Platt Perspective on Business and Technology

Meshing innovation, product development and production, marketing and sales as a virtuous cycle 13

Posted in business and convergent technologies, strategy and planning by Timothy Platt on May 19, 2018

This is my 13th installment to a series in which I reconsider cosmetic and innovative change as they impact upon and even fundamentally shape the product design and development, manufacturing, marketing, distribution and sales cycle, and from both the producer and consumer perspectives (see Ubiquitous Computing and Communications – everywhere all the time 2, postings 342 and loosely following for Parts 1-12.)

I have been delving into the issues of business process innovation in recent installments to this series, and when it would make more sense to retain these sources of value in-house as proprietary resources, and when it might make more sense to market them, either within closed supply chain business-to-business collaboration contexts, or as more openly available marketable and sellable products, or even as recurringly updated commodities (see Part 11 and Part 12 in particular for that.)

But I have taken a relatively static, timeframe-independent approach to this set of issues up to here, and one that has at most just acknowledged a simplified approach to larger contextual change that this type of innovation would arise and play out in. More specifically, I have assumed and allowed for specific individual innovation-based change events and have considered how they would be evaluated, for how best they would be maintained in-house or shared outside of the creating business’ walls. And I have treated these innovation instances as separate distinct events, and with little real regard of the longer term contexts that they would arise in, hold value in, and with time become routine and then obsolete within. At the end of Part 12 I stated that I would continue that posting’s narrative here, by discussing:

• “Contextual pace of change issues, and innovation shelf lives as sources of consideration that would impact upon strategy and its decision making processes here. And I will also discuss all of this in the dynamic and at times less than clear-cut context of global flattening as it is taking place in this 21st century, as accompanied by the reactive (if nothing else) global wrinkling and push back that accompanies that. I will at least briefly consider how those types of factors would impact upon business process improvement and innovation, and its retention or transfer that I have been addressing here too.”

I begin addressing that complex of issues from the perspective of the above-offered preamble paragraph that I immediately preceded this bullet point topics list with, and with the innovation life cycle. I do so because as I stated in recent installments to this, timing can be everything in both setting and executing strategy and planning where innovation is concerned.

Let’s begin with the fundamentals and with the initial development of a new innovation or change. And at least initially, let’s set aside the issues of evolutionary versus revolutionary change and simply consider the basic life cycle steps that any new development in what is offered faces, and whether that means offered strictly in-house and on a more trade secret basis or to an outside market. A new, in this context business process resource or new improvement on an existing one, arises and is locally prototype tested in one area of a business or otherwise vetted. And it is updated and refined based on this real world, end user facing beta testing process. Then it is rolled out in-house, and a more formal process begins if appropriate that would determine whether this would be retained in-house or offered in some manner to other businesses. I presume here that this is not a business that develops such resources to sell or license as its basic business model. And independently of that, a more product evolution processes of refinement and improvement is probably going to start too, and certainly if the initial innovative change in question is more than just a simple cosmetic one – in which case this will have already been taking place.

Now let’s set aside one of the key starting assumptions of the above paragraph and start parsing out some of the additional factors that enter into that with an at least relatively simple cosmetic change versus a disruptively novel and even game changing innovation, as this distinction would likely impact on value longevity and innovation cycles:

A. Cosmetic changes, as a simplest case in point example, can hold as ephemeral a defining value as an impulse-buy oriented fad, and can disappear into the business productivity counterpart of a discount isle at mark down prices, and seemingly overnight as a next cosmetic update arrives, and a next after that. This means that cosmetic changes, as an extreme case can and do hold only short term value, and very little marketable value even then. And if this applies to consumer markets and store settings, it does so just as strongly for minor and cosmetic changes that might be brought to business productivity tool user interfaces, as a business process-supportive example, and particularly when its users see this change as only offering cosmetic value without making those tools easier to use or more productively effective when doing so. (Note: most software changes, office productivity software included, are minor and more cosmetic in nature than they are fundamental in nature, and certainly if you set aside behind-the-scenes security patch updates from consideration here and only consider user-visible changes.)
B. A genuine disruptively novel innovation that leads to, for example, a new type of business productivity tool that would hold real value for those who use it, on the other hand, is going to hold both larger and longer lasting value. And that will hold true both for those who use it and for those who own it and license or sell it. And focusing on the later of those two stakeholder categories for the moment, that holds for those who would retain this innovation in-house in the developing company and for exclusive use there. And it would hold true for any outside customer/users who would come to depend on this new capability too. And this defining source of value will in all likelihood continue to emerge and unfold for its end users, and for its developer/owners and according to both of those scenarios as it is evolved and improved upon, and until it has become effectively mainstreamed into general use with look-alike alternatives out there on the market, produced by other competing businesses, taking away any initial first mover effect benefit that the initial developer might have started out with, or until it is supplanted by a fundamentally new next-step alternative, or both.

I offer these two examples as representing what amounts to extreme end-case alternatives that would fit upon an innovation novelty and longevity spectrum, with most innovative change fitting somewhere between them.

• Businesses in general would see little if any incentive to retain a more Type A innovation in-house (to use the above-cited labeling) and certainly if this was a possible source of at least short-term revenue generating value if marketed and sold. And return value there could mean either a bump in brand name recognition, or a probably short-term cash profitability or both.
• But those same businesses would see both possible risk and possible value from either of the scenarios of retaining in-house or offering more publically, for anything more like a Type B innovation, to further cite the above designating labels. And the more B-like an innovation is, when considered for how it fits on the innovation novelty and longevity spectrum, the more important it becomes to carry out effective cost benefits analyses that would help evaluate what type of usage and deployment strategy would work best for the developing business.

My primary goal for the next installment to this series will be to at least begin to more fully explore the options and possibilities of the second of these two bullet point. And I will at least begin to do so by posing a set of organizing due diligence questions that a business owner or executive facing this type of decision would want to be able to address:

• How much value would this innovation actually create, for its implementation and use?
• And how much value would it create, net the costs of developing and implementing it?
• And how would this innovation best be evaluated and value determined for its likely competitive value created, from how it would reshape and at least hopefully improve business efficiency for the enterprises that bring it into their systems and use it?

Then after addressing this set of issues, I will proceed with my to-address list of topic points as repeated for orienting purposes towards the top of this posting.

Meanwhile, you can find this and related postings and series at Business Strategy and Operations – 4, and also at Page 1, Page 2 and Page 3 of that directory. And see also Ubiquitous Computing and Communications – everywhere all the time and its Page 2 and Page 3 continuations.


Finding virtue in simplicity when complexity becomes problematical, and vice versa 11

Posted in social networking and business by Timothy Platt on May 17, 2018

This is my 11th installment to a series on simplicity and complexity in business communications, and on carrying out and evaluating the results of business processes, tasks and projects (see Social Networking and Business 2), postings 257 and loosely following for Parts 1-10.)

I have been at least relatively systematically discussing Information Technology help desk systems in this series since Part 7, with a focus on identifying and tapping into the right types of expertise that would be needed to resolve rarer long-tail problems, and disruptively new and novel ones. And in the course of that narrative thread, and certainly in Part 9 and Part 10, I have focused on using more openly connecting interactive channels such as version 2.0 intranets in an organization, to facilitate finding and bringing together the right people with the right skills sets and experience, to both better understand and better resolve these nonstandard challenges.

Think of this line of discussion as paralleling an approach that I offer and discuss for better managing the proactively facing challenges of innovation and disruptive innovation in a business, where a largely similar approach can also be used in the often more reactive arena of problem identification and correction, and with a goal of offering both immediate here-and-now remediation and longer-term recurrence prevention capabilities. I cite this perhaps more ancillary detail here, because my overall goal in this narrative is to offer a more generally applicable single approach that would apply across a business organization as a whole, in making it more robustly effective and competitively agile. And with this noted, I return to the context that I have been exploring here, and help desk-based problem remediation.

