Platt Perspective on Business and Technology

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

Posted in startups by Timothy Platt on April 12, 2019

This is my 37th installment to a series on building a business that can become an effective and even a leading participant in its industry and its business sector, and for its targeted marketplaces (see Startups and Early Stage Businesses and its Page 2 continuation, postings 186 and loosely following for Parts 1-36.)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

This is my 42nd posting to a series that addresses the issues of planning for and developing the right business model, and both for initial small business needs and for scalability and capacity to evolve from there (see Business Strategy and Operations – 3 and its Page 4 and Page 5 continuations, postings 499 and loosely following for Parts 1-41.) I also include this series in my Startups and Early Stage Businesses directory and its Page 2 continuation.

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

1. A new venture that has at least preliminarily proven itself as viable and as a source of profitability can go public and with all of the organizational change and all of the transparency and reporting requirements that this entails as they begin offering stock shares. (See Part 33 and Part 34.)
2. A new venture can transition from pursuing what at least begins as if following an organic growth and development model (as would most likely at least initially be followed in exit strategy 1, above too) but with a goal of switching to one in which they seek out and acquire larger individually sourced outside capital investment resources, and particularly from venture capitalists. (See Part 35.)
3. And a new venture, and certainly one that is built around a growth-oriented business model, might build its first bricks and mortar site, in effect as a prototype effort that it would refine with a goal of replication through, for example a franchise system. (See Part 36 through Part 39.)

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

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

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

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

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

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

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

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

Meanwhile, you can find this and related postings and series at Business Strategy and Operations – 5, and also at Page 1, Page 2, Page 3 and Page 4 of that directory. And you can find this and related material at my Startups and Early Stage Businesses directory too and at its Page 2 continuation.

Leveraging social media in gorilla and viral marketing as great business equalizers: a reconsideration of business disintermediation and from multiple perspectives 14

Posted in social networking and business, startups, strategy and planning by Timothy Platt on March 16, 2019

This is my 14th 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, postings 278 and loosely following for Parts 1-13.)

I began working my way through a to-address topics list in Part 11, that would apply to the analysis and planning efforts of a still resource-lean startup. And I repeat the first three entries in this list as I turn to and begin to more fully discuss its Points 2 and 3:

1. What types of change are being considered in building this new business, and with what priorities? In this context the issues of baseline, and of what would be changed from become crucially important. I assume here that change in this context means at least pressure to change on the part of business founders, from the assumptions and presumptions and business practices of their past experience: positive and negative that they might individually bring with them to this new venture, and their thoughts as to how a business should be organized and run as shaped by all of their prior workplace experience. So I will consider change as arises in how the business is planned and run, at least as much as I do when considering what would be developed there and brought to market as product or service. I will mostly just cite and discuss the later for its contextual significance in all of this.
2. Focusing on the business planning and development side to that, and more specifically on high priority, first business development and operations steps that would be arrived at and agreed to for carrying out (in light of the above bullet point considerations here), and setting aside more optional potential goals and benchmarks that would simply be nice to be able to carry through upon too,
3. Where exactly do those must-do tasks fit into the business and how can they best be planned out for cost-effective implementation (in the here and now) and for scalability (thinking forward)? Functionally that set of goals and their realization, of necessity ranges out beyond the boundaries of a Marketing or a Marketing and Communications context, applying across the business organization as a whole. But given the basic thrust of this specific series, I will begin to more fully discuss communications per se, and Marketing, or Marketing and Communications in this bullet point’s context. And I will comparatively discuss communications as a process, and as a functional area in a business there.

I focused more on the Who and How of key business decision making when addressing the above Point 1, and with the What of that considered essentially entirely in general terms. Point 2 specifically focuses on what the high priority issues are that a given startup would face, and on decision making processes and their follow-through that would lead at least ideally to their smooth and efficient resolution. And Point 2 also begs the question of how these high priority issues and needs would be identified and characterized, and both for their achievability and with what resources required for that, and for their overall needs-based priorities – setting them apart from the “more optional potential goals and benchmarks that would simply be nice to be able to carry through upon too” as noted there as well. And to further put Point 2 in perspective in this series and in this portion of it, Point 3 continues on from there, with a now-determined list of high and highest priority tasks and goals agreed to, and with their actual resolution the topic of discussion.

I continue my Part 13 discussion here with a fuller and more organized consideration of Point 2 from the above topics list, as outlined in the above paragraph, and with the question of what to do first and even right now, and what to set aside for later if at all. And I begin doing so by acknowledging that I in fact sneaked part of my answer to that challenge into the above paragraph when outlining how I would propose responding to a Point 2 challenge, when I made note of resource availability.

• Ideally, task and goals prioritization would be based entirely on here-and-now and anticipated upcoming need. But that approach can only apply, and certainly as an automatic and always-resorted to option if there are and always will be sufficient resources available and of all required types, to make it possible for a business to carry out essentially whatever it seeks to do, whenever its leadership decides that they would like to do so.
• In the real world, need and desire have to be tempered by limitations faced in what can be done, and on consideration of when the resources required for that might become possible for doing that work, and at what costs. Resource limitations and the performance bottlenecks and barriers that they create, determine the doable here.

This pair of linked points is important. And while they might seem obvious when stated as above in the abstract, it can be easy to lose track of their message in the heat of the moment and when facing immediate and impending pressures to effectively perform, in carrying out next building steps in launching a new business venture. I have certainly seen new businesses get caught up in what from a perhaps more objective perspective, might seem to be resource expending inconsequentials, and particularly when they primarily would serve to support a founder’s vision of themselves and of what they would at least ideally seek to build in their business – as an expression of that. Though ego is not the only source of challenge that can be added in, in this way here, that can skew how tasks and goals are prioritized and carried out or not.

Ultimately, the filtering and selecting of Point 2 requires dispassionate reasoning: reasoning that can both starkly illuminate and serve to evaluate the value of the assumptions and presumptions that founders can bring to the table. And as a positive measure, this winnowing and prioritization process more clearly helps to determine what would in fact be good for, and for-now best for the business as an enterprise. (As an aside, I add at this point in this narrative that this is where a founding team that is too caught up in their own agendas and their own understandings of them can find value in bringing in an outside consultant who can offer a more dispassionate outside perspective, and who will then leave when finished.)

I am going to conclude my discussion of Point 2, at least for purposes of this series, in the next installment to it where I will add consideration of benchmarks and more finalized goals to this narrative. My goal in that is to take this posting’s discussion of that topics point at least somewhat out of the abstract by addressing it as an explicit trackable path forward and not just as a more vaguely goals-oriented intention. Then, as promised above I will more explicitly turn to and address the above Point 3. And turning back to the more complete to-address list that those three points were excerpted from as initially offered in Part 11, I will then work my way through the rest of that more complete list too. And I will more explicitly tie this more business-wide narrative back to a marketing and communications context 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. You can find this and related postings at Social Networking and Business 2, and also see that directory’s Page 1. And I also include this posting and other startup-related continuations to it, in Startups and Early Stage Businesses – 2.

