Research

Applying Data Governance 2.0: Best Practices to Business Intelligence Governance

Oct 19, 2021

Available to Research & Advisory Network Clients Only

Today’s Data Governance best practices are built on the lessons of decades of missteps and frustration. The new approach focuses on building lightweight user-centric approaches, enabled with robust and flexible tools. And these lessons and practices are directly transferred to BI Governance, where the explosion of users leveraging a vast array of self-service tools demands the right governance approach. In this webinar we will cover: - The key principles for driving effective BI Governance - How to leverage effective BI Governance to engages users - A framework for BI Governance connecting enterprise strategy to critical daily action

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Data and Analytics for Tax Agency Transformation

By Shaun Barry, Deborah Pianko, Robert Morison, May 01, 2021

Tax agencies manage the essential flow of revenue to governments. That core mission has expanded even as their resources remain constrained. And they face the challenges of any major financial services organization – serve customers, operate efficiently, prevent fraud, and adjust to changing economic and social conditions. To explore how data and analytics can assist agencies in meeting those challenges and forwarding their missions, IIA spoke with Shaun Barry, Director of Government Fraud & Security Intelligence Solutions at SAS Institute, and Deborah Pianko, Principal, Government Fraud & Security Intelligence Solutions at SAS Institute.

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Inquiry Response: Graph Database For Customer Data

Mar 22, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We’re building our own customer data platform and are considering a graph database to handle a 360-degree view of the customer. Would a graph database be beneficial and also scalable for us?

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Inquiry Response: Service Health Model Monitoring and Effectiveness

Mar 15, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We want to get proactive about predicting service health and correcting customer issues. We’re struggling with growing pains when it comes to model monitoring and effectiveness. How have you seen this done?

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Inquiry Response: Ways To Improve Customer Relationship Management

Mar 08, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We supply propensity models to the marketing team to help predict customer behavior for our various brands. Beyond this, what can our analytics team be doing to support them?

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Fighting Money Laundering with Intelligent Automation

By Christopher Ghenne, Beth Herron, David Stewart, Robert Morison, Feb 08, 2021

The world of money laundering and other financial crimes – and they do span the globe – continues to reshape rapidly. The amount of money laundered is estimated at between 2 and 5 percent of global GDP. The midpoint of that range has over $3 trillion in illicit funds moving annually through the financial services industry. That’s several million dollars a minute. If the money laundering “industry” were a country, it would have the fourth or fifth largest GDP in the world…Today, continuous and sometimes radical improvement has become a business imperative. Institutions must rethink and accelerate their processes, become both more efficient and more nimble, and react faster to the changing schemes of financial crime.

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A Framework For Prioritizing Analytics Efforts

By Kathleen Maley, Jan 19, 2021

Available to Research & Advisory Network Clients Only

Project prioritization is one of those activities that seems simple and straightforward on the surface, but scratch at it just a little and hidden complexities are quickly revealed. While there is general agreement that “good” prioritization contributes to the overall effectiveness of an analytics function, rarely is any effort taken to define “good” and map out an agreed-upon approach to get there. The obvious outcome of a prioritization process that lacks intentionality is general chaos — analytics teams are overwhelmed and expressing a need for more resources, business leaders are frustrated that their needs aren’t being met, the loudest voice often gets his or her way, and the enterprise isn’t optimizing the return on its investment in analytical talent.

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Value and Opportunity: An Executive Guide to Procurement Integrity

By JEN DUNHAM, Laurent Colombant, Robert Morison, Jan 13, 2021

Procurement Integrity (PI) represents a broader problem and bigger opportunity than most businesses recognize. Comprehensive PI programs continuously validate purchasing transactions, using data and analytics to trace patterns, spot anomalies, and reduce fraud, waste, and abuse. The problems uncovered range from occasional opportunistic fraud to ongoing organized fraud, from duplicate invoices and other improper payments to regular kickbacks, from conflicts of interest to ongoing collusion with suppliers. Continuous monitoring of anomalies in procurement and supplier due diligence processes reveal potential problems, including data issues and process breaches, and help focus the efforts of audit and other investigative staff.

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Inquiry Response: Measuring Promotion Success

Dec 07, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

How can we measure the lift from coupons used and what’s the best way to deploy the models to do it? We know we have lift coming in from various combinations of promotions, but we need a more granular view. Unfortunately, we don’t have access to web data, although we can track the coupons used in our brick-and-mortar stores. What do you think?

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Inquiry Response: Scaling A NLP Model To The Enterprise

Nov 09, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We’ve developed a successful natural language processing (NLP) algorithm and think it would be applicable to other areas of the business too. How should we deploy something like this so we can share it more broadly?

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