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	<title>Comments on: Analytics &#8211; the dark side?</title>
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	<description>James Taylor on Everything Decision Management</description>
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		<title>By: The dangers of scores in decision making — JT on EDM</title>
		<link>http://jtonedm.com/2009/07/21/analytics-the-dark-side/comment-page-1/#comment-14672</link>
		<dc:creator>The dangers of scores in decision making — JT on EDM</dc:creator>
		<pubDate>Mon, 27 Jul 2009 14:37:47 +0000</pubDate>
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		<description>[...] week I responded to some concerns raised about the dark side of analytics and this prompted a very thoughtful comment from Will Dwinnell who said My fear is that much of the [...]</description>
		<content:encoded><![CDATA[<p>[...] week I responded to some concerns raised about the dark side of analytics and this prompted a very thoughtful comment from Will Dwinnell who said My fear is that much of the [...]</p>
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		<title>By: Will Dwinnell</title>
		<link>http://jtonedm.com/2009/07/21/analytics-the-dark-side/comment-page-1/#comment-14638</link>
		<dc:creator>Will Dwinnell</dc:creator>
		<pubDate>Thu, 23 Jul 2009 23:11:24 +0000</pubDate>
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		<description>Though I am someone who constructs quantitative models for a living, and who is a strong proponent of their use, I will note the following danger: There is frequently a significant knowledge gap regarding the technical nature of these predictive models, between people who construct them and people who consume their output.  My fear is that much of the nuance about what a predictive model is really saying about airline passenger THX1138 is lost, and the security guard at the gate just see that the poor passenger has been rated as &quot;83&quot; (out of 100) by &quot;the system&quot;.  Non-technical people tend to simplify things like this, and I think it would be a shame if the &quot;83&quot; was, by default, given more weight than the word of a citizen.</description>
		<content:encoded><![CDATA[<p>Though I am someone who constructs quantitative models for a living, and who is a strong proponent of their use, I will note the following danger: There is frequently a significant knowledge gap regarding the technical nature of these predictive models, between people who construct them and people who consume their output.  My fear is that much of the nuance about what a predictive model is really saying about airline passenger THX1138 is lost, and the security guard at the gate just see that the poor passenger has been rated as &#8220;83&#8243; (out of 100) by &#8220;the system&#8221;.  Non-technical people tend to simplify things like this, and I think it would be a shame if the &#8220;83&#8243; was, by default, given more weight than the word of a citizen.</p>
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		<title>By: Alison Raffalovich</title>
		<link>http://jtonedm.com/2009/07/21/analytics-the-dark-side/comment-page-1/#comment-14624</link>
		<dc:creator>Alison Raffalovich</dc:creator>
		<pubDate>Wed, 22 Jul 2009 17:51:16 +0000</pubDate>
		<guid isPermaLink="false">http://jtonedm.com/?p=2275#comment-14624</guid>
		<description>I&#039;d have to agree - at the end of the day, it&#039;s people who design analytic models, assign weightings, assess the results and decide whether to take action and what action to take.  We&#039;ve aimed our DataRush technology at delivering speed and power in analytics to, ideally, support more rapid iterations and facilitate the ability to examine more data over a longer period of time - hopefully avoiding some of the decision-making traps you reference.</description>
		<content:encoded><![CDATA[<p>I&#8217;d have to agree &#8211; at the end of the day, it&#8217;s people who design analytic models, assign weightings, assess the results and decide whether to take action and what action to take.  We&#8217;ve aimed our DataRush technology at delivering speed and power in analytics to, ideally, support more rapid iterations and facilitate the ability to examine more data over a longer period of time &#8211; hopefully avoiding some of the decision-making traps you reference.</p>
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