.html  on how they are doing so.

Electronic Health Records are critical to succeed in healthcare service, but they are not enough.From a healthcare provider’s perspective, after spending a lot of money and time on EHR, reluctance to evaluate other solutions for population health management or “accountable care” can be understood. So, healthcare providers are choosing to wait for their EHR to evolve in order to address new demands associated with taking on and managing risk. But according to industry analysts this can be a long wait as wide range of functions are going far beyond what EHRs were built to do. Here analytics tools and solutions come to the rescue. Performing analytics using clinical and claims data, organizations can gain deep insight into patients, population, and performance, predict outcomes and rapidly identify the actions needed for improvement. This insight can be gained through a wide range of analytics solutions that deliver retrospective views of activity, ongoing surveillance of current activity, predictive modelling of future activity, as well as root-cause analysis.

To read more, visit the following link:

http://ehrintelligence.com/2014/04/09/why-moving-beyond-the-ehr-is-needed-for-population-health/

Tired of hearing about Big Data? Accept it or not, you have to get used to it. Hundreds of companies are ready to offer impressive remuneration to hire people with quantitative skills. Ms. Linda Burtch, with her 3 decades of experience in recruitment, has tracked the rising demand for workers who can understand and manipulate data. In a recent interview, Chicago-based Ms. Burch talked about what companies want, how midcareer professionals can compete and why workers who are left behind could face a "permanent pink slip."

To read more, visit the following link:

http://online.wsj.com/news/articles/SB10001424052702304819004579489541746990638?mg=reno64-wsj&url=http%3A%2F%2Fonline.wsj.com%2Farticle%2FSB10001424052702304819004579489541746990638.html

Big Data! While you are reading the two words and also this blog, you may be not aware that you already have Big Data right in front of you.

Many small businesses think Big Data to be very expensive to analyze. But, let me tell you one thing – we are analyzing Big Data freely for years! Sounds unbelievable right? Okay, so here’s the thing.

Nowadays, social media has become a great means of communication for every business. Many of them have their page on Facebook, LinkedIn, Google Plus, profiles on Twitter, etc. The social media platform can provide valuable insights about their products or services and also about their target customers. With low investments, you can get to know your customers’ behavior, know their demographics and much more. But seeing large volumes of data can make you puzzled.

Nicole Fallon from Business News Daily writes about some tips to get you started. Read them at http://www.businessnewsdaily.com/6190-smb-big-data-tips.html

Most retail companies today operate in the master franchisee model where master franchisee manages the operations of the different stores of the brand. In such cases, it is important to understand the difference between what the company sells to its franchise stores and what the stores in-turn sell to the consumer. This metric is where the insights are hidden. Hence it is very important that companies track &understand this metric to optimally manage stocks and avoid costly stock-out or over-stock situations. Important decisions like the number of new stores that should be opened, best location & size of each store in different cities are not a straightforward choice! Data analytics usage in this space has proved to solve this dilemma. It helps companies to decide the optimal size of each new store they open, while ensuring that these decisions takes into account key parameters like real estate rental costs, catchment area, average incomes in the geographical area, presence of competition etc. Therefore, data analytics is simplifying complex business problems.

Arvind Nagpal wrote about this aspect in his recent article. To read more, please visit the following link:

http://www.informationweek.in/informationweek/perspective/288161/analytics-helping-retail-outlets-critical-decision

According to a new survey conducted by Deloitte, it is found that as complexity in global supply chain networks continues to increase, less than one-third (26 percent) of business executives are using data analytics tools and processes to help manage third party relationship risks.Thirteen percent of those surveyed are still learning how to use analytics software and 22 percent use no data analytics at all. Few market leading companies leverage advanced data analytics tools and forensic accounting to identify anomalies in their transactional data & getting astonishing benefits while rest are lagging far behind in this issue. Nearly one-third (31 percent) of business executives surveyed, said that their organization has faced supply chain fraud, waste or abuse in the past 12 months.

