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Service [TAC] oriented Knowledge Engineering – Framework & Process

January 27, 2012 Leave a comment

Knowledge Engineering for Services [TAC]

All the data that is being gathered over every possible transactions reside in the databases. These transactional data amassed over time has the potential to yield a lot of intelligence and provide key insight into the major four areas of Business.  [a]-Product Analytics, [b]-Customer Analytics, [c]-Process Analytics.

Technology manufacturers need to evolve their strategy every time and stay competitive, they desperately need to understand the perspectives from a VOC – Voice of Customer.

TAC Centric Knowledge Engineering will make use of a varied a host of ‘technology and product BI companies’ and ‘BI as a service companies’.
There are three types of BI as a service offerings:
1. Generic BI platform capabilities (for example, online analytical processing [OLAP], reporting, analysis, data mining)
2. Application-specific offerings (for example, Web analytics, fraud analysis, risk analysis, benchmark analysis)
3. Combination of both application BI services & product specific analytics with a expert recommendations and consulting  [KE].

Knowledge Engineering will supply the all essential human expertise to build the knowledge analytics architecture based on the business case / SWOT and  conclude recommendations.

From a Services Industry perspective; I recommend pursuits be set over three specific areas. 1. Customer Analytics, 2. Product Analytics, 3.Process Analytics. This can help accelerate service excellence and optimize operations.

Product Analytics: Solutions that allow them to analyze across a series of product performance dimensions ‘end to end’ in the product’s lifecycle. Analytics over Product reliability, third party environments, bug impacts, causes to resolutions, escalations and factors, time to resolve, and maintainability requirements, while all the time focusing on lowering support lifecycle. Product analytics will bend the traditional value chain into a “feedback loop”; evolving into product intelligence.

Customer Analytics: Customer intelligence visibility, customer satisfaction RCA & recommendations, customers and prospects, customers’ likes and dislikes, cases history and trend, as well as future wants and needs, by consolidating customer information currently in multiple silos and mining information.

Process Analytics: Business Process Analytics provides drill-down and slice and dice capabilities from various perspectives for extensive process analysis and reporting. Derivations of general and specialist advisory based on analytics rendered over  historic and real-time data.

Knowledge Engineering Framework:

JesuValiant_KnowledgeEngineering_Framework

JesuValiant_KnowledgeEngineeringFramework

Knowledge Engineering – What it takes?
•    Enumerate, analyze, catalog, and suggest improvements to the core and support processes of the business unit.
•    Ability to assimilate and correlate disconnected and and articulate their collective relevance.
•    The ability to visualize and create high-level models to extend and mature the business architecture.
•    Technical knowledge over technologies covered in the product stack.
•    Importing, cleaning, transforming, validating or modeling data with the purpose of understanding or making conclusions from the data for decision making purposes.
•    Presenting data in charts, graphs, tables, designing and developing relational databases for collecting data.
•    Information management, relational database design and development, business intelligence, data mining or statistics.
•    Utilizes data analysis techniques or best practices and draw inferences and present comprehensive analysis.
•    Critically evaluate information gathered from multiple sources, reconcile conflicts, Decompose high-level information into details, abstract up from low-level information to a general understanding.
•    Prepare reports of findings, illustrating data graphically and translating complex findings into written text.

Do you have a pain point today and are you a technology product manufacturer? Reach out to me @ jesu.valiant@csscorp.com.

Thanks for reading.

Copyrights – Jesu Valiant 2012

*Logos in the Framework diagram belong to the respective owners. Here its to highlight and recommend adoption of these systems and tools to perform Knowledge Engineering.

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Developing Social Capital – An Approach

March 15, 2011 1 comment

Its all about building a soul into the spirit of the community, Social networks have been in existence for centuries; yes… its certainly true. Human communities settled and formed communities on river banks for thousands of years and were united as a social group with goals structured around food & hunting, shelter, security, mutual support, farming, etc., these communities grew big and formed distinct civilizations. In today’s world we try doing the same over a virtual platform, things can be so basic and simple provided right insight and approach is formulated.

