Re: Amazon Ratings - One Thumb Down #ratings #prediction-markets

Ravi Arora


I 100% agree with what Bruce has to say. An inefficient and ineffective
system is as good as having no system.

a) But the fact remains how does a company ensure that people
b) People do not participate in activities that they feel are not
c) Why review a document to store it? Best is to generate a document
JIT when it is required.

Thank you,


-----Original Message-----
From: sikmleaders@... [mailto:sikmleaders@...]
On Behalf Of Bruce Karney
Sent: Friday, January 20, 2006 7:00 AM
To: sikmleaders@...
Subject: [sikmleaders] Amazon Ratings - One Thumb Down

Hi all,

In Tuesday's call, I made a comment about why I don't think "Amazon-
style ratings" are an effective KM strategy. Let me explain briefly
why I believe that, and what I think is a better approach.

Let me contrast two kinds of reviews or rating schemes. These are
not the only two kinds, but they represent the opposite ends of a

1. Peer review, prior to publication: This is the standard used by
scientists and academics. In essence, drafts of articles are
circulated to "experts" who offer advice and input prior to
publication. This input is used by the author (and perhaps the
editor of the journal) to improve the work BEFORE it is exposed
(published) to a wide audience.

2. Consumer review, after publication: Amazon, ePinions, and many
similar rating and awards systems use this approach. Because these
post-publication reviews cannot affect the published work, they
are "criticism" in the literary sense. In Amazon's case, no
credentials are required to post a review, so the reviewers are not
peers of the authors. Nobel prize winners and your local pizza
delivery guy have an equal voice in Amazon-land (and the pizza guy
probably has more free time).

Being able to write one's own review is a satisfying thing for the
reviewer, especially since it has only become possible to do this in
the last few years. However, the only way Amazon reviews impact the
world at large is to pull more readers toward a book or push a few
away. Isn't it better, especially in a business context, to use

That's what Peer Review is designed to do. If business KM systems
can't support pre-publication Peer Review, they should at the very
least focus on post-publication Peer Review and document improvement.

I also mentioned that at HP, where I used to work, most document
ratings were 4's or 5's on a scale of 1-5. I have located a copy of
study I did on the topic earlier in the year, and would like to
share my findings:

For a sample of 57 "Knowledge Briefs," which are 6-12 page technical
documents desighned to inform and enlighten, there were 12,295
downloads and only 53 ratings/reviews. This is a ratio of 1 review
per 232 downloads, and slightly less than one review per document.

ALL ratings were either 4 or 5. The 53 reviews were provided by 40
different individuals, so the vast majority of people who submitted
a review submitted only one, meaning (perhaps) that they lacked a
valid base for comparing the Knowledge Brief they were reviewing to
any other Brief. The most reviews submitted by a single person was
7, and the second-most was 3.

I contend that if you were perusing a listing of Knowledge Briefs on
a given subject, all of which were either unrated or had ratings
between 4.0 and 5.0, you would not have information that would steer
you towards best documents or away from poor documents. You would
believe that any of the documents could be worthwhile, inasmuch as
none of them had low scores. Therefore, the rating scheme provides
NO value to the prospective reader. Worse yet, if there were a
documented rated 1, 2 or 3, that rating would probably be a single
individual's opinion because of the infrequency with which Knowledge
Briefs are rated at all.

My conclusion: don't RATE documents, but create systems to provide
detailed written feedback from readers to authors BEFORE publication
if possible, or AFTER publication if that's the best you can do.

Bruce Karney

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