Breaking through the inertia that prevents data sharing
Gartner predicts that by 2023, organisations that promote data sharing will outperform their peers on most business value metrics and generate three times more measurable economic benefit than those who do not.
But what does it mean to share data? Providing access to data is not a binary decision. As we’ll see, it is far more complex.
The UK Government uses three categories of data access classification: Open, Safeguarded, and Controlled. These terms provide a useful introduction into the types of access that may or may not be granted to different datasets. This categorisation implicitly introduces two more components to think about:
Level of access – from being able to edit at source, to viewing an aggregated snapshot.
Purpose (reason) for needing access – from clear and specific to unknown and exploratory.
For projects, the picture is further complicated by multiple different ‘layers’ of data:
Activities (from tasks to bundled packages of work)
And then what we’re calling ‘systems’ where different sharing regimes are likely to apply:
Internal to your business – sharing within organisations to deliver better business results.
With your project ecosystem – sharing between people, regardless of organisation to deliver projects.
With organisations across (and beyond) your sector - sharing to innovate or improve the sector.
There are trade-offs between all these different elements, which gives rise to complexity resulting in inertia.
To cut through this complexity, we’re using a mental model that contains 3 aspects:
We’ll break each of these down in more detail in individual posts.