Platt Perspective on Business and Technology

Donald Trump, Xi Jinping, and the contrasts of leadership in the 21st century 15: some thoughts concerning how Xi and Trump approach and seek to create lasting legacies to themselves 3

Posted in macroeconomics, social networking and business by Timothy Platt on April 19, 2019

This is my 15th installment in a progression of comparative postings about Donald Trump’s and Xi Jinping’s approaches to leadership per se. And it is my 9th installment in that on Trump and his rise to power in the United States, and on Xi and his in China, as they have both turned to authoritarian approaches and tools in their efforts to succeed there. I began this line of discussion with three postings on cults of personality. And I continued from there to more fully address an approach to leadership that holds such cult building approaches as one of its most important tools, in what I refer to as the authoritarian playbook. Then I began to put all of this into a larger and longer-term historical perspective by turning to consider legacies in this type of authoritarian system. See Social Networking and Business 2, postings 367 and loosely following (there identified with accompanying tagging text that identifies these postings for their more Trump-related significance. I also offer links to them with corresponding China and Xi-oriented tagline text attached at Macroeconomics and Business 2.)

I began discussing legacies as they are conceived and shaped in an authoritarian system in Part 7 and again in the first half of Part 8 of this discussion of Trump’s and Xi’s rise to power. Then I turned from that general, organizing line of discussion in the second half of Part 8 to explicitly consider Trump and his legacy building efforts. My primary goal moving forward from here is to at least begin to discuss Xi Jinping and his legacy building, but to put that in perspective I am going to at least start it with a continuation of my discussion of Donald Trump and his. And I begin that by repeating a point of distinction that I made in Part 7 of this now nine installment progression that I will make use of moving forward in this. Legacy and legacy building can be conceptually divided into two roughly characterizable categories:

• Proclaimed legacy building as a tool for garnering continued support from a politically supportive base: legacy-oriented advocacy if you will as a marketing tool there, and
• Actively intended and pursued legacy building (which can also be used as a marketing tool but where actual building is also a key goal.)

Donald Trump has actively presented himself in terms of his legacy intentions, but at least up to now he has primarily sought to achieve proclaimed legacy, marketing oriented goals and certainly as president. And he has primarily done this to shore up his support from his base, against ongoing pressures and ongoing resistance that he has faced from his political enemies. Think of this as “lower case L” legacy for its overtly ephemeral nature. In anticipation of discussion to come, I will argue that Xi has primarily pursued a more actively developed “upper case L” legacy campaign, even as he has used the full power of both his Communist Party and his government in China to actively develop a proclaimed legacy too. And in that, he has made real effort to build his cult of personality-supportive, proclaimed legacy in ways that will endure too, illustrating how the boundaries between these two categorical types can blur.

But before delving into Xi’s story here, I will continue my discussion of Trump’s. And I will begin doing so by raising a second line of categorical distinction, that will prove to be crucially important for understanding Xi and his efforts when I begin discussing them.

• Legacy building can be pursued as a negative and as a means of breaking down and destroying what already is and has been.
• Or it can be pursued as a positive, and as an attempt to build an historically defining New.

Think of the first of those possibilities as “building,” if you will, to remove competition and other challenges from the present and past. And think of the second of them as being more entirely future oriented and as an attempt to build where no such qualifying caveats to that would be necessary.

Trump’s legacy building is much more negatively oriented than it is positive and for both his proclaimed legacy efforts and for his actively pursued, actual legacy building ambitions. Just consider how actively he has worked to demolish the Obama legacy, starting with his efforts to repeal the healthcare reforms that then president Obama was able to push through Congress and into law, and regardless of the consequences that that would have for tens of millions of American citizens who he claims to support and defend. And crucially importantly this negativity holds just as true for Trump’s efforts to actually build as it does for his efforts to break and remove, as exemplified by his long-sought xenophobia-driven attempts to fund and build his Southern Border Wall between the United States and Mexico.

Xi’s ambitions are both larger and further reaching, and much more positive in nature, even if tremendously dystopian for many of the details that he strives to put into place. And to clarify a possible ambiguity in my bullet point comment on positive legacy, New can mean building for things never seen or imagined but this can also mean realizing a perhaps largely idealized, fictionalized golden age past glory too. Xi is striving for both.

I conclude my comments here on Trump and his legacy building by offering a brief in-the-news update to my comments of Part 8, on how he “thrives in chaos.” And this can also be seen as a news update as to how a narcissistic personality can be led around by the nose by anyone who can flatter and cajole effectively enough to be able to twist their own ambitions so as to make them appear to be adulation and praise.

First, some background update:

Trump Signals Even Fiercer Immigration Agenda, With a Possible Return of Family Separations.
Trump Administration to Push for Tougher Asylum Rules.
Trump Says the U.S. Is ‘Full.’ Much of the Nation Has the Opposite Problem.

Think of this as xenophobia and the cruelty of its discontents, and think of it as pursuing what is essentially a pure form of proclaimed legacy building and of negative legacy building in the process. It is important to note that one of Trump’s strongest supporters for his immigration policy and one of his strongest and most active enforcers of this, has been his secretary of Homeland Security: until recently at least, Kirstjen Nielsen.

Nielson zealously pursued and enforced the Trump administration’s family separation policy in which infants and toddlers, and children in general were pulled from their parents’ arms and put into separate detention away from them. And tellingly, this proved to be too much for many who would see themselves as Republicans, as well as for those who see themselves as Democrats and Independents. And that within-party discontent began even before the publicized deaths of several of these children in detention, as efforts to reunite families so separated proved to be all but impossible, bureaucratically. (Though even this has not put a real dent in Trump’s rock steady 40% approval rating as maintained by his core base supporters.) And with that all noted, I add:

Kirstjen Nielsen Resigns as Trump’s Homeland Security Secretary and
Trump Purge Set to Force Out More Top Homeland Security Officials.

Nielsen was forced to resign or be fired, and others from the Homeland Security Department’s leadership are on the way out too with still more to follow. And the basic pattern that Trump has created in his administration continues, with still-remaining members of his “team”, continuing their ongoing infighting against each other: an ongoing conflict that Trump in fact encourages among the senior members of his inner circle. And they have all continued to use their access to his ear to knife and eliminate their competition, with him remaining the essential source of power and control in the middle of all of that. And that has meant Trump losing the very people who have worked the hardest to actually carry out his immigration policy and other pieces of his legacy building ambitions.

I could as easily and accurately divide legacy into short term-oriented and immediately expedient, and longer term-oriented categories, as I seek to draw clarifying points of distinction here as to what legacy even means in this type of context. And with this noted, I begin to more explicitly consider Xi Jinping and his legacy building efforts. And I will begin that by offering an historical digression, going back to a point in time that might not seem at first to be a relevant starting point here, but that I would argue has had a powerful shaping influence on Xi and the people who most actively support him, and certainly from a position of office and authority: the leadership and the nation shaping impact of China’s last hereditary dynasty: the Qing Dynasty. More specifically, I will at least briefly and selectively discuss that period of China’s history and the so called golden age of the Qing Dynasty as I begin laying the groundwork for a more detailed discussion of Xi and his ambitions here. And I will also discuss Mao Zedong and his tenure in leadership too, comparing these two historic periods for the lessons that they offer today’s China and today’s leadership there.

And in anticipation of what is to come in this series, I will divide Xi Jinping’s legacy building efforts into three admittedly closely interconnected areas of activity and intention:

• His effort to reshape China through massive infrastructure changes within the country,
• His effort to reach out to the world, using infrastructure development among other political tools to make his China a globally recognized superpower,
• And his effort to reshape China’s culture and its societal perspective, and with a cult of personality that is built around his story, of his creation serving as a defining linchpin that this ongoing New would be built from. In anticipation of this narrative thread to come, this will mean discussing Xi’s China Dream: his Zhōngguó Mèng (中国梦), and his shaping and even defining role in it.

I will begin addressing all of this in my next installment to this series. Meanwhile, you can find my Trump-related postings at Social Networking and Business 2. And you can find my China writings as appear in this blog at Macroeconomics and Business and its Page 2 continuation, and at Ubiquitous Computing and Communications – everywhere all the time and Social Networking and Business 2.

Reconsidering Information Systems Infrastructure 9

Posted in business and convergent technologies, reexamining the fundamentals by Timothy Platt on April 18, 2019

This is the 9th posting to a series that I am developing, 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 and its Page 3 continuation, postings 374 and loosely following for Parts 1-8. 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 stated towards the beginning of Part 8 of this series that I have been developing a foundation in it for thinking about neural networks and their use in artificial intelligence agents. And that has in fact been one of my primary goals here, as a means of exploring and analyzing more general issues regarding artificial agents and their relationships to humans and to each other, and particularly in a communications and an information-centric context and when artificial agents can change and adapt. Then at the end of Part 8, I said that I would at least begin to specifically discuss neural network architectures per se and systems built according to them in this complex context, starting here.

