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Predictive Analytics: Why is it important?

Predictive analytics is the utilization of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes predicated on historical data. The goal is to transcend kenning what has transpired to providing the best assessment of what will transpire in the future.

According to the IDC report, SAS is the no.1 Advanced and Predictive Analytics in terms of market share. The following are the reasons why everyone needs predictive analytics:

Why Predictive Analytics important?

Organizations are turning to predictive analytics to avail solve conundrums and denude incipient opportunities. Common uses include:

Detecting fraud: Cumulating multiple analytics methods can amend pattern detection and obviate malefactor comportment. As cybersecurity becomes a growing concern, high-performance behavioral analytics examines all actions on a network in genuine time to spot abnormalities that may denote fraud, zero-day susceptibilities, and advanced sedulous threats.

Optimizing marketing campaigns: Predictive analytics are habituated to determine customer replications or purchases, as well as promote cross-sell opportunities. Predictive models avail businesses magnetize, retain, and grow their most remuneratively lucrative customers.

Amending operations. Many companies use predictive models to forecast inventory and manage resources. Airlines use predictive analytics to set ticket prices. Hotels endeavor to prognosticate the number of guests for any given night to maximize occupancy and increment revenue. Predictive analytics enables organizations to function more efficiently.

Minimizing risk: Credit scores are acclimated to assess a buyer’s likelihood of default for purchases and are a well-kenned example of predictive analytics. A credit score is a number engendered by a predictive model that incorporates all data germane to a person’s creditworthiness. Other risk-cognate uses include indemnification claims and amassments.

Increasing sales and retaining customers: Predictive analytics gives your company the erudition needed to target customers with the opportune message at the right moment. By predictively scoring customers predicated on their next likely action—whether purchase or churn—you can more efficaciously spend your messaging dollars. Slash costs on your marketing messages and increment replication rate by suppressing those who are deemed unlikely to respond predicated on their predictive score. Similarly, offer discount codes only to those who are about to depart, preserving the cost of distributing to a wider audience.

Predictive Analytics in various Industries:

Banking and Financial Services: The financial industry, with a huge amount of data and money at stake, has long embraced predictive analytics to detect and truncate fraud, measure credit peril, maximize cross-sell/up-sell opportunities and retain valuable customers. Commonwealth Bank uses analytics to presage the likelihood of fraud activity for any given transaction afore it is sanctioned – within 40 milliseconds of the transaction initiation.

Health Insurance: In addition to detecting claims fraud, the health indemnification industry is taking steps to identify patients most in jeopardy of chronic disease and find what interventions are best. Express Scripts, a sizably voluminous pharmacy benefits company, uses analytics to identify those not adhering to prescribed treatments, resulting in a savings of $1,500 to $9,000 per patient.

Governments and Public sector: Governments have been key players in the advancement of computer technologies. The US Census Bureau has been analyzing data to understand population trends for decenniums. Regimes now use predictive analytics like many other industries – to amend accommodation and performance; detect and obviate fraud; and better understand consumer demeanor. They withal use predictive analytics to enhance cybersecurity.

Manufacturing: For manufacturers, it's very consequential to identify factors leading to minimized quality and engendered failures, as well as to optimize components, accommodation resources, and distribution. Lenovo is just one manufacturer that has utilized predictive analytics to better understand warranty claims – an initiative that led to a 10 to 15 percent abbreviation in warranty costs.


Predictive Analytics offers a unique opportunity to identify future trends and sanctions organizations to act upon them. With the growth in big data and the evolving nature of Business Intelligence, predictive analytics can offer valuable insights for organizations.

Gain the right Predictive Analytics skills with Sankhyana:

Sankhyana (SAS Authorized Training Partner in India) offers a rigorous curriculum to avail students hone their analytical and technical skills, as well as their critical cerebrating and data management. Technical skills can be instrumental in building predictive models, while analytical skills avail interpret the results.

Companies are looking to hire people to manage and denude the value and meaning of the information they are amassing. They require talented professionals to avail them translate their data into incremented revenue, better customer gratification, ameliorated product quality, and enhanced resource orchestrating.

About SAS: SAS is the leader in analytics. SAS is the no.1 advanced and predictive analytics skills to have in this data-driven world.

About Sankhyana: Sankhyana (SAS Authorized Training Partner in India) is a premium and the best SAS Training Institute in Bangalore/India offers the best Online/Live-Web training on SAS and Data Management tools.

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