“If you live long enough, you'll make mistakes. But if you learn from them, you'll be a better person.”

- William J. Clinton

Trial and error are part and parcel of our everyday work. But, learning from mistakes and performing better, is what that makes the difference. In this article, Rachel Sprung, Product Marketing Manager at HubSpot, has shared some of the mistakes in the field of analytics that she had experienced. They are:

• Thinking low numbers are always a bad thing
• Confusing correlation with causation
• Confusing visits with views (and vice versa)
• Equating more time on a page with higher engagement
• Counting internal website visits toward your goal

 To know more and avoid such mistakes, visit the following link:

http://blog.hubspot.com/marketing/marketing-analytics-mistakes

According to Mary Shacklett (president of Transworld Data), organizations need big data and analytics capabilities for immediately transferring big data into actionable decisions. According to a Gartner September 2014 report, there is an increase in investment in big data by 64% from 2013. Jeff Kelley (Big data analytics analyst from Wikibon), says that “customers expect personalization when they visit websites, so companies need to develop analytical capabilities and in the long term apply real-time will grow as Internet of Things.” Preventive maintenance analytics can be developed, if data on the Internet to thing can be analyzed. To know more about real time analytics and Internet of Things read on:  http://www.techrepublic.com/article/surge-in-real-time-big-data-and-iot-analytics-is-changing-corporate-thinking/

Punk in Punk Analytics means working fearless and having an approach to ‘do-it-yourself way’. In the last few years with the rise of new technologies, we entered into the era of punk-style analytics. Some characteristics of punk analytics are:

• No barriers for information search, as you can download easily and free of cost.
• Mistakes are part of the process, but we can overcome by using analytics software and by having familiarity with the data.
• Fast and to the point is good.
• Idea should be transparent and it should have less processed time.
• Punk Analytics are basically concentrating on the issues of the moment, as it is the starting point for active exploration.
•   Working collaboratively is important to achieve a common goal.
To know more about punk analytics follow the article link of James Richardson (Business Analytics Strategist at Qlik): http://www.itproportal.com/2015/04/19/rise-punk-analytics/

Breach of security has always been an important issue for any organization. Analytics has also provided a solution to this problem in the form of Security Analytics.

According to Eric Ahlm, Research Director at Gartner, "Security analytics platforms endeavor to bring situational awareness to security events by gathering and analyzing a broader set of data, such that the events that pose the greatest harm to an organization are found and prioritized with greater accuracy."

Two important applications of security analytics are:

• Security Information and Event Management (SIEM)        
• User Behavior Analytics (UBA)

To sum up, although security industry is still immature in the application of analytics, it still holds huge growth opportunities.

To know more, visit the following link:

http://www.firstpost.com/business/security-analytics-play-major-role-finding-breaches-says-gartner-2199152.html

An important application of analytics is Tax Analytics, which helps organizations, think differently about tax related issues and, thus, facilitates new approaches to improve business outcomes. A new function of tax analytics is to improve the understanding and management of the tax implications associated with short-term business travel. It helps businesses track travel of employees, identify areas of concern in states or countries, address locations of concern, and enhance payroll delivery by analyzing global travel-related data and potential tax implications. This creates a win-win situation for both the parties- the business and the employees traveling on behalf of the organization as it leads to cost reduction for business and satisfaction for employees.

To know more, read this interesting article by Beth Mueller, U.S. Tax Analytics Leader, Deloitte Tax LLP, in The Wall Street Journal:

http://deloitte.wsj.com/cio/2015/04/16/tax-analytics-spotlight-on-business-travelers/

The number of merger and acquisition (M&A) transactions involving insurance brokers and agents have shown a growing trend since last year. It’s important to speed up the post merger integration process for making these M&As successful. This is where the use of analytics technology comes in.

Some important areas where analytics technology is helping to make a difference in post-merger scenario are:

• Driving Efficiency
• Boosting Productivity
• Facilitating Teamwork
• Strengthening External Relationships
• Navigating Logistics
• Reconciling Different Corporate Cultures

To know more, read the following article at insurancejournal.com by Kabir Sayed, CEO of Riskmatch.

http://www.insurancejournal.com/news/national/2015/04/07/363528.htm

Analytics is seen as a ladder to succeed in today’s world. It reminds everyone of the benefits that one can achieve with its application in business. But is analytics always useful? What people chose to ignore is its downside. In retail sector, although analytics helps to predict demand, but it also helps to predict the employees required to meet the demand. This in turn, leads to less stable work hours for part time workforce. To reduce the harm to real people, retail analytics should be used in a responsible manner.

