We’re global beings, traveling at the speed of a trackpad click, reinventing ourselves with a picture and a byline, and managing our professional lives through data controlled by companies such as Facebook and LinkedIn.
But what if I told you that we’re on the threshold of a new data revolution? This movement will harness information about people more efficiently than ever before, and help to build a new layer of professional networking that will promote productive connections and drive business goals.
The movement is called “network intelligence,” and it’s a reimagining of the term that originally referred to the technology used for data analysis. This new movement focuses on people, and builds on the rise of business intelligence and analytics in both startup and corporate environments.
New products built to harness network intelligence will allow for the analysis of relationships between members of a network and their specific skill sets to help achieve business objectives. These products will bridge the gap between business intelligence analytics and goals by adding people back into the equation. After all, every organization is built upon smart and connected people.
Harnessing personal data to drive business goals
Using network intelligence to harness our online information can empower us to make business more efficient. By analyzing the data that exists within our greater network, we can save the time that would have been spent buying lists, sourcing leads or doing research. We can prioritize leads based on the quality of their relationships and their industry connections.
A couple of big players are already trying to build products based on this concept, but their efforts represent just the beginning of this new network intelligence movement.
LinkedIn Sales Navigator
LinkedIn created a network intelligence tool that allows salespeople to search their networks, identify prospects and contact them directly. This “social selling” is great for building relationships and staying aware of changes in a prospect’s career, but LinkedIn has its limitations, too.
The way users engage with LinkedIn is also inconsistent. Some update frequently and actively share insights, while others only use the site to search for jobs. Additionally, LinkedIn doesn’t have comprehensive information about people. Because no one uses the network in a standard way, it’s hard to generalize the data or look at it holistically.
Facebook at Work
With 1.39 billion monthly active users, Facebook is an obvious player in the network intelligence movement. Facebook at Work aims to bring social networking into the workplace. The company has a head start because people are already familiar with its core functionality and use the site daily. They can easily transfer their existing personal profiles to the new enterprise platform.
But Facebook has a problem attracting and keeping younger members. Also, many people so closely identify the site with personal networking that it might be hard to get them to think of the brand as part of professional life. And there are security and privacy issues: Professionals seek a site with enterprise-level security if they’re going to trust it with their business. Facebook hasn’t yet made the case that it can deliver that level of security.
The tools of the (near) future
People need network intelligence tools that are designed for work from the outset. These tools should have built-in methods of aggregating, collecting and analyzing data to help users make informed decisions and productive connections.
The network intelligence tools that will fill this gap should include a few key attributes:
A new social surface: We need a layer over the Web that breaks down data silos and indexes and organizes all the fragmented information about people. We need to make sense of all that information to turn the art of recruiting, sales and partnerships into a science.
Predictive technology: New tools must be capable of discovering and analyzing patterns in data so past behavior can be used to forecast future behavior. Over time, this technology will learn from recommendations and become even more intelligent about relevant results. We must ultimately answer questions such as, “Who are the customers who want to buy the product I’m selling?”
Understanding context: This network intelligence platform must understand you and the context that’s relevant to you. It would be a sort of personalized version of Google PageRank.
Do business for a day and you can see that it’s all about people. Companies might seem like giant machines running of their own accord, but even the largest corporations are built from the personal perspectives of individuals.
The new network intelligence movement has the potential to shape the bridge between the findings of business intelligence analytics and the potential solutions by identifying exactly the right set of people at the right time.