Tradition Vs Innovation – Story of an Ancient War
If you notice, you may observe that most of our nonintellectual discussions and conflicts are wars between tradition and innovation. Here you may find a person trying to convince others that one should stick with the legacies: experienced, practices, and patterns – not necessarily using the spoken words, but some contextual jargon; while the other person is contradicting. If only innovation and creativity can make a difference. Or in other words, you learn as you go. The same quarrel exists in our software engineering field, at least in our local industry as I see.
1. The Fundamentalist Craftsmen or Blind Followers
There are people who have strong belief in old practices. They always have the same number of documents, same life-cycle, identical design, and unbelievably a single strategy for every project. The most surprising point for me is that even the failure is unable to make them believe that there’s something wrong. Instead of trying to make some improvements and searching for the shortcoming in their practices and strategy, they start believing that failure is a norm, or it’s not failure at all. For instance, you’ll hear them saying “Clients never get satisfied” or “Losing deadlines is a norm in our industry”.
Examples -make things easier
In a software project, the offshore back-office development team shares the documents reside in their local repository with the the on-site front-office team to let them update the documents. In absence of their access on offline documents the local team shares the documents via email with the remote team. Obviously they get frequent version conflicts in documents and when it happens, they arrange a meeting and manually resolve the conflicts in the documents. For months, they suffer with this problem but avoid change in their practice e.g. having an online document repository instead of shareing the documents on email. The term coined here is Brute Force approach as Steve McConnell called it
2. The Innovator – or scientist, we can say
Away from the above category, the innovators are what most of our new graduates comprise of. They start with buzzwords like Web 2.0, cloud computing and believe that legacy practices are obsolete and that the senior folks are not creative at all. They drive their projects for learning, ignoring the ground realities they neglect the cost and risk of change and avoid exploiting legacies: patterns and practices. Since they believe that they make things better than they are, it’s possible if you see them writing their own DB connection pooling in technologies having built-in connection pooling or writing their own classes from scratch instead of extending the existing one. They often try to make simple things state-of-the-art and having insufficient knowledge and experience they get lost in the middle. The term coined here is “Silver Bullet” as Steve McConnell says.
3. Engineering Mindset: the most needful
The moderate mindset - or engineering mindset as I say- tends to utilize and exploit the experience, invested by the lots of great minds avoiding useless reinventions but never shy to address the issues with in the particular scenario, if it doesn’t fit with. The mindset says that understand your objective whether it’s build-to-learn or learn-to-build. It says that to be honest and successful, an engineer shouldn’t behave like a scientist who build and destroy just for learning. And it says that there’s always room for improvement since it’s a going concern but it’s not the ultimate goal of an engineer instead it’s to deliver the most optimal and economical.
A single practice may have different out comes when followed with or without reason. So, if a practice is being followed by majority, most probably there are reasons, try to find them, dont’ shy asking other followers if you couldn’t, but if nobody else knows, you have at least one reason to avoid it. Better to have your own with reasons instead of following blindly.
Being an engineer, I do not believe that I am right all the way, considering that I’ve limited amount of skills, knowledge, experience. Your comments and disagreements will be anticipated hoping they’ll help us having a balanced mindset.
By: Catalyst
About the Author:
1. The Fundamentalist Craftsmen or Blind Followers
There are people who have strong belief in old practices. They always have the same number of documents, same life-cycle, identical design, and unbelievably a single strategy for every project. The most surprising point for me is that even the failure is unable to make them believe that there’s something wrong. Instead of trying to make some improvements and searching for the shortcoming in their practices and strategy, they start believing that failure is a norm, or it’s not failure at all. For instance, you’ll hear them saying “Clients never get satisfied” or “Losing deadlines is a norm in our industry”.
Examples -make things easier
In a software project, the offshore back-office development team shares the documents reside in their local repository with the the on-site front-office team to let them update the documents. In absence of their access on offline documents the local team shares the documents via email with the remote team. Obviously they get frequent version conflicts in documents and when it happens, they arrange a meeting and manually resolve the conflicts in the documents. For months, they suffer with this problem but avoid change in their practice e.g. having an online document repository instead of shareing the documents on email. The term coined here is Brute Force approach as Steve McConnell called it
2. The Innovator – or scientist, we can say
Away from the above category, the innovators are what most of our new graduates comprise of. They start with buzzwords like Web 2.0, cloud computing and believe that legacy practices are obsolete and that the senior folks are not creative at all. They drive their projects for learning, ignoring the ground realities they neglect the cost and risk of change and avoid exploiting legacies: patterns and practices. Since they believe that they make things better than they are, it’s possible if you see them writing their own DB connection pooling in technologies having built-in connection pooling or writing their own classes from scratch instead of extending the existing one. They often try to make simple things state-of-the-art and having insufficient knowledge and experience they get lost in the middle. The term coined here is “Silver Bullet” as Steve McConnell says.
