Making “work intelligence systems” work for competitive intelligence

Knowledge management consultant Alan Pelz-Sharpe has come up with a new phrase – “work intelligence systems” – to describe “using AI to converge data sources and insights from employees, customers, operations, and processes into a unified whole, the goal being to drive better business decision making.”

Hard to argue against the merits of such a system. In fact, Northern Light is a true believer – we’ve been way ahead of the curve when it comes to deploying AI-based capabilities in market and competitive intelligence portals for over five years.

Pelz-Sharpe makes an important point: “When it comes to running your business, making critical decisions, planning, and transforming, [AI systems] should always be in a supporting, not the leading, role.”

We agree. The value of AI in market and competitive intelligence portals is in presenting the most relevant information to a business professional tasked with making a judgement or decision based upon it – not in making the decision for them.

There’s nothing special about a search engine presenting a list of relevance ranked documents to a user. What is special – and where AI comes into play – is the computer identifying strategically relevant concepts within the documents discovered in a search, and then automatically synthesizing those concepts into a coherent summary that accelerates the user’s time-to-insight. Because for the human decision maker, absorbing an insights summary is a lot faster and more efficient than scrolling through a virtual pile of documents, most of which the typical user would never open. Now that’s a valuable use of machine learning technology in support of the human being.

Or consider the utility of a business-oriented version of an online shopping portal’s “since you bought x, you might like y” suggestions feature. We’ve all come to expect such capability in our personal lives; why not in our work lives? In a market and competitive intelligence portal, it would work like this: A user selects documents of interest from the original search results list, then clicks a button and the system rewrites the search query to automatically generate a new, refined search of the topic that produces even more specific and relevant results. Taking that concept a bit further, AI also can add value by automatically generating content recommendations for each user based on their document download history.

The obvious next step for AI in market and intelligence portals is having the computer answer a direct question based on an instantaneous search and distillation of information stored in the content collections attached to the portal.  Not to make a decision on behalf of the human user, but to better inform the human decision-maker.

As Pelz-Sharpe says, “AI can and should be used to support senior white-collar work, not replace and automate those jobs” – which is precisely what Northern Light’s machine learning-based capabilities do for market and competitive intelligence content discovery and analysis.