Research

Inquiry Response: Focus Here When Merging Analytics And BI To Support The Business

Jun 14, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We recently joined enterprise analytics and BI into one team. As we merge into one corporate support function, what should we focus on, especially when it comes to serving business lines and functions that also have embedded analysts?

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Inquiry Response: Analytics for B2B2C E-Commerce

Jan 25, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We are relying more and more on digital B2B2C to reach our consumers. As we ramp up e-commerce, how can we apply analytics and what kind of investment should we make? What did you do in your company?

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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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Inquiry Response: Tips For Ingesting Data Into New Platform

Jan 18, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We’re in the process of ingesting data into our cloud data platform. What should we be thinking about? Do we need a central data governance team to make this work?

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Inquiry Response: Tips For Building A People Analytics Capability

By Jon Agnone, Dec 28, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We’re new to HR analytics. What kind of projects should we look to tackle to show some initial wins?

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Inquiry Response: Promoting Analysts To The Role Of Data Scientist

By Jennifer Prendki, Dec 21, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We’re building a team to focus on using machine learning to enhance our end user experience. Many of our analysts aspire to be data scientists, and we would like to fill data scientist roles with the talent we have where possible. How should we delineate roles and responsibilities of a data analyst vs. a data scientist?

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Inquiry Response: When Data Scientists Are Expected To Do It All

Oct 26, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We’re attempting to upskill our data scientists to instill good coding behavior and the tenets for model testing and system functionality for application delivery. It’s been a challenge. Do you have any suggestions?

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Inquiry Response: Working Towards Machine Learning Products with MLOps

Sep 28, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

As we work towards our goal of deploying more machine learning (ML) models into production, how do we position our MLOps needs to the organization? What needs to happen for MLOps to be successful?

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Inquiry Response: Tips for Writing an Analytics Strategy

Sep 07, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

I’m writing an analytics strategy for digital transformation. We have multiple product lines, but I decided to start with writing the strategy, with use cases and a roadmap, for only one division. Should I include the other product lines too? How much detail should I include?

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A Framework For Establishing A Self-Service Program

By Drew Smith, Doug Mirsky, 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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