3. Engineering Mindset: the most needful
The moderate mindset - or engineering mindset as I say- tends to utilize and exploit the experience, invested by the lots of great minds avoiding useless reinventions but never shy to address the issues with in the particular scenario, if it doesn’t fit with. The mindset says that understand your objective whether it’s build-to-learn or learn-to-build. It says that to be honest and successful, an engineer shouldn’t behave like a scientist who build and destroy just for learning. And it says that there’s always room for improvement since it’s a going concern but it’s not the ultimate goal of an engineer instead it’s to deliver the most optimal and economical.
A single practice may have different out comes when followed with or without reason. So, if a practice is being followed by majority, most probably there are reasons, try to find them, dont’ shy asking other followers if you couldn’t, but if nobody else knows, you have at least one reason to avoid it. Better to have your own with reasons instead of following blindly.
Being an engineer, I do not believe that I am right all the way, considering that I’ve limited amount of skills, knowledge, experience. Your comments and disagreements will be anticipated hoping they’ll help us having a balanced mindset.
By: Catalyst
About the Author:
Ahmed is a Senior Software Engineer / Tech. Lead at Avanza Solutions. He has eight years of experience in software engineering profession.
Understanding the S curve of technology innovation
September 14, 2009 by admin
Filed under Language Language
Though the inception of a new technology seems random, its evolution over time once it comes into existence exhibits a reasonably stable pattern which can best be described in terms of performance characteristic.
The performance characteristic refers to an element of interest to a designer of a product or a user of a specific technology. For example, fiber optics against the cables in traditional telephone systems provides a better voice clarity. The speed of a computer is another example of performance characteristic that is resulted in new technology. Technological performance can be expressed in terms of any attribute, such as density in the electronics industry (number of transistor per chip) or aircraft speed in miles per hour. The performance of a technology has a recognized pattern over time that, if properly understood, can be of great use in strategic planning. Technology innovation refers to the changes in performance characteristics of a specific technology over time.
The life cycle of innovations can therefore be described using the s-curve which maps again in a different way, ie, growth of revenue or productivity against time. In the early stage of a particular innovation, growth is relatively slow as the new product establishes itself. At some point customers begin to demand and the product growth increases more rapidly. New incremental innovations or changes to the product allow growth to continue. Towards the end of its life cycle, growth slows and may even begin to decline. In the later stages, no amount of new investment in that product will yield a normal rate of return.
The s-curve is derived from half of a normal distribution curve. There is an assumption that new products are likely to have “product life”. i.e. a start-up phase, a rapid increase in revenue and eventual decline. In fact the great majority of innovations never gets off the bottom of the curve, and never produces normal returns.
What is important is that each technology has a number of performance characteristics of a specific technology over time. As mentioned earlier, once a new technology comes into existence, the performance characteristics of interest show very little improvement in the early stages of the technology.
This initial stage is followed by a second phase of very rapid improvement in the performance characteristic. During the third stage, the performance characteristic continues to improve, but the rate of improvement begins to decline. In the final stage, very little improvement is visible and the graph that charts the progress in the performance characteristic of a technology over time takes an S-shape.
The s-curve of technological innovation summarizes four major stages in the evolution of a performance characteristic.
1. Emergence – (also known as embryonic stage) shows little improvement in key performance characteristic. Technology operates far below its potential. Neither the characteristics of technology nor its applicability to market needs may be well understood. A long gestation period exists before attempts are made to produce a technology. This new invention period is characterized by a period of slow initial growth. This is the time when experimentation and initial bugs are worked out of the system.
2. Rapid improvement – improves at an accelerating phase. The technology improvement period is characterized by rapid and sustained growth. As organizations engage in production, experience accumulates over time accelerating the improvement in performance characteristic. The technology becomes vulnerable to substitution or obsolescence when a new or better-performing technology emerges.
3. Declining improvement – it declines improvement.
4. Maturity – further improvement becomes very difficult to achieve. The mature technology period starts when the upper limit of the technology is approached and progress in performance slows down. This is when the technology reaches its natural limits as dictated by factors such as physical limits.
During the early phase, a new technology is introduced into the market place but its adoption is limited to a small group of early adopters and small niche markets. As the product gains ascendancy, new capabilities are introduced and refined with the goal of meeting the needs of the broadest possible segment of mainstream users. During this middle phase a dominant design begins to emerge, winning the allegiance of the market place and also effecting standardization of everything from design to manufacturing. The dominant design in turn allows heightened competition as new entrants realize opportunities for further innovation based on cost, scale and product performance.
This is the period of rapid and greatest growth as a technology matures and reaches the mainstream. During the final phase the product reaches market saturation.
Some examples of technologies that have followed this path can be stated as follows.