I stated at the end of Part 10 that I would continue its discussion with a focus on developing resources that would:

• Facilitate greater business systems efficiencies, with lean and agile businesses and lean and agile supply chain and other value chain collaborations made possible from that.

And I added that after addressing that complex of issues, and with my discussion as offered in Part 10 in mind, I will also consider how the issues raised there would be shaped for their management and resolution by:

• Focused regulatory law and its implementation level frameworks, and other outside factors.

But before delving into that topics area, and with the first of these to-address bullet points in mind, I am going to at least briefly address what in most cases would have to qualify as the key enabler technology that would have to go into any large and complex business’ version 2.0 interactive, community-involving intranet, if it is to actually offer practical, usable value: a local use search engine. And for a major corporation certainly, but for larger businesses in general, this means developing and offering, or acquiring from a third party source such as Google, an easy to use search engine user interface, backed by an effective big data search, sort and filter capability.

I find myself thinking of a company such as IBM as I write that, with its roughly 380,000 employees, counting employees at wholly owned subsidiaries, as of late 2017. I have offered the possibility of businesses offering internally facing professional social networking tools through their intranets, counterpart to a publically facing internet site such as LinkedIn. Let’s assume a business that large in which only a third of all employees actually set up a professional profile in such a system, and with enough content to offer real value for anyone using it for networking purposes. That would still mean anyone seeking to search through it, facing over 125,000 possible candidates to start with, for any targeted search that they would make. And while IBM has a large headcount, it is not by any means the largest single business that I could cite here by way of example. (See this IBM background reference for more a more detailed discussion of this business and who works there.) And to highlight the geographic spread of a company such as IBM, as of September, 2017, that company has more employees in its operations in India than it does in the United States (see this September 28, 2017 news piece: IBM Now Has More Employees in India Than in the U.S.)

• Making a business and its systems lean and agile and efficient in its outwardly facing supply chain and other value chain collaborations, can only be possible if it is lean and agile and efficient in its internal and within-business operations and strategy.
• If it cannot function effectively internally and within its own systems, it is essentially inevitable that it will prove unable to benefit from possible efficiencies that might be offered to it through its larger business-to-business collaborative contexts.
• And it will find itself unable to sustain any such relationships because it will not be in a position to offer positive value to partner businesses in return for what it is offered, either.
• So addressing the first of the two to-address bullet points offered at the top of this posting, has to begin in-house. And that has to be information and communications driven. And that brings me precisely back to the issues and challenges that I have been addressing here in this series, and certainly since its Part 7.

My goal for the next installment to this series is to at least briefly discuss the issues of bringing a business’ own house into order through improved communications and information sharing, of the type under discussion here. And I will continue to pursue help desk systems as at least one possible source of working examples there. Then, I will turn outward to explicitly bring business-to-business collaborations into this narrative. And then I will delve into at least some of the issues of larger contexts that businesses in general have to be able to function in: regulatory law and its implementation included.

Meanwhile, you can find this and related material at Social Networking and Business and its Page 2 continuation. And also see my series: Communicating More Effectively as a Job and Career Skill Set, for its more generally applicable discussion of focused message best practices per se. I initially offered that with a specific case in point jobs and careers focus, but the approaches raised and discussed there are more generally applicable. You can find that series at Guide to Effective Job Search and Career Development – 3, as its postings 342-358.

Reconsidering Information Systems Infrastructure 4

Posted in business and convergent technologies, reexamining the fundamentals by Timothy Platt on May 15, 2018

This is the 4th posting to a series that I am developing here, with a goal of analyzing and discussing how artificial intelligence, and the emergence of artificial intelligent agents will transform the electronic and online-enabled information management systems that we have and use. See Ubiquitous Computing and Communications – everywhere all the time 2, postings 374 and loosely following for Parts 1-3. And also see two benchmark postings that I initially wrote just over six years apart but that together provided much of the specific impetus for my writing this series: Assumption 6 – The fallacy of the Singularity and the Fallacy of Simple Linear Progression – finding a middle ground and a late 2017 follow-up to that posting.

I began discussing what I have referred to as a possible “modest proposal” task for artificial intelligence-based systems in Part 1 and Part 2 of this series, as drawn from the pharmaceutical industry and representing what can be considered one of their holy grail goals: developing new possible drugs that would start out having a significant likelihood of therapeutic effectiveness based on their chemistry and a chemistry-level knowledge of the biological processes to be affected. And I have been using that challenge as a performance benchmark case-in-point example of how real world tasks might arise as problems that would be resolved by artificial intelligence, that go beyond the boundaries of what can be carried out using single, specialized artificial intelligence agents, at least in their current here-and-now state of development.

Then I further developed and explored that real world test-case challenge and what would go into effectively addressing it, in Part 3 where I began delving in at least preliminary-step detail, into the possibility of what might be achieved from developing and deploying what could become multiple hierarchical-level, complex problem solving arrays of what are individually only distinctly separate specialized, single task artificial agents, where some of them would carry out single specialized types of command and control functions, in coordinating the activities of lower level agents that report to them and that more directly work on solving specific aspects of the initial problem at hand.

Up to here, I have simply sidestepped the issue of whether such a system of individually simple, single algorithm agents, with its collective feedback and self-directing control systems could in some sense automatically qualify as having achieved some form of intelligence or general intelligence. I categorically state here, that that type of presumptive conclusion need not in any way be valid or justified. And I cite, by way of well known example for justifying that claim, the feedback and automated control functionalities that have been built into complex steam powered systems going back to the 19th century, for regulating furnace temperatures, systems pressures and the like. No one would deny that well designed systems of that sort do in fact manage and control their basic operational parameters for keeping them functioning and both effectively and safely. But it would be difficult to convincingly argue that a steam power plant and associated equipment in an old steam powered ship, for example, were in some sense intelligent and generally so. There, specialized and limited in overall aggregated form, is still specialized and limited, and even if at the level of managing larger and more complex problems than any of its single component-level parts could address.

With that noted, I add here that I concluded Part 3 of this series by stating that I have been attempting to offer a set of building block elements that would in all likelihood have to go into creating what would become an overall artificial intelligence system in general, and an arguably genuinely intelligent information management and communications network and system of such networks as a whole, in particular. Think of my discussion in this series up to here as focusing on “necessary but not sufficient” issues and systems resources.

I am going to turn to at least briefly discuss the questions and issues of infrastructure architecture in this, and how that would arise and how it would be managed and controlled, in what follows. (Think self-learning and self-evolving systems there, where a probably complex structured hierarchical system of agents would over time, optimize itself and effectively rewire itself in that process.)

And my goal there will be to at least offer some thoughts as to what might go into the “sufficient” side of intelligent and generally intelligent systems. And as part of that, I will more fully consider at least some basic-outline requirements and parameters for functionally defining an artificial general intelligence system per se, and in what would qualify as more operational terms (and not just in more vaguely stated conceptual terms as are more usually considered for this.)

Let’s start addressing all of that with those “higher” level but still simple, single algorithm agents that function higher up in a networked hierarchy of them, and that act upon and manage the activities of “lower” level agents, and how they in fact connect with them and manage them, and the question of what that means. In that, let’s at least start with the type of multi-agent system that I have been discussing in the context of my above noted modest proposal example, and build from there. And I begin that by raising what might be considered a swear word in this type of narrative for how it can be expansively and misleadingly used: “emergent properties.” And let me begin addressing that, by in-effect reframing Turing’s hypothesis in at least somewhat operationalized terms:

• A system of simple, pre-intelligent components does not become intelligent as whole because some subset of its component building block elements does. It becomes intelligent because it reaches a point in its overall development where examination of that system as a whole, and as a black box system, indicates that it is no longer possible to distinguish between it and its informational performance output, and that of a benchmark presumed-general intelligence and its output that it would be compared to (e.g. in Turning’s terms, a live and conscious person who has been deemed to be of at least average intelligence, when tested against a machine.)

