Competitive Intelligence

Tactical, Operational & Strategic Analysis of Markets, Competitors & Industries

Machines of the future. Kill Sarah Conner or kill your job?

Some scary reading from NYU interactive telecommunications Professor, Clay Shirky, who was interviewed on io9 a couple of weeks ago on the subject of his new book, “Here Comes Everybody: The Power of Organizing without Organizations”.

The premise (and I’ll preface that I am no scholar of social web evolution) is that there is a growing trend towards a model where there is a large community of content creators (think personal video creators) who don’t really get paid for producing this content. Along comes someone who can create a tool to take advantage of that material and create a revenue model around it (think Youtube). You can see a lot of this happening already in a number of social sites:

- Flickr - built around a community’s photo collection.
- Napster or Torrents - built around a community’s music and movie collection.
- Facebook and MySpace - built around a community’s interaction with each other.
- Linkedin - built around a community’s contacts.

Take this a step further and think about what you do for a living?

CI at its most basic is taking a sample of information on a market or competitor and predicting future decisions or actions that a competitor or industry may make. (I know “good CI” is much more than this, selling the impact/threat or opportunity to people who matter in your company’s decision making process - but I’ll get to that in a second)

So what we do each day is take a bunch of information and make a judgement call on what our competitors might do. This is based on financials, marketing releases, patent awards, domain registration, rumour and a whole host of other inputs.

Like what the Industry Standard is doing. Here you can effectively “bet” on what the market will do, with a twist. You’re not betting on companies, but rather, betting on predictions. I’ve been right on Google’s stock price being lower than $500 at the end of Q1. I’ve been right about Salesforce.com not being acquired by the end of Q1. I’ve made a sweet little profit of $15K since I’ve joined. It’s fun and not really serious, however, think about where some of the proposed predictions are coming from? Are they from competitors, disgruntled employees, stakeholders? Now the game gets interesting. What if this engine gathered a large enough community for its predictions to be more often right than wrong?

Much like Shirky’s proposition, basic market knowledge is pretty easy to come by. All it would take would be a mechanism to take advantage of all that free knowledge. We all have feeds and massive sources of information. What we as CI practitioners do is act as the machine. We filter all of that info and come up with the insight needed to make or refine business decisions. As Business Intelligence and predictive software becomes better, our role as a CI professional will become much more centred on how we leverage the available data. More managing the flow of data and looking for leading indicators of changes from the norm or changes that deviate away from what we “expect” to happen. What would be the leading indicators of a competitor tanking in a quarter? What are the leading indicators that a competitor will create a partnership that could impact you?

The machine of CI is more about the patterns and less about profiles and SWOTs. They are important and help is to explain what we do. The challenge moving forward is how to build up those data flows so you can build your own predictive tools. I’m going to have a crack at it as well and document what happens.

In the meantime focusing on the Three A’s of CI will continue to build up your brand and give you access to more of the data you need to predict the future.

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