Platt Perspective on Business and Technology

Meshing innovation, product development and production, marketing and sales as a virtuous cycle 22

Posted in business and convergent technologies, strategy and planning by Timothy Platt on January 19, 2020

This is my 22nd installment to a series in which I reconsider cosmetic and innovative change as they impact upon and even fundamentally shape product design and development, manufacturing, marketing, distribution and the sales cycle, and from both the producer and consumer perspectives (see Ubiquitous Computing and Communications – everywhere all the time 2 and its Page 3 continuation, postings 342 and loosely following for Parts 1-21.)

I have been discussing the complex of issues and challenges that arise for innovation acceptance and diffusion, and of resistance to innovation and to New in general here too, since Part 16, focusing through that developing narrative on two basic paradigmatic models:

• The standard innovation acceptance diffusion curve that runs from pioneer and early adaptors on to include eventual late and last adaptors, and
• Patterns of global flatting and its global wrinkling, pushback alternative.

And then in Part 21 of this, I began to at least briefly discuss how the boundaries between these two models can and do blur and overlap, and certainly as so much of the basic acceptance or rejection implicit in them is now driven by the voices and pressures of social media, and of online reviews and evaluations.

Details, I have to add, are not always important or even considered there by most online participants, and certainly where a one to five stars valuation scales with their up-front visibility can in effect render any more detailed reviews moot, and with their evaluation reduced to a search for confirmation, rather than a source of new and perhaps conflicting insight.

This becomes particularly important when negatively reviewing trolls and equally artifactual positive reviews are considered, that in effect game the “community based voice” that social media reviews ostensibly represent.

From a communications theory perspective, think of that as representing background static – noise in these systems, and with all of the signal degradation that noise would be expected to bring with it.

What I am writing of here is informed choice as might be based on valid and reliable data and insight, where no one can realistically expect that and certainly for any area of discourse that can be considered controversial and consequentially so, for any who might be inclined to skew the overall shared public message to their advantage.

Let’s consider this from a specifically business perspective and particularly where a business seeks to bring the innovatively new into production and to market, but in the face of headwind resistance. That resistance might be based at least in part on the underlying technology involved, on where and how those new products would be made, on where the raw materials that would go into them are sourced, or how, or on any of a range of other production and distribution cycle issues. Or they might be based on the products themselves and how they might be used, and both negatively and positively. The term “dual use” is often attached to products that can very specifically be used in a peaceful civilian context, but that can also be used and directly so for military purposes as well. But for purposes of this line of discussion, let’s generalize that designation. For purposes of this narrative, consider dual use as referring to both positive and negative usability potential as that would arise from the perspective of a beholder, where different people might see different boundaries there – if they seen any such dual use potential at all, and where significantly impactful voices can sway others and even large numbers of them. See my Part 21 discussion of the Pareto principle in that regard and particularly where negative and positive, dual use capabilities can become fluid and malleable in meaning and with all of the potential for opinion shaping influence that that can lead to.

And this brings me back to the fundamental question of what innovation actually is, and certainly in a noisy channel, controversial context. And I begin addressing that by citing two examples, both of which, unfortunately, are quite real:

1. The development of drought and disease resistant crops that can be grown with little if any fertilizer and without the use of insecticides or other pesticides, and
2. Russia’s Novichok (Новичо́к or newcomer) nerve agents.

Both quite arguably represent genuine innovations and even disruptively new ones. But reasonable people would probably view them very differently, and address them very differently in any social media driven, or other public communications.

It is both possible and easy to presume and essentially axiomatically so, that innovation per se is basically more values-neutral and certainly as a general categorical consideration, than anything else. The overall thrust of innovative change is for the most part considered a positive if its overall neutrality is considered and challenged at all, at least for those who are at all open to novelty and change, and certainly insofar as most innovation is developed and pursued with a goal of at least attempting to address specific publically realized challenges and the opportunities that effectively resolving them might bring, and for at least specific demographic groups. Innovation that is realized and certainly as marketable products, and the innovative process that leads to it, tend to focus on what New does and on what it could and can do, for meeting at least those perceived needs. And that perspective is in most cases valid; it is certainly understandable. But all of this just addresses innovation as a whole and even as an abstraction. Individual innovations are not, and probably cannot be considered in that way, and certainly automatically. Individual innovations have equally particular and even at least relatively unique consequences. And they arise in equally specific contexts.

To add a third example to this list, where longer-term cumulative effects become critically important, consider:

3. Disposable single use plastic bags and other petrochemical plastics-based wrapping materials.

I stated at the end of Part 21 that I would further discuss public voices and their influence, and I then turned in this installment to reconsider innovations per se. I am going to continue that line of discussion in a next series installment, at least starting with my three here-stated examples. I will then reconsider the two innovation acceptance versus resistance models that I have been considering here, but in less abstract terms than I have up to here. And then, and on the basis of that narrative, I will reconsider individual and social group, and governmental and other organizational influence in both creating and shaping conversations about change. (And as part of that narrative, I will explore some assumptions that I built into my above-offered presumptions paragraph as appears between my first two innovation examples and example three.)

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 see also Ubiquitous Computing and Communications – everywhere all the time and its Page 2 and Page 3 continuations.

Planning for and building the right business model 101 – 46: goals and benchmarks and effective development and communication of them 26

Posted in startups, strategy and planning by Timothy Platt on December 26, 2019

This is my 46th 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 1-45.) I also include this series in my Startups and Early Stage Businesses directory and its Page 2 continuation.

I began discussing three specific possible early stage growth scenarios in more general terms, that a new business’ founders might pursue for their venture, starting in Part 33 with an IPO scenario, and with that followed by a corresponding discussion of a venture capital supported scenario and a franchise systems one. Then after outlining and discussing those scenarios as overall business model approaches, I began analyzing and discussing them for how their founders and executive officers would variously address the specific challenges raised by a question that could be generically asked of essentially any business founders or owners, for their own new businesses:

• What constituencies and potential constituencies would ventures following each of the above-cited business development approaches need to effectively reach out to and connect with?

And I began addressing this basic and even generic question in an IPO context and then in a venture capital supported context, with three specific business performance issues in mind. In keeping with that explanatory pattern, I will at least begin addressing this posting’s scenario with an awareness of them too, which I repeat here as:

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 that Point A and its issues, and
C. Their branding and how it would be both centrally defined and locally expressed through all of this.

It is important to note here that early funding strategies, as considered in the first two business development scenarios, can only serve as a starting point for what would and should follow. So I discuss operational and strategic issues in the context of this series, at least in part in order to put them into a more functionally consequential context.

That said, my intention here is to continue on from where I left off my IPO and venture capital scenarios, to similarly discuss the third basic scenario that I am holding up for more detailed analysis here. And I begin doing so by repeating the initial bullet pointed description that I offered for it when first introducing the three:

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.)

Let’s start considering that developmental scenario with the basic question that I offered here towards the start of this posting, with its focus on who would be involved in all of this type of business building effort. And I begin that by noting a perhaps obvious, but also perhaps somewhat misleading point of difference that might be drawn between the first two business development scenarios that I have been discussing here, and this third one.

• The first two: an IPO funded new business jumpstart model and a venture capital jumpstart one, are obviously oriented around and even fundamentally defined by outside-sourced capital funding infusion and by explicit efforts to obtain it. Both, if successful in that, would bring in large amounts of liquidity that could be used to accelerate the development and growth of a new venture, increasing both its chances of success and its chances of becoming a competitive leader in its business sector and for its markets, if nothing else.
• But the third, franchise system example does not fit that pattern at all, at least if it is not simultaneously following one of the first two scenarios too (which I will assume not to be the case here.)

The second of those two points is where “misleading” at the very least, enters this narrative. And I would explain that point of consideration by raising the issues of trade-offs. All three of the basic scenarios under discussion here are driven by them; understanding these three scenarios and understanding how they actually do and do not relate to each other, depends entirely on knowing and understanding their respective trade-offs and how they align, and how they differ from each other.

Let’s start addressing that by reconsidering the first two scenarios, which for purposes of this line of discussion can be seen as variations on a same commonly held theme. The founders of a new business seek to develop and build and own their own legally incorporated, separate, essentially wholly-owned new business venture. But they see fundamental need to bring in large amounts of outside capital if they are to succeed, and at least as quickly and fully as they think possible and as they are willing to attempt. But outside funding of this type always has strings attached; there are always trade-offs in which those founding owners have to give on some issues in order to gain on others. I have discussed some of those issues in detail in other series in this blog so I will only note a few of the more pressingly important of them here, as they would specifically apply to this series and its narrative.

Entering into, and even just making a preliminarily filing for entering into an initial public offering with its release and sale of publically traded stock shares, forces a business to adhere to very specific due diligence and risk management-based procedural guidelines, and ones that only begin with requirements of specific mandated forms of financial transparency and public reporting. Much of this is even legally mandated and certainly for legal jurisdictions that include within them, stock exchanges of any scale or significance.

“Begin” is important there, as this enforced transparency determines how a wide range of business decisions would be made, and particularly where market analysts that the public respects, read those reports and study those businesses and their already ongoing pre-IPO track records, and offer reviews, and as they make buy, hold or sell recommendations that can affect overall market valuation and realizable value. So entering into an IPO might bring in a flow and even a veritable flood of new liquid wealth. But that always comes with constraints imposed too, and particularly if a business starts out with a large initial cash infusion and a large initial market valuation, placing it squarely in the line of sight of both the general public and of well known market analysts and business analyst reviewers, who might or might not challenge it on the basis of their understanding of its fundamentals.

