Research

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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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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Inquiry Response: Managing an R&D Analytics Team

By IIA Expert, Jack Levis, Apr 13, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

I’m new to the analytics R&D space, and I’m not sure how to manage my new team and the work to ensure that the leadership sees us as valuable. Do you have any suggestions?

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The DataOps Transformation: 7 Steps To Prevent The Great War of Data Scientists

By Christopher Bergh, Mar 31, 2020

Available to Research & Advisory Network Clients Only

Join Christopher Bergh as he presents the seven steps to get these groups of people working together. These seven steps contain practical, doable steps that can help you achieve data agility through DataOps. This presentation will illustrate how to make changes to big data, models, and visualizations quickly, with high quality, using the tools teams love. We synthesize techniques from DevOps, Deming, and direct experience.

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Big Data and Analytics in the COVID-19 Era

By Jesse Anderson, Mar 26, 2020

Available to Research & Advisory Network Clients Only

Big Data and analytics are going to change in this COVID-19 era. In this Webinar, Jesse Anderson, leading expert in big data and related technologies and techniques, shares what he’s been telling his clients who call and ask, ‘Jesse, with all that’s going on what should we do now?’ Jesse explores a number of topics ranging from the implications of working from home to the tweaks that may be necessary to your current organizational models in the current economic climate.

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