And with a simple conceptual wave of the hands, an artificial construct becomes at least arguably intelligent. But what does this mean, when looking past the simply conceptual, and when peering into the black box of such a system? I am going to at least begin to address that question starting in a next series installment, by discussing two fundamentally distinct sets of issues that I would argue enter into any valid answer to it:

• The concept of emergent properties as they might be more operationally defined, and
• The concept of awareness, as a process of information processing level (e.g. pre- or non- directly empirical) simulation and model building.

And as part of that, I will address the issues of specific knowledge based expert systems, and of granularity in the scope and complexity of what a system might be in-effect hardwired to address, as for example in a Turing test context.

Meanwhile, you can find this and related postings and series at Ubiquitous Computing and Communications – everywhere all the time and its Page 2 continuation. And you can also find a link to this posting, appended to the end of Section I of Reexamining the Fundamentals as a supplemental entry there.

Dissent, disagreement, compromise and consensus 9 – the jobs and careers context 8

This is my 9th installment to a series on negotiating in a professional context, starting with the more individually focused side of that as found in jobs and careers, and going from there to consider the workplace and its business-supportive negotiations (see Guide to Effective Job Search and Career Development – 3, postings 484 and following for Parts 1-8.)

I focused in large part in Part 8, on meeting with and interviewing with a hiring manager: the manager at a hiring business who most specifically owns the hiring process and the work position that you are applying to there, and who will hold the greatest stake in any hiring decision consequences faced as a presumably best candidate is selected and brought in. Then I began addressing the issues of other stakeholders who a hiring manager might bring into this process, who would also meet with the top candidates under consideration. And I offered four basic questions towards the end of that posting that address the Who and Why of these stakeholders as participants in this, that I repeat here and that I will (primarily) address in order:

1. Why would a hiring manager bring other stakeholders into what is essentially their hiring decision making step?
2. And closely aligned with that question: who would they bring into this process and what would these stakeholders discuss with a job candidate?
3. And how would their input and insight be used in making a hire-or-not decision?
4. And given these questions and their issues, how can you as a job candidate most effectively meet with, and communicate and negotiate with these people, each with their own reasons for being included here and each with their own goals and interests in this process, so as to help you to achieve your own desired goals out of this overall interviewing process?

Let me begin with the first of these questions, as stakeholder interviews open a very revealing window into both the job that you might be applying for, and its actual requirements and priorities – and certainly when they might differ from what is stated in the job description offered.

Hiring managers at a business have their own work responsibilities and their own assigned tasks and priorities, and their own challenges and issues. And one of the primary reasons why a manager would take on the responsibilities and the additional work requirements of onboarding and then managing a new member of their team: a new employee under their supervision who they are going to be held responsible for, is that this person would help them to resolve at least one of their more significant challenges faced: a challenge or responsibility that rises to a level of significance for them to make this extra effort and commitment on their part worthwhile to them, and in ways that could not be achieved by members of their team already in place, as it is. And this leads me directly to the question of those stakeholder interviews. And I begin addressing Question 1 of the above list by categorically dividing them into two at least overly distinct groups, that can functionally overlap as I will explain in what follows:

• Within-team stakeholders, and
• Outside stakeholders.

Hiring managers bring in members of their own teams that they supervise, to meet with and interview top job candidates for a variety of reasons. This includes reality check validation that this is someone who their current team members could communicate with and work with on a comfortable and efficient basis: and a reiteration of the “fit test.” And at least as importantly, this is where a hiring manager who might not have specific hands-on expertise themselves in what this new hire would do, can have them meet with the people who they would work with who might be as close to expert as anyone there in what these potential new hires would do there. At the very least, this would include team members who they would directly have to coordinate their work with, so their combined efforts would fit together. Even if a new hire would carry out tasks that no one currently there has any real hands-on experience with, can they communicate on technical and professional issues in a way that will work for others there, so their work can fit in and actually offer value in addressing larger, team tasks?

Outside stakeholder interviewers who are included here, and certainly as specific interviewer choices, are essentially always brought into this process because they play pivotal stakeholder roles in the problems and issues that this hiring manager is seeking to address and resolve through a new hire. Think of them as people who in effect own the tasks that this new hire would work on and contribute to, that their manager and their team members are supposed to successfully work on and resolve. And as team outsiders who are nevertheless significantly involved in what this new hire would do on the job, they are people who the hiring manager is obliged to satisfy, and usually in fulfilling that key one of their own managerial level tasks or goals responsibilities that they are hiring for.

I made note, above, of the possibility of functional overlap between within-team stakeholders and outside stakeholders, and clarify that here by noting that key “owner” stakeholders of the tasks or goals that a new hire would be brought in to address, can sometimes be found within a manager’s direct supervision team too, and certainly if they have a large and complexly organized team reporting to them.

• It is a crucially important task for a prospective new hire, to identify who the task and goals owning stakeholders are who they meet with, and who the primarily fit-validating ones are.
• And one of the most important objectives there in knowing and understanding that difference, is in learning as much as possible about the issues and challenges that have led to a decision to hire in the first place.

One of the most important points that I have raised in this blog over the years, regarding consulting, is that people and businesses that hire consultants often know more about what the symptoms are, than they do about the actual underlying problems that cause them. What would you actually be hired to do, and at as much of an underlying-problem level of understanding as possible? And would you be offered the resources and opportunity needed to go beyond symptoms to address those underlying problems? Note: even when a job description and all ensuing interviews focus on symptoms to be addressed, and here-and-now, resolve for the moment issues, managers always hire with a goal of achieving longer-term results and underlying problem resolutions through their new hire.

And with this, I have addressed the above-stated Question 2, as well as Question 1 – or at least a significant measure of it. And at this point, I raise a pair of questions that I learned the importance of, the hard way in my own work life and career experience:

• Is the job that you are applying for and being interviewed for, one that this same hiring manager has unsuccessfully tried to get completed before and through earlier in-house staff or new hire attempts? And if so, how and how many times?

I write this thinking back to a consulting assignment that I took on and agreed to, just to find after I had started that the hiring manager who I met with was being pressured by his supervisor: a more senior executive, to complete a very complex overall set of coordinated tasks that he did not understand for what this required, and with time frame and other constraints that made this work impossible. So several others had been brought in to attempt this job and all had failed, and no one working under this more senior manager was willing to let on that any of this had happened in any interview meetings they participated in. They were all terrified of the boss’ boss.

• Know what you are getting into, and really listen to and speak with the people who you get to meet with: all of those directly involved stakeholders definitely included. And think in terms of reading between the lines in what they do and do not say, and in what they ask and how.
• Prior failed efforts such as the workplace example that I cite here, to achieve desired goals through bringing in new hires: in-house or as consultants, need not completely preclude you’re taking this type of job. But the more you know of what you face, and in general in a new job with its actual issues and challenges, the more effectively you can negotiate your terms for taking this work on, and with time-to-completion and performance benchmarks and resource access issues clearly spelled out. (I will come back to this point when discussing terms of employment negotiations, a little later in this series. I simply note this complex of issues here to put this posting’s interview phase of this overall process into a fuller and more useful context and perspective.)

This last comment can be seen as a foretaste of how I will address the above Question 4 when I more formally do so. I will offer come concluding thoughts regarding Questions 1 and 2 in my next series installment, and will then address Question 3, and then Question 4 as a whole to round out this phase of this overall narrative. And then I will proceed from there to discuss negotiations as to terms of employment, and with compensation and other factors definitely included in that, there assuming that the hiring manager you have met with has made a positive decision to bring you into the business as a new employee. Then, looking ahead, I will turn to consider the new hire probationary period.

Meanwhile, you can find this and related material at Page 3 to my Guide to Effective Job Search and Career Development, and also see its Page 1 and Page 2. And you can also find this series at Social Networking and Business 2 and also see its Page 1 for related material. And I particularly recommend your at least briefly reviewing a specific job search best practices series that I developed here on the basis of both my own job search experience and from working with others going through that: Finding Your Best Practices Plan B When Your Job Search isn’t Working, as can be found at Page 1 of my above-noted Guide as its postings 56-72.