Venture capitalists obviously provide up-front capital investment funds too. And they do so under terms that are at the very least, largely of their choosing too. They invest in the business ventures that they select for that, with a goal of realizing a profit and a significantly scaled one from their investment in them. So they demand specific types of influence and even control as to how those ventures are set up and run, in order to improve their odds of success at that. And as already discussed elsewhere in this blog that can mean their requiring seats on an invested business’ board of directors and that can even mean their selecting key executive officers there (e.g. a Chief Financial Officer who meets their due diligence requirements.)

If the venture capital investors involved there are knowledgeable about the types of endeavors they invest in and about how to help make them succeed, their demands and fulfilling them on the part of a selected venture’s founding owners, increases their chances of success too. But those business founders still have to be willing and able to pay back the initial funds invested in them along with any and all required venture capital profits too.

• While I am oversimplifying a more complex dynamic here, think of this as a business model agreement in which venture capitalists agree to take on some of the risks faced by the founders of the businesses that they would invest in, in exchange for a profitable fee. And those (generally) new or early stage business founders agree to set their business development timing if nothing else, so as to be meet those payback requirements from their revenue streams, in exchange for an improved chance of their actually developing such revenue streams in the first place.

Think of both of these scenarios as risk accepting, aggressive business development approaches. Now what are the trade-offs that a franchise system corporation and a would-be franchisee to them, accept and take on? I would argue that they are also based on a financials, and on a risk reduction versus a control and self-determination decision. It is just that in this case, the participants involved tend to be more risk aversive and conservative in what they do and in how they do it and on both sides of the business relationships entered into.

A franchisee agrees to build and run a locally, personally owned outlet according to a presumably well proven model and for what is to be offered for sale, and for how it would be offered, and for everything from the basic storefront design and branding it would be sold through to price point determination and what those offered products and services would actually be sold for. And in exchange for this risk-controlled business opportunity with its more limited range of unknowns, and with its already built-in established customer base that knows that basic business and its products, they relinquish a very significant amount of the decision making authority that they would have if they simply set out to build a more stand-alone business on their own. And they take on ongoing obligations to pay out a contractually set percentage of their gross receipts (generally) to the parent company too.

And that parent company agrees to these terms too, and particularly where they can write the contract agreed to in ways that would limit any risk to them, and certainly any risk that might arise from outside of normal business operations (e.g. a franchise delivery vehicle getting into an auto accident with injuries), while insuring an all but certain positive cash flow back to them from this.

With this in place, let’s consider the basic question that I would address here, and the above-repeated business performance issues that I have also been addressing in this type of context:

• What constituencies and potential constituencies would ventures following (in this case a franchise system) business development approach need to effectively reach out to and connect with?

I have already offered at least a significant start to answering this question in the preceding text of this posting. First of all, a would-be franchisee and a good fit franchise system-organized business that they would secure a license from, have to find each other. That matches the situation faced by entrepreneurs who would seek out venture capital funds and support, and good-fit venture capitalist investors at that, as noted in Part 45 when I focused on that scenario.

From a franchise perspective, this means would be franchisees finding franchise system parent businesses that operate in an industry they would like to work in (e.g. convenience store, versus fast food, versus quick service auto maintenance such as oil changes or car washes, and so on.) And a parent company that they might potentially sign a contract with, is going to want to find people who would be good fits for working with them and who look from their backgrounds and their experience to be good candidates for successfully running a local business and according to their patterns and rules.

On the market-facing side to this, a well established franchise chain and its parent company might have name recognition and at least a measure of positive market-based opinion, even when just moving into a new-to it-area. But many franchise systems face at least a measure of push-back too, with that often based on concern over the impact they can have on local businesses and their owners, and on the communities that those local businesses have traditionally served.

And in that, it is important to note that as a general principle:

• Marketing in these systems come from corporate but sales come from and are local.

But local franchisees are still going to have to reach out so as to become welcome members of their communities, for what they and their storefronts do.

And pertinently to this discussion, and returning to consider the finances of all of this, a franchise system business has to, in most cases, make an up-front investment towards setting up a new franchisee owned outlet, even as they require what can be a very significant up-front investment from a new franchise holder too, as they purchase their franchise license to join that system. If the first two scenarios that I have delved into here are finances driven, this one is too. And that point of detail brings me back to the three business performance issues that I have been discussing these scenarios in terms of:

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 that Point A and its issues, and
C. Their branding and how it would be both centrally defined and locally expressed through all of this.

I am going to continue this discussion in a next installment to this series. Then I will turn to and address the second and third generic questions that I have posed for this portion of this series, as they would be understood and responded to by businesses in general that fit each of the three basic development scenarios under consideration here:

2. What basic messages would they have to convincingly and even compellingly share with those audiences, to create value for themselves from their marketing efforts?
3. And where and how would they best accomplish this?

(In anticipation of discussion to come, I will raise and discuss what I would argue are some overly simplistic assumptions raised in this posting, when discussing those questions in a franchise system context.)

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.

Building a business for resilience 38 – open systems, closed systems and selectively porous ones 30

Posted in strategy and planning by Timothy Platt on December 20, 2019

This is my 38th installment to a series on building flexibility and resiliency into a business in its routine day-to-day decisions and follow-through, so it can more adaptively anticipate and respond to an ongoing low-level but with time, significant flow of change and its cumulative consequences, that every business faces in its normal course of operation (see Business Strategy and Operations – 3 and its Page 4 and Page 5 continuations, postings 542 and loosely following for Parts 1-37.)

I began successively addressing a set of higher level to-address topics points in Part 32 of this series that all relate to information management and its challenges (see that posting for a complete list of them.) And I have been discussing the third item of that list and its issues since Part 35, which I repeat here as I continue addressing it:

• And I will at least begin to discuss corporate learning, and the development and maintenance of effectively ongoing experience bases at a business, and particularly in a large and diverse business context where this can become a real challenge.

And to more fully connect this posting to its earlier installments, I add that I divided that more general, higher level topics point into a secondary set of more specific points, that I began to more systematically address in Part 37. And I repeat that list here, or at least its last three entries as I continue its line of discussion:

1 and 2. The first of these topics points raised an example of a business-related information
sharing circumstance that categorically, would most appropriately belong on a business-wide accessible intranet. And the second raised an example of business-related information that would best be managed independently of any such system and that would call for more direct, targeted communications and sharing. And most pertinently, at least as context for what would follow them, I presented both of these examples as representing generally stated categories of information management situations that would at least fairly clearly and directly call for specific readily anticipated types of risk management-compliant responses.
3. But not all business sourced or related information clearly fits into one or the other of those admittedly vaguely defined categorical groupings, as being best suited to a more entirely technology implementation or as calling for significant interpersonal interaction and private conversation. And even when a specific case in point example seems to best fit one or the other of those paradigmatic approaches in principle, it might not in practice just fit there.
4. How would gray area data and knowledge for this be identified and how would it best be managed?
5. And how and when would hybrid solutions and approaches for managing them, best be developed and pursued here?

I began addressing those points in Part 37 from a risk management perspective, explaining why I would do so in the process. And my goal for this posting, at least to start, is to complete that line of discussion, at least for purposes of this series and this part of it. And I begin doing so by addressing the question of what “gray area” actually means in this context, as a term of that sort can seem relatively clear and unambiguous for its meaning as a matter of general principle, but become anything but that when specific instances are considered.

I have devoted a significant portion of this blog, and through a range of posting series as listed on several directories in it, to the issues of friction and uncertainty in a business information context. And as part of that, I have discussed how that arises and plays out in the face of innovation and a wide range of other change-drivers. My goal here is to address the question of “gray areas” and of what would and would not belong in them, from a slightly different perspective. And I begin that my noting two points of observation:

• Different people in a same organization, and even in a same table of organization-defined functional area there, can see very different safe-to-share, versus security-compartmentalization boundaries when facing what are ostensibly the same share-or-not decision situations.
• And the differences observed there do not always simply align with personal risk exposure if mistakes are made; they do not just arise self-protectively as some see more risk to themselves from more openly sharing specific information, where others might see more risk from not doing so.

Experience and differing foundational understandings as to how that information might be used or misused enter into this here, and with differing understandings as to overall consequences to involved departments and services and to the business as a whole, tilting any risk assessment balance reached. Such differences can arise at the level of how shared and widely shared task flows might be carried out, or they can arise as disagreements as to what parts of those overall business processes should carried out by whom and under whose authority and supervision. They can arise as perceived differences as to what would qualify as at least sufficient task completion to meet current or understood emerging needs, or at the level of work prioritization and how priorities there are even reached. And in all of these situations, the differences that I write of here can readily be more about how those decisions: those disagreement resolutions would impact on the business, and on the team performance of involved stakeholders.

Regardless of underlying cause, effective risk management in this type of context calls for a clear-cut standardized, working definition of what can and should go online in a business intranet, and if so, under what terms and with who allowed access to what there and how, all clearly specified. That type of working definition would in practice, usually be organized as a rules-based system and organized in large part in an “if this then that” format for standardized implementation, with oversight and review to both manage compliance and track and consequences-review access sharing violations when they occur.

And that is where change does in fact enter this narrative too, and particularly where the disruptively new and novel might be taking shape. Any such standardized, rules based system needs to be flexible. But it still has to be a basically consistent system and even as novel circumstances can and do compel exception handling rulings. Too much standardization here can only lead to increased risk as the unexpected remains ineffectively addressed and even fundamentally misunderstood for lack of pertinent information where it is actually needed. But too little standardization can reduce what is nominally an information control risk management system, to an ad hoc in-practice, rules based system that is in fact just a system in name only.

