BD #21 - Art of the Possible Workshop to Get Proactive - Part 1

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A data team’s work is never done

Many data teams do a great job of serving the requests of their stakeholders. They get the job done in a timely manner, build robust, scalable solutions, even get some time to do knowledge sharing and education across the organisation.

But it’s easy to get a bit stuck in a rut.

Data and analytics isn’t easy. It takes time. These solutions are complex and complicated, often taking many iterations to develop from an idea to something that serves the business-as-usual need. Furthermore, your skills are in demand and you can add value to almost any other role or team in the organisation.

That can lead to overload - lots of different people competing for your time and attention to sprinkle some of your data and analytics magic on their workload.

You can end up on the treadmill, stuck in that “order-taker” role. Working away at whatever crosses your Kanban backlog and, if you’re lucky, getting through it at about the same rate it’s growing. Some of the great ideas you’ve had sit on the “one day” shelf, gathering ever more dust while you build yet another ETL pipeline to replace some fractal VBA nightmare.

At least someone cares

What’s worse than many people looking for your support?

No one looking for it.

Maybe you’re capable, available, keen, and ready to go but the one area of the organisation you think you could make the most impact in just aren’t interested. They don’t get it. They’re not data people. They don’t care. Or they just don’t see how things might be improved with a little help from their local friendly data team.

How do you break free if you’re in either of the above situations?

How do you get stakeholders engaged?

How do you take some control over what gets built - being proactive instead of reactive?

The Art of the Possible Workshop

I think this might be my favourite tool developed over the last few years of leading and consulting for data engagements. The Art of the Possible Workshop aims to get stakeholders excited about what they can do with data and analytics. It helps them spot opportunities across their organisation, and most importantly it gets them to prioritise a big shopping list of potential workstreams so you can take them on to the next step.

The Art of the Possible Workshop was built using the Perfect Workshop Blueprint, discussed in BD #9. If you aren’t familiar with it, this is my go-to approach to turning meetings into gold. Read it here:

The goal of this workshop is threefold:

• get stakeholders excited about the possible impact data and analytics can have

• gather a curated list of pain points and potential opportunities to drive positive change in the organisation

• get collective commitment and prioritisation on what to do next

This starts the whole co-design process. People often love the sound of an idea if they think it was theirs (even if they were coached to it). This workshop allows you to guide the group to have a bunch of great ideas for your team to start implementing.

The participants

I typically want to deliver this to between 4-8 people (too few and you don’t get a wide enough picture, too many and people don’t get enough share of the time/space). If you need more people, consider splitting it up into sub groups or categorising by role. This should be somewhat additive, so don’t be afraid to run it with a similar group at a later date once some changes have been made.

Who should be in the room depends on the remit of the data team or those you’re trying to engage. If I’m running one of these for a small company with only a handful of heads of and directors, I’ll probably try and do it as a company-wide exercise using them as spokespeople for each department. If the company is large or you’re looking to engage just one function/team (say finance), then you might want to get really specific and try to invite at least one of each job role and seniority level in that function.

The Format

I like to do these in a single day-long, in-person workshop with a whiteboard and post-its. I’ve done it remotely with online collaboration tools and I’ve broken it into lots of smaller stages, delivered over weeks. This is always the rough flow of events.

• Case study showcase

• Opportunity discovery

• Discussion

• Themes

• Ideation

• Prioritisation

• Commitment

Case study showcase - 60 minutes

This part takes the most time to prepare. You want to prepare a number of case studies that are relevant to the people you have in the room. The objective here is to get people excited and discussing blue sky, no limits things that are possible.

Draw these case studies from four places, in order of preference:

• direct competitors and similar organisations in other markets that do almost exactly what your audience do (or want to do)

• industry adjacent organisations that serve similar customers / markets but in different ways (suppliers or B2B customers in the same domain, that speak the same language)

• organisations, functions, or teams equivalent to the one you’re talking to (finance team in another industry for example)

• generally applicable case studies that will impress (think good data catalogues, ChatGPT etc.)

Nothing gets the room talking more than showing them what their fiercest competitor is doing and they aren’t. The point here is be as specific to their context and language as possible. The closer the better.

I always try to include some interesting general stuff that they might not be aware of - data discoverability tools, RPA, self-serve reporting, data quality tools etc.

Aim for roughly 10 examples, use short GIFs and video demos over pictures where possible. You don’t need to go into details. If you can link to hard, citable numbers that’s even better. Case studies by big vendors and consulting firms is where I usually start my search.

Once you’ve done this, your audience should be primed for some participation.

Next week we’ll get the post-it notes and whiteboard pens out and talk about how to turn this energy into something you can plan against.

All the best,
Adam

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