Building a startup for what you want it to become 32: moving past the initial startup phase 18

Posted in startups by Timothy Platt on May 11, 2018

This is my 32nd installment to a series on building a business that can become an effective and even a leading participant in its industry and its business sector, and for its targeted marketplaces (see Startups and Early Stage Businesses and its Page 2 continuation, postings 186 and loosely following for Parts 1-31.)

I have been focusing in this series, since Part 28 on the increasingly important role that data, and that big data in particular are assuming as drivers of even just basic competitive business strength and for an increasing range of industries and business sectors, and when addressing an increasing range of markets that they would serve. And I have reached a point in that line of discussion (in Part 31) where I have begun considering the role that with-in business developed, and third party sourced business intelligence have come to assume in a cutting edge innovative business context.

I have been focusing on what is ultimately consumer sourced data in this progression of postings: Part 31 included, and on both individually identifiable and more anonymized data in that. And that narrative progression has led me to a to-address list of points that I will work my way through in what immediately follows in this series:

1. An at least brief discussion of businesses that gather in, aggregate and organize information for other businesses, as their marketable product and in accordance with the business models of those client enterprises.
2. The questions of where all of this business intelligence comes from, and how it would be error corrected and kept up to date, as well as free from what should be avoidable risk from holding and using it.
3. And that will mean addressing the sometimes mirage of data anonymization, where the more comprehensive the range and scale of such data collected, and the more effectively it is organized for practical use, the more likely it becomes that it can be linked to individual sources that it ultimately came from, from the patterns that arise within it.

Then after considering these issues and discussing them in at least selective detail for purposes of this series, I will use that narrative as a foundation for further considering in-house versus cloud based systems, and for acquisition, processing and validation, organization, storage and use of all of the raw data and processed knowledge that arises here. And I will proceed from there to consider these issues from a more business-development timeline perspective, bringing in the issues and challenges of cost-effectively developing a business for all of this and how and when, so as to more effectively support change and scalability while controlling possible risk. My goal there is going to be one of tying all of this discussion back to a startups and early-stage business context.

But before turning to that second complex of issues as just noted in the above paragraph, I will address the three above-offered, more immediate topics points, beginning in this posting with an at least starting discussion of Point 1. And I begin that by citing two relevant series of postings as background references, that I initially offered in this blog as a consequence of conversations that I had with colleagues:

• Big Data and the Assembly of Global Insight out of Small Scale, Local and Micro-Local Data (as can be found at Reexamining the Fundamentals as Section IV), and
• Mining and Repurposing of Raw Data into New Types of Knowledge (as can be found at Ubiquitous Computing and Communications – everywhere all the time, as postings 156 and following.)

I begin discussing the third party source businesses of Point 1, that provide business intelligence as business-to-business providers, by roughly dividing them into two basic categories:

• Specialized, or niche market big data providers, and
• Generalist big data providers.

The development and proliferation of big data and of big data opportunities, has created a large and varied business sector, and even an entire industry of business-to-business data aggregators and organizers that buy and sell business intelligence as their own value-added marketable commodity.

I have cited specific target-industry examples of this phenomenon in this blog, that would fit a more niche provider business model, to describe them in terms of the above-offered dichotomy. And one such specialized niche business intelligence provider type, that I have made note of several times in this blog is comprised of automotive retail business-supporting sales leads aggregators that service the needs of automotive retail businesses for car and truck sales: each claiming to be the best in their marketing and sales area for pre-qualifying their leads offered as current and as representing potential local customers who could afford to buy and who are in the market to do so.

My point there, is that these big data aggregator businesses, offer value added data that they would argue, their automotive sales dealerships could not cost-effectively match from their own data collection and filtering and vetting efforts. And they all claim to offer the best such sales lead data that would most easily be convertible into completed sales from their value-added data filtering and processing activities. And yes this data, and for most such businesses would include both anonymized and personally identifiable customer and potential customer data and in large and varied quantities. And it would be organized and offered in ways that would connect with their client business’ business models and their sales and marketing catchment areas.

I am going to discuss this working example, niche information provider type in my detail in my next installment to this series. And I will also discuss the bigger and more widely involved players in this overall industry: generalist big data providers there too. In anticipation of that, I will discuss Google, Amazon and Facebook for how they are positioned to provide this type of service, and Facebook as a particular case in point example for how they have built so much of their basic business model around monetizing user-sourced data as their primary source of incoming revenue. They sell targeted marketing and sales opportunities; this means they sell data related to and coming from their registered users, and access to the results of their big data analysis and processing of this data.

Meanwhile, you can find this and related material at my Startups and Early Stage Businesses directory and at its Page 2 continuation.

Moore’s law, software design lock-in, and the constraints faced when evolving artificial intelligence 1

Usually I know when setting out to write a posting, precisely where I would put it in this blog, and that includes both prior decision as to what directories it might go into, and decision as to what series if any that I might write it to. And if I am about to write a stand-alone posting that would not explicitly go into a series, new or already established, I generally know that too, and once again with that including where I would put it at a directories level. And I generally know if a given posting is going into an organized series, and even if as a first installment there, or if it is going to be offered as a single stand-alone entry.

This posting is to a significant degree, an exception to all of that. More specifically, I have been thinking about the issues that I would raise here, and have been considering placing this in a specific ongoing series: Reconsidering Information Systems Infrastructure as can be found at Ubiquitous Computing and Communications – everywhere all the time 2 (as its postings 374 and loosely following.) But at the same time I have felt real ambivalence as to whether I should do that or offer this as a separate line of discussion in its own right. And I began writing this while still considering whether to write this as a single posting or as the start to a short series.

I decided to start this posting with this more behind the scenes, editorial decision making commentary, as this topic and its presentation serves to highlight something of what goes on as I organize and develop this larger overall effort. And I end that orienting note to turn to the topic that I would write of here, with one final thought. While I do develop a number of the more central areas of consideration for this blog, as longer series of postings, I have also offered some of my more significantly important organizing, foundational ideas and approaches in single postings or as very brief series. As a case in point example that I have referred back to many, many times in longer series, I cite my two posting series: Management and Strategy by Prototype (as can be found at Business Strategy and Operations as postings 124 and 126.) I fully expect this line of discussion to take on a similar role in what follows in this blog.

I begin this posting itself by pointing out an essential dynamic, and to be more specific here, an essential contradiction that is implicit in its title. Moore’s Law, as initially posited in 1965 by Gordon Moore at Intel, proposed that there was a development curve defining trend in place, according to which the number of transistors in integrated circuits was doubling approximately every year and a fraction – but without corresponding price increases. And Moore went out on a limb by his reckoning and predicted that this pattern would persist for another ten years so so – roughly speaking, up to around 1975. And now it is 2018 and what began as a short-term prediction has become enshrined in the thinking of many, and as if an all-but law of nature, from how its still persists in holding true. And those who work at developing next generation integrated circuits are still saying the same things about its demise: that Moore’s law will run its course and end as ultimate physical limitations are finally reached … in another few next technology generations and perhaps in ten years or so. This “law” is in fact eventually going to run its course, ending what has been a now multi-decade long golden age of chip development. But even acknowledging that hazy end date limitation, it also represents an open ended vision and yes, an open ended expectation of what is essentially unencumbered disruptively new growth and development that is unburdened by any limitations of the past, or present for that matter.

Technology lock-in does not deny the existence of or the impact of a Moore’s Law but it does force a reconsideration as to what this still ongoing phenomenon means. And I begin addressing this half of the dynamic that I write of here, by at least briefly stating what lock-in is here.

As technologies take shape, decisions are made as to precisely how they would be developed and implemented, and many of these choices made are in fact small and at least seemingly inconsequential in nature – at least when they are first arrived at. But these at-the-time seemingly insignificant specific design and implement decisions can and often do become enshrined in those technologies as they develop and take off, and as such take on lives of their own. That certainly holds true when they, usually by unconsidered default, become all but ubiquitous for their application and for the range of contexts that they are applied to as those technologies that they are embedded in, mature and spread. Think of this as the development and elaboration of what effectively amount to unconsidered standards for further development, that are arrived at, often as here-and-now decisions and without consideration of scalability or other longer-term possibilities.