The key area of consideration that I would at least begin to address in this posting as a part of that narrative, is that of flexibility in range and scope for adaptive ontological change, where artificial intelligence agents would need that if they are to self-evolve new types of, or at least expanded levels of functional capabilities for more fully realizing the overall functional goals that they would carry out. I have been discussing natural conversation as a working artificial general intelligence-validating example of this type of goal-directed activity in this series. And I have raised the issues and challenges of chess playing excellence in Part 8, with its race to create the best chess player agent in the world as an ongoing performance benchmark-setting goal too, and with an ongoing goal beyond that of continued improvement in chess playing performance. See in that regard, my Part 8 discussion of the software-based AlphaZero artificial intelligence agent: the best chess player on the planet as of this writing.

Turning to explicitly consider neural networks and their emerging role in all of this, they are more generically wired systems when considered at a hardware level, that can flexibly adapt themselves on a task performance level basis, for which specific possible circuit paths are actually developed and used within them, and for which of them are downgraded and in effect functionally removed too. These are self-learning systems that in effect rewire themselves to more effectively carry out data processing flows that can more effectively carry out their targeted functions, developing and improving circuit paths that work for them and culling out and eliminating ones that do not – and at a software level and de-facto at a hardware level too.

While this suggestion is cartoonish in nature, think of these systems as blurring the lines between hardware and software, and think of them as being at least analogous to self-directed and self-evolving software-based hardware emulators in the process, where at any given point in time and stage in their ongoing development, they emulate through the specific pattern of preferred hardware circuitry used and their specific software in place, an up to that point most optimized “standard” hardware and software computer for carrying out their assigned task-oriented functions. It is just that neural networks can continue to change and evolve, testing and refining themselves, instead of being locked into a single fixed overall solution as would be the case in a “standard” design more conventional computer, and certainly when it is run between software upgrades.

• I wrote in Part 8 of human-directed change in artificial agent design and both for overall systems architecture and for component-and-subsystem, by component-and-subsystem scaling. A standard, fixed design paradigmatic approach as found in more conventional computers as just noted here, fits into and fundamentally supports the systems evolution of fixed, standard systems and in its pure form cannot in general self-change either ontologically or evolutionarily.
• And I wrote in Part 8 of self-directed, emergent capabilities in artificial intelligence agents, citing how they might arise as preadapted capabilities that have arisen without regard to a particular task or functional goal now faced, but that might be directly usable for such a functional requirement now – or that might be readily adapted for such use with more targeted adjustment of the type noted here. And I note here that this approach really only becomes fundamentally possible in a neural network or similar, self-directed ontological development context, with that taking place within the hardware and software system under consideration.

Exaptation (pre-adaptation) is an evolutionary development option that would specifically arise in neural network or similarly self-changing and self-learning systems. And with that noted I invoke a term that has been running through my mind as I write this, and that I have been directing this discussion towards reconsidering here: an old software development term that in a strictly-human programmer context is something of a pejorative: spaghetti code. See Part 6 of this series where I wrote about this phenomenon in terms of a loss of comprehensibility as to the logic flow of whatever underlying algorithm a given computer program is actually running – as opposed to the algorithm that the programmer intended to run in that program.

I reconsider spaghetti code and its basic form here for a second reason, this time positing it as an alternative to lean code that would seek to carry out specific programming tasks in very specific ways and as quickly as possible and as efficiently as possible, as far as specific hardware architecture, system speed as measured by clock signals per unit time, and other resource usage requirements and metrics are concerned. Spaghetti code and its similarly more loosely structured counterparts, are what you should expect and they are what you get when you set up and let loose self-learning neural network-based or similar artificial agent systems and let them change and adapt without outside guidance, or interference if you will.

• These systems do not specifically, systematically seek to ontologically develop as lean systems as that would most likely mean their locking in less than optimal hardware-used and software-executed solutions than they could otherwise achieve.
• They self-evolve with slack and laxity in their systems, while iteratively developing towards next step improvements in what they are working on now, and in ways that can create pre-adaptation opportunities – and particularly as these systems become larger and more complex and as the tasks that they would carry out and optimize towards become more complex and even open-endedly so (as emerges when addressing problems such as chess, but that would come fully into its own for tasks such as development of a natural conversation capability.)

If more normative step-by-step ontological development of incremental performance improvements in task completion, can be compared to more gradual evolutionary change within some predictable-for-outline pattern, then the type of slack allowance with its capacity for creating fertile ground for possible pre-adaptation opportunity that I write of here, can perhaps best be compared to disruptive change or at least opportunity for it – at least for the visible outcome consequences observed as a pre-adapted capability that has not proven particularly relevant up to now is converted from a possibility to a realized current functionally significant actuality.

And with this noted, I raise a tripartite point of distinction, that I will at least begin to flesh out and discuss as I continue developing this series:

• Fully specified systems goals (e.g. chess rules as touched upon in Part 8 for an at least somewhat complex example, but with fully specified rules defining a win and a loss, etc. for it.),
• Open-ended systems goals (e.g. natural conversational ability as more widely discussed in this series and certainly in its more recent installments with its lack of corresponding fully characterized performance end points or similar parameter-defined success constraints), and
• Partly specified systems goals (as in self-driving cars where they can be programmed with the legal rules of the road, but not with a correspondingly detailed algorithmically definable understanding of how real people in their vicinity actually drive and sometimes in spite of those rules: driving according to or contrary to the traffic laws in place.)

I am going to discuss partly specified systems goals and agents, and overall systems that would include them and that would seek to carry out those tasks in my next series installment. And I will at least start that discussion with self-driving cars as a source of working examples and as an artificial intelligence agent goal that is still in the process of being realized, as of this writing. In anticipation of that discussion to come, this is where stochastic modeling enters this narrative.

Meanwhile, you can find this and related postings and series at Ubiquitous Computing and Communications – everywhere all the time and its Page 2 and Page 3 continuations. 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 28 – the jobs and careers context 27

This is my 28th 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 and its Page 4 continuation, postings 484 and following for Parts 1-27.)

I began addressing a list of issues in Part 25 of this, that can and do arise at least occasionally during longer employment tenures, that I repeat here as a whole for purposes of smoother continuity of narrative in what is to follow. And I begin this posting by noting that I have already at least preliminarily addressed the first two of the topics points of this list (as noted parenthetically here) and the first half of Part 3 as well:

1. Changes in tasks assigned, and resources that would at least nominally be available for them: timeline allowances and work hour requirements definitely included there (see Part 25 and Part 26),
2. Salary and overall compensation changes (see Part 27),
3. Overall longer-term workplace and job responsibility changes and constraints box issues as change might challenge or enable your reaching your goals there (with discussion of this begun in earlier installments in this progression of them),
4. Promotions and lateral moves,
5. Dealing with difficult people,
6. And negotiating possible downsizings and business-wide events that might lead to them. I add this example last on this list because navigating this type of challenge as effectively as possible, calls for skills in dealing with all of the other issues on this list and more, and with real emphasis on Plan B preparation and planning, and execution too, as touched upon in Part 23.

My goal for this posting is to further address the above stated Point 3 and its issues, focusing here on constraints box considerations and further expanding out the range of employee needs and options for addressing them, that can effectively be brought to the table in the types of work position and overall compensation negotiations that I have been discussing here.

Note: the issues that I discuss here can rise to critical importance because an employee’s work responsibilities have expanded out beyond any realistic interpretations of the official job description in place for work actually performed, and on an ongoing basis. That is the basic underlying reason that I have discussed up to here in these postings, for seeking opportunity to negotiate, or renegotiate terms of employment at a business. But this can also become important and even crucially so as a consequence of non-work, life issues and when an employee needs to find a better way to juggle the needs of their overall life with those of their job too. So I write here about expanding the range of options and option types that might be negotiated over, but I also write here from a wider perspective as to why these negotiations might even be needed in the first place. Remember in that context, that some of the possibilities that an employee might want and even need to gain approval for, would essentially only arise as issues for them when they have to address demands and pressures that arise outside of work. So this wider negotiating context is particularly important here in this posting.

With that noted, let’s start this line of discussion from the already at least partly addressed context of changes in job responsibilities held, and similar workplace reasons for seeking out change. And to set the stage for discussion to follow here, I explicitly note that I am not writing about special circumstance, limited duration changes in the work load expected of an employee or manager under consideration here, and certainly where everyone working at a business is facing what are essentially the same type of “crunch time” work load increases for some period of time, for what they would be expected to do. To take that out of the abstract, consider large retail businesses with their seasonally expected large and even tremendously so, increases in sales and sales-supportive business activity going into their year-end holiday sales seasons. My focus here is on fundamental, long-term and essentially permanent shifts in what at least some employees and managers are expected to do as their new upgraded but not necessarily automatically rewarded standard, expected work flow. The types of employee recognition and overall compensation changes that I address here, as negotiating goals are all long-term in nature. So are the shifts in employment context and in job requirements that I address here too. And that point is crucial to all that I have been discussing in this and the immediately preceding four installments to this series. And this understanding is equally important when thinking through and acting upon the issues that I will be addressing here as I continue addressing the rest of the topics issues of the above-repeated list.

