Theanalyticsgameisevolving01

The Analytics game is evolving “In God we trust, all others must bring data” heard of this famous quote by William Edwards Deming? Today is a data driven world. Organizations across the world are accumulating large volumes of data over the years.

Would you believe that the digital universe in 2012 was estimated to have contained approximately 2.7 Zettabytes of data (that’s 2,700,000,000,000,000,000,000 bytes, or 2.7 billion terabytes), up 48% from 2011, rocketing toward 8ZB by 20151.

What you can do with all the above data?

KIRUBAKARAN NATARAJAN is a Semi qualified Chartered Accountant He is also certified by ACL Academy (Vancouver, Canada) on ACL Analytics and Data Driven Governance Risk and Compliance (GRC).

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An enterprise’s data are among its most valuable assets.

Yet, without a way to obtain, cleanse, organize and evaluate the data, the enterprise is left with a vast, chaotic pool of ones and zeroes.

Hence all the organizations need a mechanism which can unlock the treasures hidden in its massive stores of data and that mechanism is known as ANALYTICS. The concept of analytics is not new. Operation research techniques used by the British during World War II to successfully defend Britain against the Germans is a classic example of its successful implementation.

Though, technologies that help organizations understand their data have only become available and affordable recently.

Predictions 2012: Competing for 2020, International Data Corporation

What is it?

ANALYTICS is all about discovery and communication of meaningful insights from data.

The majority of raw data, particularly big data, doesn't offer a lot of value in its unprocessed state which means they are not suitable for human consumption even though it has almost all insights that can strongly influence all of the business decisions. So analytics helps to identify hidden patterns and models in a data that has multidimensional usage.

Data Analytics (DA) coaxes order from the chaos. It helps explain patterns, which in turn help the enterprise identify what it is doing well, determine how to do it better and recognize problems before they spiral out of control.

Analytics Chain: Descriptive Analytics is the simplest class of analytics, one that allows you to condense big data into smaller, more useful nuggets of information. The purpose of descriptive analytics is to summarize what happened. More than 80% of business analytics and most notably social analytics are descriptive. For example, number of posts, mentions, fans, followers, page views, kudos, +1s, check-ins, pins, etc.

Predictive analytics is the next step up in data reduction. It utilizes a variety of statistical, modeling, data mining, and machine learning techniques to study recent and historical data, thereby allowing analysts to make predictions about the future. The purpose of predictive analytics is NOT to tell you what will happen in the future. It cannot do that. In fact, no analytics can do that. Predictive analytics can only forecast what might happen in the future, because all predictive analytics are probabilistic in nature. In the most general cases of predictive analytics, you basically take data that you have to predict data you don't have.

Prescriptive analytics is the emerging technology which goes beyond descriptive and predictive models by recommending one or more courses of action and showing the likely outcome of each decision. It's basically when we need to prescribe an action, so the business decision-maker can take this information and act.

Analytics usage We use analytics in different spheres from predicting weather patterns, understanding consumer behavior and selecting the date of release of a movie to taking decisions on the designs and number of vehicles to be manufactured. Consciously or unconsciously, analytics forms the basis of business decisions.

Research released by MIT Sloan Management Review reports that 67 percent of companies surveyed are gaining a competitive advantage by using analytics. There are many examples of how analytics can solve business-related problems across industries. 

One of the challenges faced by technology companies is to control their transportation costs by optimally utilizing vehicles and avoiding fraud-related risks (e.g., fake trips recorded by transport vendors). Analytics can help them optimize their operations by aligning transport routes with the timetables of employees, leading to a reduction in the collective overall distance travelled by them as well as in the wait and travel time for employees.

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Forward-looking analytics supports retailers in product assortment, product positioning, store designing, and dynamic pricing — long before a customer actually sets foot in the store.

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Inventory management could lock up 20%–40% of invested capital in manufacturing industries. Traditional supply chain management relied on historical data in planning inventory. Although, this is helpful in the case of planned cycles and peak requirements, yet, it is not really useful during unexpected events or contingencies that immediately affect the need for inventory. Inventory forecasting using data analytics can help organizations better integrate their sourcing, procurement and production operations.

Similar uses of analytics can be seen across the various industries ranging from scheduling planes and crews, pricing tickets, making reservations, planning the size of an airline’s fleet in the aerospace sector to local governments deploying emergency services, regulate environmental pollution, control air traffic and devise criminal justice-related policies.

The game is evolving-Get ready Analytics is predicted as the next frontier for innovation, competition and productivity.

There will be a shortage of talent necessary for organizations to take advantage of analytics.

By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions. (McKinsey Research)

Leading organizations of today use data as a fourth factor in production, along with capital, people and materials. If used appropriately, analytics can be a significant differentiator that gives enterprises a clear edge over their competitors. Compliance, security, fraud detection and risk management are among several other areas that can effectively leverage analytics.

As the business is moving from making faith driven to fact driven decisions, the usage of analytics become unavoidable.

By Business Assurance Group A division of Veeras Infotek Pvt Ltd