To cite a specific example of this, Jaron Lanier is a professional musician as well as a technologist and a founder of virtual reality technologies. So the Musical Instrument Digital Interface (MIDI) coding protocol for digitally representing musical notes, with all of its limitations in representing music as actually performed live, is his personal bête noire, or at least one of them. See his book:

• Lanier, J. (2011) You Are Not a Gadget: a manifesto. Vintage Books,

for one of his ongoing discussion threads regarding that particular set-in-stone decision and its challenges.

My point here is that while open and seemingly open ended growth patterns, as found in examples such as Moore’s Law take place, and while software applications counterpart to it such as the explosive development of new database technology and the internet arise and become ubiquitous, they are all burdened with their own versions of “let’s just go with MIDI because we already have it and that would be easy” decisions, and their sometimes entirely unexpected long-term consequences. And there are thousands of these locked-in decisions, and in every wide-spread technology (and not just in information technology systems per se)

The dynamic that I write of here arises as change and disruptive change take place, with so many defining and even limiting constraints put in place in their implementations and from their beginnings: quick and seemingly easy and simple decisions that these new overall technologies would then be built and elaborated and scaled up around. And to be explicitly clear here, I refer in this to what become functionally defining and even limiting constraints that were more backed into than proactively thought through, than anything else.

I just cited a more cautionary-note reference to this complex of issues, and one side to how we might think about it and understanding it, with Lanier’s above-cited book. Let me balance that with a second book reference that sets aside the possibilities or the limitations of lock-in to presume an ever green, always newly forming future that is not burdened by that form of challenge:

• Kaku, M. (2018) The Future of Humanity. Doubleday.

Michio Kaku writes of a gloriously open-ended human future in which new technologies arise and develop without any such man made limitations: only with the fundamental limitations of the laws of nature to set any functionally defining constraints. Where do I stand in all of this? I am neither an avowed optimist nor a pessimist there, and to clarify that I point out that:

• Yes, lock-in happens, and it will continue to happen. But one of the defining qualities of truly disruptive innovation is that it can in fact start fresh, sweeping away the old lock-ins of the technologies that it would replace – to develop its own that will in turn disappear at least in part as they are eventually supplanted too.
• In this, think of evolutionary change in technology as an ongoing effort to achieve greater effectiveness and efficiency with all of the current, basic constraints held within it, remaining intact there.
• And think of disruptive new technology as break away development that can shed at least a significant measure of the constraints and assumptions that have proven to at least no longer be scalable and effectively so. But even there, at least some of the old lock-ins are still likely to persist. And this next revolutionary step will most likely bring its own suite of new lock-ins with it too.

Humanity’s technology is still new and young, so I am going to continue this narrative in a next posting to what will be this brief series, with an ancient example as drawn from biology, and from the history of life at its most basic, biochemically speaking: the pentose shunt, or pentose phosphate pathway as it is also called. I will then proceed from there to consider the basic dynamic that I raise and make note of in this series, and this source of at least potential innovative development conflict, as it plays out in a software and an artificial intelligence development context, as that is currently taking shape and as decisions (backed into or not) that would constitute tomorrow’s lock-ins are made.

Meanwhile, you can find this and related material at Ubiquitous Computing and Communications – everywhere all the time and its Page 2 continuation. And I also include this in my Reexamining the Fundamentals 2 directory as topics Section VIII. And also see its Page 1.

Some thoughts concerning a general theory of business 23: considering first steps toward developing a general theory of business 15

This is my 23rd installment to a series on general theories of business, and on what general theory means as a matter of underlying principle and in this specific context (see Reexamining the Fundamentals directory, Section VI for Parts 1-22.)

I have been discussing a series of what can perhaps best be considered exceptions scenarios, that would arise in the hiring process in a business, in this series since its Part 20, alternating between discussion of these specific business process issues, and more general theory of business considerations, that I have been exploring by way of these special case contexts. For smoother continuity of narrative, I repeat my four hiring scenario list, with a goal of addressing its third entry here:

1. More routine hire, hands-on non-managerial employees, and I add more routine and entry level and middle managers – versus – the most senior managers and executives when they are brought in, and certainly from the outside.
2. More routine positions, managerial or not – versus – special skills and experience new hires and employees, hands-on or managerial.
3. Job candidates and new hires and employees who reached out to the business, applying as discussed up to here in this narrative on their own initiative – versus – those who the business has reached out to, to at least attempt to bring them in-house as special hires and as special for all that would follow.
4. And to round out this list, I will add one more entry here, doing so by citing one specific and specifically freighted word: nepotism. Its more normative alternative should be obvious.

And I begin addressing Scenario 3 by pointing out the similarities that can arise, and the overlap that can occur between this and Scenario 2. Both involve a business coming to realize that it needs to hire one or more very rare, high demand special-case new employees, at whatever level they would work at on the table of organization. This makes these hiring processes, seller’s market oriented with advantage held by any who can convincingly present themselves as fulfilling the wish list requirements of the hiring business. Both involve situations where more possible employers, quite arguably would wish to hire these types of people than there are actual job candidates – and certainly ones who are looking or willing to look for new work opportunities elsewhere. But even with all of that held in common, these are two distinct and separate special exception hiring scenarios.

• First of all, a really proactive, entrepreneurial professional who has skills and experience that are coming into high demand and need, and at levels the market cannot meet, can reach out to hiring managers and potential hiring managers at businesses that they would like to work at, and basically make sales pitches directed towards starting a conversation. Their goal in that would be to discuss the possibilities of what they could offer, that would specifically bring benefit to that business and to the people there who they get to meet with.
• A business in question, and at least one of its hiring managers have to have thought all of this out first, for a Scenario 3 as offered above to apply; a potential job candidate and new hire can reach out to inform and to provoke that type of thinking process, making an initial effort in order to explore their possibilities and see what they can develop. In Scenario 2, they can easily be the more proactive participants in this. In Scenario 3, it is the potential new hire catch, who would be reactive and the potentially hiring business that would be more proactive in setting this type of process in motion.
• And to cite one other at least potentially significantly differentiating detail here, Scenario 2 tends to apply more for finding and securing special here-and-now hires, and with a goal of keeping the business cutting edge and competitive from that in some rapidly changing, generally technical functional area. What is hot enough in the jobs market to qualify for Scenario 2’s preferential treatment today, is probably going to cool down enough and in a relatively short period of time, to fit more smoothly and realistically into that company’s routine candidate selection and new hire processes and procedures, and from the early job description preparation and initial candidate screening and filtering process onward. And this can happen very quickly, making Scenario 2 into more of a narrow window of opportunity phenomenon.
• Scenario 3 candidates on the other hand, and the people that a business would want to convince to become candidates, might fit that pattern. But this scenario is also were businesses reach out to special possible hires who would offer long-term defining value too, such as marketing or sales professionals with a well established golden touch track record, or senior executives who have proven track records of stellar excellence as visionary leaders and managers. I write here of having more persistent soft skills excellences, versus simply having a more state-of-the-art based, ephemeral technical skills edge.

With that offered as a starting point for discussing what Scenario 3 actually is, let’s consider it and I add reconsider Scenario 2 again, from a game theory perspective. And I begin addressing that, by picking up on the last sentence of the immediately preceding bullet point description, and the basic message that I seek to convey through it, and with timing considerations.

