Research

Why Blockchain And Analytics Don’t Mix Well

By Bill Franks, Nov 09, 2017

The concept of a blockchain is quite a phenomenon in recent times. It has quickly risen from a relatively obscure idea known mostly within some small circles to one that is being discussed as having potential to literally change some of the fundamentals of the world’s economic systems.

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2017 Analytics Symposium - Chicago Summary and Recordings

By Jack Phillips, Oct 31, 2017

Available to Research & Advisory Network Clients Only

Earlier this month, IIA held its 8th Analytics Symposium and awarded the 2017 ANNY Excellence in Analytics Award to Cisco Systems in a packed house at the Gleacher Center in Chicago. Read the key themes of the event and watch the session recordings on demand.

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It’s Not About the Algorithm

Oct 31, 2017

Available to Research & Advisory Network Clients Only

2017 Analytics Symposium - Chicago Session Recording

Morgan Stanley’s Jeff McMillan discusses the opportunities and challenges that businesses face in trying to leverage data, analytics and the emerging capabilities of artificial intelligence to achieve real and sustainable business transformation. He shares his experiences on where and how companies need to think and act differently and where traditional approaches to business management still matter (a lot). And most importantly, he talks of the practical realties of building smarter organizations that combine the best of analytical practices with the deep knowledge and experience of each individual to promote an environment in which the best decisions are made each day.

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How Analytics is Transforming Financial Services

By David Alles, Oct 25, 2017

Available to Research & Advisory Network Clients Only

IIA asked survey respondents in four segments (wealth management, US banks, Canadian banks, and credit unions) questions about their use of analytics in six customer engagement areas (customer experience, customer facing employees, web, mobile, social, and ROI). Results highlight why traditional financial services are vulnerable to disruption. Digital native companies universally excel at using analytics in these areas. However, even across leading financial services companies we see lagging adoption – especially in web, mobile, and social analytics. This is indicative of the analytics maturity gap between digital native companies and traditional companies and illustrates why traditional financial services companies have to accelerate analytics maturity to be more competitive. Based on the study findings, IIA’s faculty of top analytics practitioners and analysts then isolated key takeaways and developed recommendations for traditional companies in the financial industry to mature their analytics in effective, sustainable, and measurable ways

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Analytics Maturity Powers Company Performance

By David Alles, Sep 21, 2017

Available to Research & Advisory Network Clients Only

Does the development of enterprise analytics capability really drive superior company performance? IIA’s previous research briefs demonstrate that analytics maturity varies significantly between industries and across the top-performing companies in each industry. This follow on research brief uses IIA’s proprietary analytics maturity data – from leading companies like Amazon, Apple, Netflix and Google – and publically available financial and company data, to illustrate the positive association between analytics maturity and superior company performance.

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Inquiry Response: The Bridge Between Internal and External Reporting

By Adam Moore, Sep 11, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

We have an external reporting tool with a certified process and strong governance. Separately, we have management reporting data and analytics data, and for analytics we are standing up a data lake from disparate sources. My challenge is around the external tool and management reporting data. Right now we bridge the management reporting back to the externally reported figures, but I don’t see a need for this tie because the purposes are different. However, senior management has an emotional commitment to the bridge, so I’m wondering if that bridge is really important and whether you are seeing companies diverting from the need to build a bridge.

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“The real issue is that every business is now a tech business – whether it wants to be or not – and that means not just new skills and experiences, but a new outlook on opportunity and strategy.” This quote is from a recent Forbes analysis of the different business models companies can deploy and how each one is performing in the new digital world.

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Inquiry Response: Starting a Knowledge Management Program

By Mark Madsen, Aug 28, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

Our analytics department is starting a knowledge management program. What are some best practices of starting a program for our analytics department? We’re looking for lessons learned and anything that would help a knowledge management program be more successful for people doing analytics.

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The ever-increasing role of technology in the modern marketplace has made transactions quicker and more convenient than ever for both businesses and consumers. Unfortunately, it’s also invited a greater risk of payment fraud and other cybercrime. Fraudsters have access to a variety of sophisticated attacks that can cause tremendous harm in a very short period of time – a reality that requires advanced tools capable of rapidly predicting, detecting and responding to suspicious activity and adapting to a constantly evolving digital landscape. Perhaps no such tool is more powerful than machine learning, and businesses are increasingly turning to this technology to guard themselves against cyberattacks.

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Are Analytics Truly Self-Service?

By Thomas H. Davenport, Jul 25, 2017

I have been thinking about some of the changes over the last decade in analytics, coinciding with the revised and updated release of my book with Jeanne Harris, Competing on Analytics. The book is ten years old, and much has changed in the world of analytics in the meantime. In updating the book (and in a previous blog post about the updates), we focused on such changes as big data, machine learning, streaming analytics, embedded analytics, and so forth. But some commenters have pointed out that one change that’s just as important is the move to self-service analytics.

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