Building a startup for what you want it to become 36: moving past the initial startup phase 22

Posted in startups by Timothy Platt on February 8, 2019

This is my 36th installment to a series on building a business that can become an effective and even a leading participant in its industry and its business sector, and for its targeted marketplaces (see Startups and Early Stage Businesses and its Page 2 continuation, postings 186 and loosely following for Parts 1-35.)

I have been successively discussing a brief but important set of issues in this since Part 31 that deal with business intelligence, and particularly where that is originally sourced from individual people (e.g. individual customers) and from other businesses, and where that increasingly includes more and more types and quantities of sensitive and confidential information. And in the course of that I have at least selectively touched on the issues of how this information is gathered, organized, processed and used, and both in-house by an original aggregator business and as a marketable commodity that such a business would sell as a product or service, and primarily on a business-to-business basis.

And that has led me to the final complex of issues that I would address here in the context of this series, at least as far as this understanding of raw and processed information is concerned, in a business intelligence context. One of the key tools used in safeguarding the security and confidentiality of initial sources of all of this data and certainly as raw data, is to anonymize it, stripping it of personally identifiable markers that could be used to link it to any particular individual source. And according to that approach, most such data would be pooled demographically for use, with a much smaller amount of this excerpted out as anonymously sourced case in point examples.

That noted as background for what is to follow here, my last to-address point from the above-cited topics list that I have been working my way through here, is:

• “And that will mean addressing the sometimes mirage of data anonymization, where the more comprehensive the range and scale of such data collected, and the more effectively it is organized for practical use, the more likely it becomes that it can be linked to individual sources that it ultimately came from, from the patterns that arise within it.”

The bigger that big data becomes and the more effectively it can be and is organized into actionable knowledge, the more likely it becomes that any effort to so mask and anonymize its individual sources becomes problematical at best. And that failure of effectiveness in what has become a basic standard for managing personal privacy and for limiting individual source exposure – and for limiting the liability that can result from loss of effectiveness there, is going to become compelling overtly obvious in the coming years.

Simple data anonymization as achieved by algorithmically stripping out overtly personally identifying and similar problematical data fields, while preserving and aggregating the rest for use, can no longer be presumed to work as hoped for and with that leading to a loss of privacy and a loss of positive control over most any attempted anonymizing process currently in use and with an increased risk created from that for the businesses that would develop and market, or acquire and use such information resources.

• And this calls for new understandings of data anonymization that would actively promote the development of demographic and other data resources that can remain effectively anonymized,
• And new information management processes and technologies that would work more effectively in a big data context and regardless of how that scales up.

This is important. Traditionally, hacking with its overt theft and use of data from information storage systems, has been considered the one real threat to the anonymity of ultimate data sources. Loss of control of accumulated and maintained stores of credit card account and related personally identifiable account holder information immediately comes to mind for many in that context, and reasonably so.

But anonymization per se as it is currently more routinely carried out, in the risk management-mandated processing of increasingly comprehensive flows and accumulations of individually sourced data, is at least as big a source of threat now.

Let me take that out of the abstract with a simplistic but nevertheless realistic example. Consider a demographics level database resource that includes in it individually anonymized records, that is offered on a business-to-business basis to other enterprises. And in this example, those records include those individuals’ zip codes and the honorific that they use: Mr., Mrs., Ms., Miss and Dr. If a zip code included there covers a large population as would for example apply in most any large densely populated urban setting, this would likely afford significant anonymity for any individual whose data is included there. But consider a small town and its unique identifier zip code, with one physician living and working there. And she is the only one there who actually uses the title Doctor, and its Dr. abbreviation. In that case, any records associated with “Dr.” as an “anonymous” designator could readily and quickly be linked to that one individual.

Big data, by its very nature, allows for and supports finer detail mapping and understanding of whatever overall data universe and its source that is under consideration. That finer granularity in effect turns even the largest and most densely populated community into readily distinguished and identified small towns and villages, to keep with the terminology of my above-offered example. And that, increasingly puts all of us that much closer to being in the more readily identified position of that small town doctor, and regardless of the fact that our individual names and home addresses, etc are redacted from it as directly offered.

• The bigger and more comprehensive the big data in question and the more carefully and thoroughly it is organized and analyzed, with the accumulation of processed knowledge that comes from that, the smaller the small towns of this become. And in this regard, I offer reference here to a series that I wrote to this blog a few years ago: Big Data (as can be found at Ubiquitous Computing and Communications – everywhere all the time as postings 177 and following for its Parts 1-7. And I make particular note here to one particular installment in that: Big Data 1: the emergence of the demographic of one. I primarily focused there on the more positive side of this, and turn here to address the negative potential in ever-growing big data too. Both sides to that are very real and both will become increasing so in the coming years.

To round out this posting and its line of discussion, at least for here and now, I conclude it by offering three news and analysis links from the open online literature:

Once Again With Feeling: ‘Anonymized’ Data Isn’t Really Anonymous: a tech podcast reference.
Your Anonymous Data isn’t as Nameless as Companies Would Have You Believe, Researchers Say: from the news and current affairs division of the Global Television Network in Canada.
• And Anonymous Browsing Data Isn’t As Anonymous As You Think: from Forbes Magazine, Feb 17, 2017.

Big data and its impact have become essential parts in our day-to-day lives and certainly as they have come to be shaped by our online experience, but also in our more directly real world experiences too. I write here in this series of businesses and their acquisition and use of market-sourced and I add marketable data. But I write just as specifically and directly here, about all of us as individual consumers and citizens too, as the ultimate sources of so much of that data.

Anonymized data has become a basic tool for both safeguarding our individual privacy and confidentiality in all of that, while supporting our having progressively more personalized experiences with the businesses and other organizations around us that also enter into and shape our overall communities. I am going to continue this discussion in a next series installment where I will at least offer some thoughts on how to move beyond this current and growing impasse where this tool has so significantly begun to fail us. Then after addressing that, as at least an initial first step response, I will reconsider the impact that all of this has on:

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

And I will also circle back in this overall discussion to consider opt-in and opt-out options and systems, and the stealthy collection of more and more data and from more and more sources where neither of those choice possibilities are meaningfully possible.

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

Planning for and building the right business model 101 – 41: goals and benchmarks and effective development and communication of them 21

Posted in startups, strategy and planning by Timothy Platt on January 24, 2019

This is my 41st 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 1-40.) I also include this series in my Startups and Early Stage Businesses directory and its Page 2 continuation.

I have been discussing three specific possible early stage growth scenarios that a new business’ founders might pursue for their venture (see Part 33):

1. A new venture that has at least preliminarily proven itself as viable and as a source of profitability can go public and with all of the organizational change and all of the transparency and reporting requirements that this entails as they begin offering stock shares. (See Part 33 and Part 34.)
2. A new venture can transition from pursuing what at least begins as if following an organic growth and development model (as would most likely at least initially be followed in exit strategy 1, above too) but with a goal of switching to one in which they seek out and acquire larger individually sourced outside capital investment resources, and particularly from venture capitalists. (See Part 35.)
3. And a new venture, and certainly one that is built around a growth-oriented business model, might build its first bricks and mortar site, in effect as a prototype effort that it would refine with a goal of replication through, for example a franchise system. (See Part 36 through Part 39.)

