Over the past couple of months we’ve been finding out what existing work has been done on Data Maturity and what we can learn from it.
We’ve been trawling the internet, reading the literature, and interviewing some leading people with relevant knowledge and expertise
Our full report is available now. This post draws out some of our key findings.
What do we mean by data maturity?
The concept of data maturity is relatively new and seems to be most widely used and understood in the data science community. We found around 40-50 different models/frameworks and related theories.
In essence what many of the models explain is the journey from looking at retrospective ad hoc data to explain the past, to a more continuous ‘current/real-time’ understanding of the here and now, a level of optimizing for efficiency and effectiveness, through to the ultimate state of predicting and creating the future.
How do organisations become more data driven?
1. They put data people at the heart/centre, adjacent to leadership team
2. They start to see data as a key asset.
3. They collect the right data, relevant to the question at hand.
4. They make data accessible to many in the organisation. Helping people to query, join, relate and share the data across the organisation. 5. They start to see data as a team sport, not just the responsibility of one data person. Over time data should become an intrinsic skill and asset for every team in organization. Across the organisation encourage people to steward and query the data, asking the right questions.
6. They make the time to absorb, discuss and challenge using data.
7. They move from reporting on the past (what happened?) to the present (what’s happening now?) to the future (extrapolation, modeling, recommended action, prediction/simulation).
What stops organisations from becoming more data driven?
1. Lack of understanding on how to use analytics to improve what they do
2. Lack of management capacity (competing priorities)
3. Lack of internal skills
4. Existing culture doesn’t encourage sharing.
How long does it take?
Our research suggests that the journey to maturity is fairly long and challenging though worthwhile in the end.
Several people suggested it can take 5 years of more to develop, implement and reap the rewards of becoming a data mature and data driven organization.
What are the next steps?
There’s wide range of experience and existing resources to learn from which are referenced in our Data Maturity Report. The most well-rounded and applicable resource we found was a book called “Creating a Data-Driven organisation: practical advice from the trenches“, by Carl Anderson in 2015.
Attend one of our workshops for charity and social enterprise leaders.
Organisations like DataKind UK and Data Orchard CIC are here to help of course, and we’re collecting details of other organisations that could help.
The Data Evolution project is aiming to develop data maturity models for the social sector. You can help us help the sector by taking part in our survey.
Madeline Spinks and Sian Basker from Data Orchard CIC