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CXO INSIGHT 
Leo Barella 
By Leo Barella, VP, CTO- IT Strategic Services Team, Excellus BCBS 
Rochester, NY based Excellus BCBS is a nonprofit independent licensee of the BlueCross BlueShield Association that 
provides access to high-quality, affordable health coverage. 
The state of Hype vs reality in Big Data 
Undoubtedly, there is a lot of hype around 
Big Data. But overall, the substance 
outweighs the hype. Having said that, 
there is still a fair amount of confusion, 
for instance on how to get value from it, 
and how to create a Big Data strategy. 
On the technology level, there is a 
lot of fragmentation, and a lot of very 
niche technologies, that may offer 
specific functionality, but do not excel 
in integration. Big Data technologies, 
such as Hadoop, have become accepted 
pretty fast. 
My general advice is to go ahead, and 
invest in Big Data in your information 
infrastructure, but accept there is still 
some risk in technologies that are not 
mature enough. 
Factors playing a critical role in the 
success of Big Data projects 
Consumer–Personal Analytics: 
Analytical mobile apps, wearable 
technology, personal virtual assistants 
& smart advisors to offer suggestions, 
make recommendations, improve how 
tasks are handled, etc. 
Market–Sentiment Analysis: Who 
are the influencers in the market on 
social media, how are the brands being 
discussed, what business trends need 
to be followed that affect business 
performance? 
Partners/Suppliers/Distributors: 
Through sensor-technology, creating 
an (even) more efficient supply and 
demand chain, for flow performance, 
energy consumption optimization and 
predictive asset maintenance. 
Partners/Suppliers/Distributors: 
More real-time, behaviour-based data 
collection and prescriptive analytics for 
benchmarking purposes. 
Shareholder-Infonomics: Showing 
how the information base, sharing 
information with all stakeholders 
and its analytical activities can be 
economically valued, and contribute to 
shareholder value. 
Selection criteria to evaluate Big Data 
outsourcing vendors 
I would approach the question not from 
the infrastructure and technology point 
of view, but from a skills and capability 
point of view. 
Doing Big Data in the cloud is a 
commonly accepted approach; you 
would not be doing something “weird”. 
Increasingly, it is also the option that 
vendors of software and services offer. 
The one reason to do it on-premises 
would be the sensitivity of the data 
being in the cloud. 
Moving from cloud to outsourcing 
is primarily a question of skills. If you 
feel you don’t have both the technology 
skills and analytical skills, it makes 
sense to outsource. 
Technology skills mostly in terms 
of data integration, analytical skills 
mostly in terms of data science and data 
discovery. 
The biggest challenges towards 
successful deployment of Big Data 
projects 
If you are making Big Data an integral 
part of the business strategy, it requires 
an overall information management 
strategy. You cannot buy Big Data off 
the shelf. It requires strategic thinking 
and executive buy-in. 
The three pillars to start a Big Data 
program are: 
Vision & Strategy: This should 
supplement your Information 
Management strategy and requires the 
definition of Vision and Values 
Organization: This is not just 
another capability in your arsenal, it 
requires its own organization from 
Strategy to Operation Support 
Architecture: As described 
above the Data and Technology 
(Infrastructure) architecture needs to 
be carefully planned given the intrinsic 
elasticity of the information being 
managed 
Verticals to benefit the most from Big 
Data and Analytics 
In essence, every vertical yet Media/ 
Communication, Banking Services, 
Education and Healthcare seem to have 
the most amount of Big Data programs 
while retail, insurance, transportation, 
utilities and government are still testing 
the waters. 
However, it is very interesting to see 
what use cases there are per industry. 
My general advise which is applicable 
beyond Big Data strategies is to compare 
yourself to your peers, and even better 
You cannot buy Big 
Data o the shelf. 
It requires strategic 
thinking and 
executive buy-in 
to compare yourself to other industries 
and see what ideas you can adapt to your 
value streams. 
The next “Big Thing” in Big Data 
Simple. Big Data is moving away as a 
theme of itself. 
First, because volume and velocity 
are temporary issues. The moment we 
become more comfortable with the 
speed and the data size, it becomes 
information management as usual 
again. 
I didn’t mention variety here, which 
will remain to be difficult for the 
foreseeable future. 
Second, it becomes part of 
everything else. Big Data techniques 
will be used in mobile, social, security, 
analytics, business applications/BPM 
and every other imaginable IT field. 
 