And I continued that overall narrative in Part 40 with a set of more general comments, and by raising some generally framed questions of a type that at least categorically would apply to most any next-step business development scenario that might be considered, and certainly early on. Then I concluded that posting with a set of three issues that would have to be addressed and for most any business that would operate in a business-to-consumer context: issues that would enter into their core decision making and its execution as effort is made to build that business to be as competitively effective as possible:

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

There are two basic approaches that I could pursue here as I seek to parse out and analytically identify and discuss the issues just raised in that list. I could discuss all three of those points in order as a group, and successively so for each of the three development scenarios listed towards the top of this posting and under consideration here. That would mean my addressing each of those business development scenarios in turn and with them serving as my primary focus of attention here. Or I could more fully discuss each of these issue points, one at a time as they would arise and play out for each of the scenarios under consideration, and with them serving as my primary focus of attention. I have decided to follow the second of those organizing approaches here, and proceed as follows starting with Point A and products and services offered, or still just under consideration for that to round out this topics point.

Point A: At least in principle, the founders of a business can and do decide on their own what products and/or services they might pursue offering through their own business venture. But in reality, they always face at least some shaping influences there, and even in a simplest case organic growth oriented business model where all funding available or sought out, comes from the cash flow and positive revenue generation of the business itself, as supplemented by funding that they themselves would bring to the table, and with their not having to answer to others as equity holders in this. In that case, outside influences would still arise and have to be accommodated, as coming from their intended markets and from their understanding as to what would effectively, and profitably sell there. And more such pressures would come from their likely and current competition, as they seek to gain and retain a maximum possible market share in the face of their offerings. Both the above-stated Scenarios 1 and 2 are based on the founders and owners of a venture securing outside funding, with any additional shaping constraints added that those funding sources would attach to the support that they offer. And while Scenario 3 as stated towards the top of this posting might be centered around organic growth and arise free of the types of outside equity ownership voices that Scenarios 1 and 2 would invoke, building with a goal of expandability into what might become an open-ended range of local markets and market types can easily place at least some product and service restraints on what they could effectively offer too, and certainly if they seek to benefit from economies of scale across their entire growing business empire and if they seek to remain consistent enough across their overall system for how they develop and support unified consistent branding. Pressures towards uniformity as arising from these considerations can limit this type of business in its ability to meet more locally community-based product and service needs and certainly where such diversity would impact on any business-wide brand-specific product designs supported, as an important case in point example here.

Focusing on Scenario 1 for the moment in this Point A context: when a new or still young business seeks out initial public offering (IPO) funding, it has to be able to argue a case for its receiving such support from both:

• Prospective shareholders who would actually invest in it,
• And from stock market analysts who those prospective investors would turn to as a key part of their due diligence when deciding where to invest and with what levels of their available funds.

This means the founders and owners of such a business, would have to be able to effectively argue a case that they seek to bring profitably attractive products and/or services to market, and in ways that would at least maintain value in this enterprise as benchmarked against the price these investors would pay per share and put into it, and with at least some additional value added for them, as coming from profits generated too. And they would have to be able to market and present themselves for being likely to accomplish this, in ways and according to timeframes that those market analysts would see as meeting their reporting needs.

Dividends: those additional profits as doled out to investors on a per-share basis, might not be as important for successfully arguing that a business is a good investment if that business and its leadership can present themselves as a growth company with long-term investment value, rather than a more strictly income generating one that would primarily offer short-term and ongoing cash returns on investment. But that calls for a demonstrable focus on innovation and on this business setting out to grow and evolve and effectively so. And even then, most shareholders still expect at least modest regularly offered dividends too. And those dividends and a business’ capability to reliably and consistently offer them, becomes even more important when and as a business is positioned more as a profit-oriented venture.

• Either way, all of the stock market analysis that shareholders and prospective shareholders would turn to when making their investment decisions, would be developed on a short timeframe, and generally largely on the basis of just the most recent business quarter or half year. That would put pressures on this business to develop and offer their products and any New that they could bring to them, as quickly and efficiently as possible.

Now let’s consider this same issue point from the perspective of the above Scenario 2, and with the guidance and the pressures exerted by venture capitalists added into a basic organic growth, default business model here. Some venture capitalists selectively make at least some longer term investments and commitments to the ventures that they buy equity in through their funding. But all venture capitalists, as such, invest in what their due diligence effort would show to be likely up and coming business successes, and with a goal of gaining profits and large ones from those investments that do develop that way to cover their losses from those that do not – while still leaving a significant profit margin for the investor.

Most of the time that means their seeking out quick returns on the investments that they enter into, so they can keep their investment funds moving and working for them and not tied up in any single client business. This puts pressures on the businesses that they do chose to invest in, to develop and capture as large and profitable a market share, and as quickly as possible and with corners cut if necessary in longer-term business development preparation where that might compete for funds with this market-facing effort. All of this, of necessity, has an impact on what is going to be brought to market and how and how quickly it would be updated and tuned for greater market impact.

Scenario 3 obviously has its expected forms of impact in this issue too. I am going to continue this narrative in a next series installment where I will complete my discussion for here, of this Point A issue. Then I am going to move on from there to address the above Points B and C next, also doing so in terms of the three scenarios under direct consideration here, with commentary added as needed regarding a fourth: organic growth scenario too, as called for. And then, and with this overall narrative thread in place, I am going to discuss a core point of consideration that readily emerges from it:

• How a new, young business begins, determines if and how it can accommodate and support flexible adaptability and resiliency as it moves forward,
• With the details of that determined and shaped by what type of basic organizing path that venture seeks to follow in its business plan and its execution (where I have been discussing a set of such determinative options here in these postings.)
• Think of this as a matter of looking for longer-term consequences as they would more, or less likely arise depending on how some key early decisions are made.

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.

Leveraging social media in gorilla and viral marketing as great business equalizers: a reconsideration of business disintermediation and from multiple perspectives 13

Posted in social networking and business, startups, strategy and planning by Timothy Platt on January 9, 2019

This is my 13th 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, postings 278 and loosely following for Parts 1-12.)

I began discussing a set of issues that would arise for well established businesses that have become set in their ways, in the context of this type of series, in Part 2. And I then switched directions in Part 11 to at least begin to consider a newly forming startup example in contrast to that, which I have cartoonishly summarized for its basic form as:

• A new, young, small startup that seeks to leverage its liquidity and other assets available as creatively and effectively as possible, and from its day one when it is just starting to develop the basic template that it would scale up and grow from.

