Bridging the Insights Gap: Why Traditional BI and Analytics Fail?

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Data is the key building block of organizational intelligence. Rapid advances in technology has resulted in an exponential increase in organizational data being generated today. Efficient management of large volumes of data has become an essential function for achieving regular business goals, and long-term strategic and tactical decision making. Businesses today require intelligent systems with sophisticated algorithms, higher computational powers and storage to succeed in the market. They must have streamlined processes in place without which getting information even on simple queries will be difficult, let alone deriving any useful insights required to formulate a business intelligence strategy.

Organizations are data rich but insights poor

There is a data deluge, but how much of this data is truly accessible, accurate and usable? At most organizations, valuable data still exists across disconnected silos, in a variety of formats, and much of this data is unstructured. This explains why, on an average, companies use only a fraction of the data they collect and store. This problem is only going to get bigger, considering what the experts are saying; by 2020 there will be 4300% increase in annual data production (IDC/EMC Digital Study) by organizations. The volume, diversity and complexity of data will only increase every year.

Organizations must understand that data does not equal insights. Even with all the analytics tools available in the market, deriving actionable insights from data takes time and effort, and most companies struggle with it. Lack of insights is rampant and evident, as proved by several market studies. To give you one example - the 2016 Adobe study on the 1000s of US digital marketers, revealed that an astounding 77% have difficulty proving campaign effectiveness, 75% have difficulty demonstrating ROI, and almost 8 out of 10 have difficulty simply “understanding campaign effectiveness.”

Widening gap between data collection, insights and action

Data that exists across disconnected silos is dormant or as good as dead since it offers no insights. To fully leverage the true value of data, businesses need to democratize data across the enterprise. They need to provide real-time access to comprehensive data insights to all teams across the organization. While traditional BI and analytic tools may provide the relevant information, they are limited by functional silos and their lack of ability to provide context to information.

What organizations need are tools with cognitive capabilities that can connect their employees with the right information, insights and actionable solutions. They need tools that can not only answer the ‘whats’ and ‘hows’, but also address the ‘whys’ – tools that can bring data to life. AI powered by cognitive intelligence will help businesses anticipate and identify defects in the product, improve product design, resource management and services, identify competitors, reduce churn, and optimize marketing spend.

For example, consumer tech product companies can anticipate and preempt any design flaws, product recalls and negative publicity by analyzing customer feedback and incident reports for early identification and resolution of issues.  Pharma and health-care industries can better identify new potential drug candidates and develop them into effective, approved and reimbursed medicines more quickly. Linking cognitive capabilities with richer and more disparate sources of information on their customers with help retailers achieve optimal inventory levels while avoiding costly out-of-stock conditions. 

Businesses are in need of solutions that can help them measure what matters, ask what needs to be asked; and free themselves from the shackles of enormous volumes of data and organizational silos.  Leveraging AI, machine learning, and natural language processing they want to use the power of embedded intelligence from across all data sources to take strategic decisions in real-time.- basically have a virtual  analyst with the capacity of several data scientists and the contextual insight of a business user to understand , analyse and present the most meaningful information to users in real time.

Satykam Mohanty

Founder and Chief Light Blub, Lymbyc

Conceptualized with a vision to empower business leaders at the point of decision making – Lymbyc is designed to fulfill the role of an analyst for business leaders. . It is quick and a cost-effective product with a capacity of several data scientists, responding to most complicated and time-consuming business queries particularly of consumer and health care sector.

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Blog Author: 
Satyakam Mohanty
Machine Learning & AI
Machine Learning & AI


Lymbyc, being the world's first virtual analyst has proven its mettle in the industry . Be it the "Most innovative Data science Product" by Aegis or "the top 10 emerging Analytics startups in India to watch out for in 2018" by Analytics India Magazine, Lymbyc is making heads turns and making headlines


Lymbyc, a leading edge innovator in AI and Machine Learning takes inspiration from the “Limbic” brain — the part that stores, dissects, rationalizes and generates memories and actions. That’s exactly what we do — giving business users the power of a virtual analyst that is intuitive, actionable and context driven to answer all their business queries


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