In My Opinion: CIO Viewpoint: CXO Insight: 
Tom Wolf, SVP  CIO, 
MetLife 
Matt Wolken, VP  GM, Information 
Management Products, Dell Software 
T h e N a v i g a t o r f o r E n t e r p r i s e S o l u t i o n s 
Anjul Bhambhri, VP-Big Data, 
IBM 
MAY - 2014 CIOREVIEW.COM 
Company of the Month 
David Peters 
CEO, Emagine International 
Gayle Sheppard 
CEO and Chairman 
C I O R e v i e w|April 2014 C I O R e v i e w|MAY 2014 C I O R e v i e w|MAY 2014

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Information Management Strategy to power Big Data

  • 1. CXO INSIGHT Leo Barella By Leo Barella, VP, CTO- IT Strategic Services Team, Excellus BCBS Rochester, NY based Excellus BCBS is a nonprofit independent licensee of the BlueCross BlueShield Association that provides access to high-quality, affordable health coverage. The state of Hype vs reality in Big Data Undoubtedly, there is a lot of hype around Big Data. But overall, the substance outweighs the hype. Having said that, there is still a fair amount of confusion, for instance on how to get value from it, and how to create a Big Data strategy. On the technology level, there is a lot of fragmentation, and a lot of very niche technologies, that may offer specific functionality, but do not excel in integration. Big Data technologies, such as Hadoop, have become accepted pretty fast. My general advice is to go ahead, and invest in Big Data in your information infrastructure, but accept there is still some risk in technologies that are not mature enough. Factors playing a critical role in the success of Big Data projects Consumer–Personal Analytics: Analytical mobile apps, wearable technology, personal virtual assistants & smart advisors to offer suggestions, make recommendations, improve how tasks are handled, etc. Market–Sentiment Analysis: Who are the influencers in the market on social media, how are the brands being discussed, what business trends need to be followed that affect business performance? Partners/Suppliers/Distributors: Through sensor-technology, creating an (even) more efficient supply and demand chain, for flow performance, energy consumption optimization and predictive asset maintenance. Partners/Suppliers/Distributors: More real-time, behaviour-based data collection and prescriptive analytics for benchmarking purposes. Shareholder-Infonomics: Showing how the information base, sharing information with all stakeholders and its analytical activities can be economically valued, and contribute to shareholder value. Selection criteria to evaluate Big Data outsourcing vendors I would approach the question not from the infrastructure and technology point of view, but from a skills and capability point of view. Doing Big Data in the cloud is a commonly accepted approach; you would not be doing something “weird”. Increasingly, it is also the option that vendors of software and services offer. The one reason to do it on-premises would be the sensitivity of the data being in the cloud. Moving from cloud to outsourcing is primarily a question of skills. If you feel you don’t have both the technology skills and analytical skills, it makes sense to outsource. Technology skills mostly in terms of data integration, analytical skills mostly in terms of data science and data discovery. The biggest challenges towards successful deployment of Big Data projects If you are making Big Data an integral part of the business strategy, it requires an overall information management strategy. You cannot buy Big Data off the shelf. It requires strategic thinking and executive buy-in. The three pillars to start a Big Data program are: Vision & Strategy: This should supplement your Information Management strategy and requires the definition of Vision and Values Organization: This is not just another capability in your arsenal, it requires its own organization from Strategy to Operation Support Architecture: As described above the Data and Technology (Infrastructure) architecture needs to be carefully planned given the intrinsic elasticity of the information being managed Verticals to benefit the most from Big Data and Analytics In essence, every vertical yet Media/ Communication, Banking Services, Education and Healthcare seem to have the most amount of Big Data programs while retail, insurance, transportation, utilities and government are still testing the waters. However, it is very interesting to see what use cases there are per industry. My general advise which is applicable beyond Big Data strategies is to compare yourself to your peers, and even better You cannot buy Big Data o the shelf. It requires strategic thinking and executive buy-in to compare yourself to other industries and see what ideas you can adapt to your value streams. The next “Big Thing” in Big Data Simple. Big Data is moving away as a theme of itself. First, because volume and velocity are temporary issues. The moment we become more comfortable with the speed and the data size, it becomes information management as usual again. I didn’t mention variety here, which will remain to be difficult for the foreseeable future. Second, it becomes part of everything else. Big Data techniques will be used in mobile, social, security, analytics, business applications/BPM and every other imaginable IT field.  In My Opinion: CIO Viewpoint: CXO Insight: Tom Wolf, SVP CIO, MetLife Matt Wolken, VP GM, Information Management Products, Dell Software T h e N a v i g a t o r f o r E n t e r p r i s e S o l u t i o n s Anjul Bhambhri, VP-Big Data, IBM MAY - 2014 CIOREVIEW.COM Company of the Month David Peters CEO, Emagine International Gayle Sheppard CEO and Chairman C I O R e v i e w|April 2014 C I O R e v i e w|MAY 2014 C I O R e v i e w|MAY 2014