Building the business case for data change in organisations can be a challenge. In this webinar, Daragh O Brien looks at some basic techniques for starting smarter conversations.
Ultimately, to get change moving in an organisation and ensure management focus on the fundamentals of data, it’s important to have some good baseline numbers that you can reference to show how not tackling the problem is creating drag in the organisation or causing an avoidable cost.
In the webinar we look at three scenarios derived from Daragh’s two decades of experience.
Daragh also introduces the importance of creating a sense of dissatisfaction with the status quo to help drive change conversations, and the necessity of having some clear first steps to address root causes when people start to listen to your data rallying cry.
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Additional Resources
We have compiled some additional resources for people to give you some more information on topics covered in this webinar.
- A video of Tom Redman, the “Data Doc” talking about the Friday Afternoon Assessment (the technique used in the Car Parts scenario)
- Tom’s 2016 Harvard Business Review article discussing the Friday Afternoon Assessment
- A HBR article from 2017 discussing the research by Redman and the team in UCC’s Masters in Business Data on the cost of data quality
- Peter Davey writing about the importance of measuring the right things in data on in a recent Castlebridge Insight.
- Daragh wrote about the importance of applying data quality principles to metrics back in 2011
- Back in 2013 Daragh wrote about the challenges of measuring the effectiveness of training
- Doug Laney wrote about the value of data to organisations for Forbes recently.
- Daragh did a webinar for IRMS London in May looking at the Change Management issues in data management
- And for no other reason than Daragh mentions it in the webinar, a song from Hamilton.
Daragh has also put together an example Excel workbook showing some of the calculation approaches discussed in the webinar. This is provided as-is with no warranty, but is intended to illustrate how a simple model for the data debt in the organisation can be put together without a huge effort.