• Any specifically short-term, time limited Scenario 2 advantage that a prospective job candidate might hold in a hiring process there, would of necessity significantly shape the strategy that they would pursue, and I add that the hiring business would pursue too, when meeting and negotiating with them. This biases all that would transpire on both sides of the hiring negotiations table there, and in terms of short timeframes and in terms of strategic and game strategy considerations that would support them.
• But a Scenario 2 candidate who is hired, is in most cases going to want to continue on at that job for longer than just the perhaps brief span in which their special skills that brought them there, have lost their special edge. I am not suggesting that they would want to finish their overall career paths with this employer: only that they would want to have a say in how long they remain there, and on what they can develop and take with them from that experience, as and when they do move on. This gives them positive incentive to think and plan in terms of longer-term career strategy too, and according to a game theory approach that would promote and advance their interests along that timeframe too. And this might in fact be at odds with a strictly short-term interest and short-term planning strategy and game theory approach that they might take if only thinking in terms of getting hired in the first place.
• And a Scenario 2 hiring business, would see compelling need to pursue an at least short-term compatible hiring strategy and game theory approach at first and when negotiating to bring in such a new hire. But as an ongoing organization, they would also have to consider and take on a dual approach there too, building from day one in the hiring process for longer term viability in any hiring agreements reached.

And with this, I raise the issues of dual and competing strategies and their game theory implementations, and the need to reconcile and coordinate between them, to find what for a participant would be their best, more timeframe-independent path forward. I will continue this discussion of Scenario 3 (and of Scenario 2 as well) in my next series installment, and will then move on to Scenario 4, which I offer here in this series as one of several potentially toxic hiring scenarios. And after completing that line of discussion, at least for purposes of this series, I will step back from consideration of general theories of business as a special categorical case, to delve into a set of what have become essential foundation elements for that discussion, with further consideration of general theories per se. And looking ahead, I will then turn back to the more specific context of theories of business again, where I will begin using this newly added, more-general foundational material in its more specific context. My goal there is to follow the discussion of business hiring processes and their exceptions that I have been pursuing up to here, with one that focuses on the new hire probationary period and its dynamics. And I will use that as a source of special case examples, in order to develop and present more general theory of business considerations.

Meanwhile, you can find this and related material about what I am attempting to do here at About this Blog and at Blogs and Marketing. And I include this series in my Reexamining the Fundamentals directory, as topics section VI there, where I offer related material regarding theory-based systems. And I also include this individual participant oriented subseries of this overall theory of business series in Page 3 of my Guide to Effective Job Search and Career Development, as a sequence of supplemental postings there.

Donald Trump Xi Jinping, and the contrasts of leadership in the 21st century – 6

Posted in macroeconomics, social networking and business by Timothy Platt on May 6, 2018

This is my 33rd installment to what has become an ongoing series of postings in which I seek to address politics in the United States as it has become, starting with the nominations process leading up to the 2016 presidential elections. See my series: Donald Trump and the Stress Testing of the American System of Government, as can be found at Social Networking and Business 2, posting 244 and loosely following.

This can also be considered to represent my 60th installment to an ongoing series that I have been offering here concerning Xi Jinping and his still emerging and expanding leadership role in China. See China and Its Transition Imperatives, as can be found at Macroeconomics and Business and its Page 2 continuation, as postings 154 and loosely following. I began writing about Xi in this series after his elevation to a position of supreme leadership in the Communist Party of China and of China’s government and military. And I include this posting in that progression of them, as the United States president currently in office: Donald Trump, creates both challenge and opportunity and with the second of those predominating, for Xi and his leadership.

I begin this posting by repeating the number of postings that I have offered here, focusing on Donald Trump and his narcissistic zero attention span cupidity and venality: 33. And I have written about him at least in passing on a variety of other occasions in this blog too. As such, that number only approximates the level of specific attention that I have directed towards this man and his activates, and that of his supporters. So I offer this supernumerary addition to what I have to think of as that less than august assemblage of writings, by saying enough is enough. As of now, I am not planning on adding a 34th installment to this progression, unless and until a real change event takes place such as the release of the Muller investigation findings, in his investigation of Russian involvement in compromising the 2016 US elections – and in a manner that would lead to Trump’s impeachment. OK, that is not the only possible trigger that would prompt my offering a number 34 to this series. But any viable alternative to it that would prompt me to return to specifically writing about Donald Trump and his presidency is going to have to be game changing too, as far as Trump and his political and office holding futures are concerned.

I am planning on continuing to write about China and their leadership in further postings. But any references to The Donald in that will simply be incidental and offered as contextual background material. This is it, and certainly for now, for focusing on Trump himself.

And with that stated, I begin this posting with the citation of an historical parallel as drawn from United States history. And I turn for that to the less than laudable presidency of Warren Gamaliel Harding, as a touchstone for better understanding our current, 45th United States president. Harding is widely known as having been one of the worst of the worst, of those who have taken on the responsibilities of the office of president of the United States, and for good reason. The Teapot Dome scandal with its rampant bribery and other corruptions that Harding is perhaps best known for, as carried out by highly placed officials in his presidential administration, is only one of the well known and documented of his administration’s failings. But even a cursory review of the Trump administration, shows him and his inner circle to be much more fully and widely corrupt than that, and for essentially all of the key members of his team and for essentially all who he has tried to bring into it. This side to the history of the Trump administration, beginning at the time of his inauguration into office and continuing on to now, has presented itself as a succession of revelations of senior members of Trump’s inner circle who have proven to be corruptible and corrupt and even overtly criminally so.

Donald Trump famously ran for office on a campaign promise of “draining the swamp” in Washington. And he has continued to proclaim that as one of his administration defining self-assumed success stories, and ever since his achieving office. But if anything, president Trump has taken what might or might not properly be called a swamp in the District of Columbia and its surrounding areas and converted it into what should qualify as a superfund cleanup site. And I cite as a news piece example of how others have arrived at this conclusion:

Trump’s ‘Best People’ Are the Worst

And yes, he has repeatedly proclaimed that he is bringing in the best people as a key part of his swamp draining effort. How could the actual results achieved from his hiring efforts have happened? I could cite several reasons for that, all of which begin in a cause and effect manner from the simple fact that Trump only looks for one quality or qualification when evaluating potential candidates and hires into his administration. Anyone he would consider bringing in must swear personal, absolute loyalty and fealty to him as an individual. And any who turn on him and betray that absolute oath of loyalty in any way, is soon going to be on their way out the door.

As a particularly toxic and I add particularly publically visible example of how that works, I cite an event that president Trump orchestrated and that he directly ordered all of his cabinet officers to participate in, and with whole hearted enthusiasm demonstrably required on all of their parts:

Trump’s Cabinet Showers Boss with Praise,
Trump Invites His Employees To Praise Him During Cabinet Meeting and
Donald Trump Cabinet Praise.

The second and third of these links are to YouTube videos of this event, so a reader can see what I write of here for themselves. A normal person would not want this type of overtly forced praise, and would certainly not demand that type of public obeisance and from anyone. But a willingness to submit to participating in an exercise in public adoration of this type is precisely how Trump picks those who end up at least briefly on his team. And only the truly corrupt and shamelessly so would buy into this type of behavior on their part, as a necessary and acceptable cost of bellying up to the trough to feed. Honest, competent people of genuine integrity would not willingly seek to serve in office under a Donald Trump and certainly as he has proven that fact based decision making and action do not meet with his approval or support: only obedience to his each and every tweet, verbal utterance or thought, and no matter how unconsidered or self-serving.

And that brings me to a verbal shorthand that I have started hearing from news professionals and pendants that I find, if anything, at least as disturbing as Donald Trump’s soft relationship with empirical reality itself. I refer here to how all of this has become so much a “new normal” in the eyes and minds of so many. Phrases line Post-Fact Reality as a new norm prompt essentially the same visceral response in me that I would feel if they began seriously, studiously intoning in their reporting of Trump’s exciting new doublespeak and double think. George Orwell would spin in his grave with joy if he could somehow know that Donald Trump has taken his dystopian dreamscape and made it his, and our reality. (Think of that last sentence as my one and only interview practice run for becoming an “alternative facts” based Trump spokesperson. And think of that phrase as The Donald’s way of doubling down on speech, thought and reality, doublethink style!)

