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Disrupting the Intelligence World

The onslaught of never-ending data, the proliferation of incubation test beds, the rise of internet business disruption challenges overnight – this all has a dramatic effect on the intelligence professional’s ability to not only acquire the right data, but to be able to synthesize the analytics in order to drive it to the right conclusions, all while navigating through a non-stop, fluid information environment. Sequential processing of analytics is a thing of the past. The business climate is moving so fast that organizations need to incorporate intelligence and analytics as an integral part of their organizations.

Disruption Challenges

Disruption challengesBut for the intelligence to be truly applied universally, intelligence communities need the ability to generate executable insights at a speed which is higher than that of your competitors, and to act upon those insights at the correct moment. This requires mastering the challenge of understanding the technology curve, gathering insights and embracing business disruption challenges while identifying new opportunities for growth. Although this is something that many CEO’s do not feel comfortable with – having to think outside their business core competencies and take strategic action that may be far outside the revenue generating functions of the company, the huge risk of “disruption impact avoidance”, doing nothing, hoping that it won’t affect their company, is way too big in today’s digitized society!

The questions you have to ask:

What is the potential for this new idea?

What information do I need to add this to our business strategy?

How fast can I monetize the opportunity?

So, how does an intelligence organization capitalize on this information-rich digitized society to provide the content so organizations can be best equipped to act?

Well, they need to acquire, process and analyze data on a virtual real-time basis – realistic? Not entirely, but there are ways to help this process. Automating the gathering and processing of data through large central repositories (e.g. knowledge management systems), together with the application of machine learning to “predict” the business behavior and automate much of the analytics process, will allow organizations to provide actionable insight on a faster basis. And this is where they’ll find the biggest return on investment in today’s digitized society.

 

This was part two in our new blog series, based on the article “Machine Learning Implications for Intelligence and Insights”, written by Jesper Martell, Comintelli, and Paul Santilli, Hewlett Packard Enterprise.

Download a free copy of the article “Machine Learning Implications for Intelligence and Insight”!

Download a free copy of the article “Machine Learning Implications for Intelligence and Insight”

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