• Effective negotiations are built around what at least hopefully can become a shared effort to find commensurate, equitable resolutions in what is to happen moving forward, that would match the changes that have led to those negotiations in the first place.
• And the key words there are “commensurate” and “equitable,” as in fair and balanced, and with a goal of arriving at agreement as to what those words mean as a practical matter, in the situation under discussion.

I cited one reference in the above topics list, for constraints box and what that term means as a key jobs and careers consideration. And I begin to more fully address that larger range of possible commensurate and equitable resolution, bargaining points here by offering two more relevant reference links too:

Globalization and Your Constraints Box.
Working In-House, Working as a Consultant and Your Constraints Box.

The basic idea of a constraints box is very simple. Start out by listing all of the needs, desires and wishes that you can think of that if at least individually met, might at least incrementally positively impact upon and reshape your work life and your life as a whole from that. In effect, toss these wish list possibilities as a loose and unorganized, unprioritized collection into a box. And after you have built up your collection there for a while, open the box and begin looking for patterns in what you have put in there, and for duplications too. What have you added several times, perhaps with slightly different wording but with a same basic need or desire coming to the fore, for you repeatedly? Which of your constraints box items fit together in patterns and what do those emerging patterns have to say as to what is and is not really important for you? Which of them are outliers, but ones that are still very important to you? Which of your entries here are more whim in nature and discardable, and which are more centrally important to you?

Collectively, these listed items can help you map out the points that you would want to raise and discuss in any jobs or careers discussion, where the terms of your employment and the workplace conditions that you and an employer would come to agreement with become important. To take that out of the abstract with a specific wish list item, is flex-time work scheduling important to you so you can more easily meet pressing family obligations? And to add in a second possibility here, would you see the possibility of being able to work from home at least part time, of real value and meaning to you? Does your employer support these options or ones like them, and if so would your immediate supervisor there be supportive of this, in your case? Now, how would you best approach this type of workplace issue if you wanted to try to negotiate a deal with your direct supervisor that would allow you’re achieving one of these constraints box goals?

• Know yourself and your needs, and know your own priorities for all of this.
• Know your workplace, and from a corporate culture and business practice perspective, and from the perspective of how your supervisor more individually views the issues that you might raise here.
• Think through how best to frame and present your constraints box goals here, and with some raised for discussion as throw-away negotiating points where that might help to advance your cause, but with that option only resorted to with care.
• Think through what you might be willing to give on, in exchange for a more valuable to you concession. And think longer-term here and not just in terms of your immediate short-term needs – unless that is, you are explicitly seeking a short-term accommodation, in which case you are probably looking for accommodations that would not go into your longer-term constraints box lists in the first place.
• Know what is short-term and what is long-term there and think in terms of how you would best present them as such.
• And listen for possible flexibility in the feedback you receive in these discussions, where rephrasing and fine tuning a requested accommodation might make it more acceptable. This point cuts to the heart of what your actual constraints box entries actually are and to the heart of what their actual priorities are for you. Don’t be surprised if discussing them in this type of setting brings you to reconsider your constraints box goals here, and what really defines them for you.
• And if you seek change in the terms under which you work at a business, and certainly where that would involve changes in when, where or how you perform your work, present your case in terms of smooth continuity, or even as a potential source for you’re being able to achieve real work performance improvement – if you can make the changes that you seek, with approval from your supervisor and from your employer as a whole.
• This means thinking through how you can make the goal of that last point both true and realistic sounding, where appearance is in fact an entirely separate if equally important matter here.
• And this means thinking through how your employer reaching agreement with you on accommodations here, need not appear as you’re being allowed a special exception that would not be offered to your peer level colleagues there too.
• And throughout this process think in terms of best alternatives to negotiated agreement if you cannot secure the accommodations that would really matter to you here. What is your Plan B? Think this through before you sit down to start these negotiations, and have an idea as to how you might proceed under this set of circumstances.

As a final point here, it is important to remember that your constraints box needs will change with time. Constraints box goals and requirements that hold importance when a professional still has young children, might no longer apply as those children grow up and become more independent and as they move away from home as a part of that. Constraints box needs can and do change as jobs change too, where for example commutes become shorter, or significantly longer from working with a new employer. As such, it is important to update your constraints box periodically, and certainly when approaching the types of work and life negotiations under discussion here.

I always recommend that you start your constraints box list assembly from scratch, and without reviewing your older lists first when you revisit this exercise. The idea there is to capture your new needs and priorities as they are now, and without you’re adding in older entries simply because they made sense before. Then after you have assembled your new list, compare it to your old one and think through the differences: the changes that have entered into your thinking and your prioritization. The insight that this type of comparison can offer can help you to more effectively order and prioritize what you have in your constraints box now, and it can help you to better understand the short and longer term significance that your current list entries hold for you too. Hint: if you forgot to add in something from your old list in your new one, it probably is low or even very low in priority now at most, and even if it was high priority at some earlier date.

• The idea here is to be up to date on what you see as your needs and priorities in this, and that you approach the types of negotiations discussed here as fully prepared for them as possible, for laying out your current negotiating points and for arguing their case.

I am going to continue this discussion in a next series installment where I will turn to consider Point 4 of the above list: promotions and lateral moves. After that, I will address the remaining entries offered there. Meanwhile, you can find this and related material at Page 4 to my Guide to Effective Job Search and Career Development, and also see its Page 1, Page 2 and Page 3. And you can also find this series at Social Networking and Business 2 and also see its Page 1 for related material.

When leadership means finding a better balance between controlling and enabling

Posted in strategy and planning by Timothy Platt on April 13, 2019

… and some thoughts as to how and when controlling and enabling can come into direct conflict with each other with all of the consequences that can arise from that.

By now I have added enough postings to this blog on leadership to fill a book, or at least a small one. And that would probably even hold true as an objective assessment if only my individually stand-alone postings on that topic were to be counted, leaving off relevant installments in larger series-long efforts and even just series that focus on this general topic itself (e.g. see Adaptive Leadership and Thriving in the Face of Change, as can be found at Business Strategy and Operations – 3 as postings 404-416.)

Quite simply, there is always at least one more point that could be made, or issue that could be raised and discussed as to the nature of leadership and its best practices. And that would hold true for anyone, however experienced, who devotes any significant amount of their time and effort into studying and thinking about leadership and who seeks to lead more effectively themselves, from that. So I find myself adding to my list of blog installments on this topic again, with this posting. And the general issues that I would raise here, come in very large part from within prospective would-be leaders themselves, and not strictly speaking from the contexts and circumstances that they would have to navigate as they manage and lead.

My primary goal here is in fact to discuss two sets of issues as they intersect and as they effectively shape and even define each other. The first is that of control:

• Whether that goes from the top on down along the lines of a table of organization,
• Or whether it is encouraged and even required in others as they take a sense of ownership in what they do and in what they manage in their areas of responsibility there.

In its widest sense that expansion of leadership opportunity and responsibility can transcend title or position in a business, where experience and expertise and the interpersonal skills needed to create real value for the organization from them, are valued and supported, and so is the reasoned judgment of those who hold and would share such resources.

If a first reading of the title of this posting would lead some to assume that I would write more entirely of top-down leadership and from the perspective of a strict congruence between executive title and position, and leadership skills and their expression … they would be partly right as that is in fact a common pattern for most businesses, and for most organizations in general and certainly where overall organization-wide decisions have to be made. But I allow here for a wider leadership context as arises for need at least, in even more top-down managed organizations, and certainly as middle and lower level managers find need to organize and manage and lead the combined efforts of the members of the teams that specifically report to them and that they are responsible for.

And the second, sometimes conflicting imperative that I would write of here is that of enablement. And yes if a business is to be effective in making use of the fullest range of human resource capabilities that it has at its disposal and both on-staff and from shorter term employees, then both managerial and leadership control, and enablement have to rise to the status of imperatives there.

• I have at least occasionally written of leaving money on the table from entering into less than fully considered business deals. If the senior leadership of a business fails in carrying through on what should be their side to this duality: seeking to create value through an effective balance of control and enablement, or of control and empowerment or enfranchisement if you prefer, that can mean effectively losing that table too.

Where is the conflict that I write of here? If the senior executives of a business in effect squeeze too hard in their efforts to hold onto personal control on their part, limiting and even denying such decision making options for others under them, they can easily find they have created a situation where no one else there sees themselves having a stake or a voice in the business. And this means no one there, working for that senior leadership, seeing reason to take any extra steps in trying to offer more than absolutely required, or anything like a creative New there – and certainly if that would be met with resistance from above for not following the already standard and approved.

• You cannot legitimately expect creativity or the enthusiastic engagement that it grows from, from hands-on employees or lower level managers who see themselves as having no say and no real authority over what they do, and who as a result see themselves as being treated like drones.

