Platt Perspective on Business and Technology

Quantifying business intelligence valuation in terms of systems-indeterminacy 3: setting upper and lower limits as a due diligence exercise 2

Posted in macroeconomics by Timothy Platt on December 18, 2013

This is my third 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 Part 1: setting out the basic parameters and Part 2: setting upper and lower limits as a due diligence exercise 1.)

I stated at the end of Part 2 that I would “continue this discussion in a next series installment where I will look at circumstances and mechanisms where a more standardized valuation can in effect be carved out from the overall problem of determining fair market prices for business intelligence as a marketable product.” And I at least begin to address that set of issues here, by noting that not all business intelligence is created equal. In this, I note two criteria according to which meaningful distinction can be measured: one based on benefits and the other on risks.

• As a benefits-oriented metric, how uniquely available and valuable is this information to its marketplace and to its potential buyers?
• As a risk-oriented metric, what levels of vulnerability would holding this information entail where loss of control or exclusivity of it would create direct costs or losses, or their risk-realization equivalents?

Overall aggregate valuation would be determined from the combination of these factors. And a quality of uniqueness in what would be offered in a marketplace would tend to both increase the median expected price point for it that the market would accept, and expand out the range of possible and even likely prices that might statistically be arrived at, as fair market value.

But my focus here is on what might be considered more standard business intelligence offerings, rather than the one-off and novel as for example represented by closely held trade secret information. And as a working example, I would cite and discuss the specific example here of a standard package of personal and personally identifiable information about a specific individual.

• From a retail perspective and from a leads provider perspective this can mean businesses buying and selling vetted customer leads in an open marketplace, that could lead to new sales by those retailers.
• From a cybercriminal-supportive, dark internet marketplace perspective, this can mean essentially that same personal information profile being bought and sold for use as identity theft leads and for similar and related purposes.

And I begin discussing these two seller/buyer scenarios by repeating a point from Part 2 of this series:

• Two buyers might in fact open that same box but find what amounts to different information in it. This is because information carries meaning and value that is set in large part by the context that it is considered in.

An automobile dealership might spend $10 or more for sales leads with associated contact and related information. And dealerships often allow for a significant level of leads purchased as a basic operating expense. When people buy profiles through dark net sites and for identity theft purposes they usually at least initially purchase contact information too, but an average lead of this type and in this context might go for less than one US dollar and often for much less, each. Different contexts and different intended uses mean that even when the same data is included in a sales offering, this ostensibly same profile package can be viewed and valued very differently. In the parlance of Part 2 and in its thought experiment terms, two different observers can open the same box but see different informational content in it. But in both cases their fair market value determinations can be both justifiable and highly replicable between different buyers or different sellers for them.

• When an auto dealership buys sales leads and certainly when they do their due diligence and selectively buy them from sources that offer a good rate of return on leads purchased, they can gain a significant profit from those leads that actually turn into completed sales – and a large enough profit from them to off-set losses from leads that do not work out, and even at a cost of $10 or more per lead bought.
• When a cybercriminal buys leads from a wholesaler source their success rate for turning this newly acquired contact information into profitable scams is much lower. When, for example, a scammer sends out generic emails notifying people who they have purchased contact information about, that their PayPal account needs to be updated or it will be closed down, terminating any transactions in progress, first of all a great many recipients of this message will not have a PayPal account. And of those recipients who do, only a few will actually click to the link provided in this email and enter their account login information. When someone does, the scammer’s profit from that lead can be large too, but they have to offset that against a much larger number of failed leads that they have also purchased too.
• Risk considerations at least potentially enter into this too. Auto dealerships gain very little from buying leads from a provider, and even what should be excellent leads if three other dealerships have already purchased them and contacted them with competing offers. In most cases those leads will have already expired for any value they might have held. So when I wrote above, of dealerships using a due diligence based selection process for selecting leads provider they would buy from, making sure that they would receive exclusive leads is a big part of that.
• Cybercriminals do not generally worry whether the leads they buy or sell might be used for identity theft or other problematical purposes but they do face and they do seek to address a very real concern: that their activities might be traceable through their leads marketplace transactions. So they face risk-oriented factors in determining what a valid price for this information would be too.
• These two marketplace, and buyer/seller perspectives are in most respects very different and the numbers for success and failure rates for leads actually purchased and used are very different too. So these two types of observers see this potentially-same type of information package and even the exact same profiles on the same individuals very differently. And they arrive at very different price point evaluations for it as a result as buyers and sellers come to agreement as to fair market values for their markets.
• And this is all with essentially standard format information content and without inclusion of novel information or information types. Leads prices in both of these examples are relatively stable and across most all sellers and for most all buyers in their respective markets, at least when same sized sales are made for numbers of profiles per transaction.

I am going to continue this discussion in a next series installment, there focusing more specifically on one-off and novel business intelligence offerings, and their valuation. Meanwhile, you can find this and related postings at Macroeconomics and Business.


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