Blue Interlinks Framework: BIF
Analytics is the application of applied math, business knowledge and technology in an integrated manner, on raw data, in order to aid efficient and effective decision making
Analytics is more than a purely statistical, technical or processing exercise; In KI we believe that analytics is a tool for decision sciences and should help answer the following questions:
We strongly believe that companies need to focus on all of the above questions in varying degrees at the same time, and these activities together constitute the KI's BIF framework.
Our belief is that analytics does not end with a single solution. It is a journey and not a destination by itself. With implementation of every analytical solution, there is new learning and hypotheses to be tested and hence we need to use analytics as an ongoing process and not merely as a software application. A long term engagement thus helps develop a sustainable model for continued improvement
Given the dynamic nature of business, analytics cannot be curtailed within a set process. Analytical processes and solutions need to be flexible and should continually evolve in order to accommodate changing business needs and hence having an analytics eco-system to support such dynamism is very important
Analytics is more than a purely statistical, technical or processing exercise; In KI we believe that analytics is a tool for decision sciences and should help answer the following questions:
| What happened or is happening in the business ? (Business analytics - B) |
| Why did it happen ? (Inquisitive analytics - I) |
| What is likely to happen based on historical information and what action to be taken ? (Future analytics - F) |
We strongly believe that companies need to focus on all of the above questions in varying degrees at the same time, and these activities together constitute the KI's BIF framework.
Our belief is that analytics does not end with a single solution. It is a journey and not a destination by itself. With implementation of every analytical solution, there is new learning and hypotheses to be tested and hence we need to use analytics as an ongoing process and not merely as a software application. A long term engagement thus helps develop a sustainable model for continued improvement
Given the dynamic nature of business, analytics cannot be curtailed within a set process. Analytical processes and solutions need to be flexible and should continually evolve in order to accommodate changing business needs and hence having an analytics eco-system to support such dynamism is very important