Current Trends
1. Analytics:
Analytics is the discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight.
Firms may commonly apply analytics to business data, to describe, predict, and improve business performance. Specifically, arenas within analytics include enterprise decision management, retail analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix analytics, web analytics, sales force sizing and optimization, price and promotion modeling, predictive science, credit risk analysis, and fraud analytics.
Organizations generate and collect large amounts of data in many forms (for example: text, statistical data, qualitative data, big data) and from many internal and external sources including social media.
Organizations use predictive analytics and other kinds of analytics software to gain insights into their financial and operational performance and from their customer behaviors. With these insights, they can make accurate predictions and better-informed decisions about emerging opportunities, competitive threats and shifts in their markets to increase competitive advantage.
Studies show that organizations that apply analytics outperform their peers. Further, those with a broad-based, analytics-driven culture perform, on average, three times better. Not only do they drive more top-line growth and control costs, they take timely corrective action to reduce risks that derail their plans.
Example:
Let’s see how analytics helps in marketing. Marketing has evolved from a creative process into a highly data-driven process. Marketing organizations use analytics to determine the outcomes of campaigns or efforts and to guide decisions for investment and consumer targeting.
Analytics is the discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight.
Firms may commonly apply analytics to business data, to describe, predict, and improve business performance. Specifically, arenas within analytics include enterprise decision management, retail analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix analytics, web analytics, sales force sizing and optimization, price and promotion modeling, predictive science, credit risk analysis, and fraud analytics.
Organizations generate and collect large amounts of data in many forms (for example: text, statistical data, qualitative data, big data) and from many internal and external sources including social media.
Organizations use predictive analytics and other kinds of analytics software to gain insights into their financial and operational performance and from their customer behaviors. With these insights, they can make accurate predictions and better-informed decisions about emerging opportunities, competitive threats and shifts in their markets to increase competitive advantage.
Studies show that organizations that apply analytics outperform their peers. Further, those with a broad-based, analytics-driven culture perform, on average, three times better. Not only do they drive more top-line growth and control costs, they take timely corrective action to reduce risks that derail their plans.
Example:
Let’s see how analytics helps in marketing. Marketing has evolved from a creative process into a highly data-driven process. Marketing organizations use analytics to determine the outcomes of campaigns or efforts and to guide decisions for investment and consumer targeting.