Wednesday, March 04, 2015

Data-Analytic Thinking for Leadership

Today it has become important for all leaders to understand data science and impacts of data science - even if they would not develop data analytics application. Leaders need to think and make decisions. So data-analytic thinking helps to take better decisions. Even politicians, CEOs and NGOs are using data analytics in several ways to make decisions. The potential for success is greatly enhanced with data driven decision making Vs instincts. Even instincts can be validated with data.

Today, there is plethora of data sources and data is everywhere, information is now widely available on web pages, news channels, social media, events data and internal data in CRM, ERP,  Emails, etc. All this broad sources of data has led to increasing interest in methods for extracting useful information and knowledge from data.

Virtually every aspect of business & life is now open to data collection: Operations, Manufacturing, stock market news/trends, supply-chain activities, social media, new channels, sensor data, mobile phones, traditional IT systems, and so on.

Getting all the required data to access a problem needs careful planning, systematic data collection and analysis - and is called as Data Science.

Ubiquity of Big Data Opportunities

Data is everywhere and it comes from variety of sources and different speeds and sizes. Managers, leaders in almost every industry are focused on exploiting data for competitive advantage. Historically, this was done by a dedicated team of Business Analysts - who would use teams of statistics, data modeling tools to explore & analyze data manually. But with the digital world, the volume & variety of data have far outstripped the ability of manual analysis.

At the same time, computers have become more powerful & cheaper. Tools have been developed to collect data, analyze data to enable broader and deeper analyses than previously possible. The convergence of the ability to compute & big data has let to widespread use of data science & data mining techniques.

Probably the most well known applications of data-mining techniques are in marketing for tasks such as targeted marketing in online advertising, and recommendations for cross-selling in online retail.

Big data Analytics is also used for innovation and scientific discovery. The ability to rapidly analyze thousands of genomes is leading to new science of pro-biotics, where bacteria is being used to cure diseases!

Within an organization, virtually every department can use big data analytics: Analyze customer behavior, predict employee attrition, minimize customer churn, predict future interest rates, predict future supply-chain demands, High frequency algorithmic trading etc.

In short, companies are using data analytics as a competitive differentiator. As a result, a new business function is being formed within all companies: Data Analytics Group.

The primary goal of data analytics group is to help leaders view business problems from a data perspective and bring in data-analytic thinking as an input to decision making process - which is in addition to: intuition, creativity, common sense, and domain knowledge.

A successful leader will use data analytic thinking in decision making tool kit. 

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