February 27, 2018
Harnessing the 3 A’s to Derive Value from Your Data
I recently wrote on my blog – and spoke at Outsell DataMoney – about data becoming a commodity in the digital economy, just as oil was in the Industrial Revolution.
I mentioned in that talk at DataMoney that while the commodity is of some value, it’s the ecosystem around the commodity and the things that are made possible by the commodity that truly drives innovation.
The 3 A’s of the 2nd Digital Revolution
In what is quickly becoming the second digital revolution, this means making your data:
These 3 A’s are what refine your data, deliver your data, and what truly turns your data into the fuel for innovation.
Making Your Data Autonomous
Making your data autonomous is the most forward leaning and hard to understand aspect of this monetization strategy. Having your product react automatically to the latest data and act on behalf of the user as it arrives can create entirely new concepts.
Take self-parking cars – if you were flooded by the sensor data, would it help you to parallel park? Some, but not much. If you were given step-by-step instructions, would that help more? Yes, but once the car takes that data and uses it autonomously to park your car, what a leap forward that makes.
Imagine that kind of game-changer in healthcare, in public safety, or in entertainment. This, at the end of the day, is what we mean by “Artificial Intelligence” (AI).
Is AI Really for You?
You may think that AI is outside of your needs and that any sort of automatic response is far down the line for your product – but it may not be as far off as you think. In any case, now is the time to prepare your data to make your later insights and automation possible. Break down your data silos, consolidate them into locations that can be cross-referenced (accessible), work on standardizing access with consistent formats (approachable), then leverage that into gaining automated insights.
Don’t Fear the Robot
AI itself is nothing to be feared – having a system automatically respond to incoming data is no different than your thermostat. Whether you have a standard thermostat that responds to one data point like current temperature or a smart thermostat like Nest that leverages many data points, automated reactivity, while it was science fiction yesterday, is innovation today and it will be an expectation tomorrow. No human-looking robot required.
The Journey of a Thousand Miles…
I challenge you to look at your product and find one capability that would provide value if it automatically happened based on incoming data – whether it’s recommendations of features or goods, identifying promising sales leads, or reacting to a customer’s behaviors in real-time to provide assistance (or close a sale). Then look at what it would take to make this happen from a data perspective – is that data accessible and approachable? Like Rockefeller and Standard Oil did during the Industrial Revolution, focus on the pipelines, the refinery, and the ability to deliver your commodity data into action.
Products are moving from you tell them what to do, to them suggesting what they should do, to them taking action automatically and correcting if it was wrong. In a way, they are “asking for forgiveness, not permission.” Data, refined and purified as the new digital revolution’s fuel, is what makes this possible. As we strive for our teams to take “smart risks” and to learn from failure and mistakes, should our approach to data be any different?