The key in building social communities lies in the understanding the basic constituents. Every community and social grouping has fundamental units of functions [SFU] – Social fundamental unit,  addressing and enabling these units to function is key to the success of building community and social groups. Like in the real time communities there are some fundamentals that needs to be imbibed while forming communities.

1. Community Bonds among Individual elements.
Bonding within a community is very important, to create the bonding there needs to be goals defined and all in the community inadvertently pursue these set of goals. Its like floating a forum for users of one product series who want to achieve better product adoption and usage across as a group commune together. Some publish articles, some post questions, some answer, some pool in external references, etc., This is the key , build tools and work-flows around these goals to ensure that there is always an opportunity to debate, share, compliment, report, reference, etc., These help building relationships and bonding within a group. There is always Cohesion and Inclusion and no Confrontation or retributions.

2. Community Bonds between Groups of Elements.
Having these all out functional groups there is the next level of collaboration in the form of inter group bonding; in a community business support environment users will need each other strengths to collaborate for a solution. An example is a product buyer comes with an issue on the product compatibility with another brand over certain feature sets; he posts a question over the forum, over FB wall and possibly tweet too. Here there is an opportunity for this reported cause to get viral and many to see it for the good and for bad. There needs to be a response and this can be addressed by the Individual elements or Other Groups of Elements. There can be a technical support team that can respond; if an user reports an issue with much complexity like an interoperability then is not in the control of the support team, they can very well invoke the design & engineering team to advice and action. This is community supporting community, build bonds between groups of elements; this is also called as community support.

3. Platform as a Component.
With the complexities of real life engagements moving into a social application based interaction and responses, there needs to be a strong platform and governance model that helps in bridging the gaps between monitoring, responding, evaluating, enabling, analyzing etc., from a product manufacturer perspective. It also needs to take care of applying work-flows that will support knowledge sharing, collaboration, ideation and support, best practice mapping, etc., There are many a systems at play in the market there are a few that have listed below. These platforms offer the facility and functionalities to support most if not all of the above.

Social capital means the intensity, virality, capability of a Social community. The more the cohesive strength and collaborative spirit the higher the capital. Better Social capital translates to the following benefits for a Product & Technology Manufacturer.

1. Reduces transaction costs
2. Provides vivid and direct avenues for revenues
3. Provides a competitive edge
4. Social Capital with the best practices provides market differentiation
5. Social Capital with the right systems enable conducive collaboration environment
6. Helps build openness and transparency
7. Community Involvement Builds Social Capital
8. Promotes Accountability
9. Product and Logo Loyalty
10. Community Satisfaction & Delight
11. Direct channel with customers

Jesu Valiant – 2011

Social Media Analytics – Top Applications

March 1, 2011 3 comments

Every organization and corporate house is participating in the Social Media; its come to a point where PR’s focus now are into Social Media. Social media opens a direct channel with the customers with their respective direct identities and hence more ownership and interactions and suddenly a new transaction channel with direct implications. Value of Social media channels now has made the most stiff-necked CEO’s bend down and deploy Social media strategists, this channel has truly emerged and maturing quite fast.

With the Social media becoming a business accelerator and Gartner identifying that Social Communications and Collaboration & Social Analytics as the Top 10 strategic technologies for 2011; the game in this space is heated and the market is lapping up every possible skill to make the most of this new front. With all the transactions and the buzz around the social web that is happening there is a an immediate need to monitor, record, analyze, model, gather intel over these transactions. The market now has hundreds of Social Media analysis companies rendering services and providing products, of these products there are a host of features on offing, only few however provide the comprehensive solutions.

At the first look every product looks similar and there is not much difference; when drilled down over product usage, product adoption, flexibility, rule sets, parameters, people & pages analysis, integrations, key social web performance indicators; there are only a few that surface to meet the demands. With not in any particular order the following are the ‘surfaced’ and recommended products.