And as an orienting starting point for what is to follow, in fleshing out and examining that type of case study example, I offered a to-address topics list that can be considered startup-oriented in its basic tenor and orientation, which I repeat here for its first three entries for purposes of this posting:

1. What types of change are being considered in building this new business, and with what priorities? In this context the issues of baseline, and of what would be changed from become crucially important. I assume here that change in this context means at least pressure to change on the part of business founders, from the assumptions and presumptions and business practices of their past experience: positive and negative that they might individually bring with them to this new venture, and their thoughts as to how a business should be organized and run as shaped by all of their prior workplace experience. So I will consider change as arises in how the business is planned and run, at least as much as I do when considering what would be developed there and brought to market as product or service. I will mostly just cite and discuss the later for its contextual significance in all of this.
2. Focusing on the business planning and development side to that, and more specifically on high priority, first business development and operations steps that would be arrived at and agreed to for carrying out (in light of the above bullet point considerations here), and setting aside more optional potential goals and benchmarks that would simply be nice to be able to carry through upon too,
3. Where exactly do those must-do tasks fit into the business and how can they best be planned out for cost-effective implementation (in the here and now) and for scalability (thinking forward)? Functionally that set of goals and their realization, of necessity ranges out beyond the boundaries of a Marketing or a Marketing and Communications context, applying across the business organization as a whole. But given the basic thrust of this specific series, I will begin to more fully discuss communications per se, and Marketing, or Marketing and Communications in this bullet point’s context. And I will comparatively discuss communications as a process, and as a functional area in a business there.

Note: I also outlined some of the essentially axiomatic assumptions in Part 11, that I would bring to my analyses and discussions of all of the topics points and their issues as listed there: the above-repeated first three included. And I recommend that you review them as discussed there. That noted, I began addressing the above restated Point 1 in Part 12, focusing there on a need for effective negotiations as involved stakeholders air and argue the case for their respective understandings of the goals and priorities faced, for developing and building this new business venture. And my goal here is to finish addressing that Point 1 and its issues, at least for purposes of this series, and to at least begin addressing Points 2 and 3 as well.

To be more specific here, I approached Point 1 and its issues in Part 12 of this series, by primarily focusing on the fundamental need for informed and mutually agreed to consensus, among key stakeholders:

• As to what type of business a startup is to grow into, as it realizes its business model,
• And what its goals and priorities should be, at least in a more immediate here-and-now context, and for next steps that would be taken moving forward beyond that.
• And to add one more detail to that summary: the earlier that any really significant points of disagreement can be identified and worked through among the key stakeholders of a business, at least to the level of their arriving at basic workable functional agreement, the better. Problems of that sort that are set aside for later consideration, only fester and grow.

I turn here to consider a What and How counterpart to that Why. And I begin addressing this half of my response to Point 1 by dividing this approach to its issues, into two areas of consideration:

• What specific tasks would be agreed to and for type and priority? And what specific tasks act more as focus points of disagreement?
• And Who arrives at the determination in any finalized sense of how these discussion point decisions would be resolved and by whom, at least for immediate and next step purposes as the business proceeds forward? I simply note here in generic, generally stated response to that question, that there are circumstances where stakeholder priority in arriving at and phrasing such resolutions would best be based on equity ownership in this venture and on position and title held, and some would best be based on specific relevant expertise and certainly for more technical issues and their tasks. The details as to how this would and should play out, would of necessity be business, and business-model specific and depend on the nature of, and the decision making influence of the emerging corporate culture coming into place.
• Who would make these relevant binding decisions as far as the second of those points is concerned, when determining how specific business decisions would be parsed out according to those decision maker options? And how would their decisions and conclusions, or their recommendations if so identified, be supported and moved forward on?

The first of those points is explicitly What oriented. And together, the second and third points of that set, at least begin addressing the How (and the by whom) side of the issues raised in Point 1, above. The rest of any such answer to the question as raised there, becomes a matter of personality, and of leadership and followership, as can be found or encouraged among the key decision making stakeholders of a business. And the patterns that arise from this process, lay the foundations of the overall corporate culture to come at this new business as it becomes established and begins to grow beyond the initial founding team.

And with that, I offer a word of explicit warning:

• I have seen startups and early stage businesses succeed and even to spectacular degrees. And I have seen them flounder and fail too. And one of the core, fundamental differences between these two outcomes-defined groups can be found in how well the decision makers there, and those who can influence and shape the consequences of their decisions, can come to agreement and achieve alignment in what they do there, or fail to do so.

Abraham Lincoln’s so relevant words come to mind for me as I ponder what for me, is a repeatedly validated point of observation that they compel: “a house divided cannot stand.” Lincoln had a very different and I add more societally impactful context in mind when offering this advice, but it applies in the smaller scale of individual businesses too.

This, as experience shows, can be an even more important metric of overall likelihood of success for a business, long term, than the challenge of arriving at an effective way to profitably monetize what a business would offer to market as its primary product or service. Google, to cite a well known example there, and its founders, knew that they were building a business that would offer a best of breed online search engine as the core element of its overall market facing offerings. And they were effectively aligned in this and in how to proceed in developing their business for this. But they did not in fact work out the details as to precisely how they could best create a profitable service that would enrich the business (and themselves) from this, and even until after they initially went IPO for this venture.

They knew basically what they wanted to do and they were able to effectively capture the imagination of the public that they were trying to reach with this business, and with their online search tools. And they were able to come to sufficient agreement on all of the key business development issues that they faced as they organized and launched and began to grow this new business. And they captured a very significant market share for what they would do. Then, they figured out in more fully working details, precisely how they would earn money from all of this productive effort. Were some of those steps carried out in a very contrarian order, and one that other new businesses would best avoid trying to emulate? Yes. But they did get the most important of their basic business development decisions and steps worked out early, and even from the beginning – and at least effectively enough to make it possible to move forward in achieving all of the rest. They were at least working together in all of this, and certainly for all of the really important issues and decisions that they faced.

And with that offered here, I will turn next to more directly and fully consider Points 2 and 3 from the above list, which I just touched upon in the above narrative. Then after completing my discussions of those topic points and their issues, I will proceed through the rest of the Part 11 to-address list points, as offered in detail there. And I will connect this overall narrative as I have been developing it here, to a more strictly Marketing and Communications context, noting in advance of that, that

• While it is not possible to effectively discuss that area of business activity, or its more social media-based forms without considering the business and its markets that would enter into that,
• It is still necessary to tie any such contextual narrative back to Marketing and Communications again 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. You can find this and related postings at Social Networking and Business 2, and also see that directory’s Page 1. And I also include this posting and other startup-related continuations to it, in Startups and Early Stage Businesses – 2.

Building a startup for what you want it to become 35: moving past the initial startup phase 21

Posted in startups by Timothy Platt on December 1, 2018

This is my 35th installment to a series on building a business that can become an effective and even a leading participant in its industry and its business sector, and for its targeted marketplaces (see Startups and Early Stage Businesses and its Page 2 continuation, postings 186 and loosely following for Parts 1-34.)

I have been working my way through a briefly stated to-address list of topics points in recent installments to this series, that I repeat here as I continue to discuss them (with parenthetical notes added as to where I have discussed what of this so far):

1. An at least brief discussion of businesses that gather in, aggregate and organize information for other businesses, as their marketable product and in accordance with the business models of those client enterprises. (See Part 31, Part 32 and Part 33.)
2. The questions of where all of this business intelligence comes from, and how it would be error corrected, deduplicated, and kept up to date, as well as free from what should be avoidable risk from holding and using it. (I began addressing this point in Part 34.)
3. And that will mean addressing the sometimes mirage of data anonymization, where the more comprehensive the range and scale of such data collected, and the more effectively it is organized for practical use, the more likely it becomes that it can be linked to individual sources that it ultimately came from, from the patterns that arise within it.