I have written about Trump and his less than simply lose grasp of, or interest in reality. And I have done so many, many times in the course of assembling this series up to here, and while discussing the larger Trump-oriented narrative that I have fit that into, going back to when a pack of the hungry were vying for becoming the Republican candidate for the 2016 presidential election. I have written of his swamp draining promises and his toxic waste dumping practices for almost as long. Corruption in highly placed officials and from proposed appointees to the Trump administration has become so common and so expected as to have numbed us all into somehow thinking of this as a form of new form of normal. And that might be his longest lasting legacy from his time in high office, for the callous damaging of American sensibilities and the withering of what should be our shared ideals and standards of public conduct that he has brought us to. And truth and fact have been just as victimized in all of this and to our collective detriment too, and regardless of our political similarities or differences.

I offered Part 32 of this series approximately four weeks ago, with it going live on April 8, 2018. And just in that short period of time, several scandal and corruption unveilings have erupted out of the Trump administration, all of which individually would have been seen as administration threatening news – if that is they did not simply fit into a recurring pattern of such mind numbing regularity.

• Corruption in highly placed officials and from proposed appointees to the Trump administration has become so commonplace and so expected by now and for all of us, as to have numbed us all into somehow thinking of this as a form of normal.

And few if any of us now expect anyone in a Trump administration to offer or even accept what would under more normal circumstances be considered factual truth. This all grievously harms all of us. And it leaves us grasping at straws to understand the how and why of all of this. And with that noted, I come full circle to cite my first installment to what has become this succession Trump-centric postings, along with a recent news piece that I make note of here, simply because it is literally a grasping at straws made overtly public:

Thinking Through the Words We Use in Our Political Monologs and
Why Trump Supporters Don’t Mind His Lies.

And meanwhile, Xi Jinping in China, Kim Jung Un in North Korea, Vladimir Putin in Russia and a host of others, think circles around our US president and act accordingly, and the United States becomes more and more a non sequitur on the world stage for his inept mismanagement and from his lack of vision and understanding.

So I conclude this posting by noting the current tantalizing teases in the news of what might somehow, some time come to pass:

Mueller Has Dozens of Inquiries for Trump in Broad Quest on Russia Ties and Obstruction,
Trump Adds Clinton Impeachment Lawyer, Bracing for a Fight on Multiple Fronts,
Mueller’s Questions Point to What Trouble Trump Is In,
Why Answering Mueller’s Questions Could Be a Minefield for Trump,
The Truth Is Coming for Trump and of course
Truth Has Stopped Mattering in the Russia Investigation.

I left out a number of news piece references here that more specifically discuss how terrified Trump’s inner circle supporters are that he might actually agree to meet with Muller and attempt to answer his questions under oath, and even when he has been given copies of all of them well in advance in order to give him time and opportunity to prepare for that.

I waited as long as I did between my April 8, 2018 posting and this one because so many new (should be) scandals have kept erupting on such an ongoing, steady and reliable basis and because so many Muller investigation hint-pieces have come out too. What comes next, besides just this toxic flow of ongoing same and routine out of the Trump White House, will happen … probably … eventually. When something more game changing does happen, I will add a Posting 34 to this.

Meanwhile, I am certain to continue adding new installments to both China and Its Transition Imperatives, as can be found at Macroeconomics and Business and its Page 2 continuation (as postings 154 and loosely following.) And I expect, with time to add more to my series: Donald Trump and the Stress Testing of the American System of Government, as can be found at Social Networking and Business 2 (posting 244 and loosely following).

Innovation, disruptive innovation and market volatility 41: innovative business development and the tools that drive it 11

Posted in business and convergent technologies, macroeconomics by Timothy Platt on May 5, 2018

This is my 41st 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 6-40.)

I began a more detailed discussion of the bookkeeping and accounting, operational-details side of innovation in a business in Part 40, where I at least briefly touched on the questions of where funding would come from for a specific research project, through what lines on an overall budget. And as a part of that I at least briefly discussed the complications that can arise from resorting to multiple funding sources, and perhaps multiple budget lines for managing them. The types and levels of financial management complexity that I make note of there can add real opacity into any overall effort to track and coordinate overall research efforts, for their overall funding requirements and for tracking their overall cumulative costs accrued.

I add here that that type of complexity and opacity can even mask what presumably earmarked funds are being expended on, where what would be expected to non-research funds might be diverted into supporting more explicitly research efforts, and where expected research funds might be used for more routine funding purposes instead. And the boundaries there, and from both of these perspectives can be very blurry and uncertain at times, so none of this need involve intent and at any level to misdirect funds too.

• The type of information coordination and sharing need that of necessity can and does arise in such complex budgeting systems, can create challenges when managing overall task and goals prioritization and when tracking and measuring overall levels of performance and cost-effectiveness achieved.

So I also raised the possibility of running all such expenses and their accounting for research endeavors, through single channel systems set up for that purpose. More specifically, and expanding on what I offered on this in Part 40, I note that:

• I have already raised the possibility of setting up a dedicated research center within a business in a variety of contexts in this blog, with its own leadership and management, and its own organizational structure and its own budget lines. See, for example: Keeping Innovation Fresh (as can be found at Business Strategy and Operations – 2 for its Parts 1-16.) I raise this business organization and management approach again here too, as offering a possible mechanism for managing research financing and for better addressing the above-cited, dispersed system challenges.
• Alternatively, businesses can and do also set up special needs and related funding streams in their overall fiscal planning and in their bookkeeping and accounting of that, and both for maintaining specific risk management reserve funds, and for enabling their capturing and developing research and development opportunity too.
• And I offer these possibilities as two of a larger possible set of them that can be pursued, to keep this line of discussion more practically oriented.

Up to here, this all addresses these issues from strictly within the business, and in terms of its more internal organizational issues. My goal here is to face outward and put that line of discussion into its proper, wider context and certainly where the innovation in question is market-facing and arising in a product or service development context. To be more specific in that, my goal here in this posting is to “add in consideration of market and marketplace stability and consistency, and uncertainty and volatility.” And I begin addressing that by offering a general point of conceptually organizing observation:

• One of the primary consequences of adding consumer interest and its evolution, and marketplace stability and consistency, and the uncertainty and volatility that they bring with them into this type of discussion, is that including those and similar factors into this type of narrative adds timing and timeline pressures into it, and as strategically and operationally defining considerations.
• These considerations become essential task and goal-prioritization factors for determining the When and How of this innovation, and for when setting its overall and step-by step scale of effort and commitment too.

Let’s consider that from the fundamentals and from the perspective of acknowledging and laying out some specific assumptions. I presume:

• That a business in question here, functions and competes in an industry and business sector that is highly competitive and with that competitive pressure coming in large part from a demanding marketplace that always expects and wants new and exciting: next and different.

Technology and product generation cycles, of necessity have to be very short for any business facing these types of pressure, and both for same-technology generation updates that would serve to keep more current offerings fresh, and for the development and marketable offering of the new and disruptively new – or at least the new that can be successfully marketed as such.

As products and product types mature, next generation new development steps can and generally do become smaller – unless and until one of the businesses in such a sector, or some disruptively new entrant outsider business moving into that arena, comes up with a game changing innovation that basically reinvents the product category as a whole for what is possible and for what its market would now come to demand, and resets the clock for this evolutionary process back to zero again.

And the pressures that I write of here, tend to lead to marketing hype and certainly when businesses face pressures to tout less significant innovative change as if it were more, in order to capture or retain market share. That only complicates and confounds the marketplace as far as valid reviews and product representations, and consumer awareness are concerned, adding market side friction to this entire system.

What I just did was to discuss at least briefly, two basic approaches to both innovation and its realization, and to funding it and certainly from a more practical hands-on, operational perspective where accounting and bookkeeping are carried out. Then I stepped back to discuss a set of business and marketplace factors that would enter into any strategic, hence any operational approaches attempted for carrying all of that out. My goal for my next installment to this series, is to tie that line of discussion back to the accounting and bookkeeping systems decision making process, as a presumably best-for-business organizational approach to them is arrived at and put in place.

