Iceberg IE n°5 : du 18/04/2009 au 04/05/2009 (12 items)

IcebergIntelligenceEconomique – RessourcesIntelligenceEconomique

• Anticiper grâce au Management Profiling

  Le MP est un outil danticipation des actions et stratégies concurrentes.

• Law Firm Competitive Intelligence: CI Pro Interview with Emily C. Rushing

  Law Firm Competitive Intelligence: CI Pro Interview with Emily C. Rushing

  • Topics for our intelligence frequently include: 1) profiling competitors practice areas and clients, 2) identifying business development opportunities for the firm among existing clients and developing strategic targeting programs, and 3) developing intelligence in preparation for business development meetings with existing or potential clients.
  • I am the firms only CI professional. I am directly supervised by the Director of Business Development, indirectly supervised by the CMO, and my role is situated within the Marketing department.

• Building Bridges with the U.S. Intelligence Community

  Une plateforme collaborative pour permettre aux spécialistes de l’IE non gouvernementaux de participer à la collecte et à l’analyse du renseignement de l’état US. Le premier projet visait à mieux identifier la provenance des attaques informatiques subies par la Géorgie l’été dernier. Une démarche public-privé particulièrement intéressante.

  • About three weeks before the start of the Russia-Georgia war last August, the Office of the Director of National Intelligence issued a directive entitled Analytic Outreach. In it, DNI McConnell authorized members of the 16 agencies that comprise the U.S. Intelligence Community (IC) to reach out to people outside the IC, to explore ideas and alternate perspectives, gain new insights, generate new knowledge, or obtain new information.
  • I just decided to act on my own and launched an Open Source Intelligence gathering effort called Project Grey Goose, which brought together an eclectic mix of hackers, spooks, and techies from inside and outside the Intelligence Community.
  • In addition to being a development sandbox, BRIDGE also allows intelligence analysts to interact with outside experts whether they be in industry, academia, or other government agencies at the Federal, State, Local or Tribal level. Alternative analysis has long been a recommended approach to avoid myopic thinking by specialists. BRIDGE provides a platform for debating alternative viewpoints and comparing evidence across agencies, specialties, and borders of all kinds.
  • BRIDGE is designed to enable crowd-sourcing of intelligence applications–following the iPhone AppStore model–by providing a low barrier-to-entry platform to stimulate innovation and enable analysts to discover next generation capabilities that have value to their mission.
  • BRIDGE takes the Wiki model which enabled end users to easily contribute textual content en masse, and extends it to technology providers, enabling them to contribute technologies that enhance the intelligence mission in a matter of days.
  • Another unique characteristic of BRIDGE is that it provides an environment for Analytic Outreach–a place where IC analysts can reach out to expertise elsewhere in federal, state, and local government, in academia, and industry. New communities of interest can form quickly in BRIDGE through the web of trust access control model–access to minds outside the intelligence community creates an analytic force multiplier.
  • Here are three of the six applications currently in use on BRIDGE.
  • Collaborative Analysis of Competing Hypotheses
    • Web-based Analysis of Competing Hypotheses enables analysts to gather evidence collaboratively and think more critically about the plausible scenarios, mitigating bias
    • Collaborative views enable analysts to hone in on differences, making debate more constructive and encouraging deeper reasoning
  • Hot Grinds
    • HotGrinds serves as an evidence-based structured discourse forum at the crossroads of a wiki, a collaboration platform and social network
    • Semantic search, expertise identification, and management overviews of debate provide greater collective awareness and enhanced collaboration
  • Visually Structured Analytic Software
    • Organize ideas from many sources and many analysts into 2D conversation maps, significantly improving efficiency and situational awareness.
    • Identify the strongest evidence on all sides of an issue by tracking individual user credibility and the wisdom of the crowd

• DARPA’s TIGR Project Helps Platoons Stay Alive

  TIGR est un service qui mélange maps et wiki afin de permettre aux soldats US sur le terrain de disposer d’un historique.

