Structure in Threes: Integrating Finance and Engineering approaches to Risk

As I continue researching risk elements for designing and enterprise, it is interesting to see how implementing risk management translates differently depending upon your discipline.  Finance focuses on of course financial risk; the various forms risk takes with regard to translating investments into returns in a monetary sense.  While engineering disciplines focus upon risk that effects the degree of achievement to performance goals of a product or lately service.  Both disciplines acknowledge the others concerns but often do not provide the linkage between these.  Finance will often categorize engineering risks into buckets called operational and strategic/business risks.  Engineering will lump the various economic risks into a single bucket called financial risk.

This is mirrored in how Business Continuity/Disaster Recovery(BC/DR) and Enterprise Risk Management (ERM) are implemented in most corporations. The BC/DR practices focus on the engineering risks of project, process and product, while the ERM practices direct attention to the financial aspects of the enterprise.  What seems to be missing is the linkage between the two.  The interrelationship between the two or cascading effects appear to be a neglected concern.  This maybe due to the nature of our western culture or increased specificity of roles within corporations even in white collar positions now.  The role of the generalist or systems thinker has been diminished or dismissed or possibly transformed.  More and more of my systems thinking peers have become entrepreneurs, possibly because they do not fit the new organizational models or appear to be in direct competition with mid-level management.  This is odd in that first line and mid-level management no longer have the time to consider various degrees of consequences of actions and decisions or alternatives, but is the stock and trade of systems thinkers.  This may be one of the root causes to several of the catastrophic failures of the economic system, geo-political relationships and technology achievement misses.

Today’s research continues down the path of system dynamics and identifying the linkages between financial and engineering risk management.  It may turn out that there is no true mathematical formula that links these and the best that can be achieved is to use Bayesian logic to create priorities for a balanced scorecard that reflect enterprise values and then monitor how these correlate to the ecosystem.  Which brings me back to using system dynamic models and validating these with actual performance in the real world.

In my opinion , despite the emergence of BI and Big Data, application at this level is still years away.  The majority of enterprises and thought leaders are still at a primitive level when thinking about exploiting such technology.  Think of how sophisticated and how long it took to apply various influence and behavior models in the marketing community.  Then consider the effects of having too much information, creating an information glut.  While computers are great at dealing with volumes of data, we humans are not.  We still need to deal with the limits of cognition.  Despite all the hype about multi-tasking, the facts are coming out, something is lost when you try to focus on too many tasks at once.  In fact you’re not actually focusing on them at once, you are switching attention between them rapidly (page swapping) and eventually you either reach a limit where you get nothing accomplished or a catastrophic event happens: Texting while driving during the Grand Prix is not a good idea.  What this suggest is that it will take a long time to really sort through BI and Big Data’s potential into something practical verses creating more noise in the enterprise system.


About briankseitz
I live in PacNW in a small town and work for Microsoft as a Enterprise strategy and architecture SME. I enjoy solving big complex problems, cooking and eating, woodworking and reading. I typically read between 4-8 business and technology books a month.

5 Responses to Structure in Threes: Integrating Finance and Engineering approaches to Risk

  1. Dean Keith says:

    Your observations about systems thinkers become disconnected from corporate leadership is important. Big Data Analysis is powerful, but one of the most important adages is “Correlation is not causation”. Misunderstanding this will lead to mistakes as large as those who misunderstand how to use simulations. Since simulations inherit the bias of the suppositions built into the simulation design, real world complexity cannot be completed tested, so the only thing that a simulation can truly prove, when it works, is that the simulation structure is consistent with expectations of the hypothetical outcome. Since a simulation’s accuracy or precision is therefore hypothetical, the user must take a contrary stance and attempt to disprove its accuracy or precision, thus establishing the limits of its predictive capability.

    • briankseitz says:

      I’ve used simulations for years with great success. However, in using such I am very much aware of the limitations of models and simulations (i.e., simplifications to understand specific -NOT ALL- attributes. Two years ago I was at Enterprise Architecture summit where I introduced “Precision, Accuracy, and Cost” as an open discussion topic. Didn’t get much traction with EAs which I though was interesting, because the same topic several weeks before at an Engineering Conference garnered a huge following and active discussion. I brought up the topic due to previous projects where I saw people believe models were the same as the real object. When I was in school, that principle that models and simulations are simplifications for understanding and lack complete fidelity was hammered home and when I worked at the Skunkworks and IBM it was again reinforced by more brilliant engineering talent that took me under their wings.

      • Dean Keith says:

        Your description of lumping all Financials together from the engineering perspective, and vice versa, reminds me of the type of black box that simulates the bridge between a mechanical system analysis and an electrical one. The electrical system sees all of the mechanical aspects in one lump while the mechanical system only sees the electrical in one lump. An iteration flows back and forth as the result from one analysis is fed into the other. When the mechanical and electrical is truly tied together, it opens more possibilities.

        I appreciate your fusion of financial and engineering principles and look forward to the results.

      • briankseitz says:

        Electro-mechanical analogy is right on the money. That was the pattern I saw that brought me to this insight 🙂

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