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	Comments for David Ohnstad	</title>
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	<link>https://davidohnstad.com/</link>
	<description>Senior Data Product Manager &#124; AI, SaaS &#38; Data Strategy &#124; Duluth, MN</description>
	<lastBuildDate>Mon, 07 Sep 2026 14:22:50 +0000</lastBuildDate>
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		Comment on Data Product Manager Salary Negotiation: Why I Left $47K by Data Product Team Structure: Why $180K Failed in 90 Days - David Ohnstad		</title>
		<link>https://davidohnstad.com/data-product-manager-salary-negotiation-mistake/#comment-791</link>

		<dc:creator><![CDATA[Data Product Team Structure: Why $180K Failed in 90 Days - David Ohnstad]]></dc:creator>
		<pubDate>Sat, 05 Sep 2026 09:00:14 +0000</pubDate>
		<guid isPermaLink="false">https://davidohnstad.com/?p=446#comment-791</guid>

					<description><![CDATA[[&#8230;] I had no structural authority to influence. This is the thing most companies get wrong about data product manager salary negotiation: they pay you for accountability but deny you the authority to execute. That gap doesn&#8217;t [&#8230;]]]></description>
			<content:encoded><![CDATA[<p>[&#8230;] I had no structural authority to influence. This is the thing most companies get wrong about data product manager salary negotiation: they pay you for accountability but deny you the authority to execute. That gap doesn&#8217;t [&#8230;]</p>
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		Comment on Data Product Management: Why 82% of Analytics Fail by Data Product Manager Salary Negotiation: Why I Left $47K - David Ohnstad		</title>
		<link>https://davidohnstad.com/data-product-management-analytics-failure/#comment-787</link>

		<dc:creator><![CDATA[Data Product Manager Salary Negotiation: Why I Left $47K - David Ohnstad]]></dc:creator>
		<pubDate>Wed, 02 Sep 2026 09:00:44 +0000</pubDate>
		<guid isPermaLink="false">https://davidohnstad.com/?p=309#comment-787</guid>

					<description><![CDATA[[&#8230;] &#8220;they&#8217;re building internal tools, not revenue features.&#8221; That logic ignores that 82% of analytics initiatives fail specifically because teams treat data products as internal tooling rather than products with real [&#8230;]]]></description>
			<content:encoded><![CDATA[<p>[&#8230;] &#8220;they&#8217;re building internal tools, not revenue features.&#8221; That logic ignores that 82% of analytics initiatives fail specifically because teams treat data products as internal tooling rather than products with real [&#8230;]</p>
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		Comment on Data Product Manager Org Structure: Why Reporting Lines Fail by Non-Technical PMs Build Better Data Products - David Ohnstad		</title>
		<link>https://davidohnstad.com/data-product-manager-org-structure-reporting-2/#comment-784</link>

		<dc:creator><![CDATA[Non-Technical PMs Build Better Data Products - David Ohnstad]]></dc:creator>
		<pubDate>Tue, 01 Sep 2026 11:07:36 +0000</pubDate>
		<guid isPermaLink="false">https://davidohnstad.com/?p=245#comment-784</guid>

					<description><![CDATA[[&#8230;] to evaluate feasibility, then add technical skills as a lens to sharpen prioritization. Understanding how reporting structures impact data product success also helps clarify where organizational design matters more than technical [&#8230;]]]></description>
			<content:encoded><![CDATA[<p>[&#8230;] to evaluate feasibility, then add technical skills as a lens to sharpen prioritization. Understanding how reporting structures impact data product success also helps clarify where organizational design matters more than technical [&#8230;]</p>
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		Comment on Data Product Prioritization: Managing Competing Stakeholder Requests by Data Product Execution: Why Frameworks Fail in Practice - David Ohnstad		</title>
		<link>https://davidohnstad.com/data-product-prioritization-competing-stakeholders/#comment-776</link>

		<dc:creator><![CDATA[Data Product Execution: Why Frameworks Fail in Practice - David Ohnstad]]></dc:creator>
		<pubDate>Mon, 31 Aug 2026 16:32:34 +0000</pubDate>
		<guid isPermaLink="false">https://davidohnstad.com/?p=222#comment-776</guid>

					<description><![CDATA[[&#8230;] For more on this topic, see data product prioritization stakeholder management. [&#8230;]]]></description>
			<content:encoded><![CDATA[<p>[&#8230;] For more on this topic, see data product prioritization stakeholder management. [&#8230;]</p>
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		Comment on Data Product Manager Org Structure: Why Reporting Lines Fail by Data Product Governance: Why Cross-Functional Teams Fail - David Ohnstad		</title>
		<link>https://davidohnstad.com/data-product-manager-org-structure-reporting-2/#comment-766</link>

		<dc:creator><![CDATA[Data Product Governance: Why Cross-Functional Teams Fail - David Ohnstad]]></dc:creator>
		<pubDate>Wed, 26 Aug 2026 09:16:30 +0000</pubDate>
		<guid isPermaLink="false">https://davidohnstad.com/?p=245#comment-766</guid>