  • Well, just as you described, the problem is that in the past, the military has focused on feeding the information up the chain-of-command. The decision-makers are the colonels and generals, and so the soldiers on the ground are just collecting information so they can make big decisions. Now in Afghanistan and Iraq, really it’s the patrol leaders, soldiers on the ground, lower echelon soldiers, captains, lieutenants who need to make decisions.
  • Are they going to take this route or the other route? Should they knock on this door or that door? Has this person ever been seen before or cited before? Does he have useful information? All of those day-to-day decisions are being made at the lowest echelon and we really needed a tool to serve those low-level soldiers. And that’s why TIGR was created.
  • TIGR’s a map-based application where you can go and do searches by defining an area. It could be a rectangle, a circle, a polygon or a route even. And it’ll pull back all of the events and people and places, information along that route or in that region. And it ranges from census collection that was done in the location, names of all of the schools, pictures of schools, videos of an attack that might’ve taken place. Very rich multimedia information will be returned to you for the area that you defined.
  • And so instead of just writing a patrol report that says this happened and hoping someone might read it, you’re just really looking for geospatially relevant information for the mission at hand. If you’re going to take this route and you’re not familiar with this route that you’re thinking of taking, you can look and see how many attacks have taken place; what kind of attacks have taken place; who’s been there before. So all of that information is at your fingertips.
  • that soldiers learn very — at some cost, they learn the area that they’re assigned. That is they learn the people. They learn the villages. They learn the roads. And that knowledge that they gain over the course of a deployment is often times lost. When those soldiers rotate back to the United States and new soldiers come in and are assigned a territory, then they come in without all of that knowledge. They used to come in without all of that knowledge.
  • And one thing TIGR has done is that TIGR has made all of that information available to the soldiers that are coming in new, as it were, to an area, so that they’re acclimated and have good knowledge of the people and the places and the roads and things of this sort when they arrive.
  • So within the next six months or so, we will have a version of TIGR that you can use in the mobile environment.
  • And TIGR’s used not only after patrols but, of course, before the patrols, before the missions so soldiers can do mission planning, et cetera, on TIGR.
  • TIGR is somewhat like Google Maps and Wiki, but the backend of TIGR was very, very carefully designed so that it would work over military networks in these tactical environments where, as you can imagine, the network is very fragile and the bandwidth is sparse. And we did not want to overload the bandwidth, the network. But, at the same time, we wanted the soldiers to be able to share photos and videos and media rich information. So the backend infrastructure of synchronizing the servers in really the right way. What to share across the servers was something that we put a lot of thought into.
  • And so basically what we do is we create a network overlay, a network layer of servers. And we’re not just talking about half a dozen servers; we’re talking about many, many, many servers both in Iraq and Afghanistan. And these servers form a network. And they will share just the information that needs to be shared across the servers. So things like metadata, text, thumbnails are shared across all of the servers. But heavier information like the full-blown Power Point slide or video, you’ll only get the metadata for that.

• Towards the Web of Things: Web Mashups for the Real-World @ MEM 2009

  Une présentation par Dominique Guinard et Vlad Trifa sur le Web of Things.

• Keep it positive : using competitive intelligence to enhance business development

  Présentation d’Eric Garland lors de SCIP 09.

• Luscious Fruit: The Competitive Intelligence That Hangs in a Companys Telephone Tree : ERE.net

  Ou comment utiliser un téléphone d’une manière experte…

• Sourcers Guild – The Social /Business Network for the Names Sourcing Industry

  Site social des professionnels du Names Sourcing

• The Red Teamers Bookshelf

  Belle biblio pour les red teamers.

• Competitor intelligence or competitive intelligence

  Distinction utile entre deux concepts que l’on pourrait (peut-être) traduire par « veille concurrentielle » / « veille stratégique ».

  • Maybe the words competitive intelligence have different meanings for different people.  And that while we assume were all using the same definitions, maybe were not.
  • How many people see it primarily as the study of direct competitors or rivalsIll call this competiTOR intelligence, or TOR for short? 
  • On the other hand, how many see it as the study of a wide range of factorsincluding, but not limited to, rivalsthat can impact the value of their organization?  Ill call this competiTIVE intelligence, or TIVE for short.
  • 
  • So my hunch that competitive intelligence does not mean, in practice, the same thing to all of us was validated, at least among this group.
  • Ill make a hypothesis here that value of intelligence to the organization is created is directly proportional to the extent that the TIVE modela focus on a broad range of organizational opportunities and threatsprevails over the TOR modela focus mainly on direct rivals.  In other words, Im betting that addressing a range of threats (and opportunities) can add greater value than focusing just on direct rivals.

• Useful Approximations in CI

  Comment estimer les chiffres des des concurrents?

  • For instance, our management might want to know how much research and development money has been spent on the latest product from our competitor. This isnt a number that most companies will report publicly. So what do we do? Give up? No, rather we fall back on the article of competitive intelligence faith that there is always an ethical way to give a good answer.
  • Putting all of this together means that we can report a ballpark number to management about the R&D money spent on a new product.
  • So, Marianne Wolk (analyst at Susquehanna Financial Group), used warehouse information reported by Amazon to create a leading indicator of their future sales. That is, if Amazon increased their warehouse square footage, then that meant they were expecting higher sales.
  • One recurring realization is that public companies cannot help but signal their intentions. The challenge is to use what is public to estimate what is not public. We dont have to arrive at exact numbers. Most of the time a useful approximation (with the methods and assumptions described) will be quite valuable to management.