The CI Process: Simplified
When working in the field of competitive intelligence (CI), there is an abundance of information available and many possible routes to take when investigating a topic. Those who are just beginning in the field may ask where to start, while seasoned professionals sometimes need to take a step back and re-evaluate their basic approach. One way of looking at the process is to consider an analogy of how to fuel a car; or in the case of CI, how to power your projects.
Data Collection: Drilling
The first step of the CI process involves gathering all of the relevant data. Think of this as drilling for oil: you’ll want to dig deep to obtain the raw material for your project. It’s important to sit down with your team and perhaps involve consultants to define the scope of your data collection before beginning. Using a tool to help you gather data saves an immense amount of time and ensures that you’re covering all your bases so as not to miss relevant sources. A tool will also enable you to organize the information into meaningful classifications and facilitate collaboration with colleagues.
Next comes the oil refining process; in our case this translates to sifting through a large amount of data to find the relevant pieces. At this stage in the process, there are two great advantages to working in a team. The obvious reason is that you can divide up the work and lighten the load for each individual. The second reason, which is sometimes overlooked, is that there is a huge human element at play in data analysis. Two people can look at a piece of information and interpret it completely differently. Take the example of the photo of the dress which went viral on the Internet in February of 2015: viewers were divided as to whether the striped dress pictured on the Tumblr account by Swiked was white and gold or blue and black.
The human analysis is a critical element in the CI process -- this is precisely what converts raw data into knowledge. Even terabytes of data don’t bring any real value to businesses unless someone looks at the data and translates it into actionable information. The dress example highlights how subjective data can be. Given that people can interpret differently or identify different pieces of information as important, it is useful to have multiple colleagues analyzing together as much as resources will allow.
One of the greatest challenges for CI professionals is meeting the expectations of their internal customers. Sometimes the C-Suite doesn’t place enough importance on CI or other departments don’t have the desired visibility into the work of the CI team. The best way to combat this issue is to ensure that information is being disseminated in the most appropriate form possible. Just as some cars run on diesel and others on unleaded, internal customers may prefer different deliverables. This can take the form of a newsletter, access to a dashboard in your CI tool, a PowerPoint presentation or an in-person briefing, to name a few options. Be sure to keep the dialogue going in both directions, so that both parties understand each other’s expectations and communicate effectively.
These 3 major steps of defining the scope/gathering data, analyzing, and distributing information make up the framework of a CI project. This fundamental process is the fuel that enables business decision-makers to drive the company in the right direction.
If you'd like to learn more about how a CI tool can help you improve your processes, click here for a live demo.
The 7 Habits of Highly Successful Intelligence Analysts
Written by Jerome Maisch
Marketing Manager @digimindci. Passionate about big data & social marketing. Photography, music and hiking lover