My goal for this posting is to complete my discussion of the above Point 2 and its issues, at least for purposes of this series and this phase of it. And I begin doing so by making note of a two part news and information series that is currently running on Public Broadcasting Service (PBS) television stations in the United States as I write this, as part of their Frontline series: The Facebook Dilemma. I wrote in Part 35 of this series that we have only seen the tip of an iceberg so far, that threatens Facebook to its core for how it gathers and organizes, and then sells user information, while proclaiming that it safeguards it. This televised news piece with its on-air insider interviews, and its in-depth research and reporting put a live-action face to that news story and its emerging consequences. More will come out about that unfolding news story too; it is not going to end any time soon and either for Facebook or the businesses and other organizations that have been purchasing use of its members’ personal data, or for those member users.

I begin this posting on that note to illustrate real-time as of this writing, how pressingly important the issues of Point 2 are, and for all concerned:

• Businesses that gather and sell access to user or customer data,
• Businesses that acquire access to it for their own use,
• And the people who this data is gathered in from who might in effect be marketed and sold through this business practice, and to their direct detriment,
• And even to the detriment of society as a whole, too.

I would argue that the issues that are included in the above Points 1-3 are going to prove to be among the most important and impactful issues that we will face societally, and certainly through the coming decades. They in fact already are, and certainly insofar as misuse of massive volumes of individually sourced data has already been weaponized to skew and even throw national elections, and as a tool for advancing ethnic conflict and international aggression.

• When big data reaches a threshold scale of comprehensive reach and of fineness of detail and granularity, its growing utility and range of utility and its cost-effectiveness in providing such value create undeniable pressures to expand it out even more.
• When big date gets big enough, its own inner dynamics and its value to those who would develop and use it, compel its becoming even bigger, and as a seemingly open-ended positive feedback response.

I have at least briefly touched on the issues of where this data would come from, and the issues of its use and misuse in this discussion up to here. And that brings me to the issues of data quality and the challenges of keeping it up to date and relevant (e.g. valuable) and at least potentially to both the organization that holds it and to the people and organizations that it seeks to describe.

• The bigger a big data store is, the more of a challenge it becomes to keep the data in it cleansed of error and up to date. And this challenge expands in both the context of increasing numbers of individually sourced records, and in the context of increasingly complex records with more and more data and types of data gathered and held in them, regarding any given individual source so captured.
• But sources of increase in the potential value inherent in bigger and bigger big data: more data source records describing more individual data sources and more comprehensive records that would be tapped into there, at least in principle should drive holders of such data resources to expend the financial and other resources needed to both expand and maintain these systems more carefully, and to keep them up to date and accurate for that.

I cited utility as flowing to the original source of this data accumulation just now, and after discussing big data in a Facebook context see a need to justify that presumption. Utility and positive value can run just one way, only accruing to data collectors and users. But in stable systems, value and utility can flow in many and even in all possible directions.

Consider, by way of example, a massive emergency services database that first responders would turn to when responding to emergency calls such as building fires or health crises. And more specifically, consider fire department personnel who need to be able to access up to date building plans for structures that they might have to enter, and both to save lives and to limit damage. In principle, every building in their catchment area: their geographic area of responsibility has been inspected by fire safety and other inspectors, including building inspectors, if and when any structural changes are made there. And they would make note of and report in any changes made and certainly insofar as they would affect building accessibility. And in principle all of these presumably up to date building blueprints can be, and for more up to date systems are, available through wireless online access by first responders when needed. Now what happens when first responder firemen enter a burning building, such as an apartment building to find that entrance and egress routes that show on their screens as available have been closed off through illegal and unreported construction, partitioning larger apartments into larger numbers of smaller ones? This endangers the lives of those firemen and the lives of anyone who might be trapped in these buildings.

• The same challenges would arise if this was in fact legally reported construction but the access route and related changes that were carried out, were not added into this system yet.
• My point in this example is that negative impact from faulty and out of date information in big data stores, can and does flow in all possible directions – including ones that might not always be appreciated in advance. And accurate and up to date data can create positive value that flows in all directions too.

I am going to turn to Point 3 of the above topics list in my next series installment, and the issues and challenges of how anonymous seemingly anonymized data really is, and certainly in an ever-expanding big data context where new raw data and new knowledge derived from it, is added into its already stored raw data records and files and into the processed knowledge base already developed from all of this, and used real-time to analyze and understand both old data already held, and new data as it comes in too. Then after at least preliminarily addressing that complex of issues, I will circle back to reconsider the impact that all of this has on:

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

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

Planning for and building the right business model 101 – 40: goals and benchmarks and effective development and communication of them 20

Posted in startups, strategy and planning by Timothy Platt on November 13, 2018

This is my 40th 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 1-39.) I also include this series in my Startups and Early Stage Businesses directory and its Page 2 continuation.

I have been discussing three specific possible scenarios that a new business’ founders might pursue for their venture since Part 33:

1. A new venture that has at least preliminarily proven itself as viable and as a source of profitability can go public and with all of the organizational change and all of the transparency and reporting requirements that this entails as they begin offering stock shares. (See Part 33 and Part 34.)
2. A new venture can transition from pursuing what at least begins as if pursuing an organic growth and development model (as would most likely at least initially be followed in exit strategy 1, above too) but with a goal of switching to one in which they seek out and acquire larger individually sourced outside capital investment resources, and particularly from venture capitalists. (See Part 35.)
3. A new venture, and certainly one that is built around a growth-oriented business model, might build its first bricks and mortar site, in effect as a prototype effort that it would refine with a goal of replication through, for example a franchise system. And there, licensing fees and ongoing franchise-sourced income going back to the parent company, would provide funds that could be used for further capital development, among other things, to keep a fiscal systems focus here on what I include in this list. (See Part 36, Part 37, Part 38 and Part 39.)

And one of my goals there has been to use these more specific scenarios as a springboard for discussing the more general issues of early business transition-stage decisions, and particularly for when young enterprises and their founders and owners enter their first real growth phase. My goal here is to go beyond the specifics of the three scenarios that I have been discussing to consider transition point decisions in general, as they arise when a business first exits its early development, startup stages.

I begin doing so by noting that everything that I will address here involves making decisions that involve tradeoffs, and ones that have to be addressed in the face of incomplete and even potentially faulty information. The three scenarios that I have been addressing here and others that I could have explored here instead, all involve making choices that can become binding and essentially irrevocable as decisions, at least if costs for moving forward with the business are to be kept within acceptable bounds. And they are all approached in the presence of business systems friction and uncertainty.

What do the above three scenario options hold in common and both with each other and with other similar-stage scenarios that I could have delved into here? Let’s at least begin to address that abstractly framed question with a briefly stated initial cut issues list of more specific questions and accompanying comments, beginning with:

• What are the respective costs and benefits that pursuing each of whatever set of alternative scenarios under consideration, might bring with them?