Top Social Media Analytics Products:
Sysomos Heartbeat 2.0
Sysomos MAP
Edge3
Kontagent
Radian6 Dashboard
Radian6 Engagement Console
Alterian SM2
Attentio
DNA13
Fangle
Research.ly
Beevolve
Social Mention
CollectiveIntellect
ScoutLab
BrandsEye

Most Wanted Social Media Feature Lists:
Timeline Cohort Analysis
Funnel Analysis
Viral Optimizer & Analysis
Revenue Tracking
Traffic Source Optimizer & Analysis
Retention Workflows
Competitive Analysis
Geographic and Demographic Data
Key Influencer Identification
Key User / App / Page Engagement
Comprehensive and Spam-Free Database
Real-time feeds & captures of blogs, message boards and other types of unstructured data
Real-time analysis of blogs, message boards and other types of unstructured data
Comprehensive and constant web coverage
Social Media Metrics
Data Filtering and Segmentation
Workflow Management
Social CRM and Web Analytics Integration
Automated Sentiment Analysis
Historical Data
Listening Grid
Real-Time Coordination
Case Based Reporting
Complete Activity & Conversation History
Social Profiles
Integration and Interops Capability
Efficiency and Productivity

Jesu Valiant – 2011

Knowledge Engineering & Business Intelligence

October 30, 2010 Leave a comment

We say “Knowledge Engineering”; we then speak about “Business Intelligence”. Here are the Megladons, Great Whites and what’s in between!

Knowledge Engineering (KE) is an engineering discipline that involves integrating human knowledge into systems, frameworks, methods and processes in order to solve complex problems normally requiring a high level of human expertise. Business intelligence (BI) refers to computer-based techniques used in spotting, digging-out, and analyzing business data. BI technologies provide historical, current, and predictive views of business operations.

With complex data sets businesses keep producing over transactions of varied kind and their kindred; BI at the first layer and KE at the next layer provide complex intelligence, decision support from the data sets. Knowledge Engineering is the collective stack of ‘Expertise + BI + Research’ which results in recommendations and solutions for evolving businesses from a 360° Perspective.
There is this deep need to research and develop process and systems to extract data from varied t’eco-systems, store, tune for building dominoes, and present data structures for expert human intervention from a SME perspective. EHI enables to connect and overlay these mined>domino-ed data sets with a solution stack driving complex decision support, savior strategies, threat negations, process frameworks that redefines and edifies. BI technically has a lot to contribute especially through its native adoption of Warehousing and Analytics systems and processes. This warehousing and analytics does augment research efforts for the EHI tasks; “What is” is what is needed in varies perspectives in comprehending the data stack and this the prelude to KE. How the data stack is structured involves EHI to identify the sources and to build relativity.

There is no dearth for systems and process available in the market today; from solutions and services ‘dime-a-dozen’ to what the market leaders have in offering the lack-the gap-the missing link has always been EHI processes with its diagnostic, anatomic, molecular specifics to structure business evolutions. Be it a profit Kalashnikov of a corporation or a loss attracting black hole enterprise, investments over BI cannot be complete if you are not adopting Knowledge Engineering practices. The need… well we have them already and one tailored KE framework will certainly nuke rigidity and blow away the comprehension veils.

– Jesu Valiant

Business Intelligence

August 7, 2009 1 comment

Business intelligence is the knowledge, skills, capacities, understanding, practices and relative technologies, applications that are used to understand and interpret markets, their behavior, business dynamics and context. Storing, analyzing, and providing access to this data helps enterprise users make better business decisions. This helps companies to make faster, smarter decisions, as well as increase revenue, build customer loyalty, streamline operations, improve risk management and even enable previously impossible business processes.

BI System

A BI System provides facilities to capture data and present it for analysis; data is made available in ‘Historical’, ‘Live’ and ‘Predictive’ forms. We can integrate the wholesome business performance management aspects involving Strategy, Balance Scorecard, Strategy Translation/Cascading them into operations and business intelligence culminating into one integrated business information system which can be used as a Decision Support System.

BI Growing in Importance

The amount of corporate data is doubling every 2-3 years
Barriers of entry (costs/technology) are being removed
Continued pressure on businesses to find efficiencies and new market opportunities, client expectations
More disparate data sources than ever before

BI Usage Statistics – Source: Forrester Research Inc., 2006 survey

BI Use by Small and Mid Market Companies
48% –  Using
10% –  Planning to implement solution in 2007.
40% –  Not using
Don’t know 2%

Jesu Valiant

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