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In the first installment of this series, we discussed the origins of Mode 2 Analytics, and in the second installment we focused on how to enable this capability in your organization using Cognos. Now that we’ve learned all about how Mode 2 works, let’s walk through a sample use case that highlights the Bimodal Analytics Lifecycle as well as the technical capabilities of Cognos Analytics and how they fit together.

In this example, you are the manager of a Healthcare Call Center system that is comprised of seven (7) regional centers across the country. Each call center handles contact (phone calls and online chats) from the customers that are located within the states that make up those regions.

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When you think about the different ways that data gets used in your company, what comes to mind?

You surely have some executive dashboards, and some quarterly reports. There might be a reporting portal containing everything that IT created for anyone within the past decade.

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When defining or assessing a Data & Analytics Strategy, Ironside leverages a proven framework of understanding the current state and comparing it to a desirable future state with a focus on six key areas, or pillars.

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What is the most common, most vital need of any business? Speed.

Speed to adapt, to respond, to evolve. It is important, not just at the big picture level, but on a daily basis as well. If you’re constantly waiting for information, then you’re spending less time analyzing data and making decisions that help the organization. Speed has been vitally important in the acceptance of Mode 2 style content such as Dashboards and Stories. Response time is key when viewing daily high-level metrics or when creating that “single use” asset to analyze a potential issue.

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Last spring, I had the opportunity to attend a local analytics conference with Dr. Claudia Imhoff as the keynote speaker. As she got on stage to begin her presentation, she started out by making a statement along the lines of “For every time the phrase ‘Big Data’ is mentioned today, we will all take a shot during happy hour.” 

(Tip: Don’t try that for this article.)

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In previous releases of Cognos Analytics, we have seen a trend of integrating many of the features of metadata modeling in Framework Manager into the Cognos Analytics interface. This trend is continuing with new or improved modeling capabilities being incorporated into Cognos Analytics 11.1 Data Modules.

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Customer segmentation is defined as “the process of dividing customers into groups based on common characteristics so companies can market to each group effectively and appropriately.” By using the correct attributes to define the customer segment, it allows companies to identify the right customers for targeted and relevant offers. Those who successfully define and maintain customer segmentation can derive a competitive advantage from the implementation by improving customer experience.

However, there are potential pitfalls that can reduce the effectiveness of a customer segmentation initiative. This article will identify the pitfalls and propose solutions in order to improve the chances of a beneficial customer segmentation project.

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With the maturing and ever increasing acceptance of the cloud across multiple industries and the data gravity gradually moving to the cloud, i.e. more data being generated in the cloud, we are seeing some interesting cloud-based data and analytics platforms offering unique capabilities. Some of these platforms could be disruptive to the established market leaders with their innovative thinking and ground up design that is “born in the cloud and for the cloud.”

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From time to time every professional should take a step back and assess where they have been, where they are today and where they want to go. The Office of Finance is no exception. As we begin to plan for next year, we spent some time reflecting on what CFOs and their teams are tasked with. Based on our team’s collective experience in working with the Office of Finance, we have developed what we believe are key principles to succeed going forward. Read more

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