Mark Pearson, principal, Deloitte Financial Advisory Services LLP, speaks about why organizations need data analytics to tackle supply chain fraud. To read more, please visit the following link:

http://www.net-security.org/secworld.php?id=16641

The visual data discovery (VDD) approach increases the probability that business managers will find the information they need in time to make effective decisions. This is the main reason behind VDD’s rapidly growing fan base. While traditional BI solutions can be invaluable, they do have limitations. Dashboards come in handy in few cases, but there is still a fundamental problem – the dashboard designer must have anticipated the need for that line of questioning or train of thought when the dashboard was originally built.  So, if unexpected questions arise, business managers end up making decisions without data, operating on gut feel alone.  And that means they end up operating without real answers at all! So, here’s the key question:  Do you ever get questions in your logistics operations that are unexpected and hard to answer? This is where visual data discovery tools excel.Visual data discovery tools provide a rich, visual environment that enables business users to easily interact with, and manipulate, information directly, hands-on.  They provide a compelling solution to help business managers explore data, without the assistance of skilled IT staff.

To know more, visit David White’s article by clicking on the following link:

http://logisticsviewpoints.com/2014/04/07/new-approaches-analytics-revolutionize-logistics/

Data complexity is a major challenge faced by the healthcare industry. Now healthcare industry is going through a transformation phase. So companies like General Electric, 3M CO, Siemens and Xerox Corporation are taking initiatives to gain insights for making healthcare processes more efficient by the use of predictive analytics.

Read more at: http://www.nasdaq.com/article/analytics-a-shot-in-the-arm-for-healthcare-analyst-blog-cm337055

Many marketers find themselves faced with overwhelming amount of data and organizational complexity, rapidly changing customer behaviors, and increased competitive pressure. Data or information has always been the USP, but now people are not using that USP in their advantage. If an investment is made in big data, one can extract only the relevant information and analyze it to transform the business decisions for the future.

Please go through the link for more details:http://www.marketingprofs.com/charts/2014/24321/marketers-and-big-data-in-2014-barriers-budgets-and-opportunities

A survey conducted by Cerulli Associates, a global analytics firm, reveals that 93% of the asset managers rely heavily on secondary market intelligence. This study was based on government agencies, trade organizations and research firms.

For more information: http://www.opalesque.com/650204/Majority_of_asset_managers_rely_on_secondary_market020.html          

Analytics can help businesses greatly to increase their online sales. Surprisingly, the potential of analytics is not yet fully uncovered. In most of the cases, either the business owners or the managers do not take the full advantage of it or they don’t know how to use it.

So, how should businesses use Analytics and interpret them to decrease attrition rates and increase sales on their website? See the tips here: http://cio.economictimes.indiatimes.com/news/business-analytics/8-ways-to-use-web-analytics-to-increase-online-sales/32728371

Whether it is elections in India, or a service delivery model of a market leader in any sector, the incumbent is always at a disadvantage. Be it their government, their services like banking or healthcare, or their retail experience, the consumer wants them to continuously evolve in a direction which they perceive as beneficial to them. As time bound service contracts become passé, disruptive technology becomes available at affordable prices (think 3D printers, e-books, digital content, Google fiber, multi-core smart phones) today’s consumers and clients are exposed to a plethora of choices. With lowered exit cost barriers it is becoming imperative that a business does all it can to retain their customers.

Organizations realize that they not only have to ward off direct competitors but also cope up with tangential attacks from substitutes powered by disruptive technology. The choice between a successful well proven business model and a new idea is never easy. In the first case the organization risks its immediate client base by diverting significant funds and effort for turning an innovative idea into a winning product. This strategy has a high probability of failure which might cost them a significant market share. HTC lost a large portion of its small-medium priced phone market share in its bid to create a premium flagship smartphone model. In the second case, it believes in its business model and tries to take incremental steps to make it more robust till it is too late for them. Blockbuster, Blackberry and Borders are examples of organizations which could not counter the threat of new market players like Netflix, Android (Samsung, LG etc.) and Amazon. There is also a third case of the likes of Barnes & Noble and Nokia where the incumbent tries to play it safe by not going all out for the new technology but yet has a back-up plan to survive. So what’s the magic mantra? To me it remains the quintessential quest.