When the senior executives, or even just the (singular) most senior executive at a business makes all decisions, that stifles input and insight that they would need too. They find themselves trying to lead in what has become an unnecessary information vacuum too. And all of this leads to that business being limited to having a more reactive-only capability too, and one with delayed response times at that. So when I write of enabling in the title to this posting, I am writing about enabling the business as a whole, as much as I am writing of enabling the people there as individuals. And when I write of control, and certainly as a measure of leadership, I write of the importance of taking a wider perspective there too. And finally, when I write here of addressing two specific areas of consideration as named in the title to this posting, I have in fact used them as an opening for more widely considering the business as a whole and its dynamics.

I began this short note by citing that I have successively touched upon and at least briefly noted a wide range of issues that relate to leadership and its best practices. And I write here, of how those issues that I have written of in this context, and a great many more that I have yet to touch upon, all intersect: all interact. That noted, I have still only touched on a few of the possible lines of connection that I could raise here in this brief discussion.

To briefly add one more puzzle piece to this mix, I have frequently written of the value of agility and flexibility in a business (see for example, my series: Intentional Management as can be found at Business Strategy and Operations – 3 and its Page 4 and Page 5 continuations, for its Parts 1-51.) When the balance and distribution of control and authority, and enablement and opportunity that I write of here breaks down, capability of following anything like the intentional management approach that I offer there, with its focus on flexibility and agility, breaks down too. So I offer this posting as a view into businesses as a whole, as can be perceived through the lens of leadership and how it is attempted and pursued for two key sets of issues.

Meanwhile, you can find this and related postings and series at Business Strategy and Operations – 5, and also at Page 1, Page 2, Page 3 and Page 4 of that directory.

Building a startup for what you want it to become 37: moving past the initial startup phase 23

Posted in startups by Timothy Platt on April 12, 2019

This is my 37th 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 1-36.)

I have been discussing a succession of business intelligence-related risk management issues in this series since Part 31, and began discussing the challenges of data anonymization as a part of that in Part 36. And my initial goal at least for this posting is to continue my discussion of that complex topic, at least for purposes of this series.

I began discussing anonymization as a source of risk management concern when handling confidential and personally identifiable information, by pointing out how true, effective anonymization of original data sources is becoming increasingly difficult and even impossible at least as a zero risk goal, as big data becomes bigger and bigger, and as it is more and more effectively organized into actionable patterns. To briefly reiterate the conclusion that I arrived at in my Part 36 narrative, the more comprehensive the overall set of data types collected and the more skillfully and comprehensively they are organized and processed into meaningful actionable patterns, the more and more likely it becomes that even just sets of what would seem to be anonymous data about some individual source, would indicate the values that must have been there for key individually identifying data fields that were redacted for anonymization purposes.

I then concluded Part 36 by stating that I would offer some thoughts here on how to move beyond this current and growing impasse where this tool: data anonymization has so significantly begun to fail us. Then after addressing that, as at least an initial first step response, I said that I will more specifically reconsider the impact that all of this has on:

• Businesses that provide big data as a marketable commodity,
• Businesses that buy access to it (startups included), and
• The ultimate sources of all of this data, with consumers and other individuals prominently included there.

And I added that after addressing those issues, I will circle back in this overall discussion to consider opt-in and opt-out options and systems, and the stealthy collection of more and more data and from more and more sources where neither of those choice possibilities are always meaningfully possible. Facebook’s user information comes to mind as a source of cautionary note examples there, and I will cite and discuss that business and its practices in this regard when I reach this point in this overall narrative.

• Meanwhile, I begin addressing that new list of topics to come here, with the question of how data anonymization might at least be made more secure than it is now, as a risk management tool for limiting liability faced from violating security oversight of personally identifiable information.

I begin this by acknowledging what might be the single most important starting point assumption that the developers, managers and users of big data should consider:

• Data anonymization might be important and even crucially so and for vast numbers of businesses and business models, and ultimately for the consumers who they would serve too.
• But it can never be made absolutely perfect: absolutely secure from a risk management perspective.
• So any real effort here should be directed towards making this process and the pools of data assembled from it as risk-reduced as possible. 0% risk is never going to be possible in the real world for any business or business process, so this type of risk limiting is in fact a realistic goal and one that would meet realistically effective risk management requirements. A realistic and I add acceptable goal here should be one of acknowledging that there are specific avoidable and unavoidable risks here, understanding how they arise, and reducing them to an acceptable level where possible, and with mechanisms in place for identifying and rapidly remediating any security and confidentiality breakdowns that do occur.

Now, how would I propose actively addressing this challenge? How would I propose carrying out the intentions offered in the above three bullet points and particularly in the third one of that set?

You can only control and minimize the risk faced from anonymizing increasingly comprehensive sets of data as gathered across larger and larger numbers of individual sources, if you actively test to see if and where it might be possible to infer redacted personally identifiable data field contents, from the accumulated patterns of what would still be included as anonymized data. You have to have a team that is dedicated for at least some significant proportion of their jobs, to actually trying to break the anonymization protections that have been attempted, by testing to see what they can learn from the data that is included in anonymized, “cleaned” data sets, that would breach efforts to protect the identities and other confidential information of that data’s original sources.

• Set up a white hat hacker team for this in-house, or outsource this testing to a reliable third party specialist service provider and preferably one that is bonded and that has insurance coverage included in their consulting agreements, in the event of confidentiality breaches in the data sets that they approve as meeting their due diligence standards.

This means looking at older data that is already held in these data repositories as well as looking at new data streams as they come in. It is in fact that older data that was gathered in before this issue rose to visible prominence that might prove to be the most problematical and precisely because of that fact, and certainly where it is mixed into new data and data types as they arrive.

• Ultimately, this is all about looking for, characterizing and understanding, and remediating blind spots in your thinking as to what types of data you actually have and how all of its data fields might connect together to tell a story about its original sources.

I am going to continue this discussion in a next series installment where I will explicitly discuss the three participants in any business information-as-commodity transaction: data aggregating, developing and selling businesses, data acquiring and using businesses, and the original sources of all of this data with that ultimately coming to a large degree from individual consumers and customers. And as noted above, my goal beyond that is to take this line of discussion out of the abstract by citing and at least selectively discussing, some real world business examples: Facebook definitely included there.

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 6

This is my 6th posting to a short series on the growth potential and constraints inherent in innovation, as realized as a practical matter (see Reexamining the Fundamentals 2, Section VIII for Parts 1-5.) And this is also my third posting to this series, to explicitly discuss emerging and still forming artificial intelligence technologies as they are and will be impacted upon by software lock-in and its imperatives, and by shared but more arbitrarily determined constraints such as Moore’s law (see Part 4 and Part 5.)

I began discussing overall patterns of technology implementation in an advancing artificial intelligence agent context in Part 4, where I cited a set of possible scenarios that might significantly arise for that in the coming decades, for how artificial intelligence capabilities in general might proliferate,( as originally offered in:

• Rose, D. (2014) Enchanted Objects: design, human desire and the internet of things. Scribner.)

And to briefly repeat from what I offered there in this context, for smoother continuity of narrative, I cited and began discussing those four possible scenarios (using Rose’s names for them) as:

1. Terminal world, in which most or even essentially all human/artificial intelligence agent interactions take place through the “glass slabs and painted pixels” of smart phone and other separating, boundary maintaining interfaces.
2. Prosthetics, in which a major thrust of this technology development is predicated upon human improvement, with the internalization of these new technology capabilities within us.
3. Animism, and the emergence of artificial intelligence ubiquity through the development and distribution of seemingly endless numbers of smart robotic and artificially intelligence-enabled nodes.
4. And Enchanted Objects, in which the once routine and mundane of our everyday life becomes imbued with amazing new capabilities. Here, unlike the immediately preceding scenario, focus of attention and of action takes place in specific devices and their circumstances that individually arise to prominence of attention and for many if not most people, where the real impact of the animism scenario would be found in a mass effect gestalt arising from what are collectively impactful, but individually mostly unnoticed smart(er) parts.

I at least briefly argued the case there for assuming that we will in fact come to see some combination of these scenarios arise in actual fact, as each at least contextually comes to the top as a best approach for at least some set of recurring implementation contexts. And I effectively begin this posting by challenging a basic assumption that I built into that assessment:

• The tacit and all but axiomatic assumption that enters into a great deal of the discussion and analysis of artificial intelligence, and of most other still-emerging technologies as well,
• That while disruptively novel can and does occur as a matter of principle, it is unlikely to happen and certainly right now in any given technology development context that is actively currently being pursued, along some apparently fruitful current developmental path.

All four of the above repeated and restated scenario options have their roots in our here and now and its more readily predictable linear development moving forward. It is of the nature of disruptively new and novel that is comes without noticeable warning and precisely in ways that would be unexpected. The truly disruptively novel innovations that arise, come as if lightning out of a clear blue sky, and they blindside everyone affected by them for their unexpected suddenness and for their emerging impact, as they begin to gain traction in implementation and use. What I am leading up to here is very simple, at least in principle, even if the precise nature of the disruptively new and novel limits our ability to foresee in advance the details of what is to come of that:

• While all of the first four development and innovation scenarios as repeated above, will almost certainly come to play at least something of a role in our strongly artificially intelligence-shaped world to come, we also have to expect all of this to develop and play out in disruptively new ways too, and both as sources of specific contextually relevant solutions for how best to implement this new technology, and for how all of these more context-specific solutions are in effect going to be glued together to form overall, organized systems.