The vacuum tube technology was limited by the tube’s size and the power consumption of the heated filament. Both of these factors were natural barriers to electron conduction in a vacuum tube. Electronic engineers could not overcome these limitations. The arrival of the solid-state technology, or transistor, which permitted electron conduction in solid material, changed the physical barriers of size and power. The transistor technology started a new technology life cycle and rendered the vacuum-tube technology obsolete.
Another example is ceramics, which have higher operating temperatures and substitute for metals used in internal combustion engines; the newer technology permits better performance of the engines. The performance of the engines can continue to improve as a result of a sequence of newer technologies, each with a higher limit of the performance parameter of interest.
Reference
Narayanan, V. K (2001) Managing technology and innovation for Competitive Advantage, Englewood Cliffs, NJ: Prentice Hall.
By: Dr. Chandana Jayalath
About the Author:
The performance characteristic refers to an element of interest to a designer of a product or a user of a specific technology. For example, fiber optics against the cables in traditional telephone systems provides a better voice clarity. The speed of a computer is another example of performance characteristic that is resulted in new technology. Technological performance can be expressed in terms of any attribute, such as density in the electronics industry (number of transistor per chip) or aircraft speed in miles per hour. The performance of a technology has a recognized pattern over time that, if properly understood, can be of great use in strategic planning. Technology innovation refers to the changes in performance characteristics of a specific technology over time.
The life cycle of innovations can therefore be described using the s-curve which maps again in a different way, ie, growth of revenue or productivity against time. In the early stage of a particular innovation, growth is relatively slow as the new product establishes itself. At some point customers begin to demand and the product growth increases more rapidly. New incremental innovations or changes to the product allow growth to continue. Towards the end of its life cycle, growth slows and may even begin to decline. In the later stages, no amount of new investment in that product will yield a normal rate of return.
The s-curve is derived from half of a normal distribution curve. There is an assumption that new products are likely to have “product life”. i.e. a start-up phase, a rapid increase in revenue and eventual decline. In fact the great majority of innovations never gets off the bottom of the curve, and never produces normal returns.
What is important is that each technology has a number of performance characteristics of a specific technology over time. As mentioned earlier, once a new technology comes into existence, the performance characteristics of interest show very little improvement in the early stages of the technology.
This initial stage is followed by a second phase of very rapid improvement in the performance characteristic. During the third stage, the performance characteristic continues to improve, but the rate of improvement begins to decline. In the final stage, very little improvement is visible and the graph that charts the progress in the performance characteristic of a technology over time takes an S-shape.
The s-curve of technological innovation summarizes four major stages in the evolution of a performance characteristic.
1. Emergence – (also known as embryonic stage) shows little improvement in key performance characteristic. Technology operates far below its potential. Neither the characteristics of technology nor its applicability to market needs may be well understood. A long gestation period exists before attempts are made to produce a technology. This new invention period is characterized by a period of slow initial growth. This is the time when experimentation and initial bugs are worked out of the system.
2. Rapid improvement – improves at an accelerating phase. The technology improvement period is characterized by rapid and sustained growth. As organizations engage in production, experience accumulates over time accelerating the improvement in performance characteristic. The technology becomes vulnerable to substitution or obsolescence when a new or better-performing technology emerges.
3. Declining improvement – it declines improvement.
4. Maturity – further improvement becomes very difficult to achieve. The mature technology period starts when the upper limit of the technology is approached and progress in performance slows down. This is when the technology reaches its natural limits as dictated by factors such as physical limits.
During the early phase, a new technology is introduced into the market place but its adoption is limited to a small group of early adopters and small niche markets. As the product gains ascendancy, new capabilities are introduced and refined with the goal of meeting the needs of the broadest possible segment of mainstream users. During this middle phase a dominant design begins to emerge, winning the allegiance of the market place and also effecting standardization of everything from design to manufacturing. The dominant design in turn allows heightened competition as new entrants realize opportunities for further innovation based on cost, scale and product performance.
This is the period of rapid and greatest growth as a technology matures and reaches the mainstream. During the final phase the product reaches market saturation.
Some examples of technologies that have followed this path can be stated as follows.
The vacuum tube technology was limited by the tube’s size and the power consumption of the heated filament. Both of these factors were natural barriers to electron conduction in a vacuum tube. Electronic engineers could not overcome these limitations. The arrival of the solid-state technology, or transistor, which permitted electron conduction in solid material, changed the physical barriers of size and power. The transistor technology started a new technology life cycle and rendered the vacuum-tube technology obsolete.
Another example is ceramics, which have higher operating temperatures and substitute for metals used in internal combustion engines; the newer technology permits better performance of the engines. The performance of the engines can continue to improve as a result of a sequence of newer technologies, each with a higher limit of the performance parameter of interest.
Reference
Narayanan, V. K (2001) Managing technology and innovation for Competitive Advantage, Englewood Cliffs, NJ: Prentice Hall.
By: Dr. Chandana Jayalath
About the Author:
