How to Manage Stakeholder Expectations in Data Projects

Managing expectations in data projects is often difficult. This is especially true when the stakeholders are from the business side, not IT.

Often projects are sold as being a great thing for the stakeholders (which of course they will be!). However, those stakeholders often have limited technical knowledge and expect to see progress visually. When there is nothing visual to show, they may think little progress is happening.

This expectation especially affects data science/data visualisation projects if the source data is unavailable or immature. This is particularly true of any project that needs a significant amount of effort to source, understand and analyse data.

To proactively help overcome this challenge we use the Data Insights Project Iceberg.

The iceberg informs less technical stakeholders what to expect at the beginning of the project. It informs them a large amount of work is happening but remains unseen.

Data sourcing and crunching takes time

There is no avoiding data sourcing and data analysis.

No data in = no information out. Rubbish data in = rubbish data out.

Therefore, this data work is unavoidable, especially in environments lacking a solid data infrastructure. By data infrastructure I mean a reliable data lake/data hub/data warehouse – i.e. a place where good data is existing and simple to source.

Introducing the iceberg in early project sessions informs stakeholders from the beginning that much of the work won’t have a visible output.

And when those stakeholders forget this, which they will, remind them of the iceberg. Show them how close the project is to breaking the surface.