DecLink is a contraction of the words: decision and linkage. Our objective gained through DecLink is improving the connection between available market prices and a company’s decision about prices.

The techniques we use became practical for small companies because of the internet and the pc. The internet provides access to more kinds of data and the means of getting the data into a computer without weeks of data-crunching. The low cost computational power of the PC made it possible to examine the data; advanced mathematics is now available through pc software. The result is usable computer models.

Two other models control computer models (I mean models as in frames: the way we look at things). One of the models is accounting. It some what measures what actually happened in the microscopic scope of a single company. The second is an economic model, which estimates what could have happened on a grander scale.

Where folks have difficulty is that they think of the accounting models as objective, that is, reliable and irrefutable. In reality, it is an approximation that leading investors regard as crude — even for a single company. The accounting model’s true appeal is its familiarity.

Milton Friedman objected to facts without theory. Accounting fails the test because it has no theory. Accounting is a legal convention, not an economic construct.

The second model is economic. In many small businesses, especially those that are led by entrepreneurs, this model estimates much higher returns. The economic model is speculative in the sense that it estimates ROA base on what could, but has not yet, happened.

What we construct in DecLink is a set of facts based on theory. And we start with theory (actually, so does everyone, but I won’t go there).

When we propose DecLink we make a few assumptions for later testing. These assumptions explain the difference between returns achieved and returns possible. The difference is losses. The accounting model does not and cannot calculate these losses, so according to accounting model the losses do not occur. This is why pricing losses are viewed with skepticism; accounting cannot report them.

The assumptions are:

§ Entrepreneurial firms have higher profits than non-entrepreneurial firms.

§ Inside data is not captured to measure customer subjective value.

§ Measurement of internal cost displaces subjective value.

§ Large losses in ROA come from small losses in prices, costs, or investments.

§ Companies do what they have always done and that will be reflected in their data.

They are suppositions that do not pinpoint whether lower ROA is caused by pricing losses. But we start by eliminating things that are not a cause. We use a large array of formulas to compare the firm’s data to outside data.

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DecLink has its origins is the rough-and-tumble of commodity markets with big low-margin farms. The idea was that there had to be a better way to price. It was here that we applied our skills in the pc modeling and math software–with strong results.

Finding DecLink was something of a happy accident. We were building a model to measure risk and rewards in price, volume, and credit supply volatility because almost all the hundreds of crises and opportunities on which we have advised were long-term in origin. Timing was extremely critical in reading opportunities. And timing was a powerful tool in resolving firm-threatening crises. Our objective was to be able to get a read of economic conditions for improved performance, reduced risk, and persuading doubters of our client’s capacity. In that process, lo and behold, we found a way to read commodity markets.

The application to companies in un-traded markets was immediately obvious to us. We did not see any necessary limitations because of the difference between traded and un-traded. In traded markets prices could be “read” by what worked for the producer’s target ROA. The difference between traded and un-traded is accepting an offered price versus offering an accepted price. The psychological load on a company’s decision makers is about the same.

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I have a deep distrust of convention. It is fair to say business convention is okay to follow most of the time. But when it is not okay, it is really not okay. The results prove disastrous. But convention is so appealing because the proof is implied since others are doing the same thing.

An entrepreneur brings solutions that are somehow novel. Pricing is one way the application of convention causes common [lower] profits in spite of the uncommon solutions for the customer.

There are only two people who understand the entrepreneur’s idea: the entrepreneur himself/herself; the customer whose problem the entrepreneur solves. I say that because it points to two problems I almost always find with a firm’s data:

§ Under-utilized data including a failure to collect on the subjective aspects critical to implementing the entrepreneur’s idea.

§ Even though the entrepreneur’s idea was conceived before there was a company, and even though there are many who might be, but are not yet, customer, there is little space given to collection of date from outside the company.

It leaves the company and the entrepreneur vulnerable to convention.

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Conclusion:

Often enough the true entrepreneur does not need convincing, and therefore might not need DecLink. But the entrepreneur forgets that convincing his colleagues requires more than his or her conviction, charisma, enthusiasm, or passing rages. It requires the kind of proof conventional types need before they can act. DecLink provides that proof.

DecLink is a service of Praexis. The techniques used are widely available. The methodology we use is proprietary. In application, DecLink produces astounding improvements in profitability. However, in practice results for some companies are limited. This is because of a general distrust of economics, models, and mathematics. Some companies cannot get past it. In a few cases, results ended when companies believed they could copy the techniques and so save costs on the assumption that economic conditions and conditions within a company remain constant.

Commentaries point resistance to: people’s dislike of thinking; the expert’s presumption / resistance to calibration; a view that the subjective can’t be measured; distrust of accountability; ‘I already knew that’; data availability; character; threat to competence; implied criticism.