Quality and Innovation

How can we get better data (and better AI) faster? Everyone wants to know. And I’ve spent the past four years using Deming’s System of Profound Knowledge to find an answer… which basically boils down to the fact that the people are the problem, and the people are US. What can we do about it? That answer is Data, Strategy, Culture & Power – now available on Amazon (Print or Kindle) or as PDF eBook here.

Data, analytics, and AI teams are under immense pressure to deliver insights and solutions that drive business value, often with limited resources and under tight (or unreasonable) deadlines. They grapple with complex data infrastructures, data quality issues, and the constant need to stay up-to-date with rapidly evolving technologies. It’s a tough and thankless job.

Meanwhile, business stakeholders think of data like electricity: their data should just be available whenever they need it, as readily available and as easily accessible as flipping a lightswitch. They don’t know – and don’t need to know – the challenges involved in managing and analyzing data, setting up the services and infrastructures that deliver it, and keeping track of it along the way to monitor and ensure quality. While their demands are often unrealistic, the demands don’t FEEL like they SHOULD be unrealistic, so a perpetual disconnect is set up between expectations and what is possible in reality.

In this power dynamic, business stakeholders always hold the upper hand, creating a stressful environment where data teams are constantly playing catch-up, trying to work rapidly growing mountains of tickets while struggling to communicate the complexities of their work. As a result, data teams often find themselves mired in a cycle of reactivity. They spend more time firefighting and responding to ad hoc requests than focusing on the high-value work that could drive business impact and make everyone’s lives easier on the business side. This perpetuates the perception that data teams are an unproductive bottleneck rather than a strategic asset, further straining the relationship between them and the business stakeholders they serve.

Between 70-90% of all digital transformation initiatives fail… which includes AI & ML. Since 2020, my research has focused on the relationships between inclusion, performance, and power – and specifically how these forces impact data/AI initiatives and the people who need their contributions.

And after having to delay editorial deliverables in Q3 and Q4 2023 due to work obligations, I’m pleased to announce that my next book is finally in the late stages of pre-publication and is scheduled for paperback release on May 27th! (Check back here for Amazon links then.)

Based on the past 20 years of working with companies on data, analytics & AI initiatives, and the past 5 years advising leadership teams and CDOs, one thing is clear: EVERYONE’S dealing with the same pain points – and there are underlying factors we’re all glossing over. The purpose of this book is to highlight these gaps so you can be more conscious of them – and build strategies that are sensitive to them. In addition to this book, this research program has also generated:

• Inclusion by Design (2023) – an academic research paper that formulates a 6-element model of the ways inclusion can enhance or damage performance
• TeamX – an intelligent agent that diagnoses the next logical step a team can take to create a more inclusive environment that directly contributes to their performance goals (contact them now if you’d like to inquire about pricing or getting your team on the waiting list!! It’s not your typical assessment or teambuilding diagnostic.)

Follow me here or on LinkedIn to hear more about what we’ve learned over the past few years, and how you can use it to break toxic patterns and forge more collaborative bonds in your organizations.