In anticipation of that line of discussion to come, this will of necessity mean my breaking open the essentially black box, monolithic representation of research and development per se that I have been citing here, to consider that as a dynamic and mutable process and system of them too, and with all of the strategic and operational trade-offs and compromises that that can entail: cash flow and money management ones included.

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.

Planning for and building the right business model 101 – 37: goals and benchmarks and effective development and communication of them 17

Posted in startups, strategy and planning by Timothy Platt on May 3, 2018

This is my 37th posting to a series that addresses the issues of planning for and developing the right business model, and both for initial small business needs and for scalability and capacity to evolve from there (see Business Strategy and Operations – 3 and its Page 4 continuation, postings 499 and loosely following for Parts 1-36.) I also include this series in my Startups and Early Stage Businesses directory and its Page 2 continuation.

I have been discussing exit strategies in this series since its Part 33, that a new business might attempt when it has first started to be consistently profitable and with at least a modest consistent positive cash flow: when it as a result of that, enters its first real growth phase as an up and coming enterprise of promise. And I began discussing a specific scenario that fits that pattern in Part 36, that I repeat here as I set out to continue and for-here complete its narrative:

• A new venture, and certainly one that is built around a growth-oriented business model, might build its first bricks and mortar site, in effect as a prototype effort that it would refine with a goal of replication through, for example a franchise system. And there, licensing fees and ongoing franchise-sourced income going back to the home company, would provide funds that could be used for further capital development, among other things, to keep a fiscal systems focus here on what I include in this list.

I presumed in Part 36 that pursuing this business development path was an initial strategically considered, and a prepared-for objective for a business under consideration in this, and from the beginning. And I assumed in that, that its founders and owners have prepared and built accordingly and from their earliest pre-start planning stages on. Some franchise systems are in effect backed into, as emerging need and opportunity make them an attractive possibility. I assume here at least as a starting point, that franchise was a topic of discussion from before day one when the founders of this enterprise first began to dream and plan.

That noted by way of background to this installment, I add that I ended Part 37 by stating that I would consider the people now who would enter into this type of venture. And I begin that “… with the business founders and would-be overall owners of this type of at-least potential business empire. Then after offering at least a basic organizing discussion of who would most likely build a new venture with this possibility in mind, and successfully so, and after going on from there to consider franchisees and who would be good fits for taking that type of career opportunity on, I will reconsider the issues of business-wide consistency, as well as storefront-level flexibility, and both in prototyping new possibilities and in addressing local-to-store opportunities and challenges.”

• Who would seek to build a franchise system, and from scratch and as a starting business model objective?

One obvious approach to answering that would be to look to people who have had very positive experience working in this type of system. And look in particular for people with an entrepreneurial mind set and approach to life, who have become franchise holder participants themselves, and who have achieved real success at that. Look for people who have shown outlier levels of success developing and running single franchise outlets who dream bigger than that. And look to franchisees who have not stopped with simply managing some single franchise outlet, however successful, in such a system. Look for people who have managed, or who would wish to manage and effectively own, an at least small empire of outlets and franchise storefronts in such a system, and who have reached a point where the “effectively own” of that can no longer suffice.

I in fact raise a very important point there, that as a more general point of discussion reflects on what type of person would seek to found specific types of new businesses in general. And it is a point, as more generally stated, that connects both to my own career path and work life, and certainly as I have pursued entrepreneurial goals, and to the experience of others who I have worked with and learned from.

People who seek to build new businesses or who otherwise enter into what is fundamentally new for them professionally, almost always set out to build from a foundation of their own roots and experience, and in directions that connect with their ongoing drives and interests. True, many people make genuine career changes at least once over the course of their overall work lives. And this can mean going fairly far afield from their familiar backgrounds when doing so and for many of the at least overtly visible details of what they would do. But dramatic across the board change, and certainly as carried out for the sake of change per se, is more the exception than the rule here. And those who actively pursue that type of career transition are more likely to take their more divergent next step forward paths, because they see their old and familiar as no longer bring viable for them. And even they generally seek to capture and retain what might be considered their transferable skills and experience from old into new there.

That meshes with my own experience too, and certainly as a matter of general principle. And let me explain that with a brief digression from consideration of franchise systems and who would set out to build them per se, to consider career path transitions per se where franchise-related change would represent more specific case in point examples of that.

Drawing a few, selectively sketched out details from my own work life, where I have faced and carried out transitions, I spent a number of years working as a research scientist, and as a manager in that arena. And I went through some fairly significant career path transitions while doing this, and most certainly when leaving this type of work.

I actively carried out basic biomedical research at a key point in my earlier work life, gaining personal income and funding support for my research from privately sourced and government research grants: one of the commonest approaches there is for those who carry out research in academic settings. Then at a time when I was facing the end of my then-current round of grant support, I found myself facing a fundamental career path decision. Research grants are generally time-limited and my funding was coming up for renewal and with new competitive grant applications required and all that that entails. Should I simply try continuing along that path or should I try something new? And then a colleague of mine approached me with what he referred to as “an offer you can’t refuse” and I found that I couldn’t: I made a transition from working in a research lab to carrying out and supervising clinical research in a hospital setting, and teaching others how to do that type of work too. This meant shifting to an entirely new type of research for me in detail, while still working in a biomedical research context. But this also meant my moving into a position where my salary and benefits would arrive for me in regular, in-house employee form and not be time-limited constrained by my having to land that next funding grant.

And I built out all of the clinical research programs on a clinical service by clinical service basis at the hospital center in New York City that I was now working for, and built an overarching clinical research department out of that for them. Then for financial reasons that I have to admit, I saw coming as they arose, my department was downsized and I was downsized – and I made a more disruptive next step change, founding my first real consulting business and with a business organization and technology focus. My first real clients where drawn from the healthcare field, and came to me for assistance because they were in need of organizational guidance in setting up small businesses of their own (e.g. a medical oversight business that private ambulance services could hire, in order to meet their accreditation requirements for being allowed to respond to 911 emergency service request calls.) And I quickly branched out from there and with an information technology focus and a more general business development one as well. I came to work in and with multiple industries and businesses in them, new and established.

Why do I cite this here? First, my own work life example is my own and I know it and its details. Second, I have made both minor transitional and disruptively significant transitional changes over the years, and I have seen what was ostensibly some single same career stage evolve and morph over time, and in ways and to degrees that have cumulatively added up to being disruptive in nature. My consulting business evolution to include participation in as wide a range of business types as I have worked with, from a much more limited beginning, highlights that. The principles that I cite here, and from my own experience might not be grounded in franchise systems experience – except insofar as I have business consulted with a couple of large corporations that have franchise systems within them. But these basic career step patterns apply to those who become involved in, or who end up building franchise systems too. They reach out to new while seeking to hold onto and build from transferable sources of value and strength from their own pasts. And evolutionary change with its cumulative impact enters into that for them too.

Most everyone who I have worked with, or know for their professional career paths, have built their next career steps from as much of a foundation of what they have experience in already, as would be realistically possible and beneficial for them: myself included. People who strike out with an intent to build franchise systems, and scalable enterprises that can be built around proof-of-principle prototype storefronts, build from what for them is their familiar too – and whether that means building a franchise system around a business type they know and are comfortable with, or from comfort zone familiarity with being a franchisee per se or both. And the same applies, of course, for those to start out thinking “single location” and then build out from there to assemble what becomes a franchise system business too.

Now, who would seek to be a franchisee in such a growing business empire? I will turn to that question in my next installment to this series, and will continue on from there as noted above with discussion of… “the issues of business-wide consistency, as well as storefront-level flexibility, and both in prototyping new possibilities and in addressing local-to-store opportunities and challenges.” In anticipation of that line of discussion to come, I will approach these issues from the perspective of who would do this and why.

Meanwhile, you can find this and related postings and series at Business Strategy and Operations – 4, and also at Page 1, Page 2 and Page 3 of that directory. And you can find this and related material at my Startups and Early Stage Businesses directory too and at its Page 2 continuation.

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