Second Derivative: The Accelerating Rate of Change
- May 30, 2017
In calculus, the second derivative is the measure of instantaneous acceleration or velocity of a function of a function f. For example, the second derivative of the position of a vehicle with respect to time is the instantaneous acceleration of the vehicle, or the rate at which the velocity of the vehicle is changing with respect to time.
The second derivative is a measure of how fast things are changing and in Leibniz notation, it looks like this:
Where the last term is the second derivative expression[1].
On a graph, the second derivative corresponds to the curvature or concavity of the graph. The graph of a function with a positive second derivative bows downward (that is, is concave when viewed from above), while the graph of a function with a negative second derivative curves in the opposite way (see Figure 1).
Figure 1: The Second Derivative or Rate of Instantaneous Acceleration
The reason why I’m taking everyone back to their high school calculus days isn’t because I’m masochist (which I am) but is to highlight something that is fundamentally transforming our society – which is the instantaneous acceleration of how new technologies are transforming how we do business and how we live.
Many organizations that have spent the past several years trying to understand and ultimately monetize their big data are now being over-whelmed by the potential and hype of the Internet of Things; that is, the explosion of additional data sources from wearables, devices, beacons, onboard sensors, and more, which are now available for our consumption. While not an exact measure, one can see in Figure 2 how the interest in IOT is accelerating upwards and has usurped the interest in Big Data, whose slope of line is slightly below zero.
Figure 2: Interest in Big Data versus IOT measured by Google Trends[2]
Maybe it’s time for me to change my nickname to the “Dean of IOT,” but then I’d need to buy a new license plate for me car, so forget that.
But just as we are trying to get our hands around the potential of IOT, now comes Blockchain. And trust me when I say that Blockchain is no flash in the pan. The interest in Blockchain is growing at an even faster pace than IOT did and has already matched the interest in Big Data (see Figure 3)!
Figure 3: Comparing Interest in Big Data, IOT and Blockchain
And the rate of acceleration in the interest in Blockchain is exploding (see Figure 4).
Figure 4: Rate of Acceleration in Blockchain
Why is interest in blockchain accelerating so rapidly? The reason lies less in the technology, and more in the focus on identifying and implementing business use cases.
Blockchain is rapidly – frantically – moving beyond the “science experiment” phase into the “business monetization” phase. Leading companies are already embracing the unique capabilities afforded by blockchain to either improve existing business processes or to create new business opportunities. Below is just a very small sample of some Blockchain use cases.
One just needs to read some of the leading technology publications to see yet another example of an organization using blockchain to implement another business use case (just check out “Italian Wines Will Be Recorded on Blockchain, Authenticity Guaranteed” that came out as I was completing this blog).
The rate of technology innovation is accelerating because the rate of business adoption is also accelerating, being driven by real world “Make me more money” use cases. Instead of burying the technologies in the bowels of the organization under the guise of innovation, leading organizations are instead looking for real world use cases that can both validate as well as monetize these new technologies.
We saw it with Big Data, when the rate of Big Data adoption started to accelerate when Big Data moved out of IT and started to get incorporate into the Line of Business monetization strategies.
We are just starting to see it with the Internet of Things (IOT) where the technologies are just starting to move out of IT into operations and being used to drive operational efficiencies and eventually new monetization opportunities.
And it will happen with these new technologies such as blockchain, artificial intelligence, autonomous cars, quantum computing, the bionic man, holodecks, teleportation, and whatever else may pop up tomorrow.
The key to successful technology innovation is to move beyond IT “discovery and experimentation” and instead refocus on business “use cases and monetization”.
Starting with the business use cases is the key to transitioning from a technology science experience to powering business adoption. Identifying, validating and prioritizing the targeted business use cases is the secret sauce for driving technology adoption.
Don’t know where to find these business use cases? Then let’s go old school MBA and start with Michael Porters Value Chain Analysis (see Figure 5).
Figure 5: Michael Porter’s Value Chain Analysis
For more details on how to leverage Michael Porter’s seminal work, check out:
Start with a single business use case for analytics and then proceed use case-by-use case to build out your data, analytic and application capabilities and assets, define underlying architecture, and implement the foundational hardware, software and cloud technologies
Focusing on business adoption will enable organizations to exploit these new technologies to optimize existing business processes, reduce security risks, uncover new revenue opportunities, and to create a more compelling, more prescriptive customer engagement.
[1] https://en.wikipedia.org/wiki/Second_derivative
[2] https://trends.google.com/trends/explore?q=Blockchain,IOT,Big%20Data