Anything that helps me (and others) understand Wardley Mapping better has to be a good thing. Hereās Will Larsonās Rough notes on learning Wardley Mapping.
Have added Google Analytics to this blog, via the Sitekit WordPress plugin. I guess it will be interesting to see the numbers, but it isn’t really why I do this, so maybe I’ll switch it off again once the novelty wears off. #
I understand it, truly, the desire to know specifically what youāre going to get for your money. Itās what people have come to expect of transactions with suppliers. I give you money, you give me a caramel chai. You give me money, I give you my time.
But it only works when you are really certain that the thing youāre buying is the thing you need to achieve the outcomes youāre seeking.
Straightforward for my posh tea in a high street coffee shop. Less straightforward in a complex adaptive system like, say, education.
Because the more specificity and certainty you demand in advance around what will be delivered in order to achieve the outcome, the lower your chance of achieving the outcome.
I posted an article yesterday about writing good strategies, based on some of the work I have been doing lately. Also copy and pasted it into LinkedIn, and will send it out on a newsletter at some point too. #
A lovely chat with James⬠this morning, rather out of the blue. It was great to catch up and share stories about what we’ve been up to for the last 10 years, or however long it was since we last spoke. We talked a lot about online communities – particularly of practice – and shared a bunch of experiences and ideas. He reminded me of a few things I’d forgotten about, like the GDS community development handbookā¬. #
The community development framework⬠sets out the things that communities need really well: people, programme, and platform. I do struggle with the latter, nothing seems to work terribly well, particularly when it comes to making it easy to extract knowledge out of discussions and into some kind of searchable archive. I’ve not expressed this very well, but I do wonder whether this is the sort of thing that a large language model type thing might actually be useful for. #
Have just come across this great blog⬠from a local government technology person. They don’t mention their name on their blog, so I won’t do it on mine. Well worth a read and a subscribe though! #
This post and all its contents is published under a creative commons attribution-sharealike license. Find out moreā¬.
I’m doing a fair bit of strategy work with councils at the moment, and have hit upon a framework for putting them together which seems to help keep strategies strategic, and thus make them more useful.
I’m typing here about the work I’m doing on digital strategies specifically – although this stuff may well work for other kinds of strategies too. Also, this isn’t a ‘do you need a digital strategy?’ kind of post – it assumes you’ve decided you do need one. Finally, when I say digital, I mean it as a shorthand for technology, data, and online experience. OK, let’s get into it!
Strategy sometimes has a bad reputation – and thatās probably because a lot of strategies arenāt very good!
They donāt align with any other strategic vision
They are too detailed
They are written in weird corporate speak and fail to engage people
They try to do too many things
They date really badly
Nobody reads them, or refers to them
What does good strategy look like?
Good strategies provide a destination for organisations. They describe why things need to be different in the future.
With that vision, individual teams can use them to plan what they will do, when they will do it, and how they will deliver.
Strategies aid decision making, prioritisation, architectural decisions, team structures, culture, ways of working⦠pretty much everything! But, importantly, they don’t need to include the details of those things.
My approach to making this all a lot easier is to do the following:
Really focus on what exactly the strategy needs to do. Keep it short, high level, outcomes focused
Resist the temptation to put operational details or project plans into strategies – ie the stuff that’s likely to change
Have proper documents where that stuff can go, to ensure it still gets thought about and written down
Explaining the framework
The way this works is that all the stuff that often (wrongly, in my view) ends up in strategies is actually published in 4 separate documents (or not documents – could be any format depending on the content).
It also ensures we can be flexible with the bits that need to be flexible. Plans change, technology changes, stuff happens. That shouldn’t affect your strategic vision, themes, and principles – but it will and should change your choices, pipeline of work, and approaches to doing work.
This strategy is high level and long term. It outlines the outcomes expected from the strategy and answers the question āwhy?ā. The strategy is the formal document, which is formally adopted by the Council and will rarely if ever change.
I’m thinking of this as a maybe 6 page document (maybe more to allow for the senior person’s introduction, etc etc). It is vital that it is properly socialised across the entire organisation and referred to all the time. Maybe find a way to pull bits out of it to go on posters and things, to keep them in folk’s minds.
Blueprints are created individually for different elements of the strategy, such as core ICT, applications, data or online experience. They provide a link between strategy and delivery. They answer the question āwhat?ā. They are likely to change as decisions are made around the issues involved.
Blueprints are likely to come in a variety of formats. Could be enterprise architecture type diagrams, could be statements of approach, could be policu documents, could be organisation charts. All depends what bits of the mechanisms of strategy delivery you’re articulating.
