Research & Insights

Inquiry Response: Transitioning to a Data Lake

By IIA Expert, Mo Chaara, Aug 03, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We plan to transition to a data lake to generate future business value by enhancing analytics and reporting. Unfortunately, we’re struggling to see how to get this done and the end value.

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Inquiry Response: Best Practices For Working With Stakeholders

By IIA Expert, Kristy Mayer-Mejia, Jul 27, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We have a project management office (PMO) for our data and analytics team. This is a new role and aligning with the businesses in a more formal way is a new concept for us. Do you have any best practices for working with stakeholders?

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Inquiry Response: Moving Forward With Data Scientists In Our Sales Org

By IIA Expert, Bernie Smith, Jul 20, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We’re finally at a point where we have data scientists within the sales organization who can work on advanced analytics. However, we’re struggling with how to get the business knowledge to the data scientists and move forward. How have you solved this dilemma?

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Inquiry Response: Tips For Successful Data Consolidation

By IIA Expert, Eddie Satterly, Jul 13, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We are working on a data consolidation project in which we’re replacing four old ERP systems with a new ERP system. We’re concerned with managing customer data from the different systems and prepping ourselves for advanced analytics in the future.

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Inquiry Response: Feedback on Data Platform Architecture

By IIA Expert, Jun 22, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We’re working on a new centralized data platform so that we can perform effective analytics with a quicker turnaround. We’d like to verify some aspects of a new architecture that we’re considering. Can you provide feedback?

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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: Improving Fairness and Explainability in Risk Modeling

By IIA Expert, May 18, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We’re concerned about potential bias in the data our risk models use for lending decisions because our data is primarily made up of white males. We’re already working on accuracy with respect to different sub-populations. What are we missing?

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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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Inquiry Response: Starting an Analytics Resource Center

By IIA Expert, Chris Hutchins, May 04, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

I’m charged with driving analytic strategy, starting with formalizing an enterprise analytics function. We have scattered pockets of analytic capability. How do I ease these teams into the new paradigm?

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Inquiry Response: Thoughts on Improving Customer Lifetime Value and Churn

By IIA Expert, Ahmer Inam, Apr 20, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We have a customer loyalty program, and we want to improve our customer lifetime value (CLV) and retention, and also move more customers toward using loyalty cards. What are some interesting techniques and frameworks that could aid our efforts?

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