When we measure, “data” result. Converting these data into more valuable “Information” is a rich process. Novel outcomes occur because of emergence.

Here are my qualifications to speak to this topic. I’ve spent three decades in a variety of Pharma asset management functions, including a decade as a calibration/instrumentation technician, and another as a calibration Subject Matter Expert (SME). In the middle of all that, I spent 100 weeks working full time while acquiring an MBA.

The first cut at explaining my title

Let me try visualization to convey a little bit about the ground that I want to cover. First, the “data”. Let’s picture in our minds a clipboard that contains some results from measurements that we have received from a sensor. So far, all we have is an accumulation of integers with appropriate units. The size of this dataset doesn’t matter. It’s just data. Now think of the process that we must put this clipboard?datathrough in order to create?Information?that we believe is critical to achieving any goal that we may have set for ourselves. This applies equally to an individual or a giant corporation. The presence of any goal is what dictates and drives this transformation. We may achieve our goal, or we may not, but the presence of any goal drives the transformation of data to Information.?

We may come to see that through this process, the resulting?Information?acquires qualities that were not visible anywhere on the clipboard. This demonstrates a phenomenon known as “emergence”. Emergence is a feature of any evolutionary process. The idea of the clipboard is no longer adequate visually or in any other way to support the emerging complexity that we are beginning to see. Another way to say the same thing is that the clipboard is “flat”. I suggest that we ditch the clipboard image and use the idea of an essay as a better vehicle for visualizing this next evolutionary stage but with the supporting?data?still readily available to all readers. We write this essay about how and why we want to transform some data to serve our goal. That transformation produces?Information. This essay is a platform that helps make the emergent process transparent to anyone interested in the outcome or the success of the larger goal that made us measure in the first place.

Some emergent properties are obvious, others are surprising and novel

So far, I have only used slightly different words to repeat a common viewpoint that lots of people have described before me. So far, there is nothing new here. Next let’s look at an outcome of this emergent transformational process which very few people have discussed yet.

Businesses invest money in order to transform data into information because this supports their “business model”. The traditional view is that they invest in tangible equipment of various kinds to produce a product or service. Business Finance people label these things “business assets”. These assets are tangible enough that the IRS recognizes their existence for tax purposes and there is no more concrete kind of legitimacy in any business environment.

But there is a novel process occurring right here under our noses. That is because in addition to creating the products which the company keeps on their books as assets until their sale, by converting measurement data, the firm simultaneously creates another completely separate asset-the information itself! The cost to produce this asset is the cost of transforming the measurement data into Information. Information is a virtual asset instead of a tangible asset, and this single fact more than any other has kept it hidden from the Finance and Accounting people. So far, few organizations are comfortable with anything “virtual”, but that is changing right in front of our eyes.

Test Case?

To support my idea, I first need to prove that Information can exist as a legitimate business asset. Here’s how I am going to do that: Suppose that we consider a firm that has the good fortune to need only two identical measurement sensors in order to succeed in their business sector. It turns out that unbeknownst to the company, or their industry, they really only need one sensor, but they go ahead and purchase these two identical sensors. One of the sensors actually produces crucial measurement data for the firm, the other happens to add nothing to the value of the company’s product. The fact that the firm’s Production/Operations function recognizes this central fact about this sensor means that to them, it’s sensor data is crucial business Information. They recognize this fact not just with words or policies but in a much more concrete fashion. They use this Information every day to produce the product. If you don’t yet see these important elements in this network, imagine firing all the internal assets who know why that particular sensor is critical to the company and watch what happens.

O.K., I have demonstrated that the sensor output is crucial but how can we agree that it could ever be an Asset in a Finance or Accounting sense? Currently, does the way that Finance people view these two sensors reflect this same key fact? The answer is “No”. Today, Finance cannot reflect or track the Information value at all. To the Finance people, the two sensors are identical because they cost exactly the same as investments. As assets, they are equal. That is the only way for a Finance person to see the relative values of the sensors.?

The Finance group is not alone in this blindness. The Operations/Production people have never given the Finance function any method to assess the value of the Information produced by either sensor, even though, in one case, that value is huge. In fact, in our case, sales resulting from this Information happen to pay everyone’s salary!

Why do I call this Information an asset?

I call this Information a business asset because that is what it acts like:

Let me get into more detail to convince you that virtual Information Assets share many aspects with other more traditional and tangible iron, steel, and plastic assets.

·??????Business Information has intrinsic value to the firms survival just like any other asset that appear on their balance sheets. This intrinsic value may be damaged, reduced or ruined by management policies but there is no way to exceed this intrinsic value. Information shares this attribute with any and all other assets in which a business may invest.?

·??????Business information has a “shelf life” like any other tangible asset. Proper maintenance optimizes this life expectancy, but new technological advances may also interrupt and accelerate Information’s ageing process at any time. All efficient investment in Information maintenance requires process expertise as a part of a continuing business investment, just like all your other assets.?

·??????We can see an array of fixed and variable costs associated with the cost of maintaining Information assets just like any other assets in which a business may invest. We can also expect to see these costs rise over the life of the asset regardless of whether they are tangible or intangible. This is another attribute that should be quite familiar to any businesspeople who employ Reliability experts.?

o??It’s also perfectly reasonable that businesses should be able to amortize Information maintenance costs over a fixed period because no Information creation process is eternal. Let me give a perfect example of the rising marginal costs of Information maintenance, over time. When Data engineers repeatedly note the huge (up to 80% of all project costs) expense and drudgery of data “cleaning”, they are reflecting the fact that the older the data is that we have selected for some new analysis, the more it is going to cost to get it back into shape so that it can actually be useful. Otherwise, the dirty data is just going to crash our model.

