The Missing Link in Advanced Analytics

Sean Mccall
Office Managing Vice President, Houston Office

Recently Pariveda hosted the Data Science Innovation Summit where a long-standing hypothesis was once again confirmed. The Data Science Product Owner continues to be a key missing link in modern analytics projects, including Artificial Intelligence (AI), Machine Learning (ML), Predictive Analytics (PA), and others.

Here is why:

The Data Science Product Owner is a cross-functional role that requires many “generalist” traits that are uncommon but critical to the success of an advanced analytics project. There are elements of a “storyteller” role within the Data Science Product Owner role. Without recognizing the risk points above, the Data Science team or the Data Science team lead are responsible by default, without the specific expectations of being a Product Owner. Drawing on Agile methodology, the Product Owner is typically a project’s key stakeholder. Part of the Product Owner responsibilities is to have a vision of what he or she wishes to build and convey that vision to the scrum team.

The best way to predict the future is to create it.” – Peter Drucker

Of course, these aren’t the only reasons analytics projects fail, but they are the big ones. There is buzz in the market and participants of last week’s Data Science Innovation Summit agree and the topic was mentioned by each conference speaker, raised in audience questions and follow-up social media conversations. This timely debate confirms there is still a challenge for companies wanting to invest in advanced analytics.

How will you define the Data Science Product Owner for your next advanced analytics project?


This article was originally posted on Sean McCall’s LinkedIn page