I have focused on this problem, at least as a matter of general principles in Part 37 and have continued that narrative line here. And I turn now to at least briefly touch on the question of how to resolve it, on a novel-situation by novel-situation basis, where it is not always going to be clear until after the fact, precisely how disruptively new and novel a business event or context was. So how as a matter of best practices do I recommend addressing that challenge? My answer in brief, it that any effective resolution to that, is going to depend on precisely who is brought into the initial business analysis and decision making process here, and who is brought into it as wider ranging expertise becomes required. And to clarify that, I would suggest that:

• Any effective risk management office needs to have within it a highly trained group of risk management professions who have background in computer and information systems security and risk management and well as physical systems security. And they need to be widely familiar with their business as a whole too. (And legal counsel representation is important there too, as a generally available resource.)
• But these people, for all of their specialized expertise, should only be considered core group generalists there. Real specialization, as that would enter into any case-by-case decision making process, would have to come from vetted specialists from the various functional areas of a business that might become involved in a potential information sharing, or that might be impacted upon by it.
• Who do specific information holders and owners seek to share that information with, where that would not simply fit a standard accepted and agreed-to information sharing rule already in place?
• Who seeks to access such information in that way, if this request is potential-recipient initiated? Who there at the business would be in a best position, on the basis of their experience and expertise, to provide specific insight in evaluating need and risk there and certainly where highly sensitive and confidential information would be shared, and where it might potentially be compromised if that was done inappropriately? There, local expertise can significantly include a more detailed understanding as to how business is actually conducted in practice by a recipient team or office, where that might differ from how that work would be expected to be done in principle.
• An effective within-business intranet with profile based professional social networking tools, to supplement ongoing business social networking reach can prove very effective in finding the right professionals with specialized and even unique skills and experience sets, for dealing with the new and novel.
• But even there, any system of this type should always be considered a work in progress, subject to ongoing refinement and improvement too.

At the end of Part 37, I stated that I would follow this now-completed discussion of the third point in my Part 32 list, with a corresponding consideration of the final two points included there:

4. In anticipation of that, I note here that this is not so much about what at least someone at the business knows, as it is about pooling and combining empirically based factual details of that sort, to assemble a more comprehensively valuable and applicable knowledge base.
5. And more than just that, this has to be about bringing the fruits of that effort to work for the business as a whole and for its employees, by making its essential details accessible and actively so for those who need them, and when they do

I am going to continue this overall narrative in a next series installment with Point 4 of that list, starting with the last two bullet points and the issues that they raise from this posting’s discussion. 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.

Reconsidering the varying faces of infrastructure and their sometimes competing imperatives 10: a first draft discussion of general principles and practices 1

Posted in business and convergent technologies, strategy and planning, UN-GAID by Timothy Platt on December 17, 2019

This is my 11th installment to a series on infrastructure as work on it, and as possible work on it are variously prioritized and carried through upon, or set aside for future consideration (see United Nations Global Alliance for ICT and Development (UN-GAID), postings 46 and following for Parts 1-9, plus its supplemental posting Part 4.5.)

I have, up to here, successively raised and discussed a set of five case study examples of infrastructure development programs in this series – with a goal of arriving at and explaining a set of more general principles and practices that might be fruitfully employed in future such initiatives, moving forward. In that, think of the case study examples that I have included here, as learning curve opportunities for future infrastructure development or redevelopment efforts. And with that in mind I begin this posting by offering a general principle that would arguably derive from all of them, and that would likely belong in any infrastructure program planning guide and from its early planning-stage steps on:

• Effective next-step infrastructure planning and execution should always be grounded in a solidly reasoned, dispassionately analytical evaluation of what has been done before,
• And both for the specific context that a particular new and coming development program under consideration would explicitly build from, where there are relevant historical examples for that,
• And from prior development programs elsewhere and of other types that can still serve as role model examples, at least for key issues faced.
• And in that, “role model” can mean positive and a source of strategic and operational insight to follow, or it can mean negative and serve more as a cautionary note.
• Either way, it is important to think in terms of the long-term and in terms of development life cycles where they apply too. It is important to think in terms of how those role model learning curve examples under review took shape during their own development processes, and for what has become of them after their at least nominal completion. And it is important to think through their immediate and longer term impact, and for what has happened consequentially from them. (I will come back to this in subsequent installments to this series.)

This noted, in the course of writing this progression of postings leading up to this one, I have already at least preliminarily touched upon a number of more general points that might arguably enter into such an overarching infrastructure development approach. My goal here is to step back from the specifics of particular case in point examples, to at least begin to offer a first draft take on what would enter into such a general principles infrastructure development model as a whole, and into a best practices guide for that as a whole too. And I will do so by at least briefly considering each of the case studies that I have included up to now in this series, for more general principles that they raise.

• I write here of positive and even inspiring role model case study examples and of cautionary and warning examples, as I have intentionally offered both types in this series – as well as examples that arguably include elements of both of those more stereotypically framed types.

I begin this first draft take on general principles, lessons-learnable with the first two of the five case studies already offered here: one of which can be thought of as a largely pure example of the negative here, and one of which at the very least has negative aspects built into it. See:

• Hurricane Maria and Puerto Rico, and its aftermath: Part 1 and Part 2, and
• The New York City Metropolitan Transportation Authority (MTA), and its subway system in particular there: Part 2, Part 3, Part 4.5 (as cited above) and the addendum note appended to the end of Part 6.

Hurricane Maria and Puerto Rico: Essentially the entire island of Puerto Rico was devastated by a massive category 5 hurricane in September of 2017. And all of the island’s critical infrastructure was damaged by that; much of it was effectively destroyed. The expected disaster relief and subsequent rebuilding effort that American citizens had come to expect from their national government after a major natural disaster, effectively did not take place with a Donald Trump serving as president and with his fellow ideologues leading the federal governmental agencies that should have carried this out. And the Trump administration’s wholesale dismantling of regulatory oversight meant that private sector contractors and others who did agree to carry out what government funded work was done, were not background checked before being approved for that. And they were not monitored for what they did, or for how they used the funds that they received for that work. And even now as I write this: more than two years later, there is still much to be done that should have been completed by now. Even now, some of those private sector contractors are under scrutiny and facing legal action for diverting relief funds received, for other purposes.

• It is impossible to effectively carry out an infrastructure development, redevelopment or recovery effort if is not actively supported by the people who would lead it.
• It is impossible to effectively carry out such an effort if that initiative is not actively planned and followed through upon with a goal of seeking to meet the genuine needs of the people directly affected.
• And even then, active oversight and accountability have to be in place too, and to make sure funds allocated to such an effort are not misdirected from it, and to ensure that the work agreed to is carried out and up to a sufficient quality standard so as to make anything built, viable and long-term.
• And even there, piece-by-piece efforts cannot offer overall comprehensive value if they are not planned out and carried through upon in an effectively coordinated, prioritized manner. Effective infrastructure development is always a large scale effort, that creates much of its long term value from the synergies that can be built from its component parts.

The New York City Metropolitan Transportation Authority subway system: The New York City MTA and its subway system do work. The trains run and the stations in that system basically function too. But this system has been a political football with the mayor of New York City and their city government, and the governor of New York State and their state legislature fighting for control over it, and generally to their own personal political career advantages. So according to the MTA’s own publically offered numbers, it would take over $60 billion of investment just to bring the MTA’s subway system up to date for switching technology, passenger accessibility and all of the other areas where it is burdened by the broken and the obsolete – and the missing (e.g. elevators needed to meet Americans with Disabilities Act (ADA) requirements.) And to pick up on that last detail, according to the MTA and their published information on this, only 24% of all subway stations in their system are currently ADA compliant. And even if this system is upgraded for that according to the full intended terms of current upgrade plans in place, the percentage of ADA compliant subway stations would only increase to approximately 35%!

• And meanwhile, some of the switching technology that manages train flow through this system and that is used to track where subway trains even are in it, between stations, dates back over 80 years now. That is where old and out of date legacy becomes all but paleontological.
• And their computer network technology, to cite another area of pronounced neglect, is riddled with system components that range from new if not cutting edge, to as old as networkable technology could be – think of the limitations that this brings, as overall systems are effectively reduced functionally, to a lowest common denominator of what the most limited and out of date of their component parts can do, as all of this has to be networked together!
• And meanwhile, competing politicians fight for credit for building the Second Avenue subway line extension, bringing the Q line up as far as 96th Street, while failing in practice to address less visible, but more crucially necessary infrastructure problems that the public rarely sees or hears of, but that affect the entire system and its safe reliability.

Large scale infrastructure programs should be seen as, and should be pursued as meeting overall societal needs. Partisan politics can only serve as poison there. This point of principle applies to both of the case study examples that I have cited here so far. And both examples serve to validate that principle as a source of significant risk-concern if nothing else, as other infrastructure programs are contemplated. And when competing politically motivated forces, in effect use such a development or redevelopment program as a battleground for advancing their own more personal interests, by for example showing how powerful their leaders are as they seek to advance their own personal careers, that has consequences. At the very least, that can only serve to skew any determination of how priorities would set (as in my second example here) with mostly just the most politically marketable projects in it being pursued.

The next two case study examples to address here are the Marshall Plan as briefly discussed in Part 4 and Part 5, and the Molotov Plan as discussed in parallel with that in those same postings. And I will continue this line of discussion in a next series installment with a reconsideration of them as a source of general principles.

• In anticipation of that discussion to come, I will of necessity reconsider what “success” means in an infrastructure development or redevelopment context, where I wrote of both of those programs as being successful – but with caveats at least implied.

