30 years ago the technology industry attempted to import Lean practices — it failed. Instead of “continuous improvement,” progress halted. Agile is incompatible with UX research, design, and scalable development. It always will be. It’s time to create a new…

Nuances and Considerations for Implementing Data Mesh A data mesh architecture distributes data ownership across domain teams with federated governance and decentralized data products. Data mesh contrasts with other data architectures because it is highly decentralized, and distributed as opposed…

The Analytics Leadership Consortium’s (ALC) Q3 theme on Funding and Budgets focused on three aspects: establishing and justifying value, sourcing funds, and allocating budget. While many valuable points came through in our confidential discussions, two ideas stuck out. First, communicating…

Managing data science projects — or more specifically engineering teams building data products — is in my experience an art form, and a mysterious one at that. Anyone who has brought a data product to life will undoubtedly have tales…

How many analytics organizations can quickly identify the top five capabilities they are actively building to prepare for their business needs 3-5 years from now? Perhaps not many. Many leaders are able to identify what analytics capabilities they are building…

Throughout my career, I’ve seen a number of different analytics teams; as you might expect, there are a handful of similarities and a handful of differences in how each team operates. But one thing that has consistently stuck out is…

You’re interviewing for a job in data science: maybe it’s your first job or maybe it’s a Chief Analytics Officer role. One struggle people have is when to talk salary with the employer. Certainly, this issue isn’t unique to data…

The Inequality in the Data Science Industry Data science as a discipline has received an increasing amount of attention in the public consciousness over the past decade from many, including undergraduate students considering lucrative career paths and leaders of companies…

Many analytics leaders will agree that talent is the most valuable asset in their organization— and the most challenging. But how much time do analytics leaders really spend designing the team they will need five years from now? For many,…