Though one thing I firmly believe in, is that the fickle consumer / client has become even more choice aware and will try out the new flavor of the month if they feel that their implicit or explicit objectives are not being met in the vendor-client relationship. Thus it is essential that organizations know the pulse of their clients and consumers and be geared towards meeting their changing demands. Analytics can play a key role here. Predictive analytics can help organizations preempt attrition by taking mitigating measures while social media and web analytics can help them know what some of their consumers are thinking and provide insights into their future behavior.

While the objective of analytics i.e. to provide actionable insight, remains the same, the demands of the information consumer have drastically changed. They want a lot more data crunched in much shorter time frames and yet presented with all the bells and whistles. With today’s scalable cloud computing infrastructure like AWS available and tons of reporting packages which play well with them it’s almost possible. It is also possible for the security conscious to invest and manage the requisite infrastructure in-house. The JIT (Just in time) lean principle applies here as well. An organization should only generate information and insights at the speed which it can take action on. Anything more could be a waste of resources.

Thus at the end of day, know the customer’s pulse, make an informed choice between evolutionary and revolutionary changes to your business model and be prepared to be blind-sided by someone your organization may have never heard of. To be or not be is an incumbent’s curse but making an informed choice and being prepared for change must never be a dilemma.

In this era of advanced analytics, there are many new challenges involving privacy and security of individuals, as computing power allows nonprofits, businesses, and researchers to gather ever-larger troves of information. Though it can be observed that there is a colossal increment in the amount of available data, we still only have two eyeballs and one brain! How a traditional library will look without a librarian, or an encyclopedia without an index? Scale that prospect up to the realms of web analytics, astronomy, high-speed finance, or even basketball statistics, and the problem becomes clear.

Research scientist Fernando Pérezof, University of California, Berkeley, recently spoke about it at a symposium titled “Weathering the Data Storm: The Promise and Challenges of Data Science,” hosted by the Institute for Applied Computational Science (IACS) at the Harvard School of Engineering and Applied Sciences (SEAS).

To read more, Please visit Harvard university article link given below:

http://news.harvard.edu/gazette/story/2014/01/the-promise-of-big-data/

Communication is an absolute essential entity to allow successful improvement in healthcare industry. Effective communication will allow relevant and correct flow of data through the organization. With more relevant data, analysis will also be more accurate and will automatically lead to improvement in the healthcare industry.

Please go through the link for more details http://healthcareanalytics.info/2012/03/successful-healthcare-improvement-requires-analytics-and-effective-communications/#.UyhlIqIyX4s

Balancing privacy, policy, and innovation is important to achieve harmony in health care, but, it is also difficult. While both population health and patient centered care seek to improve health care, at some level they are fundamentally at odds. Managing the health of population in a sustainable and scalable way requires uniformity of care across large groups for prevention, wellness, resource utilization, etc. Often, the most predictive clues about our health, exist in information that lives outside of traditional health care. This can be unearthed with the help of new innovations in Big Data. With the right policies and safeguards in place, trust can be established that will give individuals greater comfort and confidence to share information with their healthcare providers.

Harry Greenspun, MD and Senior Advisor for Health Care Technology and Transformation at the Deloitte Center for Health Solutions talks more about it here: http://blogs.deloitte.com/centerforhealthsolutions/2014/03/balancing-privacy-policy-and-innovation-to-achieve-harmony-in-health-care.html?id=gx:2sm:3tw:chsblog:awa:chs:032214:deloittehealth#