Big Data. Big Decisions
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Jim Ditmore

New Technologies Require New Organizational Approaches

The cloud, mobile and big data movements put a premium on speed and innovation, not just efficiency and security.

IT organizations are challenged to keep up with the latest wave of cloud, mobile and big data technologies, which are outside the traditional areas of staff expertise. Some industry pundits recommend bringing on more technology "generalists," since cloud services in particular can call on multiple areas of expertise (storage, server, networking). Or they recommend employing IT "service managers" to bundle up infrastructure components and provide service offerings.

But such organizational changes can reduce your team's expertise and accountability and make it more difficult to deliver services. So how do you grow your organization's expertise to handle new technologies? At the same time, how do you organize to deliver business demands for more product innovation and faster delivery yet still ensure efficiency, high quality and security?

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Rather than acquire generalists and add another layer of cost and decision making to your infrastructure team, consider the following:

Cloud computing. Assign architects or lead engineers to focus on software-as-a-service and infrastructure-as-a-service, ensuring that you have robust estimating and costing models and solid implementation and operational templates. Establish a cloud roadmap that leverages SaaS and IaaS, ensuring that you don't overreach and end up balkanizing your data center.

[ Use the latest technologies to boost server efficiency and performance. Read Why Your Data Center Costs Will Drop. ]

For appliances and private cloud, given their multiple component technologies, let your best component engineers learn adjacent fields. Build multi-disciplinary teams to design and implement these offerings. Above all, though, don't water down the engineering capacity of your team by selecting generalists who lack depth in a component field. For decades, IT has built complex systems with multiple components by leveraging multi-faceted teams of experts, and cloud is no different.

Mobile. If mobile isn't already the most critical interface for your company, it will be in three to five years. So don't treat mobile as an afterthought, to be adapted from traditional interfaces. And don't outsource this capability, as mobile will be pervasive in everything you build.

Build a mobile competency center that includes development, user experience and standards expertise. Then fan out that expertise to all of your development teams, while maintaining the core mobile group to assist with the most difficult efforts. And of course, continue with a central architecture and control of the overall user experience. A consistent mobile look, feel and flow is essentially your company's brand, invaluable in interacting with customers.

Big data. There are two key aspects of this technology wave: the data (and traditional analytic uses) and real-time data "decisioning," similar to IBM's Watson. You can handle the data analytics as an extension of your traditional data warehousing (though on steroids). However, real-time decisioning has the potential to dramatically alter how your organization specifies and encodes business rules.

Consider the possibility that 30% to 50% of all business logic traditionally encoded in 3 or 4 generation programming languages instead becomes decisioned in real time. This capability will require new development and business analyst skills. For now, cultivate a central team with these skills. As you pilot and determine how to more broadly leverage real-time data decisioning, decide if it will be necessary to seed your broader development teams with these capabilities.

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Competing Demands

Overall, IT organizations must meet several competing demands: Work with business partners to deliver competitive advantage; do so quickly in order to respond to (and anticipate) market demands; and provide efficient, consistent quality while protecting the company's intellectual property, data and customers. In essence, there are business and market drivers that value speed, business knowledge and closeness at a reasonable cost and risk drivers that value efficiency, quality, security and consistency.

Therefore, we must design an IT organization and systems approach that meets both sets of drivers and anticipates business organizational change. The best solution is to organize IT as a hybrid organization to deliver both sets of capabilities.

Typically, the functions that should be consolidated and organized centrally to deliver scale, efficiency and quality are infrastructure (especially networks, data centers, servers and storage), IT operations, service desks and anything that should be run as a utility for the company. The functions to be aligned and organized along business lines to promote agility and innovation are application development (including Web and mature mobile development), data marts and business intelligence.

Some functions, such as database, middleware, testing and project management, can be organized in either mode. But if they aren't centralized, they'll require a council to ensure consistent processes, tools, measures and templates.

For services becoming a commodity, or where there's a critical advantage to having one solution (e.g., one view of the customer for the entire company), it's best to have a single team or utility that's responsible. Where you're looking to improve speed to market or market knowledge, organize into smaller IT teams closer to the business. The diagram below gives a graphical view of the hybrid organization.

The IT Hybrid Model diagram

With this approach, your IT shop will be able to deliver the best of both worlds. And you can then weave in the new skills and teams required to deliver the latest technologies such as cloud and mobile.

Which IT organizational approaches or variations have you seen work best? How are you accommodating new technologies and skills within your teams? Please weigh in with a comment below.

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By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

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Hadoop is for unstructured data; SQL is for relational databases
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We're not interested in Hadoop
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