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Analytics and Effective decision making

Per Gartner's prediction, the top 6 BI trends for 2012 are BI in Cloud, Mobile BI, Analytics, In-memory analytics, Agile approach to BI and Big Data. Of these analytics is the next progression of modern BI which uses algorithms to search for patterns and explanations, looks at historical data to predict future activity for better business decision making. A recent MIT Sloan Management report found that organizations using analytics are more than twice as likely to substantially outperform their competitive peers. Analytics will help companies differentiate themselves, it will allow them to run more efficiently, make the most of their customers and increase profitability. Analytics provides organizations with actionable intelligence.

 

Having said these, what are the keys factors for right analysis and effective decision?

1.     Tool?: Not always.  Using the data right is the key. Tools are required if the data volume is huge and need processing power for real time analysis. Analytics happens  in our day today life OR in small business also. For these there are no tools required, but still insights are derived based on the historic data and decoded accordingly. For eg, a small restaurant owner knows that he need to plan for a specific  menu item with right quantity for a certain age groups during a specific day of a week. He gets these insights through past experience and trend, with a small set of data and not leveraging any tools. However, if the restaurant is a large chain, then one need tool to gather the data from various sources/geographies, analyze and process to provide a right insights. In this case data volume and processing speed is the key for effective analytics an so need tools.

2.     Right data at right time? : YES. Give the people (analysts/business) what they want and when they want, for them to plan effectively. The right data at the right time delivers intelligent decision. For eg, due to bad weather many flights will get delayed at the airport resulting in more people stranded at the airport, which in-turn creates more demand for coffee at the airport stalls. So getting to know about the bad weather upfront would enable business to plan better in ensuring enough supply of coffee type during that period. 

3.     Good Data Quality / Inference ?: YES. Identifying good and credence data is a key for an effective decision, as bad data may give extremely opposite outcome. For eg, before finalizing a design, its a good idea to to collect feedbacks (not obvious about the design and with all confidentialty maintained) from some social medias like FB/twitter and take action / rework. However, identifying the right feedback/comment based on the person who provided the same, his/her profile/demo etc.. is the key. 

What is your thought about the "lightning connector" in iphone5? 

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