Start building your enterprise data ecosystem strategy

These days it’s a given that data needs to flow between systems, teams and partners in order to deliver digital customer experiences and drive competitive insights – but very few companies take a strategic approach to governing these data flows across their business ecosystems.

Instead of being reactive and considering individual data movements in isolation, today’s top CDOs are future-proofing their innovation potential by defining scalable ecosystem strategies for data assets.

Depending on your organisation’s stage of data collaboration maturity, you may be further along in the process of defining that strategy. For those just getting started, here are the steps that we know need to be addressed for data ecosystem strategy success.


Conduct a data ecosystem audit 

Conduct an audit of the data movements in and out of your business. You’ll likely already have elements of a data ecosystem in place, but they might be named different things. If you don’t already have a central register of data movements, create one and log specific legal agreements in use, permitted-use as well as how the actual transmission of the data is taking place.


Define your strategic imperatives

Define the imperative behind this initiative: why do we need to collaborate on data and what does our organisation hope to achieve? Defining aims for commercialisation and data product creation can also be part of this step, but these strategic goals are more advanced activities.

It’s equally important at this stage to decide who ‘owns’ the governance and management of the enterprise data ecosystem. Does our organisation have a Chief Data Office? Are they imbued with the necessary legal or technical authority to make ‘the call’ on data collaboration? Creating a chain of command for data collaboration will help empower teams once they know who to go to for approval.


Prioritise use cases and partnerships

Consider the ideal state of data exchange and how this aligns to organisational objectives. Prioritise the data partnerships and use cases depending on those objectives. Consider what use cases your organization is comfortable with and also who are existing commercial partners you can more efficiently launch projects with.


Map workflows and technology mechanisms

The next stage is to understand the current ‘organisational load’ for data collaboration enablement, and then consider how you could streamline these processes. If you had to provision data to a partner tomorrow how would you get it done? Who would need to approve a license or prepare a data package? How would the IT team allow a file to be shared? Mapping out the stages of a data collaboration project and the key people at each stage will provide you the scope for managing this type of project. Then you can easily see where the road blocks may arise before getting started.


Gain consensus on the methodology

Getting buy-in from leadership and stakeholders is essential for data collaboration and eventually a data ecosystem strategy to be successful. But you don’t have to jump straight into advanced data projects. You can start small and grow over time. Use a crawl, walk run approach detailed in our whitepaper: Innovation Executive’s Playbook.


Want to know more about defining your data ecosystem strategy? Watch our webinar to get more detailed insights.

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