Making a Map of Risks

I’m currently exploring how “Wardley maps” can be applied in strategies for testing. Here is an example of how I used a map to understand and work with risks.

In my current projects the system under test is not software development, but rather a end-2-end transition of IT services. The technology is part reinstallation, part spin up of containers – in other words, some elements are more or less commoditized. Also some elements are more or less visible to the stakeholder. It seems like a good fit for a Wardley map….

How to use Wardley Mapping to understand how you deliver customer value

Read the intro by Stephan Willemse on Medium

First I need to tailor the horizontal axis a bit. I have read up on the articles by Simon Wardley and Ben Mosior with regards to the framing of “evolution”. For a quick intro read Erik Schön describes the four stages, like this:

• Genesis: the unique, the very rare, the uncertain, the constantly changing and the newly discovered. Our focus is on exploration. 
• Custom Built: representing the very uncommon and that which we are still learning about. It is individually made and tailored for a specific environment. It is bespoke. It frequently changes. It is an artisan skill. 
• Product (+ rental): the increasingly common, the manufactured through a repeatable process, the more defined, the better understood. Change becomes slower here. Whilst there exists differentiation particularly in the early stages there is increasing stability and sameness. 
• Commodity (+ utility): scale and volume operations of production, the highly standardized, the defined, the fixed, the undifferentiated, the fit for a specific known purpose and repetition, repetition and more repetition. 

There is also a relevant article, where Evolution is the level of ambiguity – which is just one of the relationships Wardley Mapping have with the Cynefin Framework.

The key legend to the horizontal axis is the relative position from unknown/uncharted to embedded/industrialized – to you or the organization being mapped. It’s possible to tailor the labels specifically to the components being mapped – like the legends of altitude lines, buildings and roads on a map. Here’s one for the specific risk context above:

Original	Concept	Hypothesis	Theory	Accepted
Risk legend	Uncharted	Known	Stable	Standard
Elaboration	We don’t know the risks yet	We see these risks.	Risks are stabile.	Risks are reduced to standard components

Experimental tailored legend

First I map the system landscape: relative to the business vertically and relative to Risk stage horizontally. It gives me this anonymized map:

It’s probably only half-way right, but with this I can consider:

• How far can I move the elements to the right?
• What inertia blocks movement?
• Which ones can I move the furthest?

With the map (position and movement) I can consider what happens when risks change and evolves – how does evolution affect the test strategy?

If we automate Configuration, the risk is significantly reduced.

Reinstallation can only get us to a certain point, due to:

don’t make any changes to our mother-ship