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 three facets to a successful MBR meeting:
As the MBR lead, many of these responsibilities fall on your shoulders. The MBR meeting is resource intensive, high stakes, and complex given the need to manage both the people and content in the meeting. The success of the MBR will
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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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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. …
I have often found that it is difficult to explain to business stakeholders what exactly a data analyst on my analytics team does. And even beyond that, I have sometimes
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Key Performance Indicators (KPIs) are management tools for monitoring and improving business processes. KPIs are helpful in understanding if you’re hitting your business objectives, improving over time, and helping to
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As the new year rolls around, many Data leaders are thinking about (or have already created) 2019 road maps for their team and function. Since Data often works cross functionally
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I often get asked by junior data professionals how they can improve as data scientists. Today I will outline a generic framework for thinking about learning and provide a few
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A hypothetical tech company just completed an A/B test of two experiences, A (the test) and B (the control). The test was set up properly and executed successfully. The following
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The sprint prioritization meeting is integral to the agile process. While many people may be more familiar with meetings such as sprint planning, stand up, back log grooming, and retro,
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A lot of Data Science literature focuses on the mathematical and algorithmic aspects of model building. This is after all what much of academia spends time grappling with. However the
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