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<oembed><version>1.0</version><provider_name>Planview Blog</provider_name><provider_url>https://blog.planview.com/se</provider_url><author_name>Dr. Richard Sonnenblick</author_name><author_url>https://blog.planview.com/se/author/dr-richard-sonnenblick/</author_url><title>Learning From Our Forecasting Foibles - Enrich Consulting</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="rry8r31dAq"&gt;&lt;a href="https://blog.planview.com/se/learning-from-our-forecasting-foibles/"&gt;Learning From Our Forecasting Foibles &#x2013; Enrich Consulting&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://blog.planview.com/se/learning-from-our-forecasting-foibles/embed/#?secret=rry8r31dAq" width="600" height="338" title="&#x201C;Learning From Our Forecasting Foibles &#x2013; Enrich Consulting&#x201D; &#x2014; Planview Blog" data-secret="rry8r31dAq" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>The prevalent tendency to underweight, or ignore, distributional information is perhaps the major source of error of intuitive prediction...The analyst should therefore make every effort to frame the forecasting problem so as to facilitate utilizing all the distributional information that is availab...</description><thumbnail_url>https://media.planview.com/enrich-blog/wp-content/uploads/2016/03/government_and_industry.gif</thumbnail_url></oembed>
