Clayton Christensen in his brilliant book titled “The Innovator’s Dilemma” spoke about disruptive innovation using the following framework:
While established companies in any sector focus on existing customer needs and sustained innovation at the top of the market, they might leave the space open for new competitors to use simple and disruptive innovation that identify unmet customer needs. These start at the bottom of the market and then relentlessly move up. – See more at: http://www.claytonchristensen.com/key-concepts
It’s a trend we have seen across every sector today with technology often leading the disruption.
Now imagine if we apply this paradigm to the world of Competitive Intelligence (CI); a discipline that is supposed to monitor the changes in the market and the competitive threats for its business? Is CI also monitoring disruptive innovation that is creating in a ripple in its own waters?
Let’s look at 3 companies and 3 specific technology-led ideas by which they could potentially disrupt CI: a) Crowdsourcing, b) Temporal analysis, c) Artificial Intelligence
a) Not far from the madding crowd:
The potential disruptor: Owler.com
Business Model: Crowdsourcing of Competitive Intelligence
How it works: The company launched its API with data on over 10 million companies. Once you subscribe and identify your competitive set, it gives you information on Company Background, History, Financials, Location, Leadership, Industry information and provides reports such as business round-ups, company profiles as well as breaking news alerts, directly to the subscribers’ mobile.
So what?: So the company lets you monitor your competitor set and sends you automated alerts and company profiles. And it has ambitious plans to have profiles for every single company, public or private? So what you ask? Aren’t they just making information search an automated and mobile process without providing real intelligence?
The real differentiation comes from the feature called “Poll Builder” – this allows polls to be conducted for the competitors. These polls could be around revenue, employee strength etc. Now imagine researching a private company where information is at best extremely difficult to access, forget analyse. These polls, even though not completely accurate, could give you an indication of the sentiment about that company.
Why it could be disruptive: A simple bottom of the curve innovation could change the way CI analysts access and look at private company data, in particular.
What could make it fail: Data quality issues could be a killer for this model.
b) Spinning a web of Open Data:
The potential disruptor: Recordedfuture.com
Business Model: Temporal Analysis Engine to understand Real Time Threat Intelligence
How it works: The firm deploys what it terms as a Temporal Analysis Engine to understand history and progression of events of interest, correlate past predictions with actual events and show the results real-time through a visualization layer. It claims to track over 650,000 web data sources. For example, if you were to search for “Driverless Cars” and try to look ahead and see who’s going to dominate the future, the API will help you reduce the noise: signal ratio you get by typing the same text in google search. By visualizing futuristic or predictive statements from companies on this theme, it will show companies other than the usual suspects such as Google who are quietly investing and preparing for this innovation.
So what: It is just another text analysis+social listening+visualization tool that gives you more information with no actionable insight? Well, what differentiates the firm is the ability to use its temporal analysis engine to time-stamp events and analyse forward looking statements and future events such as plans to launch product, protest declarations etc.
Why it could be disruptive: Can its API help CI analysts bring predictive power to analysing news signals? If that happens, it could be powerful.
What could make it fail: In the recent past, the company has been speaking about many use cases from monitoring cyber attacks to terrorist attacks. The impact from the different use cases remains to be seen.
c) Meet the new Storyteller: Big Data
The potential disruptor: Narrativescience.com
Business Model: Transform data into narratives with Artificial Intelligence
How it works: The firm starts off saying “while advances in data science and visualization are helpful, they don’t take you to the last mile”. And the last mile, according to them, is being able to craft the right story and communicate the insights that people can act on. The firm’s Artificial Intelligence (AI) powered platform first identifies the key facts that are foundational for the narrative, uses natural language software to automatically write the content and then delivers 1:1 written communication in a brand-consistent voice.
So what: Is it just a bunch of charts and data? But the firm goes further. It looks at crafting narratives for the usual reports various teams are requested for starting from Fund Portfolio Commentary for Wealth Management and Investment Management firms to marketing and sales performance reports. These reports earlier took weeks to write in the right executive -ready language.
Why it could be disruptive: From showing the data to telling the story, can the firm actually craft the right narrative for the senior leadership? That could not just crunch time but reduce a lot of report writing manual effort.
What could make it fail: Despite the spate of AI driven innovations, the heart of the story you tell, I feel, will still remain with the mind and the pen of the writer. While Narrative Science could conjure up simple, repeatable narratives, it would be hard for them to provide original narratives or commentary.
Crowdsourcing, Temporal Analysis, Artificial Intelligence. 3 disruptive ideas. Will they re-shape the way companies are currently looking at Competitive Intelligence? Going back to Clayton Christensen, that depends on the balance between sustaining innovations and disruptive innovations as compared to the pace of technological progress.
As George Bernard Shaw said: “Some look at things that are, and ask why. I dream of things that never were and ask why not?”
Innovators’ Dilemma indeed. Are you seeing such innovative companies disrupting the traditional way of doing Competitive Intelligence? The 3 companies mentioned here are just samples for a technology-led innovation explosion we are seeing around us. They may or may not be the real disruptors. Would love to hear your thoughts on the disruptors you are seeing in your business.