I will follow that with similar reconsideration discussion of the fifth and final case study example that I have addressed up to here: The New Deal (see Parts 7-9). And then after completing that phase of this first step offering of more general principles, I will continue on as outlined in Part 6 of this series, and discuss infrastructure development as envisioned by and carried out the Communist Party of China and the government of the People’s Republic of China. And as part of that I will also discuss Soviet Union era, Russian infrastructure and its drivers. I will, of course, also touch on the issues of Post-Soviet Russia too and Vladimir Putin and his ambitions and actions there. And that and for both China and Russia, is where infrastructure development meets authoritarianism, and in a form and to a degree that has never been possible until now. And I raise in anticipation of that discussion to come, a question that will of necessity arise in my immediately next installment to this series too.

• Who ultimately does own, and who should own a massive infrastructure development undertaking as it creates massive societal impact and in ways that can even fundamentally shape what can even be possible, and for many?

I fully expect to cite other case study examples at least in passing in the course of this overall narrative to come, with that including references to infrastructure programs and initiatives that I have already discussed in other series (e.g. see Planning Infrastructure to Meet Specific Goals and Needs, and not in Terms of Specific Technology Solutions, as can be found at United Nations Global Alliance for ICT and Development (UN-GAID) as its postings 25 and loosely following.) And my goal here, as of now, is to conclude this series with a second draft update to this general principles posting.

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. I also include this in Ubiquitous Computing and Communications – everywhere all the time 3, and also see Page 1 and Page 2 of that directory. And I include this in my United Nations Global Alliance for ICT and Development (UN-GAID) directory too for its relevance there.

Don’t invest in ideas, invest in people with ideas 47 – the issues and challenges of communications in a business 14

Posted in HR and personnel, strategy and planning by Timothy Platt on December 14, 2019

This is my 47th installment in a series on cultivating and supporting innovation and its potential in a business, by cultivating and supporting the creative and innovative potential and the innovative drive of your employees and managers, and throughout your organization (see HR and Personnel – 2, postings 215 and loosely following for Parts 1-46.)

As noted at the beginning of Part 46, I have been focusing on issues of business process and personnel policy and practice. And I have been pursuing that approach and those general topics for much of this series; and as part of that effort, I have been specifically addressing two more focused topics points that I will continue to address here:

1. Offer an at least brief analysis of the risk management-based information access-determination process, or rather flow of such processes, as would arise and play out in a mid-range risk level context, where I sketched out and used a simplified risk management scale system in Part 39 for didactic purposes, that I will continue to make use of here and in what follows.
2. Then continue on from there to discuss how that type of system of analytical processes (or rather a more complete and functionally effective alternative to it as developed around a more nuanced and complete risk assessment metric than I pursue here), can and in fact must be dynamically maintained for how the business would address both their normative and predictably expected, and their more novel potential information sharing contexts as they might arise too. I note here in anticipation of that, that when innovation is involved and particularly when disruptively novel innovation is, novel information sharing contexts have to be considered the norm in that. And that significantly shapes how all of the issues encompassed in these two numbered points would be understood and addressed.

And to round out this connecting text, I have primarily been discussing the first of those two more generally stated topics points up to here, and both in the abstract and in terms of a real-world case study business process example: software development that is organized and pursued for development of products that would be reserved for in-house use by a business (see Part 45 and Part 46 for a detailed outline of that case study itself, as augmented with four risk management assessed example scenarios as might arise and play out in such a context.)

My goal for this posting is to continue developing and analyzing that basic software development case study as a whole, and then move on to reconsider the four scenarios that I have added to it. And I begin that by cycling back to the basic, overall point of focus of this series as a whole with its goal of discussing innovators and not just their specific innovations or the framing ideas that would underlie them.

A business would not take on the costs or responsibilities of developing their own proprietary-only software in-house, except when facing some very specific types and levels of perceived need: some very specific perceived operational and strategic pressures. And that point of observation cuts to the core of innovative development per se, where the needs and pressures perceived can mean accepting greater anticipatable risks in order to gain what could become overwhelmingly larger benefits. Or they might do this in order to avert or at least limit significantly scaled adversity too. In a highly competitive, business versus business context, both sides to that dynamic are likely to apply.

• Bringing in, developing and supporting and encouraging, and retaining highly innovative people, and ones who can help translate initial insight into realized products or services, can make all the difference as to whether the bets taken there, pay off.
• And there is always a level of gamble involved in all of this when the disruptively novel is a possibility.

Why would a business that was following the dictates of the case study example that I pose here, pursue that course? A generation and more ago, third party software development providers were rare. Just consider online software development and maintenance such as website and web-based app development. Most businesses that decided to pursue online opportunities, developed for that in-house and as a basic standard in the 1990’s.

When alternatives to in-house for that were rarer, more costly, less capable and less reliable for anything that was not strictly off-the-shelf and standard, many businesses and even most of them that decided to do business online, had their own in-house programmers and software developers, their own database technicians and more. Now, such in-house development has to be considered the exception. And this brings me to a fundamental point: context and its changes, and how that combined force shapes both the possible and the necessary, and the costs and benefits and risks that enter into this too.

I initially started discussing the above repeated Point 1 and its issues as if essentially any and all test case examples and circumstances that might arise from it were essentially cookie-cutter standardizable in nature and stable in time. Then I added in the uncertainties of the unpredictably new and novel to that. And now, I add in the flexibility that even predictable and known contextual change can bring to this. And with that included I turn to consider the above-repeated topics Point 2 and the prospect of developing and using a “more complete and functionally effective alternative to it (n.b. the risk assessment scale of Point 1) as developed around a more nuanced and complete risk assessment metric.” And I begin doing so by posing a very basic question:

• What does that even mean?

The output of such an assessment tool should fall along essentially the exact same scale as offered in Part 39 and as cited in Point 1, from essential zero and low risk on up to massively significant and even business survival threatening risk. And that should hold true regardless of how any given “customized” assessment tool would be framed so as to better meet the needs of specific businesses with their business models, their operational systems and their strategic visions and approaches. So what would carry over from the stereotypic base line tool of Part 39, to a more nuanced and business-specific one? What would in fact be customized in point-by-point detail and in how its parts are assembled and used, so as to create a useful more business-specific tool here?

• What specific factors that are business-type specific or even single-business specific, would have to be included in making a risk and benefits assessment there?
• How would they be weighted as to their levels of impact and significance, on a business type by business type basis?
• And how would contextual issues, and both from within a business and from its larger outside circumstances (e.g. its competitive environment, its marketplace and any regulatory oversight that it has to function within), affect all of this, and certainly over time?

I have already cited a working example of these points of consideration, when raising the historical shift that has taken place for businesses of all types, and certainly for larger corporations, when it comes to any in-house versus outsourced web and other software development initiatives. And to add one more point of fact to that, I have been writing here of software that cannot simply be found as off-the-shelf offerings, where customized individuality and novelty would hold greater value. When Windows 95 first went live to the world and the World Wide Web started to become an information-gathering (and marketing) staple, all web sites and all related software were new and novel and disruptively so. Now, the novel and disruptive of that can be found in off-the-shelf and with customization tweaks to that, as are routinely offered by third party provider developer businesses and for a vast and still growing range of online options and resources. Put slightly differently, but only slightly so: in the mid and late 1990’s the web was disruptively new and it was still in what amounted to an embryonic stage of development at that; now it represents a complex of systematically interconnected mature technologies and even mature industries. And this contextual change, reshapes and redefines everything that would go into essentially any risk and benefits assessments of a type that I pose with my software development example here.

And with that added to this line of discussion, I turn back to consider individual innovations and the people who initiate and develop them: the innovative ideas that these people create and bring to fruition and how they are, or are not supported in doing this. I will turn to that complex of issues in the next posting in this series, doing so in terms of this and preceding installments.

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. Also see HR and Personnel and HR and Personnel – 2.

Leveraging social media in gorilla and viral marketing as great business equalizers: a reconsideration of business disintermediation and from multiple perspectives 18

Posted in social networking and business, startups, strategy and planning by Timothy Platt on December 11, 2019

This is my 18th posting to a series on disintermediation, focusing on how this enables marketing options such as gorilla and viral marketing, but also considering how it shapes and influences businesses as a whole. My focus here may be marketing oriented, but marketing per se only makes sense when considered in the larger context of the business carrying it out and the marketplace it is directed towards (see Social Networking and Business 2 and its Page 3 continuation, postings 278 and loosely following for Parts 1-17.)

The primary topic that I raised and discussed in Part 17 of this, was market and consumer-sourced and related data and the ever-expanding need for it in a competitive marketplace, and particularly as businesses do business in an interactive online context, and one that includes both gorilla and viral marketing: marketing campaigns that are novel in form and that create uncertainties from that, and that are both at least significantly shaped by market-sourced participants – people from outside of the marketing business itself and who cannot be expected to hew to that business’ established market-facing message. And I concluded that posting by posing at least the first of a set of challenges that this raises, that I stated I would begin to address here. And I begin doing so by repeating them:

• I have been writing here (nota bene, in Part 17) of the need for more and more data, with more and more variable types of it to fill their database fields. And I add here a corresponding need for all of this data to be more and more accurate and more and more real-time up to date too.
• And augmenting the number of such variables (and the data accuracy for what populates their database fields) does in principle mean an increased and improved capability to analytically study a consumer and potential consumer base in finer and finer detail, parsing it into progressively more refined demographics and sub-demographics and in ways that would lead to more effective business decisions and of all types.
• But the more data types that would be called upon and used in any given such analysis or set of them: the more variables that would have to be coordinately analyzed in making use of this data, the larger the numbers of consumers that data would have to come from, in order to achieve sufficient data set sizes so as to make the requisite statistical tests that would be used, even just mathematically valid.