That question is still so generally stated so as to offer little if any real value as a planning tool. The value that can be found in it arises as it is restated in more specific and focused form and with a more precise awareness of the actionable issues in place, that are glossed over in it. To start out with, costs and benefits may begin with and end with cash flow and reserves considerations. But most entrepreneurs who seek to build their own businesses do not simply want to find a means for themselves of bringing in some measure of income but without their necessarily having a voice in how. “Middle ground” issues of decision making authority and voice enter into this too. And timeframe tradeoffs are crucially important here too, and they do not explicitly enter into the above question at all, at least as initially stated.

• Who gets to decide what, and with what outside constraints in place that would shape and even limit the decision making powers and authority of the owners and founders who are in fact taking any real overall risk from entering into this new venture?
• And turning back to consider financial costs and benefits, all three of the above scenarios and others that I could have raised instead involve costs and risks, and benefits and profitability. But they do not all play out in simple lock step and along a same simple timeline. Scenarios 1 and 2, above, both involve what can be large early-arriving cash infusions: with the risks and debt obligations that they carry with them. And to be realistic, looking beyond the strictly cash-flow of that, both also place constraints on what decisions can be made by the business’ founding owners too. This cash influx might arrive early and even essentially all at once, or at least according to a settled and agreed to funding payment schedule and with agreed to benchmarks for that (for Scenario 2.) But the debts due, and both in specific terms for Scenario 2 and in principle if investors were to lose faith in the business and sell and sell, are longer-term. What is the best way to plan out and build and run this new venture so as to minimize costs and risks, and maximize at least the likelihood of benefits and profits, when the first more general question that I am building this line of discussion from is expanded out to explicitly address these issues?

And this brings me very specifically to the issues of uncertainty and of having to build and decide and continue building in the presence of incomplete and at times faulty information.

• How can the founders of this enterprise build for resiliency and flexibility and adaptability, so as to be able to weather challenges and capture unexpected opportunity too?

I briefly noted in Part 39, a set of related issues that would logically enter into this narrative at this point and then set it aside, at least there. I will turn to consider those issues in light of this posting, in the next installment to this series:

• Fine tuning products and/or services offered,
• Business operations and how they are prioritized and carried out, and
• Branding and how it is both centrally defined and locally expressed.

I will at least begin discussing these three specific topic points there, and will continue from that to discuss how a new, young business begins to build for flexible adaptability. 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.

Leveraging social media in gorilla and viral marketing as great business equalizers: a reconsideration of business disintermediation and from multiple perspectives 12

Posted in social networking and business, startups, strategy and planning by Timothy Platt on October 29, 2018

This is my 12th 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, postings 278 and loosely following for Parts 1-11.)

I have been developing this series, since Part 2 in terms of case study examples, primarily focusing up to here on what might be a less intuitive example of how disintermediation can play out in an enterprise, and certainly when a Marketing and Communications context is considered for it.

The basic example that I refer to there, and that I have primarily focused upon in this series, at least up through Part 10 is, as briefly summarized in single bullet point format:

• A larger, established business that has become at least somewhat complacent and somewhat sclerotic in the process, and with holdover systems and organizational process flows that might not reflect current actual needs or opportunities faced.

I would argue that this is a less intuitive example than my other, startup-oriented example, because businesses that are so solidly and I have to add inflexibly established so as to fit the pattern of that bullet point, are more likely to resist change than they are to embrace it – and particularly where that would challenge the power and authority of entrenched managers and their more individual fiefdoms, as any organizational simplification and of any type would compel.

I raised my other working example in Part 2 when first posing the above one. But I did not begin to actively consider and discuss it until Part 11, when I offered an at least somewhat detailed to-address list of topics points that I will successively delve into for it: starting here and in following series installments. That case study example as also outlined in single bullet point, simplified format is:

• A new, young, small startup that seeks to leverage its liquidity and other assets available as creatively and effectively as possible, and from its day one when it is just starting to develop the basic template that it would scale up and grow from.

My goal for this posting is to at least begin a discussion of the issues raised by the first point of my Part 11 to-address list, and I will do that here. But before I begin that, I want to at least briefly explain a point of at least seemingly presumptive conclusion that I offered in that posting. I stated without reference or explanation that it is intuitively more obvious and certainly in broad brush stroke outline that the simplifying disintermediation approaches that I address in this series, and options such as gorilla and viral marketing that they would enable, would more readily apply in a startup setting. An at least brief analysis of that statement and of how I arrived at it, would serve as an effective starting point for considering the more specific-detail oriented topics points listed in Part 11, that I offered there as a means of fleshing out its above-stated single bullet point description.

Startup founding entrepreneurs are often all but automatically presumed to be people who are driven, and for whatever combination of reasons, to break out on their own and build their own businesses – where they would make all of the key decisions and where they would live with the consequences of them, while garnering an owner’s and founder’s share of any cash profits and any other sources of value created from that effort. And startups begin small and simple, and both for resources available and for organizational structure. Critical resources definitely include both available cash liquidity and available personnel in this context, and both for headcount and for range of expertise available where personnel limitations are considered. And simple and direct organizational structure of necessity also includes simpler and more direct communications too, and certainly when the headcount of a new enterprise is still small enough so that everyone involved could meet together around a member’s dining room table.

Startup founders are also often, if not usually viewed as being more break-away mavericks by nature than they are complacent followers of standard processes and understandings in place. Couple that presumption with limited resources and of all types, and disintermediated communications patterns, and I have to add disintermediated lines of authority and oversight in this descriptive mix too, and a basic stereotypical pattern begins to more fully emerge.

Disintermediated lines of authority and oversight, to pick up on one point of detail in that last sentence, can even become largely inevitable in this type of context. Note that I did not include a word such as “egalitarian” there and I did not write of participants holding anything like equal say or equal authority there either. I have worked with startup founders who take a very top-down approach to working with others and to leadership at their new ventures, and even when their overall teams are still very small and all included in them are essentially certain to become C level officers there if this new business really takes off. And this can hold with equal force when all of the core founding team members that a founding owner brings in, are people who they personally know and trust too. But setting that set of considerations aside, and certainly as a source of within-the-business issues, startups and even top-down organized and run ones, can be seen as naturals for seeking out resource use-magnifying options such as gorilla and viral marketing to get the word out and even actively help drive early business success.

I offer the above as an intentionally simplistic cartoon depiction of what in reality tends to more complex and nuanced realities. And one of my goals in addressing the list of topics points offered in Part 11 will be to identify and consider areas where real world startups cannot be contained within the constraints of that type of depiction.

The above noted, I turn to consider the first topics point of my Part 11 startups example topics list, which I repeat here for smoother continuity of narrative:

• What types of change are being considered in building this new business, and with what priorities? In this context, the issues of baseline and of what would be changed from, become crucially important. I assume here that change in this context means at least pressure to change on the part of business founders, from the assumptions and presumptions: positive and negative that they might individually bring with them to this new venture, as to how a business should be organized and run. So I will consider change as arises here in how the business is planned and run, at least as much as I do in what would be developed there and brought to market. I will in fact mostly just cite and discuss the later for its contextual significance in all of this.