I would specifically stress the two sides to that more generally and open-endedly stated fifth option here, that I just touched upon in passing in the above bullet point. I write here of more locally, contextually specific implementation solutions, here for how artificial intelligence will connect to the human experience. But I also write of the possibility that overarching connectivity frameworks that all more local context solutions would fit into, are likely going to emerge as disruptively new too. And with that noted as a general prediction as to what is likely to come, I turn here to at least consider some of the how and why details of that, that would lead me to make this prediction in the first place.

Let’s start by rethinking some of the implications of a point that I made in Part 4 of this series when first addressing the issues of artificial intelligence, and of artificial intelligence agents per se. We do not even know what artificial general intelligence means, at least at anything like an implementation-capable level of understanding. We do not in fact even know what general intelligence is per se and even just in a more strictly human context, at least where that would mean our knowing what it is and how it arises in anything like a mechanistic sense. And in fact we are, in a fundamental sense, still learning what even just artificial specialized and single task intelligence is and how that might best be implemented.

All of this still-present, significantly impactful lack of knowledge and insight raises the likelihood that all that we know and think that we know here, is going to be upended by the novel, the unexpected and the disruptively so – and probably when we least expect that.

And with this stated, I raise and challenge a second basic assumption that by now should be more generally disavowed, but that still hangs on. In a few short decades from now, for all of the billions of human online nodes: human-operated devices and virtual devices that we connect online through, that will collectively only account for a small fraction of the overall online connected universe: the overall connectiverse that we are increasingly living in. All of the rest: all of the soon to be vast majority of the rest of this will all be device-to-device in nature, and fit into what we now refer to as the internet of things. And pertinently to this discussion that means that a vast majority of the connectedness that is touched upon in the above four (five?) scenarios, is not going to be about human connectedness per se at all, except perhaps indirectly. And this very specifically leads me back to what I view as the real imperative of the fifth scenario: the disruptively new and novel pattern of overall connectivity that I made note of above, and certainly when considering the glue that binds our emerging overall systems together with all of the overarching organizational implications that that option and possibility raises.

Ultimately, what works and both at a more needs-specific contextual level there, and at an overall systems connecting and interconnecting level, is going to be about optimization, with aesthetics and human tastes critically important and certainly for technology solution acceptance – for human-to-human and human-to-artificial intelligence agent contexts. But in a strictly, or even just primarily artificial agent-to-artificial agent and device-to-artificial agent context, efficiency measures will dominate that are not necessarily human usage-centric. And they will shape and drive any evolutionary trends that arise as these overall systems continue to advance and evolve (see Part 3 and Part 5 for their discussions of adaptive peak models and related evolutionary trend describing conceptual tools, as they would apply to this type of context.)

If I were to propose one likely detail that I fully expect to arise in any such overall organizing, disruptively novel interconnection scenario, it is that it will most likely reside at and function at a level that is not explicitly visible unless directly connected into, in any of the contextual scenario solutions that arise and that are developed and built into it: human-to-human, human-to-device or intelligent agent, or device or agent-to-device or agent. And this overarching technology, optimized in large part by the numerically compelling pressures of device or agent-to-device or agent connectivity needs, will probably take the form of a set of universally accepted and adhered to connectivity protocols: rules of the road.

I am going to continue this discussion in a next series installment, where I will at least selectively examine some of the issues that arise considering how essentially everything in such a system and at all levels of organizational resolution in it, is rapidly coevolving and taking form, and both in its own context and in this larger overall rapidly emerging connections-defined context too. And this will of necessity bring me back to reconsider some of the first issues that I raised in this series too.

Meanwhile, you can find this and related material at Ubiquitous Computing and Communications – everywhere all the time 3 and also see Page 1 and Page 2 of that directory. 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 28: a second round discussion of general theories as such, 3

Posted in blogs and marketing, book recommendations, reexamining the fundamentals by Timothy Platt on April 6, 2019

This is my 28th 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 1-25 and its Page 2 continuation, Section IX for Parts 26 and 27.)

I began this series in its Parts 1-8 with an initial orienting discussion of general theories per se, with an initial analysis of compendium model theories and of axiomatically grounded general theories as a conceptual starting point for what would follow. And I then turned from that, in Parts 9-25 to at least begin to outline a lower-level, more reductionistic approach to businesses and to thinking about them, that is based on interpersonal interactions.

Then I began a second round, next step discussion of general theories per se in Part 26 and Part 27, to add to the foundation that I have been discussing theories of business in terms of, and as a continuation of the Parts 1-8 narrative that I began all of this with. More specifically, I used those two postings to begin a more detailed analysis of axioms per se, and of general bodies of theory that are grounded in them, dividing those theories categorically into two basic types:

• Entirely abstract axiomatic bodies of theory that are grounded entirely upon sets of a priori presumed and selected axioms. These theories are entirely comprised of their particular sets of those axiomatic assumptions as combined with complex assemblies of theorems and related consequential statements (lemmas, etc) that can be derived from them, as based upon their own collective internal logic. Think of these as axiomatically enclosed bodies of theory.
• And theory specifying systems that are axiomatically grounded as above, with at least some a priori assumptions built into them, but that are also at least as significantly grounded in outside-sourced information too, such as empirically measured findings as would be brought in as observational or experimental data. Think of these as axiomatically open bodies of theory.

Any general theory of business, like any organized body of scientific theory would fit the second of those basic patterns as discussed here and particularly in Part 27. My goal for this posting is to continue that line of discussion, and with an increasing focus on the also-empirically grounded theories of the second type as just noted, and with an ultimate goal of applying the principles that I discuss here to an explicit theory of business context. That noted, I concluded Part 27 stating that I would turn here to at least begin to examine:

• The issues of completeness and consistency, as those terms are defined and used in a purely mathematical logic context and as they would be used in any theory that is grounded in descriptive and predictive enumerable form. And I will used that more familiar starting point as a basis for more explicitly discussing these same issues as they arise in an empirically grounded body of theory too.
• How new axioms would be added into an already developing body of theory, and how old ones might be reframed, generalized, limited for their validly expected or discarded as axioms per se.
• Then after addressing that set of issues I said that I will turn to consider issues of scope expansion for the set of axioms assumed in a given theory-based system, and with a goal of more fully analytically discussing optimization for the set of axioms presumed, and what that even means.

And I begin addressing the first of those points by citing two landmark works on the foundations of mathematics:

• Whitehead, A.N. and B. Russell. (1910) Principia Mathematica (in 3 volumes). Cambridge University Press.
• And Gödel’s Incompleteness Theorems.

Alfred North Whitehead and Bertrand Russell set out to develop and offer a complete axiomatically grounded foundation for all of arithmetic, as the most basic of all branches of mathematics in their above-cited magnum opus. And this was in fact viewed as a key step realized, in fulfilling the promise of David Hilbert: a renowned early 20th century mathematician who sought to develop a comprehensive and all-inclusive single theory of mathematics as what became known as Hilbert’s Program. All of this was predicated on the validity of an essentially unchallenged metamathematical axiomatic assumption, to the effect that it is in fact possible to encompass arbitrarily large areas of mathematics, and even all of validly provable mathematics as a whole, into a single finite scaled, completely consistent and completely decidable set of specific axiomatic assumptions. Then Kurt Gödel proved that even just the arithmetical system offered by Whitehead and Russell can never be complete in this sense, from how it would of necessity carry in it an ongoing requirement for adding in more new axioms to what is supportively presumed for it, and unending and unendingly so if any real comprehensive completeness was to be pursued. And on top if that, Gödel proved that it can never be possible to prove with comprehensive certainty that such an axiomatic system can be completely and fully consistent either! And this would apply to any abstractly, enclosed axiomatic system that can in any way be represented arithmetically: as being calculably enumerable. But setting aside the issues of a body of theory facing this type of limitation simply because it can be represented in correctly formulated mathematical form, for the findings developed out of its founding assumptions (where that might easily just mean other axiomatically enclosed bodies of theory that so not depend on outside non-axiomatic assumptions for their completeness or validity – e.g. empirically grounded theories), what does this mean for explicitly empirically grounded bodies of theory, such as larger and more inclusive theories of science, or for purposes of this posting, of business?

