Research

Inquiry Response: Graph Database For Customer Data

By IIA Expert, 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

By IIA Expert, 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

By IIA Expert, 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

By IIA Expert, Ashutosh Sanzgiri, 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

By IIA Expert, 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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A Framework For Establishing A Self-Service Program

By Doug Mirsky, Drew Smith, Aug 31, 2020

Available to Research & Advisory Network Clients Only

As with many terms in the analytics space, “self-service” tends to have many meanings, depending on the vendor using the term. Self-service is used to describe both business intelligence and (advanced) analytics, and is frequently co-mingled with a number of other terms, including “data democratization,” “citizen data scientist” and, more recently, “data literacy.”

In general, this collection of terms points in the direction of a conscious strategy to have more employees in an organization, with broader and deeper access to data, use those data sets to make better, more timely data-driven decisions with little or no intervention from a centralized BI or analytics function, or IT professionals.

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Inquiry Response: Working Alongside Agile Teams

By IIA Expert, Michael Bewley, Aug 17, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

Our data science team works alongside a strict Agile data engineering team and we’re finding collaboration to be difficult. Do you have any suggestions?

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