Thursday, August 29, 2013

What will you say about Mobile Enterprise in 10 seconds !

In the recently concluded #IBM Redbooks Social Media Residency for Mobile Enterprise thought leadership, we had great fun taking video shoot on the idea exchange on #MobileFirst. When I was invite to speak a few words, thoughts from all corner gazed at me. I strongly believe mobile is the best social computing platform which can be the intelligent interface between simple humans and complex machines. Thus humans, mobiles and complex machines like #IBM Watson together can build a smarter planet. More importantly, we should know why are we building it. It is for a connected living in a network society.

Disclaimer: The Opinions are my own.

Digital Front Office: The Enterprise Social Bus for Digital Economy !

Watch your thoughts; they become words.
Watch your words; they become actions.
Watch your actions; they become habits
Watch your habits; they become character.
Watch your character; it becomes your destiny.’
(From the famous quote of Lao-Tze)

If we have a time machine that can watch every customer 24× 7 like the above words, it will be one of the most resourceful devices for the social business and digital consumer! How does Customer Experience Lab realize Digital Front Office innovations? What is digital front office for you: A social business hub or customer experience laboratory? … Either ways, you are right! Digital front office is a multi dimensional platform for your business needs. 

We strive to analyze, predict, and transform customer experience through a deeper understanding of customer’s thoughts, words and action. ‘Digital front office’ is the convergence of all the techno social efforts in this perspective. The synergy of social, mobile, cloud and big data innovations is realizing this perennial dream of world markets and business leaders a real social business story. The ubiquitous smart phones, spontaneity of analytics, pervasive social media and the cost effective cloud solutions have made today’s consumer truly digital. Thus the new age digital consumer expects a digital front office in the transactions and experiences. 

Realizing a digital front office requires the right mix of business and technical innovations to the life of customer. At the IBM Customer Experience lab, researches and business innovators work in tandem to envision the world class customer experiences. Located at the T.J. Watson Research Center, with additional virtual collaborators around the world, the IBM Customer Experience Lab is a partnership between IBM Research and IBM Global Business Services. 

When digital front office is a significant business value accelerator (BVA) and primary innovation hub for better digital consumer experience, at the same time it is a virtual window to the world of social business. Social Business thrives on the mobilization of social capital and new social identities. Thus a digital front office can watch the real time trends in social fragments and social identities through various modes of analytics. Innovations like ‘transformative analytics’ are progressing in this trajectory. From media and entertainment industry to micro finance institutions, we can see vivid and variant models of social business. 

A digital front office strategy with an evolutionary and adaptive approach to customer experience analytics(CEA) can realize social business platforms with global market reach and solid growth potentials. This is where IBM Customer Experience Lab meets next generation market dynamics.

Saturday, August 3, 2013

Transparency and Measurability :: The twin towers of Digital Economy

People and Technology: How they enrich a social network?
#Facebook, as the name goes, became this ubiquitous a social media only with a human face and a treasure chest of information. These two constitute the twin towers to build a powerful social media. These two ends should enrich each other in a social media platform. More people means more information, more information means more attractive to people. 

Without people, read & write web ( web 2.0 paradigm ) will just be a pipe dream. Social Media as a source of data opens up anew opportunities for collaboration, new insights, further more modes of communication and so on.

Yet making relevant decisions from social media remains a daunting task for many information management systems. We evolve complex algorithms and decision systems for this. We traverse the path of natural language and cognitive networks for this aim. Why?

The data formats and the metadata about people varies significantly across social media. This diversity often inspires the evolution of various ecosystems around each social networks. When #Pinterest gains momentum, the network society around it various substantially with #Twitter communes or #Google Plus hangouts.

Social Media Observatory: A step towards Digital Front Office
Beyond this multiplicity of modes of communication, a unified strategy for web intelligence from social media has a lot of challenges even today. The data exchange across social media need to be more transparent and measurable for this. Social Media Observatory concept is a landmark concept in this direction. An observatory is a platform which can access and plot the patterns and constellation of ideas and aspirations in social media.

This transformation is an imperative in making social media a viable channel for Smarter commerce, further leading to a comprehensive digital front office. This envisions the need for a front office digitization  (#FOD) strategy incorporating social media evolution as well. That will take us near the goal for a fully digitized globally integrated enterprise. A Digital enterprise cannot exist without a digitally segmented market and a digitized channel for network society. And that means the synergy of social media, big data, cloud and mobile platforms as a prelude and a stage setter. 

Friday, August 2, 2013

Big Data is not born in a Day !

Adieu to an Algorithmic Age::

Intelligence every where! Sensors every where! Data seems to be liberated from all the corners of universe. One may wonder, where was all these exabytes and petabytes of data hidden. Or is this internet universe that spawn monsters of data from nowhere? 

Absolutely not. Big Data is not born in a day ! This rich collection of data that we see accumulating in minutest measures of seconds was nothing but encapsulated in the abstractions of an algorithmic age. 

A Critique of Classical Computational Models:
In the scientific computing community, there is an emerging realization that we are moving ahead of an algorithmic age to an age of intelligence and adaptation. We emulate more and more the natural cognition. Data structures have grown beyond the linkages and contextual affinities of algorithms. We may look back for a while. What were we doing with information spaces all these while? Data structures in various information spaces where conditioned by a logic that could approximate a mathematical behavior.

In a way , Boolean logic is largely a mathematical behavior or an operational approximation for the convenience of calculation. Mathematical behavior can be modeled by approximations. Thus we created concept machines based on Boolean logic.Mathematical behavior or for that matter any behavioral logic is just the reflection of a larger set of conditions. If we look from a higher abstraction, we were trying to fix the multidimensional data structures into a partial projection of Boolean logic. Thus my argument is that Boolean logic was insufficient to capture the computational complexities of data streams.

Data Structures and Dialectical Logic
Then what is inherent in data structures: in reality, do they exist at all? I am not an exponent enough to lay down my arguments in mathematical formats. However, I may try in terms of dialectical logic here. Data as such is a representation of a physical entity or a cognitive process. It may have its own primary structure or it may be derived or dependent on a much more relatively invariant structure.  This integral between representational mathematical format ( symbol ) and the corresponding primary or secondary structure constitute a data structure. This visualization is in terms of dialectical logic. 

In the measures of physics, we may use the metrics of space time in many models. But when the data streams are dependent or realizations of energy structures the scenario becomes more interesting. The high energy physics and the future smart sensors may become the sources of such #energy structures. As the data explosions gains momentum, we may need inner eyes to capture the innate structures behind the 'Big Data' ecosystem.