I begin addressing that question, by explicitly noting what has to be considered the single most fundamental a priori axiom that underlies all scientific theory, and certainly for all bodies of theory such as physics and chemistry that seek to comprehensively descriptively and predictively describe what in total, would include the entire observable universe, and from its big bang origins to now and into the distant future as well:

• Empirically grounded reality is consistent. Systems under consideration, as based at least in principle on specific, direct observation might undergo phase shifts where system-dominating properties take on more secondary roles and new ones gain such prominence. But that only reflects a need for more explicitly comprehensive theory that would account for, explain and explicitly describe all of this predictively describable structure and activity. But underlying that and similar at-least seeming complexity, the same basic principles and the same conceptual rules that encode them for descriptive and predictive purposes, hold true everywhere and throughout time.
• To take that out of the abstract, the same basic types of patterns of empirically observable reality that could be representationally modeled by descriptive and predictive rules such as Charles’ law, or Boyle’s law, would be expected to arise wherever such thermodynamically definable systems do. And the equations they specify would hold true and with precisely the same levels and types of accuracy wherever so applied.

So if an axiomatically closed, in-principle complete in and of itself axiomatic system, and an enclosed body of theory that would be derived from it (e.g. Whitehead’s and Russell’s theory of arithmetic) cannot be made fully complete and consistent, as noted above:

• Could grounding a body of theory that could be represented in what amounts to its form and as if a case in point application of it, in what amounts to a reality check framework of empirical observation allow for or even actively support a second possible path to establishing full completeness and consistency there? Rephrasing that, could the addition of theory framing and shaping outside sourced information evidence, or formally developed experimental or observational data, allow for what amounts to an epistemologically meaningful grounding to a body of theory through inclusion of an outside-validated framework of presumable consistency?
• Let’s stretch the point made by Gödel, or at least risk doing so where I still at least tacitly assume bodies of theory that can in some meaningful sense be mapped to a Whitehead and Russell type of formulation of arithmetic, through theory-defined and included descriptive and predictive mathematical models and the equations they contain. Would the same limiting restrictions as found in axiomatically enclosed theory systems as discussed here, also arise in open theory systems so linked to them? And if so, where, how and with what consequence?

As something of an aside perhaps, this somewhat convoluted question does raise an interesting possibility as to the meaning and interpretation of quantum theory, and of quantum indeterminacy in particular, with resolution to a single “realized” solution only arrived at when observation causes a set of alternative possibilities to collapse down to one. But setting that aside, and the issue of how this would please anyone who still adheres to the precept of number: of mathematics representing the true prima materia of the universe (as did Pythagoras and his followers), what would this do to anything like an at least strongly empirically grounded, logically elaborated and developed theory such as a general theory of business?

I begin to address that challenge by offering a counterpart to the basic and even primal axiom that I just made note of above, and certainly for the physical sciences:

• Assume that a sufficiently large and complete body of theory can be arrived at,
• That would have a manageable finite set of underlying axiomatic assumptions that would be required by and sufficient to address any given empirically testable contexts that might arise in its practical application,
• And in a manner that at least for those test case purposes would amount to that theory functioning as if it were complete and consistent as an overall conceptual system.
• And assume that this reframing process could be repeated as necessary, when for example disruptively new and unexpected types of empirical observation arise.

And according to this, new underlying axioms would be added as needed, when specifically faced and once again particularly when an observer is faced with truly novel, disruptively unexpected findings or occurrences – of a type that I have at least categorically raised and addressed throughout this blog up to here, in business systems and related contexts. And with that, I have begun addressing the second of the three to-address topics points that I listed at the top of this posting:

• How would new axioms be added into an already developing body of theory, and how and when would old ones be reframed, generalized, limited for their validly expected or discarded as axioms per se?

I am going to continue this line of discussion in a next series installment, beginning with that topics point as here-reworded. And I will turn to and address the third and last point of that list after that, turning back to issues coming from the foundations of mathematics in doing so too. (And I will finally turn to and more explicitly discuss issues raised in a book that I have been citing here, but that I have not more formally gotten to in this discussion up to here, that has been weighing on my thinking of the issues that I address here:

• Stillwell, J. (2018) Reverse Mathematics: proofs from the inside out. Princeton University Press.)

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 and its Page 2 continuation, as topics Sections VI and IX there.

Innovation, disruptive innovation and market volatility 46: innovative business development and the tools that drive it 16

Posted in business and convergent technologies, macroeconomics by Timothy Platt on April 3, 2019

This is my 46th 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 and its Page 2 continuation, postings 173 and loosely following for its Parts 1-45.)

I began discussing some of the core issues of this series in Part 43, in terms of a specific case study example that can serve to illustrate them. My goal for that has been to take a more general line of discussion than I have often pursued up to there, and at least somewhat more fully take it out of the abstract.

More specifically and to explicitly connect the immediate preceding installments of this series to this one, I have recently been discussing a new synthetic polymer-based outdoor paint type as an innovation example, as developed by one organization (a research lab at a university), that would be purchased or licensed by a second organization for profitable development: a large paint manufacturer. At least up to now, I have focused for the most part on the innovation acquiring business that is participating in this: on that paint manufacturer and its due diligence and related considerations as they would decide whether or not to proceed in this transaction, and how to do so if they decide that they should.

My goal here is to at least begin to more fully consider the issues raised here from the perspective of the innovation-originating organization: that university with its innovation development office as set up to manage all patent and licensing agreements that would arise in that institution, and the research lab there that this innovation was actually created at. And I begin doing so at the starting point for all of the activity and potential activity that I have been discussing here: that innovation discovering research lab itself and the people who run it and who work there.

• A university research lab is both a place where research and discovery are matters of defining purpose, and a place where graduate school and postdoctoral level training are centrally important too. Ongoing efforts to achieve these dual goals inseparably interconnect, with most of the hands-on research that is done carried out by graduat students and postdoctoral fellows, and with the research and the teaching and mentoring that take place in them, enabling and shaping each other and on an ongoing day-to-day basis. I write this, thinking back to my own years of working in this type of setting, and from my longer timeframed efforts to more fully understand the capabilities and the dynamics of these organized systems in general.
• And I stress here, the significance of their being “research laboratories.” Their goal for the most part is to develop new knowledge, working on and at least ideally resolving one question or problem or set of them, to move on from there to work on a next question or problem or set of them that could only arise if preceding ones had been successfully worked upon, building a knowledge base needed to proceed forward. These are not applied research oriented product development facilities, except perhaps in a special and limited sense, where that would specifically support more basic research. Their goal is not, for the most part, to take the largely more-basic knowledge that they develop and verify and translate that into specific practical marketable applications. They are not geared to do that and the people who work there are not in general seeking out opportunities to do that either, at least while they are pursuing this part of their overall career paths. And these facilities do not in general even have the resources or funding needed for practical specific-product oriented development either.
• And one of the driving forces that would shape that reality comes from where so much of the funding for this research and training comes from: outside-sourced grants and with a great deal of that coming from government sources and certainly in countries such as the United States. I applied for and competed for funding from the US National Institutes of Health for much of my university-based research as most of my early hands-on research certainly, was biomedical in nature. In a case study scenario of the type that I write of here, it is likely that the professor who runs that lab would turn more to agencies such as the National Science Foundation for funding as that lab’s principle lead grant writer and applicant. Though a significant amount of research funding that goes to universities and their research labs comes from private sources too, and both from nonprofit foundations and from corporate sources. Either way, this funding is essentially always earmarked for more fundamental research and not for applied research or specific product development, and certainly when government funding is significantly involved.
• In this case study, the nature of the research problem worked upon strongly points to specific possible types of application: here the development of new outdoor paints as based upon new developments in the underlying polymer chemistry that would lead to them, that this lab has been working on developing. But this is still basically a more fundamental knowledge oriented university research lab that created this paint chemistry breakthrough – and if it is to be developed into specific profitably marketable products, that would have to mean bringing in a more applications oriented business that would take the next steps for that, and for final applied technology testing and certainly for product manufacturing.
• And from the developing lab’s perspective and that of the university that it exists in, the dynamics of the about-outlined system and the financial potential that it might hold, would in effect be thrown away if those new innovation-based technology transfers where not entered into and efficiently so. Traditionally, this type of loss of opportunity was in fact fairly standard for most universities as they saw the innovations created on their campuses either remain fallow and unused, and drift out their doors with little if any real return value gained from them. And that, led directly to universities developing offices within their own systems for setting up and managing such technology transfer agreements, and with that carried out in as standardized and efficient a manner as possible so as to gain as much from these opportunities as possible – and both for the researchers involved and their labs, and for these universities as a whole.
• And yes, the contractual agreements that researchers enter into when applying for and accepting outside grant money and from both government agency and from private sector sources, enter into this too. And one of the core functions of a university’s innovation development office is to more efficiently navigate any terms or restrictions that might be included there, when dealing with and coming to agreement with businesses that might purchase or license technologies developed there, so as to meet those restrictions, if any. To take that out of the abstract, when foreign owned or operated businesses are involved and international technology transfer restrictions are in place as is often the case for dual-use technologies that can be used in both civilian and military contexts, that can and does include determination of even just what business organizations that university can be allowed to negotiate with and come to agreement with, and for which specific innovations that might be on the table.

