What Business Leaders Can Learn From Intelligence

By Thomas H. Davenport, Dec 16, 2014

There is little doubt that the intelligence sector in the US - including the Central Intelligence Agency or CIA, National Security Agency or NSA, parts of the Federal Bureau of Investigation or FBI, Homeland Security, and many other agencies - and elsewhere is quite accomplished at several aspects of data management and analytics. It’s also clear that businesses can learn from these organizations in several respects. Below are a few lessons from which business leaders could draw.

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Ignore Your Business, Rake In The Profits

By Bill Franks, Dec 11, 2014

Want to uncover interesting ways to drive value from data? Look for ways to provide value to external, third party stakeholders through analysis of the data that your organization initially collects just for itself.

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Is Embracing Analytics a Rush to Judgment?

By Gary Cokins, Dec 09, 2014

Allow me to take a contrarian view to the rapid interest in applying analytics. Have we seen this kind of story before? Is there a rush to judgment that analytics is the elusive cure-all magic potion or panacea that management has been seeking to achieve extraordinary high performance?

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2014 Analytics Predictions, Revisited

By Jack Phillips, Dec 04, 2014

Last year, IIA revealed nine predictions for 2014 that ran the gamut of organizational challenges, benefits of technology and staff augmentation, and new applications of analytical methods.

We’ll give a more in-depth review of the 2014 predictions during our 2015 Analytics Predictions Webinar on December 10. But for now, I wanted to offer my own quick take on the 2014 predictions, and see what we got right, and where we missed the mark a little bit.

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The Privacy/Value Tradeoff

By Thomas H. Davenport, Nov 28, 2014

Unless you are willing to become a recluse and go completely off the grid, you are stuck with a high degree of transparency of your personal data. The only real course of action is to be selective in the services and relationships you consume that affect your privacy.

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Retail Analytics Systems Still Need a Human Touch

By Robert Handfield, Nov 26, 2014

As more data becomes available in the grocery and retail environment, organizations are re-thinking their supply chain processes to drive increased automation, improved performance, and increased inventory turns. They are also re-thinking the design of their supply chains, thinking about how much of their product goes through distribution centers, distributed to stores, or shipped directly from suppliers to store locations.

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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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