I’ve been continuing to mull on the idea of how techniques familiar in the realm of Service and User-centred Design might be adapted to help shape data products – groups of data that can be used in various ways within an organisation for different sorts of purpose.

I’ve always liked the Customer Journey Map as a way of being able to help teams to visualise the way in which people interact with a service. It helps to allow people to see what they do from the outside in, and identify where there are pain points for consumers of services (that often are handover points between teams).

So could something similar be done to map the journey of data through an organisation? Here’s a first attempt…

The content is fictitious, and because it’s hot I’ve used a client service organisation similar to the one I work for, to think about the course that Customer data takes through its lifecycle.

Across the top role you have notional steps in a customer journey – from initial contact, through business development/pitching phased, to onboarding, delivery and then offboarding when the work is done.

The rows that follow are as follows:


Who is it that is interacting with customer data at this point in the journey?


Are there particular meanings that at this stage of the journey are important to call out. For example, prior to any deal being done a customer is often known as a “prospect” or a ”lead”, and indeed whilst the customer might be thought of as a person, for a B2B organisation the customer is another business and the people may be known as contacts.


I’ve lazily taken terminology straight from the Miro customer journey map template here, and this might be better thought of as Systems, but essentially where at this stage in the journey does the customer data reside?

Data Quality

At this stage of the journey, how good is the quality of the data? It’s not at all uncommon for data quality to fluctuate over time, and gradually diminish generally the longer it is held. I’ve used traffic lights here, but I do find them a bit over-reductive.


What issues with data at this stage of the journey could be improved thus providing business value?

Data ownership

Who (if anyone) owns the data at this stage in the journey? Where are the handoffs? Does data go into ownerless voids at any point?

At first play, this feels like it could be useful as a way to facilitate research with end users to talk about data in the context of it’s lifecycle. What do you think?

2 thoughts on “Data journey maps

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