Stepping back from this line of reasoning and from the systems that I am discussing here, to consider these two businesses again: the innovating university that is functioning as a business here, and the manufacturer, both critically depend on and require sound finances to continue to operate. And both depend on financial performance for that, that is highly performance based with the manufacturer here depending on its own cash flow and reserve-building capabilities, and the university depending on the effectiveness of its research as its driver for bringing in more funding. Both sides of this transaction capability have to operate in very competitive arenas, with small numbers of the more successfully innovative researchers on the university side of this gaining a disproportionately large share of the grant money that is out there to apply for, and with more successful marketable product developers and manufacturers often finding themselves in a stronger position to successfully enter into these agreements too. And that shapes the environment that all of the above plays out in.

I am going to continue this line of discussion in a next series installment where I will complete, at least for here, my discussion of this university research lab and outside for-profit manufacturer scenario. I will then step back to at least briefly consider this basic two organization model in more general terms, where for example, the innovating organization there might in fact be another for profit business too – including one that is larger than the acquiring business and that is in effect unloading patents that do not fit into their own needs planning. I will also specifically raise and challenge an assumption that I just built into the immediately preceding paragraph here, regarding the value of scale in the innovation acquiring business in their being able to successfully compete in this type of innovation as product market.

Meanwhile, you can find this and related postings at Macroeconomics and Business and its Page 2 continuation. And also see Ubiquitous Computing and Communications – everywhere all the time 3 and that directory’s Page 1 and Page 2.

Donald Trump, Xi Jinping, and the contrasts of leadership in the 21st century 14: some thoughts concerning how Xi and Trump approach and seek to create lasting legacies to themselves 2

Posted in macroeconomics, social networking and business by Timothy Platt on April 2, 2019

This is my 14th installment in a comparative progression of postings on Donald Trump’s and Xi Jinping’s approaches to leadership per se. And it is my 8th installment in that on Trump and his rise to power in the United States, and on Xi and his in China, as they have both turned to authoritarian approaches and tools in their efforts to succeed there. I began that line of discussion with three postings on cults of personality. And I continued from there to more fully address an approach to leadership that holds such cult building approaches as one of its most important tools, in what I refer to as the authoritarian playbook. Then I began to put all of this into a larger and longer-term historical context by turning to consider legacies in this type of authoritarian system and its use. See Social Networking and Business 2, postings 367 and loosely following (there identified with accompanying tagging text that identifies these postings for their more Trump-related significance. I also offer links to them with corresponding China and Xi-oriented tagline text attached at Macroeconomics and Business 2.)

I concluded Part 6 of the authoritarian-oriented thread of this narrative, stating that I would turn from there to consider Trump and Xi and their specific legacy building stories. Then upon further reflection, I added Part 7 as a more general, orienting discussion of authoritarian legacies per se, that I would use as a starting point for discussing Trump and Xi and their more individual efforts in this.

My goal for this posting is in fact to explicitly discuss Donald Trump and his legacy building efforts, with a corresponding discussion of Xi Jinping and his to follow. But before doing so, I will offer a few more thoughts concerning authoritarian legacies in general, in order to put my more case study-specific discussions to come into clearer perspective:

• I wrote in Part 7 of this progression, of how the dynamics of authoritarianism itself can make lasting legacies ephemeral, and particularly where a would-be authoritarian succeeds in following the playbook by actually making themselves truly indispensible as a stabilizing force in their nation’s society and in its governance. Success there might ensure their holding onto power and on an ongoing basis, while they live. But their very success there is all but certain to lead to power vacuums and societal instability when they do finally leave office, and whether that is at a ripe old age and through natural causes, or earlier and as a consequence of violence. And this type of instability and the conflict that it can lead to, is not conducive to developing or even just preserving lasting legacies per se.

But what of authoritarian systems that are set up so as to create more peaceful succession in power, with next in line supreme leaders chosen from among inner circles of authoritarian insiders? I cited Hitler and Tito as my working examples in Part 7, for their ambitions and efforts at creating lasting legacies for themselves as more “stand alone” authoritarians. And I turn to consider Joseph Vissarionovich Stalin (born Ioseb Besarionis dze Jughashvili) here as a third case in point authoritarian example, and as an example of an authoritarian who rose to power through a more succession-oriented system of the type that I discuss here.

Stalin rose through the ranks of the Communist Party that Vladimir Lenin (born Vladimir Ilyich Ulyanov) led in its creation. And he succeeded at that, partly from his cunning and tenacity and partly from his ruthlessness and his willingness to employ any level of violence needed in order to achieve his goals, and the goals of his Party while he was still rising through its ranks. Then Lenin died and Stalin navigated his way to taking essentially absolute power in both the Soviet Union’s Communist Party, and through that of the Soviet state itself. And at least superficially, Stalin and his fellow leaders of their Communist Party, built Lenin’s legacy, expanding and glorifying it and him until Lenin was revered as if a god: a true Communist god. Lenin’s body was preserved when he died on January 21, 1924, for public display. And his body remains on public display in a special mausoleum build for that purpose in Moscow to this day, carefully re-embalmed on a regularly scheduled basis to keep him looking as lifelike as possible as he lays in perpetual state.

There is at least some evidence that would suggest that Lenin did not die of natural causes that day in 1924 at the age of 53. And an ambitious Stalin might have played a hand in that. Regardless of that sort of detail, Lenin’s god-like legacy was build and maintained from then on and by all of his successors in power and it still is in the post-Communist, post-Soviet Union Russia that exists today.

Lenin the man was very quickly replaced with Lenin the stereotyped symbol and with Lenin the administratively supportive tool that his successors could and did use. And that transformation began even more quickly than was needed to drain the blood out of his now lifeless body and replace it with his first course of embalming fluid. And when Stalin – a veritable self-anointed Soviet Communist god in his own life died, he was similarly embalmed and displayed too … at least until his successors decided to reexamine his legacy and (selectively) publicize “all” of his flaws and errors. Then he was buried and so was much of his legacy, and certainly as he himself had sought to create and direct it.

Yes, there are still many in today’s post-Communist Russia who still hew to the communism of their youth as if to a religion. And many if not most of them still honor Stalin as one of the brightest stars in their Communist firmament. But even there, questions can be asked. How much of that veneration represents a genuine effort to maintain and preserve the legacies of Stalin or of Lenin for that matter, or of any of their increasingly stolid apparatchik successors as leaders of the Soviet era Russian Communist Party? (As for that question and its second half, how many people remember Leonid Brezhnev for his gravitas or as a new and emergent legacy builder?) And perhaps more importantly here for purposes of this narrative, how much of that continued reverence is an expression of a desire simply to preserve a piece of the past, even if just a cartoon representation of it with all rough edges smoothed off? And focusing on Stalin in all of this again, how much of that reverence (and how much of the denigration that followed it) actually represents a preservation of and a continuation of the legacy that he wanted to leave in his people’s collective memory of himself, and how much of it is an invention that would be oriented towards benefiting his still living successors in power, and their legacies as such?

I offer this in terms of a specific example, but would argue that I am in fact discussing more general principles here. Even when an authoritarian lives and functions as such in a context that would create a directly dynastic continuity of power, next generation leaders tend to reframe and revision their predecessors and their legacies to promote and advance their own agendas and their own legacies. For a genuinely familial dynasty example of this, consider the current de facto royal family of North Korea with its founder, Kim Il-sung succeeded by his son: Kim Jong-il and with him now succeeded by his son: Kim Jong-un too. And the grandfather Il-sung was turned into a cartoon figurehead and an instrument of power for his son as he advanced his own agenda. And a still more refined stereotyped cartoon image tool of him, as well as a cartoon reimaging of Jong-il himself, now serve as tools of power that Jong-un uses today as he wields control over what is now his nation.

Donald Trump rose to his current position of power and authority as president of the United States through what is ostensibly such a succession of power-enabling system, advancing to his current position in government through a political party system that is legacy and power perpetuation-based. It is an unwritten but nevertheless potent plank in the Republican Party platform, and one of long-standing, that the long term goal of the party is to gain and hold onto power, and in perpetuity if possible and in all possible elected and appointed offices attainable.

And as an authoritarian of the type that I have been discussing here, Trump has been directing his energies to prevent anyone else in his sphere of influence from developing a power base within “his” Republican Party that might make it possible for them to in any way challenge him (or de facto to succeed him either.) In that he is following the authoritarian playbook in a pure form with no pretext of doing otherwise.

In this context, I cite how even Trump’s strongest supporters defensively argue his case by proclaiming that he thrives on chaos, as an explanation as to why his inner circle of high level appointees is in such turmoil with such a high turnover rate among them, and why he so actively undercuts anyone on his team who fails to praise him sufficiently – and certainly if they in any way publically disagree with him. And a similar line of argument is used to explain and justify why Trump attacks fellow Republicans in Congress and in state level office if they do not fully, automatically follow his lead and on all matters. Congressional pushback, including Republican resistance there regarding the funding of Trump’s signature piece Southern Border Wall is one of the most pressingly visible examples of that, and it is also one that is particularly appropriate in the context of this posting as that is the largest and most impactful piece to the Trump legacy that he is attempting to actually build. For three examples of how this set of issues have been discussed and analyzed by others, at least in general terms, see:

Trump’s Chaos Theory for the Oval Office Is Taking Its Toll,
Trump’s Chaos Engine Finds a New, Higher Gear and
The White House is in Meltdown.

