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Intelligence Center for an Enterprise in the Digital Era

Kamlesh Mhashilkar
Head ABIM (Analytics, Big Data and Information Management) Delivery - Digital Enterprise-Tata Consultancy Services
Monday, January 2, 2017
Kamlesh Mhashilkar
The perimeter of human cognition evolves from self to community to universe over a period. The figure shows how an enterprise exists within the universe. The ecosystem boundary forms the frame of reference for the enterprise to reside. The more the influence of the enterprise on the ecosystem, the more is its area of control. The re-imagination of the services in Digital Consumer Economy opens a huge risk (as well as huge opportunities) for the traditional business players. There are cases of business espionage by new players e.g. banks losing business to hi-tech mobile companies or mobile service providers. On the other hand the traditional players are also entering new business models, international markets, M&A and forming alliances. The changes are so rapid and disruptive in nature that traditional analytical methods and processes cannot cope. PESTLE changes also influence the ecosystem boundary where understanding the unknown unknowns becomes essential. Intelligence Agencies (e.g. DoD, CIA) have been handling these kind of scenarios for a long time. These agencies are the Intelligence Center for the Government and have been solving complex problems and giving stability to the countries as well as the world. Only in recent years, their ideas have been applied in the commercial environment as well. An Intelligence Center can facilitate the strategic, tactical as well as operational decision making in an enterprise for sustaining and extending the business in the digital era.

There are four Key Focus Areas which form the foundation of the Intelligence Center.

�Agile Culture: Instead of always following a waterfall model from problem definition to solution delivery, how agility can be induced in the culture for outcome driven delivery. Prioritization of requirements, synchronized vocabulary, adaptive processes, fail-fast approach and highly motivated and co-active teams facilitate the agile culture, which is the foundation for the disruptive innovation on continuous basis. Unlike Waterfall, the delivery cycles are shorter. Since there is no fear of failure in long term, the team becomes more confident to take calculated risks. But not everything can be agile by process e.g. the efficiency of technology or data migration program delivery is much higher using Factory than Agile Methodology. That means multiple execution models (Waterfall, Factory, Agile, Self Service and Service as an Intelligent Software) need to exist simultaneously to cater to the dynamic requirements. It is like multi-modal culture with right balance.

�Human Intelligence and Competence: The enormous flow of information, limited time and numerous decisions to be taken in the given time. This scenario is becoming more and more difficult in the digital era. Prioritizing the areas of decisions and building "unconscious competence" (like refluxes of master black belt in karate) in decision making is important. This sometimes supersedes the machines as well. E.g. experts give a gut-feel based but precise Box Office prediction of a movie by analyzing story, cast, director. Various new self-service techniques such as Visual Analytics make it easier for humans to look at voluminous data in easy and intuitive way. It improves productivity as well. These days, psychologists are bringing disruption in the analytics portfolio. Such new type of (relevant) talent needs to be accepted and evaluated for the out of box thinking.

�Artificial Intelligence: Investment in intelligent machines and systems is necessary to relieve humans from mundane jobs or synthesizing data, learning and acting in a short span so that humans do not need to do it manually. Making these systems more intelligent is the natural progression towards self-optimizing enterprise. Artificial Intelligence spans across the branches of Reasoning, Knowledge representation, Automated planning & forecasting, Machine Learning, Natural Language Processing (NLP in communication) and Perception (speech, facial, object recognition). There are long term goals of Social Intelligence, Creativity (Practical and Theoretical i.e. Psychological + Philosophical) and General Intelligence (self-awareness), but those will take a few years to come to commercial markets.


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