Research

In a previous blog post, we discussed the foundation of building an analytics team including the four key elements: Leadership & Governance Structure, Scope of Services Charter, Teams and Roles. This blog installment will center on the design of centralized and decentralized models and will also touch on the interdependencies and how firms manage work across organizational lines.

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As organizations go through the process of establishing its organization structure for an Analytics function, it is imperative to start the design and launch of a new analytics organization with a basic blueprint to ensure that all of the roles, skills, and capabilities are in place from the beginning. It is this blueprint that we will review from top to bottom so that as you serve your organization as a decision-maker or key stakeholder you will be well-equipped as an architect or influencer to make certain that the right structures to fit your company’s needs can be put into place from the beginning.

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Miss The Right Connections At Your Own Peril

By Bill Franks, Nov 12, 2014

While connection analytics won’t solve all of your organization’s problems, it can probably help solve some of them better. Given that it isn’t widely adopted yet, there is a chance to get a competitive advantage by putting it to use first. Ignore connection analytics at your own peril!

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Progressive companies, those truly ready to adapt to the growing digital presence are going to run into hurdles, make bad decisions, and experiment with new ideas. These are the companies that will learn from their mistakes, they will do testing and learn quickly what works and adjust accordingly; they will be able to measure incremental changes to the business.

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I recently had a meeting with one of the largest companies in the world, where we discussed concerns about ongoing maintenance and, more importantly, ongoing repair required for analytics processes. The conversation helped solidify in my mind a major disconnect that often occurs when organizations deploy an analytics process into a production setting. Let’s walk through that disconnect here.

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Minds + Machines: A New Generation of Analytics

By Thomas H. Davenport, Oct 02, 2014

If a huge, big-iron-focused company like GE can jump headfirst into the data economy, any firm should be able to do it.

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For those of us 45 and older, it was the norm to start with a company at the lower level with aspirations of working hard and over the years gaining a senior leadership role. Yes, working with a single company for your entire career. For the most part you were rotated through different areas of the company, giving you a total perspective of the business. Your primary training was still the core of what you specialized in, but the peripheral areas provided you more experience and opportunities for collaboration and integration across divisions.

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Five Clusters of Opportunity with Big Data

By Robert Morison, Sep 23, 2014

In what areas of your business can big data have the greatest impact? In many organizations, that’s a very difficult question to answer. Why? Big data offers so many new opportunities and so many different kinds of opportunities, from using real-time sensor data to mining the unstructured conversation on social media.

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The Data Product Era Begins in Financial Services

By Thomas H. Davenport, Sep 18, 2014

It’s evident that financial services are going to be very interesting users of big data over the next few years. Of course, there will be important regulatory and consumer privacy issues to navigate. It will also be important to figure out just how to make money from these data products.

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Do Your Metrics Matter?

By Kimberly Nevala, Sep 16, 2014

Your organization has well-defined metrics. Executives track them diligently. Managers include them in status reports. Key Performance Indicators (KPI) are prominently featured in annual reports and PR. So isn’t the company, by definition, data-driven?

The answer, unfortunately, is: not necessarily.

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