Platt Perspective on Business and Technology

Innovation, disruptive innovation and market volatility 30: innovative development at the business-to-marketplace collaboration level 8

Posted in business and convergent technologies, macroeconomics by Timothy Platt on December 27, 2016

This is my 30th posting to a series on the economics of innovation, and on how change and innovation can be defined and analyzed in economic and related risk management terms (see Macroeconomics and Business, posting 173 and loosely following for Parts 1-5 and Macroeconomics and Business 2, posting 203 and loosely following for Parts 6-29.)

I have been discussing a new approach to visualizing a business and its process flows in this series, and how complex organizational maps of that type require three dimensional mapping (see Part 28 and Part 29.) And in the course of that, I have been at least briefly discussing tools and resources that would be necessary, in order to make this approach economically feasible enough and user-friendly enough to surpass threshold resistance to trying and adapting it in the marketplace and by business professionals.

I have raised the issues of software and hardware support for this type of visualization tool, and particularly in Part 29 of this series. And I at least briefly turn here to more fully consider hardware requirements. I have written in this series and in my concurrently running series: Intentional Management (see its Part 30) of how virtual reality headsets could be adapted to this use, and at essentially standard product prices as competitively reached for a more general consumer market. This detail is very important here; the types of tools that I propose here do not need any new specially designed or manufactured hardware beyond what is already being developed, manufactured, marketed and sold for gaming visualization, and for immersive 3-D movies and other multimedia content.

• This means a wider range of hardware options to choose from as competing manufacturers seek to gain greater shares of this emerging market.
• It also means built-in capability for supporting multiple participant use – where several or even many might be viewing the same business systems model at the same time and with some just observing, and some actively editing and changing what is being shared but with all at least actively involved in the ongoing discussion. And this capability – already at least significantly developed for multi-player games and similar usage contexts, could be transferred over to this new context too and at reduced software development costs from being able to use pre-developed image management algorithms and more too.
• I take this one step further here, and suggest that the best solution for this type of application might be reality augmentation hardware and software, rather than fully immersive hardware and software systems – where a user can see and directly interact with other same-system users who are physically present with them, while collaboratively using these systems.
• I will add that totally immersive systems can be disorienting too, as users see one thing for example and seem to be experiencing one context for it – while their inner ears are experiencing something very different. Reality augmentation systems where your actual physical reality is still visibly there as a guiding framework, are much easier to adapt to and have much easier learning curves. And products such as Google Glass are already available on the market and with all of their basic underlying operating system and basic app support already available off the shelf.

(I add in two reality-check points to the above here, regarding the current state of the art for both virtual reality and augmented reality hardware. First of all, unlike roller coaster simulations, viewing and rotating and otherwise moving, and parsing and sectioning a business model representation of the type proposed here, would not likely create much opportunity for eye/inner ear confusion or conflict, so this is a context were even fully visually immersive virtual reality should work comfortably for most people. And second, current and early generation Google Glass devises are primarily oriented towards presenting flat, two-dimensional images as they show them to one eye. But it is essentially certain that Apple and others will actively move into true 3-D augmented reality imaging too, so resorting to a still primitive for that, Google Glass need only be seen as an early development phase for what will soon be possible – and for what is already heading to market as I write this.)

And with this added here as a starting point for this posting, I turn to the end note that I added to Part 29 of this series where I said that I would:

• Turn to consider new and novel tools and approaches in general – and successfully developing the disruptively new and bringing it to market. In anticipation of that, I will discuss how novel new approaches qualify for that disruptive label, and how they can become adapted and with time more widely used in spite of their initial barriers for that.
• And in the case of this posting’s particular new analytical approach and the software and hardware that it would call for, that means beginning with the right target audience, that would be more inclined to be pioneer and early adaptors for it. I refer there to business management consultants and their (mostly larger-scale) change management and business reorganization requiring clients.