To know more, read the following Forbes article:

http://www.forbes.com/sites/sap/2015/04/15/abusing-the-power-of-retail-analytics/

According to Vincent Weafer (Senior Vice President of Intel Security), analytical capabilities will help you to be ahead of your competitors. Predictive Analytics help you to analyze the future trends more accurately and help you to realize your threats and opportunities which affects budget, purchase and staffing decisions. For prediction, a large amount of data is required from a range of activities which organizations perform, historical events and third party intelligence and to make predictive analytics more effective, you need to build foundational abilities like real-time hunting, prioritization and scoping of security incidents in their environment. You need to analyze your stakeholders for blocking decisions. Read more at: http://www.darkreading.com/partner-perspectives/intel/predictive-analytics-the-future-is-now/a/d-id/1319956

According to a 2014 survey of more than 2,000 business professionals by MIT Sloan and SAS Institute, 87% respondents share a common restlessness to elevate their organizations to the next level of analytics.

Being data driven, has now become a necessity for all businesses, especially financial institutions. Using predictive data analytics to interpret a wide range of internal and external data on customers helps financial institutions to identify best targets for a particular product and earn more by making timely pitches.

Russ Bunham, in his Forbes article, gives four tips on how financial institutions can use big data analytics to their advantage:

1. Creating a customized, consistent customer experience
2. Dissolving internal silos to have one view of the customer
3. Ensuring data insight flows to the right person to make the pitch
4. Using big data knowledge to enhance customer relationships

To understand them in detail, visit the following link:

http://www.forbes.com/sites/centurylink/2015/04/14/4-ways-financial-institutions-can-bank-on-big-data-in-2015/

The focus of any news organization is to understand what it is that readers like, what they actually read and what they really should know about. To achieve these goals, The Guardian, is using its in house analytics engine, Ophan, to track page views, median attention time and identify the type of marketing required for each article. It also provides exploratory data for further research. According to Chris Moran, The Guardian’s digital audience editor, “Being informed by the data can actually lead to higher quality journalism.” 

By measuring site data more closely, The Guardian has now become a news powerhouse. To know more, visit the following link:

http://thenextweb.com/media/2015/04/13/how-the-guardians-ophan-analytics-engine-helps-editors-make-better-decisions/

Over the last two years, Big Data and technological advancement have transformed the way industries operate and compete. Financial Services industry, in particular, has adopted big data analytics to inform better investment decisions with consistent returns. It is widely used by investment banks, asset management firms, insurance firms and stock exchanges, to name a few.

The Investopedia article by Trevir Nath, talks about 3 V’s of Big Data i.e. volume, variety and velocity, how they are applied by financial services industry, algorithmic trading and the challenges faced by this industry in the increasing embrace of big data. In the nutshell, this article explains that despite the challenges, the financial services industry is trending towards Big Data and Automation.

Read more at:

http://www.investopedia.com/articles/active-trading/040915/how-big-data-has-changed-finance.asp

Big Data Analytics is generally used for building models to periodically optimize processes i.e. After-it-Happens business. But this limits the use of Big Data as there is always a delay in the data-to-action cycle and also, the analytical capabilities are limited at the business’s disposal. A better application of big data analytics is using it for As-it-Happens business. It enables us to leverage the data and models moment by moment to make an impact on business operations in real time.

Steve Wooledge, Vice President of Product Marketing at MapR, gives examples of real life applications that leverage a big data environment that integrates OLTP and analytical databases in his following article:

http://www.forbes.com/sites/teradata/2015/04/09/creating-the-as-it-happens-business-analytics-drives-action/

 According to Dave Blanchard (Industryweek), customer’s demands for lower delivered costs are seen to be a big challenge. But, by using predictive analysis, we can identify patterns and predict future events. An organization using predictive analysis can make better decisions. George Prest (CEO of MHI) says that companies that continue to use traditional supply chain models will struggle in the future.  According to the MHI/Deloitte study, it was found that less than 25% of companies have adopted predictive analytics though that number is expected to climb to 70% over the next three to five years.

 Read more at: http://www.industryweek.com/supply-chain/predictive-analytics-let-manufacturers-see-more-clearly-their-supply-chains

Predictive analytics is a “business game changer” that will separate the winners from the losers, according to Forrester. The better a company is at predicting what will happen in the future, the better positioned they are to do something about it. While data scientists will do the heaviest analytic-related lifting at big enterprises, the improvements that have been made to predictive analytic (also called advanced analytic) applications enables regular business people and developers to partake of the predictive bounty. With so many companies coming into the foray of analytics services, today the users have more options to choose from keeping the cost-benefit & need-value trade-offs in mind.  RapidMiner offers a “rock solid” enterprise solution with more than 1,500 methods that address all stages of the analytics lifecycle and has among the tightest integration with the cloud, Forrester says. There are also other options like SAS, SPSS, KNIME, sap, oracle to name a few.

