Platt Perspective on Business and Technology

Quantifying business intelligence valuation in terms of systems-indeterminacy 10: information determinacy and indeterminacy and the prediction of value 2

Posted in macroeconomics by Timothy Platt on January 30, 2014

This is my tenth installment to a series in which I discuss and analyze the valuation of information in a business context and from a due diligence and risk remediation perspective, and in terms of what in a physical systems context would be called quantum indeterminacy (see Macroeconomics and Business, postings 137 and following for Parts 1-9.)

I began discussing predictive business intelligence in Part 9 from a simple perspective, without taking into consideration buyer and seller usability contexts. Instead, I focused there on the basic issues of access exclusivity, and information age and quality. My goal for this next series installment is to at least begin a discussion of context, and of context and usability based valuation. And I begin that by citing two very different types of business organization and two very different seeming needs and usability contexts. The first example is based on a type of organization that is not even usually thought of in business terms: a national military force. The second example that I will at least briefly explore too, comes from the pharmaceutical industry and more specifically the highly competitive manufacture of over the counter, non-prescription drugs.

Military planning, at least in principle, addresses the same set of fundamental issues that any business faces through analysis of its strengths and weaknesses, and its possible and emerging opportunities and threats (SWOT analyses). This effort is directed towards meeting overall governmentally defined and led strategic goals and initiatives. And I focus in this example on understanding potential threats posed by potential adversaries where one measure of that is in knowing their current actively available troop strength (e.g. how many soldiers their army could effectively field at any one time, and from where, and with what general areas of specialization.)

Many military forces offer their troops access to stores where they can purchase personal items such as magazines, cigarettes, deodorant, toothpaste and the like on-base. This, among other things means their troops to not have to leave base to obtain toiletries and other personal items that they might need. Sales volumes as to the levels of business for these on-base stores are in most cases categorized as highly classified government owned and controlled information, and for a very good reason. If you know precisely how much of each of a range of personal grooming and related products are being sold and the rate at which they are sold and at which bases, you can very accurately predict the numbers of troops at those bases. You can then match this to information that you have as to the basic mission and specialization of those bases which in most cases correlates with what units are based there, and you can determine, for example, the numbers of combat infantry that this army could currently field, or the number of special operations teams or field artillery units they have available. Depending on what you know about the functional focus of these facilities, you can map out both specialty distributions and also identify changes in levels of different types of resources available with troop build-ups or drop-downs or force reallocations.

I have touched on this basic example in other contexts and repeat and expand upon it as I do here, as an example of how predictive intelligence can be developed that can be directly applied, and both for understanding a potential competitor now, and for making more refined and effective strategic contingency planning decisions for moving forward. And in keeping with the basic focus of this series, I discuss this in terms of information determinacy and value.

If you are a commander or senior strategic planner for a military force, you have to assume that any competitor that you would seek to understand and plan for is led by people who also understand the potential value of this type of information. And you have to assume as a basic due diligence consideration that sales volume information for these on-base stores will get out, and if not from the stores themselves then from any private sector or other non-governmental manufacturers or distributors of these products that enter into their supply chains. And in fact strategically, you might even want certain of this information to get out and into the hands of the strategists and planners responsible for potentially competing military forces and their political leaders – if you are “rebalancing the numbers” so as to indicate force levels and distributions that you would like a potential adversary to see and assume correct.

Now look at this from the information buyer’s perspective. When you acquire this type of intelligence, you are buying the type of black box-wrapped information product that I first began writing about in Part 2. Before you complete your purchase you do not know precisely what you will be getting, and certainly for accuracy – unless that is you can also acquire as bundled with that sales volume information, supporting information that would validate its level of accuracy, and as a result indicate where it might have been strategically altered which in and of itself might be useful information.

I am going to continue this discussion in a next series installment where I will delve into my second, pharmaceutical industry example as noted above. And I will then more fully consider information determinacy and indeterminacy per se. Meanwhile, you can find this and related postings at Macroeconomics and Business.

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