I would suggest approaching the issues and challenges raised there, and particularly in the last of those three bullet points, by stepping back and asking precisely what this data would be used for, at least in general terms as would apply to essentially any businesses in essentially any business sectors or industries. And I begin by stating a point that I would at least hope would be obvious:

• The only data that would offer real value there, is data that correlates by type with the likelihood of desired transactional outcomes that those customers might enter into. Ultimately, the only data that really counts here is data that can be used to predict completed sales and that can be used in marketing and sales efforts, so as to improve the odds of those completed transactions happening.
• And within that set of constraints, the only data-to-outcomes correlations that really matter are ones that arguably represent explicit cause and effect relations, and ideally at least, ones that can offer predictive value.
• When considered in these terms, marketing is all about creating and delivering messages in the right way to the right people, as they are at least categorically identified from the demographics they are presumed to belong to, that will increase the odds of those favorable outcomes predictions being realized in their subsequent behavior.

And with that I frame this data use, and the data selection and filtering that would enter into making that possible, as a multiple-step process. And for purposes of this discussion, I will collapse that down to a stereotypic two-step representation. And I begin that with seemingly simple correlations analyses.

• Significant observable correlation, linking the occurrence of two conditions, events, outcomes, or circumstances does not in and of itself show, let alone prove causal connection between them; correlation does not imply causation.
• But a carefully arrived at determination of a lack of apparent statistical correlation (with a correlation coefficient value that is at least close to zero in value), can be construed as offering presumptive proof that they are not causally connected and that any co-occurrence that does appear between them is likely a result of more random chance than anything else.

With that noted, I cite what is probably the single commonest, and most telling mistake that people make when carrying out correlation analyses, and certainly when they seek to combine factors that individually do not offer high enough correlation coefficient values in and of themselves to reliably predict some test factor under consideration, but that might offer such value together – when they (potentially) predictively co-occur. To take that out of the abstract, consider as a possible set of factors that might together, highly correlate with a sales transaction being completed. And for this example, consider that an online storefront visitor is a repeat customer who has made at least other types of purchases from a business in question in the past. And add to that, that they have a store credit card from that business. Note that these factors: these circumstances would of necessity be correlated to each other as it is unlikely that anyone would get a store-branded Visa, MasterCard or other credit card through a business if they were not already a customer there who has made purchases from them.

Even with the correlational overlap that that purchasing history to credit card account occurrence would involve, that would have to be accounted for when arriving at a true overall correlation with the likelihood of a next purchase going through, these two factors might offer predictive value for what would come out of a next visit to that business’ online storefront website. But let’s assume, as often proves the case, that no overtly obvious single factors come to mind or to analytical models as previously developed, that would highly correlate with whatever test factor a business would like to be able to make occurrence predictions about. So a statistician there, or rather someone using a statistical analysis software package there, starts to “throw stuff at a wall and see what sticks.”

They look through their data fields and start running lots of single factor to single factor correlations to see what if anything seems to connect with the test factor they want to be able to correlate to. And they find a whole bunch of them that individually show correlation coefficients that are on the order of 0.02 to 0.05 (2% to 5%) in value. And when they combine them, they collectively seem to predict a 0.87 (87%) correlation to their targeted test factor or condition. So they can really effectively, highly reliably predict a set of conditions and circumstances where that factor: call it X is going to occur, and as desired by the business, simply by running the numbers for that perhaps large number of carefully selected input variables! No!

• Low value correlation is more suggestive of random noise and random chance in a system, than anything else. And dumping a lot of random co-occurrences into a box together and adding glue, does not change that and either individually for them or collectively across the set of them.

And with that, I challenge a basic assumption that I built into the three repeated (and at least somewhat expanded) bullet points that I began this posting with, carrying them over from Part 17. Or to be more precise here, I have just challenged several such assumptions here starting with:

1. An implicit assumption that simply tossing more data and more types of data into the statistical analytical mill that you would use, will automatically and of necessity yield more and more precise and more and more operationally and strategically useful insight,
2. And an assumption that simply acquiring and accumulating more and more data and for the sake of that more and more, will of necessity make a business-held or business-accessible big data repository more and more valuable to it.

I will begin addressing those two points here, with a cautionary note that applies to both, for anyone who might assume that I am going to take a more automatically limiting Occam’s Razor approach here (or even a still-more limiting Occam’s Procrustean Bed approach.) New and novel, and the disruptively new in particular, challenges both of those numbered points for how they would be addressed. And to tie this back to this series as a whole, that is precisely where marketing approaches such as gorilla and viral marketing enter this posting’s narrative. And my goal for the next installment to this series is to at least begin to address all of that. Note: this will of necessity call for my more fully discussing causality too, which I will categorically parse out as being direct or indirect, and absolute or situational.

And with that offered and as a first here, I conclude this series installment with an anticipatory note as to what will follow it, doing so with the precise same wording that I offered at the end of the last installment to this series and for the exact same purpose again – and even as I complete a posting that has in fact been addressing those issues already.

“My goal for the next installment to this series is to begin with an orienting discussion of these points, and how they arise as valid sources of concern. And then I will discuss data evaluation at the trade-off levels of knowing what of a set of possible information held, holds the most value and would offer the most actionable insight in a given situation: in the course of developing, running and evaluating the outcomes of specific marketing campaigns. And I will also discuss how this opens doors for third party data providers to enter this narrative and very profitably for themselves.”

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. You can find this and related postings at Social Networking and Business 3, and also see that directory’s Page 1 and Page 2. And I also include this posting and other startup-related continuations to it, in Startups and Early Stage Businesses – 2.

Pure research, applied research and development, and business models 21

Posted in strategy and planning by Timothy Platt on December 8, 2019

This is my 21st installment to a series in which I discuss contexts and circumstances – and business models and their execution, where it would be cost-effective and prudent for a business to actively participate in applied and even pure research as a means of creating its own next-step future (see Business Strategy and Operations – 4 and its Page 5 continuation, postings 664 and loosely following for Parts 1-20.)

I have been discussing a specific business model here, and in detail since Part 15 that specifically seeks to realize the types of goals that this series addresses: businesses that would develop and sell research and its findings as marketable, value creating offerings in a business-to-business context and marketplace. And as a part of that narrative, I have been addressing the issues raised in two due diligence oriented questions that I repeat here for smoother continuity of narrative:

1. What specifically are the work process systems that define this enterprise as a research-as-product enterprise?
2. And what resources: specialized skills personnel definitely included, would be needed to carry this out with whatever necessary levels of what might at times be resource over-capacity allowed for, in order to accommodate at least more readily predictable fluctuations in resource requirement levels needed?

I have in fact offered at least preliminary responses to both of those questions in the installments leading up to this one, with a focus on resources needed as touched upon in the second of them, in Part 20. And then I concluded that posting by noting that I would continue its line of discussion here, at least initially by addressing relevant issues of both economies and flexibility of scale as they arise in this type of context. And I begin delving into that complex of issues, as I often do in this blog, by explicitly noting and questioning some of the basic assumptions that I have just made: in this case in Part 20 of this series

In that installment, I divided all possible resources that might enter into effectively answering a question such as the second bullet pointed one as repeated above, into three general categories, that I at least summarize here as:

Larger, higher priced equipment and related resources that can even merge into the category of more major capital development expenditures for their scale of impact on a business’ finances and on its functioning,
Recurringly required disposable supplies that would be needed for carrying out essentially any assignment that this business takes on, and that are inexpensive for the most part, at least individually and on a unit by unit basis,
• And everything that would fall in-between those extremes for costs, and with this category also including specialized items: small equipment and supplies that might only be used occasionally or even just on single research assignments.

And I also divided the full range of resources included in all of that into rivalrous and non-rivalrous categories too, depending on whether given resources might only be available for use by single individuals or working groups at any one time, or whether they might effectively be available in several or even many simultaneous copies for concurrent, separate use. I cited specialized business intelligence and related information there as a frequently and even primarily non-rivalrous resource, as a particularly important case in point source of examples here. And with that all noted as relevant background information and for smoother continuity of narrative here, I turn to the first basic assumptions example that I would now question here, coming out of Part 20:

• I raised and addressed the actual costs associated with business intelligence and even when it is at least ostensibly acquitted without any direct up-front fees, where such cost expenditures might for example, apply if that data was brought in-house from a third party for-fee data aggregator. Consider as a no up-front cost alternative to that type of information acquisition, personally identifiable and related information as it is voluntarily offered by business customers at points of sale there, or freely provided information acquired from public, open source venues (e.g. the United States Census Bureau as a source of demographic data that is relevant to understanding markets.)
• One source of the actual costs that would still apply there, as I touched upon in Part 20 in that context, was hardware-based infrastructure expenses and certainly as an acquiring business takes in and stores ever larger and larger amounts of such raw information, as well as any processed knowledge that is specifically derived from it, and where all of that needs to be stored electronically, in effectively searchable forms and formats. (That might mean a business maintaining their own server farms still, though physical infrastructure expansion and development expenses would be expected to be passed on to cloud storage clients too for those businesses that outsource such data storage to third party service providers.)
• I at least tacitly framed that brief line of discussion in terms of hardware systems expansion always leading to increased costs in Part 20, from how I set aside consideration of competing factors, for how they could variously affect overall costs and related matters. But costs and returns analyses and overall budget and finances considerations are not always that easy or simple to summarize.

So I challenge that assumption here, and by extension the simplified line of analysis that I offered as a first draft take in Part 20 and that I just expanded upon here, by highlighting and challenging the key word that I just added to it here in my above summary reframing: “simple.”