Just because I can express this idea in a single sentence doesn’t mean that I think that realizing it in a business is an easy process at all. It can be difficult or impossible for any particular firm. It isn’t primarily a technical challenge, it’s often a cultural or strategic alignment challenge. These also happen to often be the toughest business problems! There are two pitfalls that currently block further acceptance of this concept of Information as a business asset, although, over time, I expect that these barriers must fall.??

Pitfall #1: We cannot always tell the difference between “data” and “information”

The clearest symptom of our current primitive state of understanding is the way that we frequently conflate the terms “data” and “information”, as if they had identical meanings. These two terms ARE NOT synonyms, NOR are they interchangeable. Information is data that we have transformed.

Data automatically result from any and all measurement processes. They fit quite nicely on our clipboard. Data exist regardless of whether or not we pay any attention to them. Data exist whether or not we record their existence. The critical question is whether and how we can gain any usefulness from these data. Converting data into Information assets requires experience, sharp business focus and process knowledge. When we choose to invest in the cost of this conversion from Data to Information, we incur a cost and make an investment. I am saying that this conversion process creates a new actual business asset, and one that is parallel to but separate from our original production process value stream. “Data” are potentially useful results that always come from measurements. They become “Information Assets” when we convert them to actual, deliberate business usefulness.?

Let me be clear.?I don’t fault the Finance Department because their skill set doesn’t include process measurement technology. I fault the management team because they have not aligned their departments, nor are they fully performing their duties to any stockholders, or their Board.?They are supposed to manage a network of functions and see that these network elements mesh properly. In this case, their process produces critical Information vital to their continued success, yet they remain blind to this fact. Consequently, they do nothing to safeguard the stability and organization-wide awareness of the existence and value of this Information,?even though that is their job.?The next time you read or hear anything about managing or changing the “culture” of a business, please remember that the concept of “culture” is no more virtual and quite a bit vaguer than the assets that I am saying are already sitting right in front of Management’s eyes.

I have already touched on the traditional view that business assets are concrete pieces of equipment likes tools, pumps and parts. They can only be physical, tangible and “real”. Here I can appeal to my Reliability colleagues. If, as we see many times, business managers sometimes decide to not maintain the maximum value of their physical hardware assets, how likely are these same managers to recognize the similarities between their physical hardware assets and their Information Assets???My Reliability colleagues have complained about this weakness for decades. Here, I am just reframing the dilemma that Reliability people are stuck on. I am describing the data and Information environment in a way that may also happen to tease out a reason that Reliability initiatives fail before they even start.

Pitfall #2 Lack of business alignment

In our analogy above, our Production/Operation people knew something important about the measurement output from one sensor, but the Finance people were procedurally blind to that important fact. They could easily see the sensors cost; they were blind to any possible value to the firm from its output. It’s not that they couldn’t grasp this fact intellectually. It’s just that they have no way to fold it into their function. They had no procedural way to align with their colleagues. Even today I can locate companies with a partial understanding of the technical features of this fundamental discussion. The measure of the spread of this understanding, not it’s “culture”, is the measure of the firms strategic alignment. That is because measurement itself is fundamental to fulfilling any goal including any business goal. Like making a profit.

How and why will this change?

What trends will propel the acceptance of the fact that business Information is a business asset even in Accounting or Finance terms? I know that every added dollar of business investment in ML (Machine Learning) and AI (Artificial Intelligence) methods will bring this idea closer to sneaking under the Finance tent flap. That is simply because as these investment dollars become larger and larger in proportion to the total cost of doing business, Accounting and Finance people are going to demand better tools for managing these dollars efficiently on a balance sheet. That is why these functions exist in the first place, and how they discharge their responsibility to their management team and the Board of Directors.

Some Data/Information people are making big strides in preparing the ground for this idea. One person who has influenced me while bringing me a lot of clarity to this topic is Nick Barrowman. I can very enthusiastically recommend his short essays?“Correlation, Causation, and Confusion”?[i], or?“Why Data Is Never Raw”?[ii].??He is a huge breath of fresh air in the current environment in which there is so much hype about Big Data and AI topics. I have transposed his views into a generic business management environment. That is my decision alone and my responsibility. However, Nicks position as a Senior Statistician with the Children’s Hospital of Eastern Ontario has given him a great deal of insight into the way that data conversion can knit widely spaced functions within a larger organization. This process of knitting functions together leads to what business leaders call “alignment”. He speaks clearly to a wide audience.

Stephen says, “check him out”!

I have a request for those of you have stayed with me so far. If you think that what I have said so far is useful, how would we fill in the blanks concerning Information evaluation? If we are onto a good idea here, what steps come next in its implementation???I discussed a sensor producing data that transforms into critical Information paired with an identical unit whose output is trivial in the eyes of the customers. What path could Measurement people supply to help realize a metric that corresponds to these two value streams? Because of my own prejudices, I am convinced that a metric would help us must include the effects of the measurement uncertainty attached to these critical data. By itself, uncertainty is necessary but not sufficient because both sensors have uncertainty but only one matters to our goal of tying Information to dollars in sales. After we build in measurement uncertainty, with what do we surround it?

[i]??thenewatlantis.com #43, essay from summer/fall 2014.

[ii]??thenewatlantis.com #56, essay from summer/fall 2018.?