To read more, visit:

http://www.datanami.com/2015/04/07/predictive-analytics-now-in-reach-of-the-average-enterprise-forrester-says/

Investing in talent management software can assist HR professionals in gathering and analyzing the data of employees. Applying big data analytics to measure employee performance can help organization to find strength and weakness of their employees e.g. many companies use wearable tech to improve communication within its stores, to track employees when they're at work. Employee satisfaction surveys, team assessments, social media, exit and stay interviews etc. can help HR to predict employee's attrition. Conducting performance appraisals and 360-degree performance reviews can help HR in better understanding the effectiveness of their professional development efforts. Big data analytics can be an advantage while hiring employees. Read more at: http://www.entrepreneur.com/article/244247

In this customer focused world, supply chain is no longer an internally visible process. The focus has now shifted to knowing where the supply chain needs to be. Predictive Analytics helps answer this question. According to Bill Abernathy, head of North America product supply logistics excellence, Bayer CropScience, “Predictive analytics are changing consumer buying behavior and supply chain professionals need to be able to satisfy the increasing demands of consumers who expect products delivered exactly when promised.” With the help of predictive analytics, manufactures are now able to make better decisions that are based on anticipating present and future customer preferences. Dave Blanchard, Senior Editor, IndustryWeek, has written in his article link about how predictive analytics is becoming a necessity for manufacturers. 

Read more at: http://www.industryweek.com/supply-chain/predictive-analytics-let-manufacturers-see-more-clearly-their-supply-chains 

Digitization has seen a rise in India in the past few years. Due to this, huge amount of data about our daily lives, needs and preferences is easily available. This is BIG DATA. If companies are already using this, then why can’t Government? Using big data analytics by government in policy making is a big step in improving its effectiveness. Moreover, government already has data in the form of Aadhaar Card details to start with. This data analysis can be used in a number of areas like formulating better policies for farmers by using Kisan Call Centre records, improving the transportation system, etc. This idea has already been implemented in Singapore and Germany on a smaller scale, but implementing it in India on a large scale can set another benchmark in evidence based policy making. Implementing this idea also faces various challenges like inefficiency of the public sector in India, invasion of right to privacy and not focusing on relevant information on such a large pool of data. The government already has initiated this idea but the need is efficient implementation.

Read more at: http://www.livemint.com/Opinion/LaTyG3Q111tuYa73XNMXsJ/The-promise-of-big-data-analytics.html

The latest development in the use of data and analytics is: Advanced HR Analytics. It is the application of new techniques and new thinking to talent management. It involves human resources and has a huge impact on an organization. Various organizations are already using it for following purposes:

·         Increasing the engagement and productivity of their employees

·         Reducing compensation expenditures

·         Reducing retention bonuses by $20 million

·         Reducing employee attrition by half

·         Detecting previously unobserved behavioral patterns

The insights that these companies have gained from data analytics are highly useful. Risk is always involved where there is a human element. But, developing data analytics to drive better people decisions can help companies compete in a better way.

To know more, read the following article in March 2015 edition of McKinsey Quarterly by Bruce Fecheyr-Lippens, Bill Schaninger, and Karen Tanner:

http://www.mckinsey.com/insights/organization/power_to_the_new_people_analytics

In a recent research, it was found that annual revenues from connected healthcare and fitness online services will approach $2 billion by 2019 i.e. nearly six times the $320 million value estimated for 2015. The study also found out that connected healthcare devices and the data they generate will benefit consumers of these new products.  The study further found that the importance of hardware will diminish at a much faster rate than other IoT market segments and demand for analytics software (that can extract meaning from data) will increase. Read more at: http://www.socialmediatoday.com/technology-data/2015-03-31/demand-big-data-apps-fitness-and-healthcare

Big Data means a huge amount of data and is characterized by 3Vs: Volume, Velocity, and Variety. Big Data has become very clumsy. So, the trend is shifting towards Fast Data, which means processing of massive data in real time to gain instant awareness and detect signals of interest on the spot. Another trend is Actionable Data, which synthesizes the predictive analytics and what-if analysis which enables you to take actions with feedback. Another new trend is Relevant Data which is critical to identify pertinence in the data set, and which leads to understanding of unrelated events and sequence. The last trend is Smart Data which is meaning-based computing and cognitive analytics that make solutions intelligent and self-improving. In a nutshell, Fast Data, Actionable Data, Relevant Data, and Smart Data (FARS) are replacing Big Data. Read more at: http://www.socialmediatoday.com/technology-data/2015-04-04/big-data-really-dead