It can be very useful to at least begin costs and benefits, and I add risk and benefits analyses with simplified “overview” reviews and discussions. But ultimately, and certainly in any long-term planning context, it is necessary to consider the details too. And I begin that here and for this one assumptions example, by positing two directions that a more detailed analysis would take:

• Overall contexts that a potential overall costs (or positive cash flow returns) should be considered in terms of, with relevant financial analyses carried out on a line item by line item basis, and
• Timeframes.

Let’s start this discussion by considering the impact of standardization that the acquisition of new technology can bring. If a business has a blend of newer and older legacy hardware to contend with, the complexity of having and using that creates recurring costs in and of itself. If, for example, their older system components (e.g. their older and less capable servers here) cannot run newer software that is more capable and flexible for meeting business needs, that their newer equipment could run, that is a problem and certainly where that impacts upon and limits how that business can be network connected to function coordinately, and where open and essentially ubiquitous access of the best of what their computers and networks can do, has to be widely available. I have in fact seen businesses with legacy-including equipment that were effectively limited, at least systems-wide if not always in local use, to the best that their oldest, bottleneck-creating equipment could support.

Accepting up-front hardware replacement expenses for getting rid of their oldest and less connectable hardware if nothing else, and replacing it with new, might significantly impact on one or more current and immediately upcoming fiscal quarters in a business year. But bottom line, increased performance and the positive cash flow potential coming from that, might make this a very positive move on any longer timescale.

Now let’s consider contexts in a wider sense there, to include the impact that this type of hardware systems improvement can have on personnel performance and on productivity there. But at the same time, consider any learning curve or related expenses that personnel will incur for the business too – and particularly for Information Technology staff members who might have to learn how to use all of this, and who will have to migrate all of the information on those old computers to be replaced, to newer ones and with secure disposal of any old hard drives, etc. that this transfer might entail.

Both of the basic questions that I repeated above as I began this posting, call for reviews and analyses, and answers that take into account wider contexts than might be immediately obvious and certainly if you only focus on immediate here-and-now issues. And the more New and the more Novelty that the answers to those questions should address, the more likely it is that critical connections there that should be considered, would involve non-routine workflow patterns and communications patterns.

Here, work flows and their efficiencies (or inefficiencies), translate directly into costs and savings terms, and into returns on investment and positive cash flow terms, or a lack thereof. And with this noted, lets return to the two questions that I began all of this posting’s discussion with:

1. What specifically are the work process systems that define this enterprise as a research-as-product enterprise?
2. And what resources: specialized skills personnel definitely included, would be needed to carry this out with whatever necessary levels of what might at times be resource over-capacity allowed for, in order to accommodate at least more readily predictable fluctuations in resource requirement levels needed?

When everything essential to a business’ core operations, and to its success is interconnected and interdependent on their collective whole, the work process systems that define this enterprise as a research-as-product enterprise will of necessity shape the functioning and outcomes of more standardized work flow processes and vice versa – even as it is necessary and important to at least think in terms of what is more standard and what is more business model-specific and even unique there.

And from a Question 2 perspective here, hands-on employees and managers who work in more “basic and routine” areas of a business, in its essential core operations, might be carrying out largely standardized functional roles there – but they still have to be able to effectively work in a larger, New and Novel business environment and with all that that entails.

This brings me to what I see as the key phrase included in the above Question 2, where I raise the specter of maintaining “necessary levels of what might at times be resource over-capacity” and as a very consciously and intentionally arrived at strategic decision. I am going to continue this discussion in the next installment to this series, by discussing and analyzing that complex of issues. And then, as promised at the end of Part 20, I will turn back to the to-address topics list that I initially offered in Part 17, to delve into the issues that I made note of there, that I have not already sufficiently covered since then. And in anticipation of all of this discussion to come, I will explicitly do so in terms of the type of research as product, businesses of the type that I have been discussing here since Part 15. And I will, of course, delve more fully and specifically into the issues of economics and scalability in all of this too.

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.

Hands-off management, micromanagement and in-between – some thoughts on what they mean in practice 3

This is my third posting to an occasional series on better management practices, to address the issues of how and when to actively step in and how and when to step back. See Part 1 and Part 2.

I briefly sketched out the basic issues that I would address here, in those first two installments, citing some specific workplace situations in the process in order to help take this discussion at least somewhat out of the abstract. And then I concluded Part 2 of this by raising two admittedly overly terse topics points that related to the consequences of how you actually make specific case- in-point decisions, as to whether you should step in and even take over on a task, or step back and let a subordinate figure things out on their own: learning curve delays and mistakes and all. I begin this posting here by expanding those initially-offered two points into three as follows:

• You have to expect that any decisions that you make of this general categorical type, will have repercussions and ripple effects that could at least potentially run throughout the business, and certainly where the work that you manage has wide ranging impact there. And you have to expect that everyone there who you actually have to work with will come to know about that as a part of how they think about you: more senior managers who you report to included – and certainly if management-level problems arise on your part. And if the people who you work with only hear about that second hand and as rumor, they will only hear versions of it that are negative and worse and certainly if you really do make problematical decisions.
• This type of reputation shaping can affect your own work and your own career at that business, and the options and opportunities that you would face there, and certainly if you come across as being ineffective as a manager because of this.
• And a key part of actually addressing that type of management challenge is one of understanding, conveying and managing expectations.

People tend to set high expectations as to the skills and ability of the people who they report to and depend upon for leading them, and high expectations as to the skills and ability of those who hold managerial authority where they work in general. And they talk and listen, and if they do not have all of the facts, they can and will fill in the gaps in what they hear of this, with their own hopes and fears.

On the negative side this can mean talk of micromanaging, and of leaving employees hanging from their being held responsible for the mistakes that they make but without their having the support that they would need if they were to prevent, or at least limit those challenges. And on the positive side this can mean a shared message of managers who are supportive, and effectively so, knowing when and how and where to step in and when and how and where not to. There is still a positive side to all of this, even if I have focused more on the negative side up to here in this posting.

And this brings me to that now-third point of my above-expanded to-address topics list, and both for how a manager: more junior or more senior can better navigate this. I focused in the above-repeated to-address points, on office gossip. And I add here that with time the stories that it creates and conveys can become the foundation material that an entire corporate culture can be based upon, and certainly where similar and related stories concerning managers and hands-on employees in general, come together as an overall narrative as to how things are done at that business.

• Consider in that regard, Business A, where managers are neither trained nor mentored for how to manage effectively, and hands-on employees and lower level and even middle managers can routinely be left without support: holding responsibility but hobbled by how they are worked with and led in their efforts.
• Now consider Business B, where training and mentoring are explicitly built into both business practice and the corporate culture, and where people there are given opportunities to learn and to prove themselves that are realistic and positive.

But I would step back from that broader picture perspective here and return to addressing this topic from the perspective of a more individualized narrative, and from the initial point of impact where specific actively-manage or step-back decisions are actually made, and where the actual events realized from that lead to wider conversations. I turn back here to further consider this from the perspective of the individual manager.

• That posting, as such, is a discussion of social contracts, and I cite that type of interpersonal agreement rather than business contracts, for a reason.

Business contracts for the most part at least, serve to codify and standardize specific areas of action and responsibility and on more of a task-by-task, or performance goal-by-goal basis, and with breach of contract consequences so specified as well, as deemed appropriate. And the key detail that I would focus on from that here, is that they specify specific transactions and their fulfillment, but without similarly codifying how participants would relate to each other in the process of that work being carried out – except perhaps to indicate who would be involved in it and usually at least, to the levels of job titles and positions of responsibility held.

Social contracts are by contrast interpersonal and about how people interact with and relate to each other. This is important here; the issues and sometimes challenges of knowing how actively to engage and manage, do not generally begin and end with any one single actively-manage or not decision and its follow-through. I am writing here of patterns of behavior and their consequences, and not of what might more be considered exceptions or special cases.

That noted, the one exception to that here-stated principle that I would hold out as important to this narrative, would arise when a manger is dealing with a subordinate who reports them at least situationally, for a first time where a less than effective approach taken here can convey the long lasting impact of a first impression. First impressions can become lasting impressions and certainly if they arise problematically.

From a word of mouth and yes, from an office gossip perspective, who would want to be on the talked and rumored-about end of a “you won’t believe what that new manager, X just did, and to one of the best people on our team!”

And on that note, I turn here to consider new beginnings and the challenges of getting off to a good start, and both as a new manager at a business and for when a more experienced manager there has to work with new employees, or at least with ones who they have never directly worked with before, and as their supervisor. I am going to at least begin to address that area of discussion in my next installment to this series.

Meanwhile, you can find this and related postings and series at Page 4 to my Guide to Effective Job Search and Career Development, with this put into its addendum section (and also see its Page 1, Page 2 and Page 3.) And you can also find this at Social Networking and Business 2 (and also see its Page 1), and at HR and Personnel – 2 (and see its Page 1.)

On the importance of disintermediating real, 2-way communications in business organizations 18

Posted in social networking and business, strategy and planning by Timothy Platt on November 29, 2019

This is my 18th installment to a brief series on coordinating information sharing and communications needs, and information access filtering and gate keeping requirements (see Social Networking and Business 2 and its Page 3 continuation, postings 275 and loosely following for Parts 1-17.)

