Locally Optimistic - A blog about data organizations

User Research for Your Data Team, Part 1

In Culture, Roles & ResponsibilitiesTags Data Culture, self service, Tools, user researchMay 4, 2021

Your team invested a lot of effort into building self-service data tools, but your stakeholders aren’t using it as much as you hoped, or in the ways that you hoped. User research best practices can help you understand your users’ pain points, encourage usage of your data projects, and build strong relationships with your stakeholders.

Treat your data products like software products

Every data team has a range of products and features. Dashboards, reports, forecasting tools, self-service data platforms, and

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Run Your Data Team Like A Product Team

In Culture, ManagementApril 20, 2021

Emilie Schario and Taylor A. Murphy, PhD

Data teams aim to help the people in their organization make better decisions. Many data teams aren’t doing this as well as they could and are missing out on a

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Forecasts and targets (Part 4)

In Business Inteligence, Culture, ManagementTags KPIMarch 18, 2021

Ilan Man

In part 2 of this series, we learned that every new initiative a team undertakes should be accompanied by an expectation on how the initiative will perform. For example,

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Facilitating the meeting (Part 3)

In Business Inteligence, ManagementTags Data Culture, KPI, ManagementJanuary 21, 2021

Ilan Man

The MBR meeting is the focal point of the MBR program. Here you will publicly interrogate KPIs, align on action items and hold people accountable. There are typically

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Two hands putting ballots or surveys into green ballot box

Data Team Surveys – Learn What Your Stakeholders REALLY Want

In ManagementTags Data Culture, Management, Process, RoadmapJanuary 11, 2021

Caitlin Moorman

Getting regular feedback from your organization can help the data team to prioritize the work that will have the biggest impact on your stakeholders. However, it’s hard to turn ad-hoc

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Developing KPIs for the MBR (Part 2)

In Business Inteligence, ManagementTags Business Intelligence, KPIJanuary 4, 2021

Ilan Man

KPIs are central to the business review program since they provide a way to reason about the success or failure of an initiative. Core to the success of a

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Starting a Business Review Program

In Business Inteligence, CultureTags KPIDecember 21, 2020

Ilan Man

As an analytics leader, my job is to ensure that my organization makes the best data-driven decisions possible. One effective mechanism that I employ — and other analytics leaders can too — is the business review program. This program is a rigorous and systematic review of the most important Key Performance Indicators (KPIs) across the company, with involvement by senior leadership in an ongoing and iterative fashion, punctuated by a regularly occurring cross-functional meeting. …

A data scientist in an oversized lab coat is juggling beakers and doing lots of things all at once.

Lean Data Science

In ManagementTags Agile, Data Science, LeanSeptember 29, 2020

Michael Kaminsky

It’s becoming more and more clearly recognized that the promises of the machine-learning revolution, at least for your average non-big-tech company, are not delivering the value that many had hoped

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Map with a relatively straight line from the starting point to the goal point

Linear and Circular Projects in Data, Part 2

In Management, Roles & ResponsibilitiesTags Agile, Communication, Management, Project Management, StakeholdersAugust 17, 2020

Alexis Johnson-Gresham and Caitlin Moorman

In our last post, we talked about the differences between linear and circular projects. The distinction is valuable because it can help data teams manage expectations and build processes

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Map with lots of confusing, circuitous paths from the starting point to the goal.

Linear and Circular Projects in Data, Part 1

In Management, Roles & ResponsibilitiesTags Agile, Communication, Management, Project Management, StakeholdersAugust 10, 2020

Alexis Johnson-Gresham and Caitlin Moorman

The nuances of data projects add an extra layer of challenge to project planning and agile project management approaches. Even the most efficient data team must manage the inherent moving-target

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Treat your data products like software products