44 Not every problem needs a hammer, but nails need hitting

I sometimes get challenged with a comment like "Not every problem is a nail, so to fix them you need other tools (for business analysis, strategy, fixing issues or whatever) than your dynamic-models hammer."

The challenger generally means either that other modeling tools are better suited to many challenges, or that dynamic models need to be supported with statistical or other technical tools. All true! - but ...

There are universal principles at work. I have made the point before that there is deep, rigorous theory behind dynamic business models (see my post on why theory matters). Those principles explain the behaviour and performance of any business system or its parts - and many other types of system too.

Business leaders face a huge range of time-based challenges. Whether developing and delivering a complex strategy for a whole organisation, or just fixing some small, local issue in one function, or anything in between - we have a few basic needs. To understand why the system is doing what it is, anticipate how it might develop in future, test strategies and choices to improve that future, and manage that future as events unfold.

The range and variety of time-based challenges

Here are some of that wide range of challenges that share those needs - all elements of what it means to do "strategic management".

These are all time-based challenges, whether they are short-term or long-term, one-off episodes or continuous. And that is precisely what the system dynamics method deals with - indeed, it does not deal with any other kind of challenge. Here's some examples of what digital-twin business models can do ...

Tools for time-based modeling

But system dynamics is not the only time-based modeling tool, and has limitations. It deals with business factors in aggregate. It can deal with groups of customers or staff, but is not well suited to modeling individual entities or events. We need discrete-event or agent-based modeling for those purposes. (Those methods also conform with the solid underlying theory).

However, aggregate-level modeling has advantages - models are relatively compact, need less detailed data, and are fast to build.

The second challenge is also valid - that dynamic business models can be still more powerful if supported by statistical and other analytic tools. But that is an extra opportunity - we can solve very many challenges without having to resort to those add-ons.

So - there are millions of "nails" out there - go hit them with that hammer!

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One class of time-based challenges concerns performance-improvement programs - rolling out a substantial set of changes to lift some performance metric to a better level. Examples include improved data security, better health and safety, reducing energy use and carbon emissions ... See our short course here on how dynamic models can support the planning and implementation of performance-improvement programs.

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