Research

Inquiry Response: Moving Beyond Demand Forecasting For Supply Chain

Sep 13, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We want our supply chain team to expand their efforts beyond demand forecasting. Where are the low-hanging fruits where a centralized advanced analytics team could provide value? Alternatively, is demand forecasting actually a good use of our resources?

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Inquiry Response: Getting Started With Supply Chain Analytics

Aug 23, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

As a global manufacturing company with factories and distribution centers in many countries we’d like to do more with supply chain analytics. How do we get started?

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Inquiry Response: Moving Beyond Membership Analytics

By Steve Stone, Jun 28, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We have extensive loyalty club data and perform extensive membership analytics. What should we be thinking about when it comes to data monetization? What types of data governance are necessary for our current state? Beyond membership analytics, what are some common use cases we should consider focusing on next?

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Inquiry Response: Graph Databases for Customer Data Complexity

Feb 08, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We’re developing a customer data platform and are challenged by the wide variety of ways our customers interact with us. How are other organizations trying to solve this problem?

Response:

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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: Beginning Considerations for Global Supply Chain Analytics

By Mark Molau, Dec 23, 2019

Available to Research & Advisory Network Clients Only

Inquiry:

We’re a consumer products multinational, and we need to expand our supply chain analytics efforts. What should we be thinking about?

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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.

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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.

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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.

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We’ve had technical people focused on the ingestion and management of data for decades. But, only recently has data engineering become a critical, widespread role. Why is that? This post will outline a somewhat contrarian view as to why data engineering has become a critical function and how we might expect the role to evolve over time.

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