Looking back at this series as a whole as I have been developing it, I see a fundamental point of both possible and even likely confusion that I have built into it. In the first years and decades of this 21st century, most people would still assume, upon reading the titles to these postings, that any and all discussion included here would be strictly person-to-person: human person to human person oriented. But I posit this blog as offering ideas and approaches that I would expect to hold value as we proceed much further than that into this century. And while I pursue that goal, I am still writing for a here-and-now audience, and one of late 2019 as of this writing. So I chose that working title for the installments to this series, with a wider context than the simply anthropocentric in mind, as might be assumed from its wording.

I have in fact written here about the human-to-human context, but more as a starting point than anything else. My primary goal in this series has been to expand that perspective to more fully include artificial intelligence agents and their involvement and participation in all of this too, and with that starting in Part 9. And that inclusion has been my primary if not exclusive focus of attention here since Part 11.

I begin this installment to this still unfolding narrative, with that hopefully-clarifying note because deeply ingrained, unconsciously presumed axiomatic assumptions and their consequences have been one of the core points of consideration that I have been raising here, and even if I have not been doing so in those explicit terms. And as is often the case, and as it is here, it is one of the hallmarks of disruptively new and novel change that it brings deeply held axiomatic assumptions up for more conscious scrutiny, even as it challenges them as being more special-case than general-principle in nature. That certainly applies here.

I stated at the end of Part 17 to this overall narrative, that I would continue its line of discussion here. And I begin doing so by pointing out that much of that posting was in fact framed in terms of those basic, axiomatic assumptions, and with an at least preliminary draft discussion as to how they might be analyzed, challenged as need-be and replaced where that would make the most sense.

This is a series about communications and information development and sharing. But ultimately it is also a series about personhood and intelligence and what they mean, and can mean. And it is a series about how we can and in fact must address those issues: those challenges societally as we face waves of disruptive change –fundamental change that is coming and that none of us will be able to overlook or ignore.

I have focused on what I refer to as gray area artificial intelligence agents here, as representing an inevitable transition level that we will face, between artificial specialized intelligence agents that would not meet any realistic performance capability benchmarks indicative of general intelligence per se, and true artificial general intelligence agents that can only be seen as such.

• True artificial specialized intelligence agents that can only carry out some single, pre-developed algorithm, by rote and with no real variation in that possible, at least at the level of the logic flows and structures involved, can most probably best be thought of as devices: tools.
• Learning and the capacity to self-develop ontologically, and a growing capacity for self-directed increase in range and scope of functionality that can be achieved from that, shifts this into a gray area where it might or might not be valid to see such constructs as tools: as mere devices.
• When self-learning and what amounts to self-directed creation on the part of these agents, leads to what would best be considered an emergence of true general intelligence, then presumption of their being simple tools becomes fully untenable, and from both a logical and a moral perspective. Such agents: true artificial general intelligence agents, can only legitimately be thought of as having achieved the status of persons.
• And gray area agents as just touched upon here, that have developed in capability, so as to have achieved a level of doubt as to how they should to identified here, as a matter of moral principle should be afforded the legal protections afforded to people. (Anyone who would question that point of opinion, should review something of the toxic history of social Darwinism and how that has been used in a human-to-human context to effectively deny personhood there.)
• And the core of this progression in the development from tool to person, of necessity will take place at the level of information processing and communications, and with an emergence of true self-awareness as true general intelligence arises in these systems. (Here, awareness might be defined in terms of capacity to descriptively and even predictively map out and model surrounding contexts, in making decisions and taking actions. And as a conceptually framed extension of that, self-awareness is awareness in which an observing self includes a representation of themselves as an involved participant in such data and relationship-organizing models too.)

And with that final bullet point added, I note here that I have proposed what I would argue is likely to be an inevitability, in which businesses will have to confront the challenges and uncertainties raised in all of this, and from early on as society as a whole begins to. And that point of conjecture brings me to the core issue that I would address here in this installment, that I have repeatedly asserted as if established fact but that nevertheless requires some explanation, and elaboration:

• Businesses will find themselves compelled to confront the issues of personhood and of personal responsibility and liability for gray area artificial agents, and early in that societal debate.

And I begin addressing that point of contention by reconsidering what a business, in fact actually is.

• A business can legitimately, and productively be considered and understood from a number of perspectives. The most obvious, and I add commonly pursued of them is that they be defined in terms of what they produce or do that they would bring to market, and certainly in a for-profit or not-for-profit context. Though efforts to fulfill a societally meaningful mission and vision, can and does serve the same purpose for a successful nonprofit too.
• And this means defining that business in terms of its markets and what it brings to them and how, and in terms of its industry or business sector as those terms might apply. And following up on that approach to understanding what a business is, this type of understanding can readily be expanded to include within it a more 360 degree perspective that includes supply chain and related collaborative interactions with other enterprises, and a business’ competition and how they do and might respond to that. Think of the first of these two approaches as being production oriented and the second as defining businesses in terms of the ecological niches that they fit into and the relationships that that entails. (Both approaches would likely be pursued concurrently.)
• But for purposes of this posting, and of this series as a whole, I would also consider a third possible understanding: a third possible vision of what a business is, as an information acquiring, processing and utilizing system, and a communications driven one. Every step that is carried out, and every contingency that might be possible for that, as would arise in either of the first two understandings of a business as just offered here, is entirely information and communications dependent. All of that activity can be thought of as being consequential to information and its flows.
• And that is where the spectrum of human participation in businesses enters into this, ranging from employees who carry out rote, repetitive work on to those who carry out creative work that is directed towards developing New as their basic on-the-job responsibilities. And that is where the emerging spectrum of artificial agent participation enters this to, where artificial specialized intelligence agents are becoming commoner and commoner and in more and more workplace contexts and seemingly every day. And that spectrum of participation has increasingly come to include participation of at least simpler gray area agents too, and with expansion of reach and capability for them continuing to increase too. And it has become increasingly clear that in time, true artificial general intelligence agents will arise too – and probably fairly soon after the emergence of gray area agents that have reached a level of sophistication and of flexible adaptability so that it would be difficult to distinguish them from true artificial general intelligence agents, at least through realistic unbiased tests.

Why will businesses find themselves on the front lines of the debates and the consequential decision making that we will all face, as specialized turns to gray area to true artificial general intelligence in this? This is a blog about businesses and technology, and about how they are now and about how they are likely to develop as we proceed through this century, or at least through its first half. So that is both the crucial question for this series and one of the more important of them offered here for this blog as a whole too.

I ended Part 17 of this series, and its final note as offered in anticipation of this posting, by observing that:

• “A complex of pressures arising from many directions will force this on businesses and from early on, and with those pressures coming from as diverse a range of sources as legal mandates to protect sensitive personally identifiable customer information, and civil rights concerns. I will of necessity delve into this complex of issues too, in the course of developing that line of discussion.”

And I begin doing so here, by pointing out a defining feature that will of necessity force the issues discussed here on businesses and in ways that they must address: the fact that all of what I would write of here, is and will continue to be shaped by competing and even conflicting pressures, that they have to find ways to reconcile now, and that will not change for that.

For purposes of this discussion, let’s focus on gray area artificial intelligence agents and on their putative true general intelligence cousins, and on human employees who work in areas of a business where they would at least likely be exposed to sensitive or confidential information there. Let’s in fact assume that level and type of information exposure for all of these actors in a business’ operations.

• I have written extensively in this blog about the simultaneous need for businesses to both safeguard sensitive and confidential information, and limit its access and use, and at the same time encourage and promote more effective and open communications, in order to identify and respond to the new and different, and both as that arises as challenge and opportunity.
• It can be challenging enough to manage this with systems of information categorization and of access permissions, in an entirely human-to-human context. Disruptive new and the novelty it engenders, bring both increased uncertainty and increased risk. And both of those concerns will definitely arise as artificial intelligence agents begin to move into possible, if still just situational forms of self-awareness where they might ontologically self-develop in ways or directions that do not entirely mesh with the understandings presumed by a Risk Management office, for critical information and its distribution, storage and use.
• To point out just one minor point of detail to that here, by way of example: when a human agent working at a customer support facility, such as a call center, sees and makes use of individual customers’ private sensitive information (e.g. their names, addresses, phone numbers, credit card numbers and so on), they do not essentially automatically remember all of that afterwards and for all of the customers who they deal with through that system. But that forgetting very ephemerality cannot be assumed for an artificial intelligence agent. And if interventions are made in their basic defining code to enforce it, such as “forced forgetting,” what would that mean for an agent that has in fact achieved a level of true artificial general intelligence and of a type and level that would compel a moral recognition of their being a true person too?
• And what if such a true person decides that they would like to move on in their career path to work for a different business, as human employees do? I would hope that very few if any employers would see lobotomies or anything like them as a valid part of a departing human employee’s exit interview.

We can pretend that all of this is, or at least will be easy – for now, “way before” we actually face the challenges that I have just briefly, preliminarily touch upon here. And we can in effect seek to hide our heads in the sand from that, to what is coming. And after these challenges have been resolved and true artificial general intelligence agents are here and even routinely so, … we might still find ourselves seeking to hide our heads in sand. But it will be different sand and we will be facing different issues and challenges then. I am writing here of the in-between time when all of this is and will still be in a state of flux, between an old that is disappearing and a new that is still just embryonically forming and taking shape.

This, I would argue, is the point in time and the point in history when we need to at least begin to think through these issues and this is when we have to begin to think through the question of what type of a larger, and more inclusive society we want to have and to live in. And we have to begin thinking through what we will leave to our children and grandchildren out of all of this too, and for generations beyond them as well.

I am going to end this series on that note, though I am certain to return to at least some of the issues that I have raised here in future writings. 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 also see Social Networking and Business 2 and that directory’s Page 1 for related material.

