Using Agile with a Data Science Team

Agile helped a data science team to better collaborate with their stakeholders and increase their productivity. As priorities became clear, the team was able to focus and deliver. Buy-in of the data science team by taking them through a journey of agile was crucial to making it work.

Snigdha Satti, a product owner and senior business analyst at News UK, shared her experiences from using agile with a data science team at Agile Tour London 2020.

When starting her assignment with the data science team, Satti mentioned that the first thing she did was to speak to each and every member of the team and their stakeholders to understand each individual’s pain points:

It was quite clear that the team didn’t have a clear direction and motivation, which led to loss in productivity and eventually missing the deadlines. Similarly, stakeholders were frustrated that things were being promised but not

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Applying agile in POCs for emerging technologies

There’s plenty of new and exciting technology for developers, engineers, and data scientists to kick the tires on, learn how to apply, and evaluate for potential business applications. To learn about it, technology and data teams often conduct POCs (proof of concepts) to validate use cases, performance, integration capabilities, and other requirements. IT and data teams conduct POCs on new JavaScript libraries, devops tools, public cloud capabilities, low-code platforms, database technologies, machine learning models, and data integrations.

Applying agile methodologies such as scrum to execute a proof of concept has many benefits. The agile team defines its objectives at the start of a sprint and then uses what they learn to prioritize new experiments and validations in upcoming sprints.

Using POCs to conduct rapid reviews of new technologies is relatively straightforward when the agile team or other technologists are the subject matter experts and can determine success criteria. Agile teams

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Pandemic Drives Supply Chains to More Agile Future

KNOXVILLE, Tenn., Oct. 19, 2020 /PRNewswire/ — Before COVID-19, consumers, policy makers and even corporate executives were mostly oblivious to the global complexity of supply chains. This year’s empty grocery shelves and missing medical supplies changed that. Eight months after the pandemic’s onset, transportation systems still aren’t back to “normal,” and researchers from the University of Tennessee, Knoxville’sHaslam College of Business expect they never will be.

“Volatility, uncertainty, complexity and ambiguity – or VUCA – has been spurring supply chain innovation for decades,” Mary Long, director of the Supply Chain Forum at Haslam’s Global Supply Chain Institute (GSCI), says. “Disruption on a pandemic scale has amplified the sense of urgency to build more integrated supply chains, since visibility is the new competitive advantage.”

Mary Holcomb, the Gerald T. Niedert Professor at Haslam and one of transportation’s leading experts, agrees that the pandemic has accelerated innovation in the

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