Strategy Deployment and Impact Mapping

I’ve had a couple of conversations in recent weeks in which Impact Mapping came up in relation to Strategy Deployment so here’s a post on my thoughts about how the two fit together.

An Impact Map is a form of mind-map developed by Gojko Adzic, visualising the why, who, how and what of an initiative. More specifically, it shows the goals, actors involved in meeting the goals, desired impact on the actors (in order to meet the goals), and deliverables to make the impacts. The example below is from Gojko’s website.

As you can see, an Impact Map is very simple, reductionist visualisation, from Goals down to Deliverables, and while the mind map format doesn’t entirely constrain this, it tends to be what most examples I have seen look like. It does however work in such as way to start with the core problem (meeting the goal) and allow people to explore and experiment with how to solve that problem via deliverables. This is very much in line with how I define Strategy Deployment.

Lets see how that Impact Map might translate onto an X-Matrix.

The Goal is clearly an Aspiration, so any relevant measures would neatly fit into the X-Matrix’s bottom section. At the other end, the Deliverables are also clearly Tactics, and would neatly fit in the X-Matrix-s top section. I would also argue that the Impacts provide Evidence that we are meeting the Aspirations, and could fit into the X-Matrix’s right-hand section. What is not so clear is Strategy. I think the Actors could provide a hint, however, and I would suggest that an Impact Map is actually a good diagnosis instrument (as per Rumelt) with which to identify Strategy.

Taking the 4 levels on an Impact Map, and transposing them onto an X-Matrix, creates a view which can be slightly less reductionist (although not as simple), and opens up the possibility of seeing how all the different elements might be related to each other collectively. In the X-Matrix below I have added the nodes from the Impact Map above into the respective places, with direct correlations for the Impact Map relationships. This can be seen in the very ordered pattern of dots. New Tactics (Deliverables) and Evidence (Impacts), and possible more Aspirations (Goals), would of course also need to be added for the other Strategies (Actors).

Even though this is a very basic mapping, I hope its not too difficult to see the potential to start exploring what other correlations might exist for the identified Tactics. And what the underlying Strategies really are. I leave that as exercise for you to try – please leave a comment with what ideas you have!

This post is one of a series comparing Strategy Deployment and other approaches.

The Messy Coherence of X-Matrix Correlations

I promised to say more about correlations in my last post on how to TASTE Success with the X-Matrix .

One of the things I like about the X-Matrix is that it allows clarity of alignment, without relying on an overly analytical structure. Rather than consisting of simple hierarchical parent-child relationships, it allows more elaborate many-to-many relationships of varying types. This creates a messy coherence – everything fits together, but without too much neatness or precision.

This works through the shaded matrices in the corners of the X-Matrix – the ones that together form an X and give this A3 its name! Each cell in the matrices represents a correlation between two of the numbered elements. Its important to emphasise that we are representing correlation, and not causation. There may be a contribution of one to the other, but it is unlikely to be exclusive or immediate. Thus implementing Tactics collectively contribute towards applying Strategies and exhibiting Evidence. Similarly applying Strategies and exhibiting Evidence both collectively contribute towards meeting Aspirations. What we are looking for is a messy coherence across all the pieces.

There are a few approaches I have used to describe different types of correlation.

  • Directness – Can a direct correlation be explained, or is the correlation indirect via another factor (i.e. it is oblique). This tends to be easier to be objective about.
  • Strength – Is there a strong correlation between the elements, or is the correlation weak. This tends to be harder to describe because strong and weak are more subjective.
  • Likelihood – Is the correlation probable, possible or plausible. This adds a third option, and therefore another level of complexity, but the language can be useful.

Whatever the language, there is always the option of none. An X-Matrix where everything correlates with everything is usually too convenient and can be a sign of post-hoc justification.

Having decided on an approach, a symbol is used in each cell to visualise the nature of each correlation. I have tried letters and colours, and have recently settled on filled and empty circles, as in the example below. Filled circles represent direct or strong correlations, while empty circles represent indirect or weak correlations. (If using likelihood, a third variant would be needed, such as a circle with a dot in the middle).

Here we can see that there is a direct or strong correlation between “Increase Revenue +10%” (Aspiration 1) and “Global Domination” (Strategy 1). In other words this suggests that Strategy 1 contributes directly or strongly to Aspiration 1. As do all the Strategies, which indicates high coherence. Similarly, Strategy 1 has a direct/strong correlation with Aspiration 2, but Strategy 2 has no correlation, and Strategy 3 only has indirect/weak correlation.

Remember, this is just a hypothesis, and by looking at the patterns of correlations around the X-Matrix we can see and discuss the overall coherence. For example we might question why Strategy 3 only has Tactic 2 with an indirect/weak correlation. Or whether Tactic 2 is the best investment given its relatively poor correlations with both Strategies and Evidence. Or whether Evidence 4 is relevant given its relatively poor correlations with both Tactics and Aspiration.

Its visualising and discussing these correlations that is often where the magic happens, as it exposes differences in understandings and perspectives on what all the pieces mean and how relate to each other. This leads to refinement of X-Matrix, more coherence and stronger alignment.

TASTE Success with an X-Matrix Template

I’ve put together a new X-Matrix A3 template to go with the Backbriefing and Experiment A3s I published last month. Together, these 3 templates work well together as part of a Strategy Deployment process, although I should reiterate again that the templates alone are not sufficient. A culture of collaboration and learning is also necessary as part of Catchball.

 

While creating the template I decided to change some of the language on it – mainly because I think it better reflects the intent of each section. However a side-benefit is that it nicely creates a new acronym, TASTE, as follows:

  • True North – the orientation which informs what should be done. This is more of a direction and vision than a destination or future state. Decisions should take you towards rather than away from your True North.
  • Aspirations – the results we hope to achieve. These are not targets, but should reflect the size of the ambition and the challenge ahead.
  • Strategies – the guiding policies that enable us. This is the approach to meeting the aspirations by creating enabling constraints.
  • Tactics – the coherent actions we will take. These represent the hypotheses to be tested and the work to be done to implement the strategies in the form of experiments.
  • Evidence – the outcomes that indicate progress. These are the leading indicators which provide quick and frequent feedback on whether the tactics are having an impact on meeting the aspirations.

Hence working through these sections collaboratively can lead to being able to TASTE success 🙂

One of the challenges with an X-Matrix template is that there is no right number of items which should populate each section. With that in mind I have gone for what I think is a reasonable upper limit, and I would generally prefer to have fewer items than the template allows.

This version also provides no guidance on how to complete the correlations on the 4 matrices in the corners which create the X (e.g. Strong/Weak, Direct/Indirect, Probable/Possible/Plausible). I will probable come back to that with a future version and/or post.