Seizing The Market Whitespace With Incremental Innovation & Exponential Transformation
A learned visionary with over two decade of experience, Amit addresses forums on outsourcing and business transformationI have seen some companies grow from strength to strength, while others struggle to survive. Although the reasons for this disparity vary from case to case, much of it can be attributed to the inordinate focus on unstructured innovation. Granted, exponential transformation is a game changer, but there is no escaping incremental innovation if business leaders, innovators and experts are to retain market and mind share. In other words, these growth strategies necessitate a dual approach that involves aiming for radical transformation while systematically leveraging and improving upon the known technology parameters and best practices.
On the ground, this means being ambidextrous much like entrepreneurs. To survive and eventually thrive, products will need to undergo countless iterations. The idea is to continually refine foundational functions and deliver differentiated experiences with each reincarnation.
The Fluid State: Being Experimental & Safe
Let’s talk about innovation in the online retail sector. Incremental innovation has paid off in multiple spheres and Amazon’s Go is a great example of this. The reimagined in store experience of ‘walk in, grab and go’ is based on a refined version of the company’s baseline business model. Through the fusion of logistical capabilities with digital technology, a completely novel offline shopping experience has been created for customers.
In the hi-tech industry too, there are numerous cases that demonstrate the power of incremental innovation.
Take for instance the smartphone market which has
experienced exponential growth in recent years. As soon as consistent ER&D in the semiconductor space breached Moore’s Law, smaller hardware and OTT upgrades were rolled out in quicker cycles. Considering that the industry has been able to deliver more computing power in the form factor of a pocket calculator than the system used for the Apollo landing in a space of 50 years, there is no question that rapid incremental innovation is crucial to remain competitive.
Creating a Closed Loop of Exponential Transformation
Short innovation cycles traditionally and consistently have proven to be the foundation for significant transformations. Take for instance, Apple, the technology major built on the initial disruption caused by the iPhone and continued to significantly improve its products and margins by refining its flagship product with the support of better hardware and software. The CEO even decided to open up beta testing to public in order to resolve issues with existing iterations. Even after a decade and in its seventh incarnation, the iPhone remains best-selling smartphone in the world, having laid the foundation for an entirely new ecosystem.
Such agile development principles call for the early and frequent delivery of a working product. It begins with the development of a minimum viable product (MVP) that helps establish a baseline of data generated by customers. The MVP should be defined well enough to generate a single, compelling metric that can prove or disprove the hypothesis underlying the product’s concept. With the baseline data, R&D teams can rapidly work across channels to improve products.
In today’s connected economy, businesses have access to large volumes of customer data. With the right set of engineering analytics tools, this data can reveal insights on pain points and customer expectations and can also help define and develop MVP.
Think of this from the perspective of a book which has many editions. The first edition is useful, but it is the second edition that contains factual updates,richer descriptions, and even clarifications around previously confusing sections. For most businesses, the aim should be to simplify the product and constantly identify the next iteration creating a closed loop of continuous improvement. In simple words, exponential transformation is never achieved as an isolated objective, it is always built on the foundation of iterative enhancements, refinements and discoveries which lead to a disruptive end-product or a service.
experienced exponential growth in recent years. As soon as consistent ER&D in the semiconductor space breached Moore’s Law, smaller hardware and OTT upgrades were rolled out in quicker cycles. Considering that the industry has been able to deliver more computing power in the form factor of a pocket calculator than the system used for the Apollo landing in a space of 50 years, there is no question that rapid incremental innovation is crucial to remain competitive.
Exponential transformation is never achieved as an isolated objective, it is always built on the foundation of iterative enhancements,refinements and discoveries
Creating a Closed Loop of Exponential Transformation
Short innovation cycles traditionally and consistently have proven to be the foundation for significant transformations. Take for instance, Apple, the technology major built on the initial disruption caused by the iPhone and continued to significantly improve its products and margins by refining its flagship product with the support of better hardware and software. The CEO even decided to open up beta testing to public in order to resolve issues with existing iterations. Even after a decade and in its seventh incarnation, the iPhone remains best-selling smartphone in the world, having laid the foundation for an entirely new ecosystem.
Such agile development principles call for the early and frequent delivery of a working product. It begins with the development of a minimum viable product (MVP) that helps establish a baseline of data generated by customers. The MVP should be defined well enough to generate a single, compelling metric that can prove or disprove the hypothesis underlying the product’s concept. With the baseline data, R&D teams can rapidly work across channels to improve products.
In today’s connected economy, businesses have access to large volumes of customer data. With the right set of engineering analytics tools, this data can reveal insights on pain points and customer expectations and can also help define and develop MVP.
Think of this from the perspective of a book which has many editions. The first edition is useful, but it is the second edition that contains factual updates,richer descriptions, and even clarifications around previously confusing sections. For most businesses, the aim should be to simplify the product and constantly identify the next iteration creating a closed loop of continuous improvement. In simple words, exponential transformation is never achieved as an isolated objective, it is always built on the foundation of iterative enhancements, refinements and discoveries which lead to a disruptive end-product or a service.
