Research
Value and Opportunity: An Executive Guide to Procurement Integrity
By Robert Morison, JEN DUNHAM, Laurent Colombant, 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.
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?
Inquiry Response: A/B Testing For Mobile Applications
By IIA Expert, Oct 12, 2020
Available to Research & Advisory Network Clients Only
Inquiry:
How do other companies perform A/B testing at scale for their mobile apps? We’d like to work on optimizing user experience performance.
Inquiry Response: Tips for Small Data Science Teams and Targeted Marketing
By IIA Expert, Ahmer Inam, Aug 24, 2020
Available to Research & Advisory Network Clients Only
Inquiry:
We have a small, centralized data science team that performs machine learning (ML) analysis for marketing insights into our various brands. Our data scientists are overwhelmed with their workloads. Do you have any organizational or Azure architectural tips that could help us to help them? Also, for marketing activities, how can we improve our individual targeting?
Inquiry Response: When To Merge Customer Data Records
By IIA Expert, Jan 06, 2020
Available to Research & Advisory Network Clients Only
Inquiry:
We have a wide variety of systems that create and store customer data. What’s the best way to bring these records together to improve the customer experience?
Response:
2020 ANALYTICS PREDICTIONS AND PRIORITIES
By Thomas H. Davenport, Bill Franks, Drew Smith, Robert Morison, Dec 19, 2019
Each year, the International Institute for Analytics ends the year with a look at the latest analytics trends and the most pressing analytics challenges currently facing organizations. Our predictions are based upon our day-to-day work supporting and advising analytics leaders and organizations. We take advantage of the breadth of expertise and cross-industry perspectives we encounter every day from our clients, partners, and members of the IIA expert network. This is our 10th annual look toward the upcoming year, and our annual Predictions and Priority research brief and the associated webinar have become among IIA’s most popular content of the year. This year, we’ve stuck with our approach of augmenting each of our predictions with a specific priority for leaders to focus on as they attempt to address that prediction. As a result, each priority provides specific guidance as to how to best prepare for, and adapt to, its corresponding prediction.
Inquiry Response: Building Out Your Customer Data Program
By IIA Expert, Ahmer Inam, Dec 09, 2019
Available to Research & Advisory Network Clients Only
Inquiry:
We’re charged with expanding our customer data program. We have an initial framework for the platform itself, but now we need to think about our product offerings and the skills set required so we can build out the program. Do you have any advice?
Inquiry Response: Getting Started With a Customer Data Program
By IIA Expert, Ahmer Inam, Nov 04, 2019
Available to Research & Advisory Network Clients Only
Inquiry:
We’re in the process of starting a customer data program that will include real-time data from marketing campaigns and digital activities. What is the best way to get started?
The Fuzzy Line Between Good and Evil Data Science
By Bill Franks, Sep 12, 2019
Available to Research & Advisory Network Clients Only
The vast majority of people building analytics and data science processes have every intention of being good and ethical. As a result, most potentially unethical and evil processes arise in situations where that wasn’t the intention. The problem is typically that proper focus and governance is not in place to keep analytics and data science processes on the side of good. On top of that, what is good and what is evil isn’t nearly as clear cut as we’d wish it to be.
Mapping an Information Economy
By Doug Mirsky, Aug 16, 2019
Available to Research & Advisory Network Clients Only
The data warehouse revolution began in 1991 when Bill Inmon published Building the Data Warehouse. Inmon observed, early in that book, that every organization has a naturally occurring information economy, and that most naturally occurring information economies were inefficient, duplicative and prone to produce suboptimal decisions.