12 Jun 2010 mindcrime   » (Master)

Capability Case #2: Technology Radar

Following on from yesterday's post about Project Shelley Capability Case #1: Collaborative Filtering for Information Retrieval, here is the next detailed capability case for Project Shelley Capability Case #2: Technology Radar. Also available in (pdf) and (odt) format.


Technology Radar



              Identify technological developments - which may present either a threat to the enterprise, or a groundbreaking new opportunity - as early as possible. 



New technologies are being developed at a dizzying pace.  Worldwide, private enterprises, academic researchers, and open-source hackers are all constantly pushing the envelope, developing new approaches and tools.   Some of these advancements may represent a huge threat to your organization, perhaps by enabling a competitor to cannibalize your existing business model with a much less expensive alternative.  Others may represent an opportunity to break new ground with products, product features, or services that can represent sizable new revenue streams. It is advantageous to identify these advances as soon as possible, in order to out maneuver the competition and take maximum advantage of new developments.


As Downes and Mui point out in their book Unleashing the Killer App, this kind of awareness requires a technology radar consisting of a fat pipeline, a sensitive radar screen and sophisticated intelligence.


Solution Story:

              At MegaCorp, developers of the market leading Flozzit product, leaders are constantly jousting with rival HyperCorp, each striving to release the most advanced product in order to steal customers from the other.  Recently, HyperCorp has released a multiple new versions with features that no one at MegaCorp had considered, or believed possible at the time.  After the most recent release, MegaCorp leaders dug in and discovered that HyperCorp had integrated advanced technology developed by researchers at Miskatonic University.  “Why,” asked MegaCorp CEO Howard Phillips, “did we not know about this sooner? This is actually a better fit for our product..  if we had done this first, we could have taken a huge chunk of HyperCorp’s market share, instead of letting them jump further in front of us”  No one had an answer.

              In order to address this lack of awareness of emerging technologies, MegaCorp decide to implement a Technology Radar.  An “emerging technologies” channel is created, where every member of the organization can submit links to documents, articles and news-feeds that touch on technologies related to MegaCorp’s industry.  Users throughout the organization vote, tag and comment on each submission, allowing the collective intelligence of the organization to filter the less important items, while pushing the key ones to the top.  Product Managers and executives begin to make browsing the latest ‘top items’ on the channel a routine habit... and some users configure the system to send them a dynamic alert via instant messaging when an entry reaches a certain score.

              A few months later, the Flozzit Product Manager receives such an instant message... the link is to an article published by Arkham University, announcing the development of a  new algorithm which solves a problem that MegaCorp engineers have been struggling with.   AU has released the source code under a permissive open-source license, and MegaCorp begin integrating the new approach, and also recruit two of the students from AU who worked on the project.

              Using the new technology, MegaCorp are able to deliver a new release of Flozzit with several features which they believe that HyperCorp cannot match.  Amazingly, the new HyperCorp release comes out six weekslater, and is almost totally equivalent to the new Flozzit.

CEO Phillips talks to his mangers and explains why he’s happy with developments; “We weren’t able to leap-frog them this time... but if we hadn’t rolled that new stuff out when we did, their new release would have been a dagger into our heart.    Now we’ve shown them, and the market, that they aren’t always the ones on the forefront of technical advancements.  And the two new guys we hired from Arkham are already hard at work on some stuff that’s going to blow everybody away.”



Mature Commercialization             



Corporate culture which fosters a “Not Invented Here” syndrome. 

Lack of incentives for participation in the system.

Lack of belief in the utility of the system.

Lack of participation in the system by executives and other decision makers.





Business Results:

              Better awareness of technological advances which are significant to the organization.                            Ability to gain early mover advantage over competitors by incorporating advances              


Lower risk of being one-upped by the competition with a significant technical             




              Share links to web-sites, documents and other items of interest

              Categorize links by topics using channels

              Tag links with specific keyword

              Rank items by voting them “up” or “down”

              Search and filter by topic, keyword, and/or score

              Sort view by various statistical measures, such as “all-time score”, “hotness”, and              


Dynamic alerting, via email, instant messaging, etc.,  when items reach certain thresholds.


Typical Use Scenarios and Guidance:

              A technology radar is established to pull in information from many disparate sources:

              RSS feeds, Twitter streams, email lists, and user submitted links to websites, documents               and articles.  Collaborative filtering through collective intelligence is used to filter the                             lower value submissions, while ensuring the relevant information gains visibility.               

Employees through the organization view the radar, through the “emerging technologies”              

channel and take advantage of the information. 


In some cases this may represent a “bottom up” scenario, such as an engineer finding an interesting new library which enables a feature the engineer likes... he quickly knocks out a prototype, shows it to senior management, and it is eventually adopted into a product release.  In another case, this may be a “top down” scenario, where a senior leader discovers a new technology, and issues a mandate that R&D investigate it’s applicability to their product.


Applicable Technologies:

              Fogbeam Labs “Project Shelley”

Other corporate knowledge repositories (blog servers, forums software, document              

management systems, HR management systems, etc.)

Existing Data Warehouses / Databases / Knowledgebases

External information sources (web pages, databases, etc.)


Implementation Effort:




              Project Shelley can easily integrate any knowledge source which can be accessed via

HTTP and which exists in a format which can be parsed into text tokens for indexing by              

Lucene.  Where text extraction is not possible, location through metadata is still possible (ex, mp3 audio files, video, etc).



Integration Mechanism:

              RSS feeds, HTTP, OpenSearch


Integration Status:



Syndicated 2010-06-12 17:02:14 (Updated 2010-06-12 17:03:15) from openqabal

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