I begin addressing that complex of issues by explicitly advising that anyone reading this, stop and read Part 11 first. This may the first time that I have recommended that type of preparation in this blog, and certainly so strongly and directly as I do here. But I do so here, and even given my intention to write postings that can stand alone for offering value to a reader, because of one other narrative element that I wrote into that installment: a set of what turned into seven basic assumptions bullet points that I offered there, that can be viewed as laying out what I axiomatically presume when writing and offering this case study example. If you read through and at least understand them as I offer them, you will at least understand what I more fully mean here and how I arrived at that. And that review of perspective taken will probably help you bring any points of disagreement with me that you arrive at, into clearer, sharper focus too.

One of the keys to understanding the first to-address topics point of this now-unfolding startup-oriented case study example, can be summarized in three clarifying bullet points:

• I wrote in that topics point of individually arrived at perception of change and its necessity. Whatever is arrived at there, arises as what amounts to a conclusive summary that might still remain at least somewhat fluid, as the people involved think through what they would preserve and continue from their professional past, and what they would change from that if given a deciding voice. Prioritization becomes crucially important there, where an individual might see it as worthwhile for example, to put up with a more minor irritant of a problem from how things have been done in their prior work experience, if that is a necessary cost to reaching consensus on what for them is a more important change-driven issue.
• And I have just oversimplified the overall point that I would raise here with that bullet pointed statement. It is complete and fully considered individuals who have lives outside of work, as well as professional lives, who make these nuanced decisions. The decisions and the choices that arise from them do not and cannot take place in a work life only vacuum. Outside, non-work issues and considerations can and do shape workplace decisions too, and certainly where desirability and importance evaluations enter this narrative. This can also mean making workplace decisions and pushing for workplace approaches and resolutions that meet larger family needs too. Such needs in fact can become the most powerful drivers in this type of decision making process, and certainly when workplace decisions can impact on all else in a founding team member’s life.
• And finally: I have written the above two bullet points in terms of the individual and their decision making processes, without and with consideration of larger family contexts. And I have already at least posited the prospect that individuals involved in this, would think and act in negotiating terms when developing and presenting their case and arguing their preferences and priorities for how things are to be done in this new venture. Team participation always means negotiating. I made passing note of top-down managing, authoritarian leadership a bit earlier in this posting as a possible working example approach. Even then and even when a single owner business leader would make any final binding decision, that does not or at least should not mean that they cannot and will not listen to others and gather in feedback and insight that might inform or even shape their own decision making processes. This last point goes directly to the seven assumptions points that I offered in Part 11, as to what I mean and assume in the above-repeated startup case study. I assume here that everyone involved is actively and effectively communicating and that they are all at least listened to. Founding team members who are not listened to and consistently so, simply leave and fairly quickly as a general rule, so that can be a fair and valid assumption.

Bottom line, the first topics point of this to-address list, hinges upon participants arriving at their own particular balance points, juggling what they do and do not want and prefer according to all of the possible prioritization combinations that can arise for them. And it is all about who can most convincingly negotiate their perspectives on what, as an overall working consensus is developed and arrived at for the founding group and for the newly forming business as a whole.

I am going to continue this discussion of this first to-address point in a next series installment. And then I will proceed from there by addressing the rest of the topics points of the Part 11 list in what follows it. 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 2, and also see that directory’s Page 1. And I also include this posting and other startup-related continuations to it, in Startups and Early Stage Businesses – 2.

Building a startup for what you want it to become 34: moving past the initial startup phase 20

Posted in startups by Timothy Platt on September 17, 2018

This is my 34th installment to a series on building a business that can become an effective and even a leading participant in its industry and its business sector, and for its targeted marketplaces (see Startups and Early Stage Businesses and its Page 2 continuation, postings 186 and loosely following for Parts 1-33.)

I have been discussing some of the core issues that arise when considering where business intelligence comes from in this series, since Part 31. And I have focused in this, primarily on third party raw data and processed business intelligence providers. I initially offered a brief to-address list of topics points that I would frame this line of discussion around, and certainly for purposes of this series, that I repeat here as I continue working my way through its issues:

1. An at least brief discussion of businesses that gather in, aggregate and organize information for other businesses, as their marketable product and in accordance with the business models of those client enterprises. (I began addressing this point in Part 31, Part 32 and Part 33.)
2. The questions of where all of this business intelligence comes from, and how it would be error corrected, deduplicated, and kept up to date, as well as free from what should be avoidable risk from holding and using it.
3. And that will mean addressing the sometimes mirage of data anonymization, where the more comprehensive the range and scale of such data collected, and the more effectively it is organized for practical use, the more likely it becomes that it can be linked to individual sources that it ultimately came from, from the patterns that arise within it.

My goal for this series installment is to complete my discussion of Point 1 of the above list, and to at least begin to address Point 2 as well while doing so. To be more specific, and certainly with regard to how I will continue addressing Point 1 here, I will:

• At least briefly discuss Facebook’s involvement with Cambridge Analytica, and the Facebook–Cambridge Analytica data scandal.
• I will cite at least a brief and select set of in the news links related to how Facebook sells access to user data in general too, and as a matter of explicit intent on their part.
• Then I will turn to consider the third business that I have promised to discuss in this Point 1 context: Amazon and how it leverages the data that it collects through its web site as a major source of incoming revenue.

I begin all of this with the still as of this writing, raw wound that we have all come to know as the Facebook–Cambridge Analytica data scandal. First some recent background context to put that into perspective: Facebook has been facing a tremendous amount of scandal and censure for its long-standing failure to in any way limit the flood of fake news and disinformation, and of cyber-weaponized troll behavior on its site. The company has made something of an effort to rein this problem in: recently by blocking and even banning disinformation sources such as InfoWars: one of the largest and most influential sources of alt-right conspiracy creating and sustaining stories, and alt-right spun genuinely fake news that has been available online. And they have finally started to take down content from white supremacist and other overtly bigoted sources too. But at the same time, their founder and CEO, and leader: Mark Zuckerberg, has repeatedly put his foot in his mouth from how he has explained both the delays in his business making these necessary moves, and in explaining what they are doing to address those issues and why. And this has included his offering self-damaging testimony before publically open US Congressional hearings when testifying under oath, as well as in news-oriented public statements. All of this has perhaps served to push the older news story of Cambridge Analytica and its Facebook activities aside and out of public awareness. But in a real sense it was that story, and certainly when it became exposed in the news, that started all of the rest that has followed, as that scandal helped to bring all of the rest of this into raw, open public awareness.