And with all of that noted as background, let’s consider president Trump’s specific legacy building ambitions and efforts, at least up to now as I write this posting in early April, 2019. And I begin that by noting a categorical distinction between two fundamentally different areas of intention if not action, that would fall under an overall legacy rubric here:

• Proclaimed legacy building as a tool for garnering continued support from a politically supportive base: legacy-oriented advocacy if you will as a marketing tool there, and
• Actively intended and pursued legacy building (which can also be used as a marketing tool but where actual building is also a key goal.)

President Trump has in fact actively pursued both of these approaches, and particularly visibly in the first of those two categories. In that, he has for example actively championed the cause of coal miners in West Virginia and other marginalized communities, whose basic historically supportive industries have ceased to be viable in a modern world. And he has done this despite the objectively very real fact that most if not all of those particular industries are heavily polluting, increasingly uneconomical and financially failing or both. Turning back to reconsider those coal miners and their communities in the rural Appalachia of West Virginia, their marginalization has arisen for both economic reasons and environmental reasons, with fossil fuel’s impact on the global warming debate and with mountain top removal strip mining (as is now used in coal mining) viewed as a poster child example of how to do it wrong and on all counts.

These are communities that have traditionally been centered around what have become marginalized, and technologically obsolete industries with some of that coming from the disappearance of anything like viable markets for what they used to produce, and more coming from the development of less labor-intensive technologies that have taken away jobs, and from outsourcing out of the country, and even from outright automation and on a massively large scale. And people caught up in all of this feel isolated and left out, with all of the anger and anomie that that would bring. This has made them and their communities, targets for Donald Trump’s form of populism and ready joiners of his personally supportive base.

Looking at his overall reach and his overall message nationally in developing and maintaining his base, Trump has in fact actively reached out to stoke the resentment and anger of the marginalized, and certainly in communities that see themselves as being left out, in order to gain their support. And he has succeeded there, and in ways that have ratcheted up the tension and the rage and the risk of violent action on the part of these supporters against those he identifies as their enemies. For a reference in support of that, see:

Trump ‘Fear-Mongering’ Fuels Rise of U.S. Hate Groups to Record.

But Donald Trump has done nothing to actually help any of these people or their communities, even as he claims that he will bring coal mining back in the United States, to continue with that example, and fully bring it back to the fullness of its now former glory. And on a larger and at least potentially more pervasive and far-reaching scale, he has proclaimed that he will expend over one trillion dollars of US Federal support to rebuild and update and strengthen the critical infrastructure of the United States as a whole. Then after running as a presidential candidate on that promise and after winning office, he began making references to private sector participation in this with federal matching funds possible. And now this is an issue that he has stopped talking about, though it is likely to reappear from him as he ramps up his 2020 reelection campaigning.

The most visible legacy building effort that president Trump has in fact pushed for, and even against the wishes and interests of his own political party’s members of Congress, has been his wall: his effort to keep out Mexicans and other Hispanics where he specifically targets them as “enemy other,” as he follows the authoritarian playbook with its us versus them approach.

But more importantly, even if less publically visibly, Trump has also made wide-ranging and all too effective efforts to roll back federal governmental regulatory oversight and on all fronts: environmental protection, banking and financial institution oversight that seeks to protect the interests of investors and more. And his and his administration, empowered by a Republican led US Senate have made real inroads in shifting federal courts to the right politically, and to the far right with that including both Appellate and Supreme Court appointments.

I essentially began my more general discussion of authoritarian legacies in Part 13 of this, by quoting one of Shelly’s poems: Ozymandias. What of Donald Trump’s intended or at least proclaimed legacy can and will he actually build, besides the monumental offerings of his Trump-branded buildings and golf clubs? And what of that will last beyond him, and actually serve as the stuff of his historical image and his historical legacy? It is too early to answer that now and certainly in anything like specific realized detail, but to cite one likely piece of it that he does not particularly speak of or acknowledge, remember what The Donald has done to the Party of Lincoln and the Party of Teddy Roosevelt, and even to the Party of Ronald Reagan. I have written in this posting progression of how successfully following the authoritarian playbook in one’s life, can only increase the chances of subsequent power vacuums and the turmoil that they create. Time will tell how this plays out in a post-Trump world, and as political sea changes take hold under the guidance of a new leadership.

I will have more to add to this narrative in subsequent postings to this series on Donald Trump and his story here, but will turn to more fully consider Xi Jinping next and his legacy building story. Meanwhile, you can find my Trump-related postings at Social Networking and Business 2. And you can find my China writings as appear in this blog at Macroeconomics and Business and its Page 2 continuation, and at Ubiquitous Computing and Communications – everywhere all the time and Social Networking and Business 2.

Planning for and building the right business model 101 – 42: goals and benchmarks and effective development and communication of them 22

Posted in startups, strategy and planning by Timothy Platt on March 31, 2019

This is my 42nd 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 and Page 5 continuations, postings 499 and loosely following for Parts 1-41.) I also include this series in my Startups and Early Stage Businesses directory and its Page 2 continuation.

I have been discussing three specific possible early stage growth scenarios that a new business’ founders might pursue for their venture, in recent installments to this series, which I repeat here for smoother continuity of narrative as I continue addressing them:

1. A new venture that has at least preliminarily proven itself as viable and as a source of profitability can go public and with all of the organizational change and all of the transparency and reporting requirements that this entails as they begin offering stock shares. (See Part 33 and Part 34.)
2. A new venture can transition from pursuing what at least begins as if following an organic growth and development model (as in exit strategy 1, above) but with a goal of switching to one in which they seek out and acquire larger individually sourced outside capital investment resources, and particularly from venture capitalists. (See Part 35.)
3. And 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. (See Part 36 through Part 39.)

And more recently here, I have been analyzing and discussing all three of these business development options, in terms of how they address a specific set of key issues that any business that connects with and serves a market in any way, would have to explicitly focus upon if it is to succeed, and certainly long-term:

A. Fine tuning their products and/or services offered,
B. Their business operations and how they are prioritized and carried out, and certainly in the context of this Point A, and
C. Their branding and how it would be both centrally defined and locally expressed through all of this.

I began a discussion of the first two business development approaches as listed above: the IPO and venture capital supported scenarios, and how pursuing one of them would explicitly impact upon, and in turn also be shaped by Point A decisions and follow-through, with an at least brief digression there into Point C issues as well, as that and Point A consequentially and therefore operationally overlap. My goal here in this posting is to conclude my Point A discussion at least for here and now in this series, by explicitly considering how its issues would impact upon a franchise or similar growth business model, with its drive towards templated consistency as a path to successful growth.

I began my discussion of that business model scenario in Part 41 with a brief orienting discussion of product and service consistency, and both as a (Point C) branding issue and as a source of economy of scale and other value. Ultimately, franchise systems that succeed as such, tend to be consistent in what they do and in how they do it and in what they offer, and in the types of market and consumer-facing venues that they would conduct all of this through. That at least forms their basic business-defining patterns and both as a system of reliably consistent franchise outlets that a steady customer base would turn to, and as a reliable steady pattern that they can continue to grow from, from that.

At the same time, however, franchise systems have to be flexible in the face of overall marketplace trends and shifts, and in the face of more local-community needs and preferences too. And this means their capacity to both meet local needs and to prototype and test new offerings and new business approaches that might in fact become their new next overall system-wide norm or at least components of that.

• I wrote in Part 41 of the constraints and shaping pressures that businesses face and particularly in my discussions of the IPO and venture capital scenarios under consideration here. I would continue to use the term “shaping pressures” here in this context as well, but note that the constraints that I could cite in this narrative can be enabling and expanding as easily as they can be restrictive and limiting. In fact, and here I write with all three of the above business model scenarios in mind, successfully pursuing any of them of necessity means a business’ owners and senior managers being able to successful tip the balance there, where “enabling and expanding” outweighs any also-faced “restrictive and limiting” and both for operational flexibility and capability and for the business’ overall profitability and longer-term prospects for that.

And turning back to explicitly focus on franchise or similar templated growth and development scenarios again, this leads me directly to the issue of how such a business would in effect standardize and mainstream change and the testing and allowance of new and different into its systems, and as a matter of both what they do and how, and as a matter of branding and how they market and present themselves to the public too, as I will delve into in a Point C discussion that I will offer in a soon to come installment to this series.

I have already begun addressing the above Point B and its business process and operations issues in this posting and will explicitly focus on that complex of issues in my next installment to this series. And then as promised above, I will explicitly turn to and consider Point C and its issues as a separate topic area. And I will continue to draw out points of connection between these areas of consideration while doing all of this.

Meanwhile, you can find this and related postings and series at Business Strategy and Operations – 5, and also at Page 1, Page 2, Page 3 and Page 4 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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