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	<title>Comments on: Bad data can mean more than bad research</title>
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	<link>http://www.meaning.uk.com/analysis/research-industry/bad-data-can-mean-more-than-bad-research/</link>
	<description>Consulting services in research technologies, systems and organizations</description>
	<lastBuildDate>Sun, 13 Jun 2010 20:44:13 +0000</lastBuildDate>
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		<title>By: TimH</title>
		<link>http://www.meaning.uk.com/analysis/research-industry/bad-data-can-mean-more-than-bad-research/comment-page-1/#comment-43</link>
		<dc:creator>TimH</dc:creator>
		<pubDate>Tue, 02 Feb 2010 13:01:48 +0000</pubDate>
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		<description>Interesting article. A couple of points

   DP/Technical side.
      I&#039;ve come across similar issues raised in the article. The following may appear over-semantic but despite our industry introducing QMS systems such as BS5750 and its successors we still seem to be reliant on &#039;Quality Control&#039; which as I understand it is incomptabible with QMS. QC is something that occurs at the end of the process just before shipping wheras QMS is meant to achieve quality at all stages of the process. There seems to be an unwritten view that &#039;nobody will die&#039; as a result of poor data so it doesn&#039;t really matter if we continue using &#039;traditional&#039; approaches. The article emphasises that our data may be important than we perhaps sometimes appreciate.  I would like us to learn from other industries who are perhaps more advanced than ourselves in dealing with these issues. Maybe if we started looking at our specs, scripts or whatever as &#039;mission critical&#039; things may start to get better.

   Our clients, internal &amp; external.
     The impression I&#039;m getting is that clients are increasingly saying that the MR industry needs to provide less in the way of data and information and more in the way of &#039;insight&#039; or whatever word best describes 
 that which will make the presentation audience jump out of their seats. They seem to be saying that we&#039;re too focussing building a better widget and not enough on building the right widget. If this is correct then the first point I made will simply be navel-gazing unless we can persuade our clients of a clear  relationship between data integrity and insight. A more systematic approach to data integrity will inevitably require changes in thinking patterns, training and investment. The question &#039;Is it worth it?&#039; will need a suitable answer.</description>
		<content:encoded><![CDATA[<p>Interesting article. A couple of points</p>
<p>   DP/Technical side.<br />
      I&#8217;ve come across similar issues raised in the article. The following may appear over-semantic but despite our industry introducing QMS systems such as BS5750 and its successors we still seem to be reliant on &#8216;Quality Control&#8217; which as I understand it is incomptabible with QMS. QC is something that occurs at the end of the process just before shipping wheras QMS is meant to achieve quality at all stages of the process. There seems to be an unwritten view that &#8216;nobody will die&#8217; as a result of poor data so it doesn&#8217;t really matter if we continue using &#8216;traditional&#8217; approaches. The article emphasises that our data may be important than we perhaps sometimes appreciate.  I would like us to learn from other industries who are perhaps more advanced than ourselves in dealing with these issues. Maybe if we started looking at our specs, scripts or whatever as &#8216;mission critical&#8217; things may start to get better.</p>
<p>   Our clients, internal &amp; external.<br />
     The impression I&#8217;m getting is that clients are increasingly saying that the MR industry needs to provide less in the way of data and information and more in the way of &#8216;insight&#8217; or whatever word best describes<br />
 that which will make the presentation audience jump out of their seats. They seem to be saying that we&#8217;re too focussing building a better widget and not enough on building the right widget. If this is correct then the first point I made will simply be navel-gazing unless we can persuade our clients of a clear  relationship between data integrity and insight. A more systematic approach to data integrity will inevitably require changes in thinking patterns, training and investment. The question &#8216;Is it worth it?&#8217; will need a suitable answer.</p>
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