Cambridge Analytica was a data mining and brokerage business: a third party gatherer, organizer and provider for fee, of business and related intelligence as product. And it turned out that its primary, best paying clients were political campaigns and their leading operatives, and other agencies that have sought to sway elections through use of their often illegally obtained data. And it now appears that Donald Trump’s 2016 presidential campaign and agencies that sought to influence that election, were among their best, most lucrative customers in particular. Facebook became involved in this business when they allowed a researcher to collect personal data through their site from some 87 million of their service’s users without their knowing what they were providing, which he then sold to Cambridge Analytica, which they then sold to the Trump election campaign and others. Ted Cruz also purchased access to this largely illegally obtained and sold data and used it in his 2016 election campaign, and it was used to help sway the results of the Brexit referendum vote in the United Kingdom too. And it was also used in 2018 by Mexico’s dominant Institutional Revolutionary Party to help them sway their general election of that year when they found themselves facing real competition. But that is only part of this story

• Cambridge Analytica gathered all of this Facebook user data by offering a “game app” called “This Is Your Digital Life”, that they could use to vacuum up user information through, including personally identifiable, sensitive information as those users “played.”
• Alexander Nix, the CEO of that company publically bragged that his company provided surreptitiously gained personal information about millions of people to influence the outcomes of 44 political races in the United States alone, and just in 2014. And that was just a starting point for what would follow.

I am not entirely sure what of this is worse: that Facebook stood by while all of this data was being gathered after giving the provider of this app permission to place it on user pages all over their web site, or that their information management security system was (and still is) so limited and flawed that they were literally unable to see what was being done with this app as the torrent of raw personal data that it was gathering, was collected and then put into active use – and from their own website. Why …, How is it that no red flags were raised out of all of this? Ensuing Facebook scandals that have largely pushed this story into the background, have recurringly illustrated the undeniable fact that Facebook was not in fact doing any meaningful due diligence or information security management at all, on what was being posted or done on and through their web site. And that included their not even being aware of the existence of tens of millions of fake, robo-accounts that were used to post well-orchestrated disinformation (much coming from Russian sources) to help sway (throw) to the 2016 US presidential election and install Donald Trump in office, as well as influencing the outcome of numerous US congressional races that year.

I offered above, to share some links to news stories related to how Facebook in effect sells its user members as commodities to businesses and other organizations. Here are four recent news pieces of this sort that at least begin to map out what is involved here, with the fourth and most recent of them having just gone live today as I write this:

Facebook’s Data Crisis Deepens as Questions Mount (as came out on March 20, 2018),
Facebook: Your Personal Info for Sale (as came out on March 21, 2018),
Let’s Talk About Mark Zuckerberg’s Claim that Facebook ‘Doesn’t Sell Data’ (as came out on April 11, 2018), and
‘Weaponized Ad Technology’: Facebook’s Moneymaker Gets a Critical Eye (as first came out on August 16, 2018).

News stories of this type have continued to appear and both in print and through television and other electronic forums for many months now and at a steady rate, and will likely continue to do so too for quite a while to come too.

I would not even try to estimate the odds of this outcome from all of that coming true, but ultimately this unfolding public relations disaster for Facebook, might very well force Mark Zuckerberg to step down from his position as CEO there. Cambridge Analytica has fallen and so have its founders and executives. Facebook and its leadership will pay a price that has not yet fully come into focus yet, but that will come due too. (Yes, I remember that Zuckerberg founded Facebook, and that he holds vast numbers of its voting stock shares. And I remember that this company is still the largest and most powerfully positioned business in the social media sector. But when repeated publically visible failures of decision and action, and of judgment keep bringing a business into question, that eventually has to have an impact upon it and its leadership, and even for one of the largest corporations.)

And with that all noted, I turn back to considering a business that has actively sought to avoid problems and scandal in how it gathers, stores and uses, and shares data that ultimately has come from its user customers: Amazon. I began this line of discussion by citing and at least briefly discussing one responsible company: Google. Then I turned to consider a second company that is arguably out of control and rudderless for these issues and challenges: Facebook. And I complete the circle, at least for here by turning to consider a more responsible company again.

Amazon is primarily an online retail business, and an online storefront but it also generates income from a wider range of services that includes targeted ad placement and work with partner businesses that sell through its systems, tapping into the strength of its brand name and its product inventory and its purchasing user data: its vast data accumulations on what millions of individuals have ordered and purchased through its web site, that they can use to predict what they might chose to buy there next. Those third party partner businesses pay to sell their products and services online through the Amazon platform, and pay to have their ads positioned on key word defined and selected search results pages that Amazon visitors call up when shopping there.

Like Google, this primarily means offering access to anonymized and demographic level data, or rather access to sales value scoring results derived from that data, and the further sales value potential that can be developed from that. But in anticipation of further discussion to come, this is also one of the places were Point 3 of my above-repeated to-address list enters this narrative, and the problem of how individually anonymous, anonymized data really is and can be, in a big data context. So firewalling from visibility to those third party providers, anything like the raw data that would go into determining which individual customers get to see which third party business provider ads, is an important part of their business model there. That is a very important point of difference that separates how Amazon and I add Google handle and seek to develop profitable value from the consumer information that they have come to hold, from what Facebook has been doing with their site user, member data. And for Amazon, to focus on that business example again, that primarily if not exclusively means partner businesses just purchasing opportunity to link their sales efforts to Amazon customer product searches as a marketable business-to-business product, and as anonymized purchasing request data at that – at least until a customer agrees to actually make such a purchase from them.

All of this raises two crucially important questions that holds import and significance for both the businesses that provide third party sourced business intelligence, and any businesses that buy this data and processed knowledge as marketable product:

• What data can safely and effectively be offered and used, and by whom and for what purposes?
• And who in this system of information development and exchange holds what levels and types of responsibility if and when information security and confidentiality problems arise?

I am going to offer at least a broadly stated response to those questions when addressing Points 2 and 3 of my above-stated to-address points that I began this posting with, and that I repeat here:

2. The questions of where all of this business intelligence comes from, and how it would be error corrected, deduplicated, and kept up to date, as well as free from what should be avoidable risk from holding and using it.
3. And that will mean addressing the sometimes mirage of data anonymization, where the more comprehensive the range and scale of such data collected, and the more effectively it is organized for practical use, the more likely it becomes that it can be linked to individual sources that it ultimately came from, from the patterns that arise within it.

As a key part of that I will flip around the line of discussion that I have been developing here, to discuss third party data sourcing from the perspective of businesses that would buy access to it, and how that would fit into their own more internally developed business intelligence data flows. And I will discuss this from the perspective of their due diligence and risk management needs and responsibilities too.

And with all of this offered here in this posting, I briefly turn back to reconsider my first third party provider example again: Google, to at least briefly highlight how difficult it can be for a major corporation to remain clean on all of the issues I have been addressing here and on information systems management risk in general. Google’s formally noted and publically known motto is “Don’t Be Evil.” But where and how should they draw what lines that they should not cross there, and how can they best abide by the terms and limitations of such decisions? I offer three news story links from the past few months that suggest that line approaching and crossing have arisen as real problems for Google at times, and even with dissent and criticism of the company coming from within their own ranks:

‘The Business of War’: Google Employees Protest Work for the Pentagon,
Google Will Not Renew Pentagon Contract That Upset Employees, and
Google Employees Protest Secret Work on Censored Search Engine for China.

Google quite arguably, addresses line crossing problems and challenges very differently than Facebook has. But the types of challenges faced by any business that acquires and uses business intelligence, or that offers data processing tools or resources for that matter, keep disruptively emerging de novo, and morphing into new forms once they have arisen. So avoiding falling into pits from all of this has to be an ongoing strategic and operational goal.

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

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