Designing Data as a Service

Sketchnote showing the things you need to consider to build 'data as a service', including people and skills, user needs, data privacy and governance

Data is a vital business asset, but unlocking its power for your organisation goes beyond technology.

Yes, the infrastructure needs to be in place to capture and transform multiple sources of data to reveal new insights – but the starting point has to be with the users. You need to understand what they want from the data, how to make it accessible for them and how to create a culture of data ownership.

This is the concept of Data as a Service. By taking a service design approach, rather than a purely technical one, you make ownership and access to data available to the whole organisation.

At a minimum, good service design for data needs to consider the following things:

User needs

Who are the different users you’re targeting and what are the problems they’re trying to solve? Data analysts, scientists and operators are the obvious candidates to talk to, but who else? Marketing teams, HR, product and many other functions will all have outcomes they need to achieve using the data.

Designing for the user also covers the experience people have when they interact with your data service. Is it simple to access? Are consistent patterns and components used in interfaces? Will users require coaching, training and technical support to help get the most out of it? 

And just as importantly, how do you change the culture so that teams become data-informed in their decision making?

The strategic picture

Previously data systems were built individually for different functions or business initiatives. This led to duplication, inconsistent formats and varying standards around data sharing.

Nowadays, we don’t just want to know about individual transactions, we want a 360 degree view of the customer experience or an end-to-end view of ROI.

This means taking a step back and adopting an organisation-wide perspective to build a platform that supports multiple initiatives and use cases. You don’t need to know all the initiatives upfront, but you need to design the platform to be adaptable to new uses as they are uncovered.

Data governance

Barriers to data sharing occur when different functions and initiatives use inconsistent standards and formats. Or there is a lack of trust between functions, e.g. if we share our customer data with you, will you start contacting those customers without our permission?

The key role of governance is to ensure data remains consistent, accurate, accessible, available and secure. Protection of privacy is a must and governance principles, frameworks and processes need to be in place, but there’s also a need to develop a culture where it’s everyone’s job to use data effectively and securely.

Designing data as a service, not a technology

The key takeaway from this is mindset. If you take on a data initiative purely as a technical problem to solve, you’ll miss the fundamental factors that’ll make it a success. This is why it’s so vital to take a human-centred service approach to leverage the data you need to meet your business goals.

Reference links:

Managing data as an asset: An interview with the CEO of Informatica

5 design principles for the data system

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