9 Cognitive Patterns Delivering Shareholder Value

POSTED IN: Building Bridges from R to IBM Watson

As I work on more integrations of Watson Developer Cloud services - I've seen a few "Cognitive Patterns" developing on how technology pieces are composed to deliver Shareholder Value.  This is less about the 'point and shoot' APIs and more top level - describing how problems can be solved (KPIs) or money made  (ROI) by weaving the tools together.

List is not comprehensive, and there is certainly overlap - but I hope these patterns are interesting / useful as you consider your project and down-select potential candidates!



Capacity Building

Fortune 500 seeking to create and cultivate skills within organization. Multiple benefits: strategic: understand opportunities from cognitive in future.  Innovate internally.  Evaluate projects and proposals. Knowledge backbones.


Cracking Carbon

Signal Extraction from Unstructured Data; Dark Data; Data Exhaust; Information contains signals that once analyzed, produce actionable intelligence.  Organizations engaging or building tools to crack the carbon and release signal.


Data Discovery

With new data, new tools and new signal - a new generation of tools for data discovery is emerging.  Visualizations that move beyond eye candy to actionable intelligence, and are more accessible and intuitive for more stakeholders in the org.


Predictive & ML

Dozens of great tool suites exist today to leverage machine learning and predictive models to understand what features in high dimensional data are meaningful to outcomes.  No PHD needed. Data science democratized!  Very clear ROI and KPIs


Segmentation 2.0

New methods of understanding how to segment customers – based on traditional information (demo, geo) and new information (psychometric, tone, ML features) results in new, dynamic and more powerful ways to think about and engage with customers.



As segmentation methods evolve, and leverage Personality Insights and other methods – automated cognitive systems have ability to deliver best fit – automatically, at scale.



Leveraging automation to develop automated bots that don’t suck.   Conversational applications that actually work.   Deliver faster and better automated outcomes.  Systems that self monitor and adapt to different customers and different flows.


Verbal Interfaces

Just ask.   Just speak the thing you want to know, or want to have happen –and have the “tell me” and “help me” needs satisfied.  Verbal interfaces to BI systems, SQL databases, Augmented Reality, personal bots & cognitive wingman.  



Cognitive sensemaking systems can see, hear, and begin to engage in “Sensemaking” – towards understanding.  Can augment Business Intelligence ERP, call centers, operations groups, robotics, automotive and IOT, etc..


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About the Author

Ryan Anderson

Ryan Anderson

Hi! I like to play with data, analytics and hack around with robots and gadgets in my garage. Lately I've been learning about machine learning.

About this blog

This is an informal blog that explores tools, code and tricks that group members have developed to engage IBM Watson cognitive computing services - from the R Programming Language. Packages include RCURL to access Watson APIs - for services that include Natural Language Classifier and Speech to Text. THIS IS MY PERSONAL BLOG - it does not represent the views of my employer. Code is presented as 'use at your own risk' (it has lots of bugs)

Created: September 13, 2015


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