Asset Management Insights. Celso de Azevedo

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      It has never been so easy for an organization to achieve the alignment of its objectives and the monetization of its risk factor. The tools and skills required for these tasks are now universally available. The fantasy, deeply rooted within the industrial spheres and which depicts Asset Management as a field of experts estranged from economic realities, must necessarily be revoked. It is crucial that the agents of Asset Management succeed in sensitizing organizations to the added value that would come out of a proper management of their industrial assets, and to the necessity of implementing such a management.

      Today, we are capable of drawing out and quantifying the entire set of economic consequences resulting from a good or a bad CAPEX. Why should we not do so? We are also able, when choosing or designing an asset, to anticipate the technical and economic consequences in both qualitative and quantitative forms (through previsions tied with OPEX and risk). Once more, why should we not do so? By what logic can a design office manager consider that it would be wiser to refrain from implicating an Asset Manager? In this regard, the stellar rise of the Building Information Modelization (or BIM)—an approach very similar to Asset Management practices, and which has quickly been adopted in the sphere of construction—is exemplary. Industries cannot allow themselves to pass on such opportunities any longer; they must, consequently, equip themselves with means of value anticipation. The future will undoubtedly confirm my intuition that Asset Management will be the spirit (and BIM, the skeleton) of the infrastructures of tomorrow.

      Through these examples, we have attempted to show that organizations must become aware of the importance of a rational management of their assets from the earliest stages of their life cycles. We will now draft out a few of the methods, inherent to Asset Management, which allow industries to establish an optimization of the creation of value in the preoperational phase.

      At the core of this notion are the ideas of Asset Breakdown and Asset Register. The former can be defined as a tree-structured model, which presents the functional and material components of the asset that is to be acquired or produced; the latter is an accounting method, which consists of taking an exhaustive inventory of an organization’s assets fleet. Therefore, it is clear that a thorough practice of the Asset Breakdown allows for a better definition of the parameters and the contents of an organization’s Asset Register.

      Today, the Asset Register has become a sine qua non requirement for an operational asset system to be in compliance with the current standards; how practical, for contemporary industrials, that equipment is now systematically delivered with its Asset Register (which entails the complete listing of an organization’s assets categorized in at least three sub-classes: Asset Portfolios, Asset Systems, and Individual Assets). One should keep in mind that it has not always been so, much to the detriment of operators. Additionally, the massive democratization of ERPs—these tentacular informatic programs that link every organizational function—has also introduced new protocols of intra-tree structure relationships between assets, often comprised of nine levels (familial hierarchy between the assets of the Asset Register). In some alternative cases, ERP editors have imposed the use of the standardized protocol defined by the ISO 27000 (Security of Information Systems), which also presents the data imputable to the assets on different hierarchic levels. We should therefore rejoice over the growing influence of Asset Management inputs on the very structure of the industrial world, since in this case we’ve truly witnessed, throughout the last few years, a process of clarification and standardization of Asset Register practices, to the extent that they can now be regarded as truly reliable.

      This first phase of an asset’s life cycle, which covers its breakdown and its inclusion in the Asset Register, is much simpler nowadays than it had been in the past. Thus, considering how useful it can prove to be in the long run, it is now unjustifiable for an industrial manager to accept that this phase be neglected. Indeed, this process constitutes a stellar opportunity to effectively connect the preoperational phase with the remainder of the assets’ life cycles.

      If an industry succeeds in making it so that tomorrow its Asset Register is more proactive and more effective in taking into account the entirety of the assets’ life cycles, then this industry will be ripe for establishing what is known as a one-to-one correspondence between the Asset Register and the Asset Costing. This step is a crucial one in the path towards implementing a strategic alignment, which, in turn, may give way to techno-economic alignment.² Indeed, ISO 55001 requirements clearly demonstrate that operators have much to gain by having one-to-one correspondences between physical assets and their attached economic and accounting existences. In a truly functional and optimal alignment system, one must be able to identify physical codes that clearly correspond to the equivalent accounting codes. If this is the case, one can speak of a “paired” system.

      Over time, the engineers who make up design offices have been able to develop very exhaustive approaches to the preoperational phase, in order to address every important question raised throughout the design, specification, and procurement stages. More recently, in parallel to the development of reliability anticipation techniques and to the emergence of systems that allow for a modelized simulation of technical and operational performance, the engineering world has witnessed the rise of FEED (Front-End Engineering Design) approaches (see Figure 1.1).

      The FEED approach relies on a modelized simulation that primarily takes the form of Reliability Block Diagrams (RBD). Thus, Asset Management generates models that will allow engineers to visualize very early on in the process of architectural and technological arbitrages whether the assigned objectives, in terms of productivity and operational availability, are optimal. Nowadays, one can draft out scenarios of economic consequences—and not only of technical consequences—from these different simulations and project options. The qualitative input obtained from this type of approach is furthermore immense.

      Obviously, even if one relies on such modellings, a number of uncertainties remain; however, we now have the tools to scan these scenarios and assess their levels of sturdiness (in mathematical terms). Thus, one can evaluate these scenarios both qualitatively and quantitatively (through the analyses of “best,” “worst,” and “basic” cases) in order to determine in an informed manner the ideal course of action.

      These new methods endow us with a true choice panel in the sense that one can now elect to reproduce a design or to innovate completely, or even to freely reimagine the solutions that engineering may procure. One can only hope that these solutions will aim towards more value extraction in the long term rather than stopping at the oft-imaginary or self-imposed constraints that until now, impeded the horizons of potential scenarios.