Intelligence Center for an Enterprise in the Digital Era

Date:   Monday , January 02, 2017

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.

Governance: While understanding the performance capability and ecosystem equations the tolerance to manage the risk exposure, appetite to take risk and ability to stretch limits need to be highly governed with different lines of defense mechanisms. Especially, when it comes to governing the point of no return, the balanced Human and Artificial Intelligence with Agility plays the lead role. Governance should not be set to as a hurdle in actions, rather it should be set as a protective gear in disruptive innovation. Digitization of governance across people, process, technology and data brings the necessary agility in responding to the market than becoming a usual bottleneck.

As per John Nash\'s game theory, when all the players have same objective in the game only then the outcome can be maximized. When all these four things have been directed towards the same objective of business excellence, then predictability of outcome can be certain. E.g. with a centralized command center global power generation operations can be monitored and predictive maintenance can improve generator availability and reduce loss, demand driven supply chain can be managed by CPG companies through a single global operations center. In the absence of same objective, Governance can block the agility and human intelligence can choose to override the artificial intelligence most of the time. And the results will obviously be the ineffective enterprise.

With the backbone of Intelligence Center, enterprises can institutionalize innovation by correlating Performance, Relationship and Risk to achieve the state of Universal Intelligence, which is known as \"Turiya\" in the Indian Philosophy.