Playbooks define the ways of working and approaches to delivering the work. They answer the question āhow?ā. They ought to be truly living documents that evolve as the organisation gets better and more mature in their approach to doing digital related work.
I think the best playbooks tend to be online and easy to refer to. So, could be on the intranet, or on a blogging platform, or using something like Gitbookā¬. It’s important that it’s easy to access and easy to update and add to.
Roadmaps are created individually for each theme. They describe the activities to deliver the strategy outcomes, in other words, the āwhen?ā. It’ll be updated all the time, as prioprities switch around, things take longer to deliver than expected, or where emergencies arise.
The nice way to do a roadmap would be with some nice software to make it pretty – there are loads out there. But it could be a Gantt chart type thing, or a simple portfolio list that shows when things are planned in to be done.
Hopefully that makes sense. The idea is simple – keep the strategy strategic, and make sure everyone understands it. All the detail still needs documenting, but in the appropriate place and in an appropriate format.
I absolutely love thisĀ – a Chrome browser extension that lets you play Breakout against your Google Calendar – bash the ball into the appointments to destroy them! Thereās even an option to automatically decline the meetings you destroy! š Temptingā¦.
This is a re-publish of a thing that went on LinkedIn, my newsletter, and the Digital Leaders newsletter. I’ve backdated the published date on this post to reflect this.
Summary: all this tech called ‘AI’ is genuinely exciting. But the impact of it is unlikely to be felt for several years. Don’t expect quick results, and don’t expect them to come without a hell of a lot of hard, boring work first.
It’s hard to look at LinkedIn these days without being instantly confronted by AI enthusiasts, almost foaming at the mouth as they share their vision for how the public sector can save millions, if not billions, of pounds by simply using AI.
It sounds so easy! As a chief executive I would be reading this stuff and thinking to myself, ‘why the hell aren’t my people doing this already?’.
In fact, I am hearing from digital and technology practitioners in councils all over the country saying that this is happening. That the AI hype is putting pressure on teams to start delivering on some of these promises, and to do so quickly. I find this troubling.
It’s always worth referring to my 5 statements of the bleedin’ obvious when it comes to technology in organisations:
If something sounds like a silver bullet, it probably isnāt one
You canāt build new things on shaky, or non-existent, foundations
There are no short cuts through taking the time to properly learn, understand and plan
Thereās no such thing as a free lunch ā investment is always necessary at some point and itās always best to spend sooner, thoughtfully, rather than later, in a panic
Donāt go big early in terms of your expectations: start small, learn what works and scale up from that
How does this apply to using AI in public services? Here’s my take on the whole thing. Feel free to share it with people in your organisation, especially if you think they may have been spending a little too long at the Kool Aid tap:
The various technologies referred to as ‘AI’ have huge potential, but nobody really understand what that looks like right now
Almost all the actual, working use cases at the moment are neat productivity hacks, that make life mostly easier but don’t deliver substantial change or indeed benefits
Before we can come close to understanding how these technologies can be used at scale, we need to experiment and innovate in small, controlled trials and learn from what works and what doesn’t
Taking the use of these technologies outside of handy productivity hacks and into the genuinely transformative change arena will involve a hell of a lot of housekeeping to be done first: accessing and cleaning up data, being a big one. Ensuring other sources for the technology to learn from is of sufficient quality (such as web page content, etc) is another. Bringing enough people up to the level of confidence and capability needed to execute this work at scale, for three – and there’s a lot more.
The environmental impact of these technologies is huge, and many organisations going ham on AI also happen to have declared climate emergencies! How is that square being circled? (Spoiler – it isn’t.)
The choice of AI technology partner is incredibly important and significant market testing will be required before operating at scale. There’s an easy option on the market that is picking up a lot of traction right now, because it’s just there. This is not a good reason to use a certain technology provider. Organisations must be very wary of becoming addicted to a service that could see prices rocket overnight. More importantly perhaps is whether you can trust a supplier, or those that supply bits of tech to them, to always do the right thing with your data. There’s always going to be an element of risk here: but at least identify it, and manage it.
Lastly, the quality of the outputs of these things cannot be taken on trust, and have to be checked for bias, inaccuracies and general standards. Organisations need to have an approach to ensuring checks and balances are in place, otherwise all manner of risks come into play, from the embarrassing to the potentially life-threatening.
This ended up being a lot longer than I first imagined. But I guess that just shows that this is a complex topics with a whole host of things that need to be considered.
Just remember – any messages you see claiming that AI is a technology that takes hard work away for minimal investment or effort, is at best just guesswork and at worst an outright lie.
Related to this post is a set of slides I presented to a conference in Glasgow: