There are two kinds of Content Discovery for Enterprises: INTERNAL and EXTERNAL. Internal Content Discovery has to do with every piece of "Content" that the Enterprise "owns"; every piece of "media", from Invoices to Spreadsheets to Documents to Emails to Digital Images. Anything and everything that is communicated or shared between anyone within an Organization is content that can be "discovered". This can be done through some form of "content audit" and a vast body of literature exists on the subject (for starters, see: Discovery - for legal its legal counterpart - and Digital Asset Management, Enterprise Content Management, Information Lifecycle Management, and so forth). I want to talk about External Content Discovery where we are dealing with digital objects and their informational content, not their intrinsic value, or digital artifactual value.
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| Image via CrunchBase |
There are many reasons a Company might want to go foraging for content outside its four walls. Usually, the purpose is to acquire some kind of competitive or business intelligence. It can take place anywhere that Content, i.e. any "media" whatsoever, any piece of communication whatsoever, can be found, but for our purposes we are monitoring the World Wide Web, one of the richest sources of content pertinent to corporations and their strategic foresight. There are many ways to "monitor" the web; a virtual panoply of tools exist, from newsreader applications to more formal "discovery engines", tools for acquiring "social media intelligence".
It's up to these newly minted "discovery agents" to build a Content Discovery grand
strategy and as was indicated, content discovery tools abound. A few
examples are Trap.it, Eqentia, Trove, Zite, Google Reader, etc. Twitter,
Facebook, and Google+ are also great sources of Content relevant to
your Organization. But if all these "tools" frighten you, you really
need nothing more than a organic, vanilla search engine, and for that
Google Search, though not the best, will certainly suffice.
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| Image via CrunchBase |
As previously mentioned, there are many reasons or "purposes" for engaging in Content Discovery outside the Enterprise. Usually, though, its purpose is to find "auxiliary information", "external knowledge", "side information", that can be collected and analyzed and used to provide some form of "intelligence" that will aid the Company in question in their quest to Innovate and stay Competitive or "Cutting Edge". It aims to attain a situational understanding or assessment through "Situational Awareness".
Content Discovery involves the Gathering of information, i.e. "Content". Content is any type of medium whatsoever, as stated before. The Collection phase of the Discovery process involves a) finding credible sources of information, b) collecting content or information from those sources and there is a third phase c) what you do once you've amassed said collection (which involves various forms of storing and organizing, classifying, data analysis, social data analysis, content analysis, business intelligence, collaborative intelligence, predictive analytics, etc.
In essence, the Gathering phase involves any form of what can be called "Environmental Scanning":
I will leave it at the Gathering phase for now and continue in a second article which will focus on the Relevance Paradox in decision-making / decision processes in certain corporations. If you enjoyed this article and what to pursue your readings, there may be something of worth to you in an old article I wrote on market signals which can be found here. The Market for Scepticism + The Virtue of Failure
In the next article or series of articles, I will talk more about the kinds of auxiliary information corporations are currently looking for, and how they may not be making optimal decisions in what I call the priority queue, or queuing process. So we look at suboptimal cases of that. I will get into market signals, social media intelligence, the brand graph, scepticism in business, failure analysis, how failure contributes to the advancement of Design Science, a bit on Taxonomies and Data Analysis.
In the next article or series of articles, I will talk more about the kinds of auxiliary information corporations are currently looking for, and how they may not be making optimal decisions in what I call the priority queue, or queuing process. So we look at suboptimal cases of that. I will get into market signals, social media intelligence, the brand graph, scepticism in business, failure analysis, how failure contributes to the advancement of Design Science, a bit on Taxonomies and Data Analysis.
Hope that you are well. Take care, thanks for stopping bye, and keep stay tuned - more is coming. If you want to get in touch, many channels are available.
You can find me here:
On Twitter: @jonasthanatos
