Research

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 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.

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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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Inquiry Response: Paid Promotion Optimization with Low Price Elasticity

By IIA Expert, Mike Gamage, Aug 10, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We’re concerned about paid promotion optimization for a brand of products with low price elasticity. Currently we put them on discount when our competitors do. Now we’re wondering if this is the best strategy. How can we improve our data to make better decisions?

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Inquiry Response: Communication Strategy Goals for BI and Analytics

By IIA Expert, Keyur Desai, Jul 06, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

Internally, we’re struggling with our internal communications plan for analytics. We never get beyond high-level discussions. Can you help us think more specifically about communications for BI reporting and a new advanced analytics mandate?

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Creating A Data Strategy: A Framework

By Doug Mirsky, Jun 15, 2020

Available to Research & Advisory Network Clients Only

There is a tendency to jump into something called a “data strategy” without understanding what it is at its core. In IIA’s view, at the center of a data strategy is a schematic of an entity’s information economy1 with in-depth awareness of the constituent needs on the demand side of the economy — the data consumers. Because ultimately the primary purpose of a data strategy is to solve questions about how to improve the availability, timeliness and quality of data, in that order of priority, for the constituencies demanding it.

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Inquiry Response: Notes on Assessing Decision-Making Models for Bias

By IIA Expert, May 11, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We build models in-house to determine lending for people who buy our products. We rely on these algorithms for auto-approvals, and we’re concerned about model bias. How can we address this issue?

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