					<description><![CDATA[[&#8230;] Data Product Manager Org Structure: Why Reporting Lines Fail covers the structural challenges of where data PMs sit in the organization—whether they report to engineering, product, analytics, or a dedicated data office. But reporting structure alone does not solve governance. David Ohnstad has seen data PMs report directly to the Chief Data Officer and still lack decision authority because governance was never formalized. [&#8230;]]]></description>
			<content:encoded><![CDATA[<p>[&#8230;] Data Product Manager Org Structure: Why Reporting Lines Fail covers the structural challenges of where data PMs sit in the organization—whether they report to engineering, product, analytics, or a dedicated data office. But reporting structure alone does not solve governance. David Ohnstad has seen data PMs report directly to the Chief Data Officer and still lack decision authority because governance was never formalized. [&#8230;]</p>
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		Comment on Data Product Management Myths: What Actually Matters by Data Product Managers: Stop Solving the Wrong Problem - David Ohnstad		</title>
		<link>https://davidohnstad.com/data-product-management-myths-debunked/#comment-765</link>

		<dc:creator><![CDATA[Data Product Managers: Stop Solving the Wrong Problem - David Ohnstad]]></dc:creator>
		<pubDate>Wed, 26 Aug 2026 09:16:13 +0000</pubDate>
		<guid isPermaLink="false">https://davidohnstad.com/?p=406#comment-765</guid>

					<description><![CDATA[[&#8230;] opens but not decision changes, and who mistake stakeholder consensus for validated demand. The data product management myths persist because the underlying skill gaps are invisible until a product launches and nobody uses it [&#8230;]]]></description>
			<content:encoded><![CDATA[<p>[&#8230;] opens but not decision changes, and who mistake stakeholder consensus for validated demand. The data product management myths persist because the underlying skill gaps are invisible until a product launches and nobody uses it [&#8230;]</p>
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		Comment on Data Product Adoption: Why Dashboards Fail Without User Strategy by Data Product Adoption: Why High Login Rates Miss the Mark - David Ohnstad		</title>
		<link>https://davidohnstad.com/data-product-adoption-dashboard-failure/#comment-755</link>

		<dc:creator><![CDATA[Data Product Adoption: Why High Login Rates Miss the Mark - David Ohnstad]]></dc:creator>
		<pubDate>Mon, 24 Aug 2026 09:21:03 +0000</pubDate>
		<guid isPermaLink="false">https://davidohnstad.com/?p=246#comment-755</guid>

					<description><![CDATA[[&#8230;] Data product debt doesn&#8217;t announce itself. It accumulates silently while your dashboards keep refreshing and your pipelines keep running. You discover it when a critical stakeholder stops using your product, when a downstream team builds a duplicate solution, or when an executive asks a question your data product should answer but can&#8217;t. By then, you&#8217;re not fixing a small issue. You&#8217;re recovering trust. For more on this, see Why dashboards fail without strategy. [&#8230;]]]></description>
			<content:encoded><![CDATA[<p>[&#8230;] Data product debt doesn&#8217;t announce itself. It accumulates silently while your dashboards keep refreshing and your pipelines keep running. You discover it when a critical stakeholder stops using your product, when a downstream team builds a duplicate solution, or when an executive asks a question your data product should answer but can&#8217;t. By then, you&#8217;re not fixing a small issue. You&#8217;re recovering trust. For more on this, see Why dashboards fail without strategy. [&#8230;]</p>
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		Comment on Non-Technical PMs Build Better Data Products by Data Product Management vs. Standard PM: Key Differences - David Ohnstad		</title>
		<link>https://davidohnstad.com/non-technical-pms-data-products/#comment-741</link>

		<dc:creator><![CDATA[Data Product Management vs. Standard PM: Key Differences - David Ohnstad]]></dc:creator>
		<pubDate>Sun, 23 Aug 2026 03:49:58 +0000</pubDate>
		<guid isPermaLink="false">https://davidohnstad.com/?p=407#comment-741</guid>

					<description><![CDATA[[&#8230;] is why understanding non-technical product managers data products challenges matters—the technical complexity is real, but the organizational complexity is what [&#8230;]]]></description>
			<content:encoded><![CDATA[<p>[&#8230;] is why understanding non-technical product managers data products challenges matters—the technical complexity is real, but the organizational complexity is what [&#8230;]</p>
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		Comment on Data Product Management: Why 82% of Analytics Fail by Data Product Hiring: Why Technical Requirements Backfire - David Ohnstad		</title>
		<link>https://davidohnstad.com/data-product-management-analytics-failure/#comment-740</link>

		<dc:creator><![CDATA[Data Product Hiring: Why Technical Requirements Backfire - David Ohnstad]]></dc:creator>
		<pubDate>Sun, 23 Aug 2026 03:49:29 +0000</pubDate>
		<guid isPermaLink="false">https://davidohnstad.com/?p=309#comment-740</guid>

					<description><![CDATA[[&#8230;] with PMs who can write elegant schemas but cannot explain why the product matters. As explored in Data Product Management: Why 82% of Analytics Fail, the root cause of most analytics failures is not bad technology—it is bad problem [&#8230;]]]></description>
			<content:encoded><![CDATA[<p>[&#8230;] with PMs who can write elegant schemas but cannot explain why the product matters. As explored in Data Product Management: Why 82% of Analytics Fail, the root cause of most analytics failures is not bad technology—it is bad problem [&#8230;]</p>
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