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    Advanced Data Analytics

    Challenge

    The wrong attitude for incorporating analytics into decision-making.
    Fear of integrating new technologies into existing IT architectures.
    Misappropriated staff.
    Lack of innovative leadership.

    Solution

    Advanced analytics is not just about gathering lots of data, buying some technology and hiring a few quants. When done right, analytics has the potential to prioritize workloads, detect buying patterns to initiate action, optimize processes and identify insights—to transform your business operations.To develop a sustainable analytics culture you first must know what you’re trying to achieve. Start by asking questions – how do you plan to coordinate multi-channel data? Or unstructured data? They seem like simple questions but these will quickly open up the strategic mindset of senior managers.You need to formalize reporting goals and measures. Whether it’s new customer acquisitions, share-of-wallet, customer loyalty or retention, you need to establish these up front.And you must establish and maintain an analytics infrastructure. That requires rolling out the technology capable of integrating “architectural integration” challenges and onboarding the right set of employees with the appropriate skill-set to maintain and manage them.

    According to Ventana Research, 55 percent of businesses say the challenge of architectural integration is a top obstacle to rolling out advanced analytics. There is an innate fear of adding a new technology to the big data “chaos.”To breakdown this architectural chaos, you need to consider three stages of big data management: “Organizing”: the storage, organization and retrieval of data; “Visualizing/Analyzing”: where data insights are discovered through pattern detection and other techniques; and “Operationalizing”: pushing the insights out to the organization and modifying customer communication accordingly.Too often, organizations are planning for an advanced analytics project and are just considering the first stage with Hadoop. While Hadoop has often been closely associated with big data and advanced analytics projects, it doesn’t do everything. Hadoop is an excellent platform for cost-effectively storing lots of data, but other tools are needed to convert it into information of value.

    According to an Accenture report, the next 20 years will be about integrating analytics into everyday work. Traditional BI tools were designed for IT and data specialists, so if you wanted to use them you would need to be trained. Moving forward, advanced analytics projects won’t be an “IT-only” party. As the world and businesses move towards a data-driven approach, a much larger audience for data tools is emerging: a whole new type of non-technical user needs easy and quick access to relevant information, and not only information about what’s happening, but information to inform business actions.Through this, analyzing and developing the talent in the organization is as important as hiring talent with a passion for analytics. Training the workforce and appropriating the right talent for the right project is vital to your success.

    Managing data in a hyper-paced environment requires creative, out-of-the-box thinking.The single most important step you can take is to promote leaders with a passion for data analytics at every level—especially in the C-suite. Take Ken Rudin, the head of analytics at Facebook. His versatility and passion for analytics enabled him to bridge two diverse worlds (business and technology) and deliver value-added business solutions. How? He set out to be an analytics evangelist, not an oracle. Through this approach, he was able to influence leadership on new approaches and strategies.It’s also important, of course, to work with technology vendors who will act as a strategic partner as you build your analytics practice. The challenge and opportunity in rolling out advanced analytics is not only in the breadth and variety of technology options available, but also the effort that is required of organizations to improve data literacy and encourage innovation. By finding ways of understanding how this new world of advanced analytics can potentially solve problems, you’ll create compelling opportunities in your business.

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