I begin this with the first of these two bullet points, and by noting that my start to this posting was centered around making this new business tool approach, and its realized implementation, less novel and less disruptive in general, and as much less so as possible. I propose doing so by building this type of resource as specific product offerings, using as close to an off the shelf, consumer technology as possible. That means making this less customized and less expensive. It means being able to tap into all of the learning curve value that has already become available from developing and producing and selling this type of technology for consumer market audiences and uses. And it also at least potentially holds out a possibility of reducing the resistance threshold to adapting new technologies for those who do not comfortably see themselves as pioneer or early adaptors – business purchasing agents, and performance-pressed managers included.

And this is where I continue this discussion into bullet point two, from above. And I begin that by questioning the basic assumptions that the just addressed first of these bullet points raises – doing so at least initially by taking a still recent-history digression: consideration of the early adaptation curves and their consequences for graphical user interface computers when they first reached market in Apple’s early desktop computers.

I have been discussing Apple, Inc. as an ongoing case study example in a concurrently running series: Rethinking Vertical Integration for the 21st Century Context (see Ubiquitous Computing and Communications – everywhere all the time 2, postings 328 and following.) And to briefly summarize a few details here, that I more fully explore there, Apple in particular offered a new computer user interface that is so much easier to use, and so much more user friendly for people who are not computer programmers, than was the old command line interface that predominated, that businesses should have felt compelled to bring it into their offices and workshops and as quickly as possible. They should have seen it as more cost effective and more productivity enhancing and for more of their staff and managers than old command line systems could ever be. But the people who made purchasing decisions for businesses in general, saw this new technology opportunity as more game-like and as something that serious business professionals would not need or use.

That eventually changed with time, and there are only a few contexts where older legacy system command line interface systems are still in use. But that specific shift as graphical user interface acceptance diffused out to include later adaptors, did not change the existence of or the dynamics of the early adaptor to late adaptor diffusion curve or the pace in general, that disruptively new becomes more widely accepted.

I couched the second bullet point that I am discussing here, in terms of pioneer and early adaptors who favor buying in early. And I couched it in terms of purchasing decision makers and end user managers who see compelling need to accept change where any realistic alternative to that would be more costly and onerous. From a marketing standpoint,

• The story of opportunity lost in business effectiveness and competitiveness, from a failure to adapt easier graphical user interface computers earlier
• Might be made convincing to businesses that need a competitive edge that more effective business modeling and strategy could provide – based on a deeper and more accurate understanding of what their business actually does functionally and not just on what it is supposed to be doing from earlier planning and simplistic modeling.

As a final thought here for this posting, I wrote in Part 29 of bringing in real-world business professionals who would fit into the target demographics for buying and using this type of system, to help identify the features and to help specify the user interfaces that would best meet their needs. One way to jumpstart sales and acceptance here would be to offer discounted prices for early adaptors who would provide post-sales feedback for further product refinement – and who would allow word of their experience with this system to be highlighted in advertising for it. Business consulting firms might see value to themselves in this in particular, where they in turn could use this increased visibility to help market themselves for their cutting edge effectiveness. I offer this suggestion as a case in point example of marketing this type of innovation through social media and by feedback-driven interactive means in general.

I am going to turn in my next series installment to at least begin to consider business process innovation and its buy-in – and how this is shaped by the business analysis and management tools available. I have been addressing a specific case in point example of the issues that I will be addressing there in recent installments to this series, and will step back to consider more generally applicable issues relevant to this, next.

Then, looking ahead I will explicitly tie this line of discussion back to the core focus of discussion of this series, when I deal with the question of information availability as an innovation driver – and as that helps to set the boundaries between innovation per se and disruptive innovation. And as part of that, I will discuss process systems complexity and the role of developing lean and agile systems as innovation enablers. Meanwhile, you can find this and related postings at Macroeconomics and Business and its Page 2 continuation. And see also Ubiquitous Computing and Communications – everywhere all the time and its Page 2 continuation.

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