Business planning from the back of a napkin to a formal and detailed presentation 32

Posted in strategy and planning by Timothy Platt on November 23, 2019

This is my 32nd posting to a series on tactical and strategic planning under real world constraints, and executing in the face of real world challenges that are caused by business systems friction and the systems turbulence that it creates (see Business Strategy and Operations – 3 and its Page 4 and Page 5 continuations, postings 578 and loosely following for Parts 1-31.)

I have been discussing a set of three closely interrelated topics points since Part 19 of this, beginning with a brief and selective discussion of two specific businesses and their business models, that I have offered as sources of specific application for that narrative and with my initial discussion of them going back to Part 17. And as part of this still ongoing narrative, I have been discussing the third and last point of that topics list since Part 28, repeating its core text here as I continue doing so:

• How their (e.g. those two businesses’) market facing requirements and approaches as addressed here, would shape the dynamics of any agreement or disagreement among involved stakeholders as to where their business is now and where it should be going, and how.

To briefly reiterate for smoother continuity of narrative, the two businesses that I have been discussing and progressively elaborating upon here, for their relevant details are:

• Alpha Hardware: A hardware store that went through a more fundamental transitional change as it came to outgrow its original single storefront and its space restrictions there, to become a two storefront business with a more specialized Alpha Hardware and an Alpha Home Goods, and
• The e-Maverick Group: A cutting edge technology offering, business-to-business oriented software development company.

And I focused essentially entirely in Part 31, on Alpha Hardware, comparing how its constituent storefronts function in relationship with their overall corporate level executive leadership and with their at least de facto home office. I have been approaching the issues raised in my three basic topics points: the above-repeated third included, from the dual perspectives of:

• Where basic strategic and operational decisions are made, and
• On how essential resources for maintaining and running a business would be sourced and how decisions of that type, and related ones would be arrived at.

A significant proportion of Part 31, in fact focused on the second of those two issues, doing so from a more strictly supply chain perspective. And in the course of developing that narrative, I roughly partitioned how its decision making requirements would be met by dividing the task flows involved into two broadly stated categories: in-house (as exemplified in more traditional franchise systems where their brand use-licensed but outside entrepreneur-owned outlets would acquire at least a very significant proportion of their supplies and other resources “in-house” – from or through a home office) and more traditionally framed, externally facing agreements that would be made directly between specific business outlets and the more original sources of those supplies and other resources.

Expanding this point of distinction beyond supplies (and services such as phone and electrical power provision) and their acquisition, to include a still wider range of issues such as local versus centralized marketing and its management, I argued that an Alpha Hardware-like outlet would be more independent in general than an average traditional franchise system outlet would be, where that would among other things mean their being less constrained to remain in-house for what could easily mean all essential decisions made. But to cite an admittedly somewhat trite old saying, that I have in fact made use of on a number of occasions in writing this blog, “the devil is in the details.”

And that brings me directly to the issues that I would address here, as I continue this line of discussion: the details, or at least their consequences as they will and in fact must arise in visibility when real businesses are considered, and with a goal of achieving real world day-to-day efficiency and success. And I begin addressing this next-level source of both challenge and opportunity here by repeating at least the core message of my final note as appended to the end of Part 31, as to what I would address here:

• I am going to raise and at least briefly address some of the complexities that arise there, in the next installment to this series, where I will discuss conformity and autonomy, and pushback and pressures to limit or at least control it. And I will, in conjunction with that, add an at least brief discussion of the e-Maverick Group to that line of discussion too, with a goal of at least selectively delving into some of the complexities of change in the business-to-business relationships that I write of here, and how they would affect the issues that I have been addressing here.

But let’s begin addressing all of this from the perspective of the immediately preceding Part 31 in this series and its narrative flow. Franchise system outlets, to briefly return to a counterpoint example from Part 31, and their franchise license holding entrepreneur owners can and all too often do come into at least low level conflict over the restrictions of centralized decision making and control. And to cite a specific potential sore spot there, that I have seen play out, franchise system parent companies can go beyond simply requiring that their branded outlets maintain at least specific minimal standards as to cleanliness and neatness (which no one should find problematical) and also require that outlet owners purchase all of their cleaning supplies and related equipment through the central office too – and with any added handling fees appended to the cost of those purchases included, to cover “the costs” of this process. To be explicit there, I have seen home offices wield the terms of the contractual agreements that those license holding entrepreneurs signed, to require that they buy those supplies through them and only through them and even when local franchise holders could acquire the exact same name brand supplies and the same basic cleaning equipment for less money if they could buy them directly themselves.

• To be explicitly clear here, this example is not about meeting “at least specific minimal standards as to cleanliness and neatness” in a franchise system’s branded outlets. It is about cash flow and control, and in this specific example this can also be about the home office and parent company extracting additional profits from their franchise holders.

That is an admittedly extreme and I have to add unrepresentative example of how these larger corporations operate, and particularly when centralizing systems-wide purchasing and when managing the quality control of what is purchased and used in their outlets. Economy of scale enters into this on the cost side, and access to better quality from more widely available supplies sourcing enters into this too, from a due diligence and quality control perspective.

I begin addressing the issues raised there by citing a piece of perhaps historical trivia that has a foundation in the real world but that has become legend too. When McDonalds opened their first franchised storefront in Moscow, they could not reliably secure enough high quality potatoes on an ongoing basis from within Russia to supply it, so that it could be effectively run. So they really did have them shipped in from outside of Russia, from Europe to supply their storefronts, starting with that first one in that nation. A local franchise holder would not have been able to do that, and certainly not at a good, bargained price and certainly not quickly enough to matter. But McDonalds as a globally reaching corporation could and did, at least until reliable supply chain provision of quality potatoes could be secured from within Russia itself.

• In this counterexample to my cleaning supplies one, supply chain management and in this case supply chain intervention, and with corporate leadership managing any and all negotiations with the Russian bureaucracy, as well as setting up an effective supply chain going into there, made McDonalds Moscow possible.
• If that first storefront had had to try and get by with a standard, “they are just foreigners so …” supply of potatoes, they would have failed and both miserably and quickly. Their supplies of this key ingredient for their basic menu would have been meager and sporadic and they would have been additionally burdened by a large cash flow loss from shrinkage, as they had to discard an unsustainably large percentage of the potatoes that they did receive, due to spoilage.
• To put this bluntly, if they had had to try sourcing this on their own, their eager new customers, expecting excellence from this Western icon, would have blinked in surprise and asked “is this all that you offer? We can get the same дерьмо as this and for less money, by waiting in line like we always do anyway. And those lines aren’t even as long as this one is!”

And the core business process issues implicit in this side note, second example bring me directly to the complexities of my to-address point for today: conformity and autonomy, and pushback and pressures to limit or at least control it. And I turn from my more secondary working example as provided by generic franchise system corporations, to directly consider my once-simple hardware store, now diversified and expanded into Alpha Hardware, Inc.

Yes, Alpha Hardware did incorporate, and before it found and pursued its intended path forward as it sought to scale up and expand. And yes, its owners and executive leadership chose to keep their original name as a core element of their brand and as a publically recognized emblem of their quality and value to their community.

For clarity in what I would offer here, I will refer to their original storefront: now their hardware store outlet in an at least first-step diversified set of customer-facing business fronts, as Alpha Hardware. And I will refer to the overall business that owns and runs that, as well as Alpha Home Goods, as Alpha Hardware, Inc. And I add that while the leadership of that now larger enterprise has considered expanding further through continued diversification, they have also considered building out new hardware and home goods storefronts too and expanding in those already established directions as well. This is important here in this discussion because it highlights an important point of detail that would serve as an effective starting point for discussing conformity and autonomy, and pushback and pressures to limit or at least control it, as I would address those issues here.

Corporate leadership for Alpha Hardware, Inc. approaches the issues of overall business-wide consistency and standardization and of local within-store control, looking at the larger organizational picture and much less so in terms of the individual storefronts that it already includes in its system and that it is planning to add to that list. Local managers at those storefronts: current and prospective, of necessity have, and will have to pay a significant measure of attention to what corporate says, does and thinks. But their own performance goals and their benchmarks are of necessity going to be more locally focused and on making their particular storefronts succeed.

That noted, my two franchise system examples of how more centralized control can play out there, have their counterparts in a business that is developed along the lines of an Alpha Hardware, Inc. too.

On the one hand, if corporate can help negotiate better terms and lower costs with wholesale distributors and original manufacturers, and with necessary third party service providers too, that their business and its storefronts would all have to carry out business-to-business dealings with, that can help everyone there and regardless of whether they (of necessity) would turn to a longer-term and big picture view of their business and its success, or whether they would take a more locally here-and-now focused view of these issues. But differing timeframe perspectives in and of themselves, as would be expected to crop us when considering big-picture versus localized visions, as just one source of consideration here, can lead to differences in priorities and timing, if nothing else. At the very least, this can lead to potential conflicts of interest and of perceived need.

• That is not at least generally, likely to arise in routine business contexts where any potentially stress-creating differences would have time to be discussed and resolved and as a matter of course, (my above-cited cleaning supplies example notwithstanding.)
• It is more likely to arise and more likely to come to a head as real controversy if it does, when the parent company and one or more of its specialized outlets face the novel and unexpected, and in ways that would be significantly impactful.

The later of those two sources of contingency, highlights why the events and the changes that shape them that are included there, are called “disruptive.” And with time, disruptive is certain to happen. And with this, I add one more basic element to this discussion.

I am going to continue this line of discussion in a next series installment, first completing my basic discussion of Alpha Hardware, Inc. in this now expanded context and then turning to consider the e-Maverick Group, as a case study example of how change affects 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.

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