Hey, I’m Lindsay, the host of Make Sense w/ Lindsay T., Lady Engineer®, a weekly podcast where my guests and I simplify complex topics at the intersection of people & technology. We analyze whatever hot mess is in the news, evaluate trending innovations through a human-first lens, and take deep dives on a need-to-know basis.
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C-Suite executives are throwing money at AI as if it will magically fix everything, but will it solve the real problems plaguing your workday? Are we truly looking at an AI revolution or just another IT nightmare?
In celebrating the 50th episode of this podcast, I shared that the topic of enterprise software (the tools most of you use at work) will continue to be a recurring theme as I believe its ineffectiveness both drives macro system-level problems and the micro daily frustrations most employees have with their jobs.
The people deserve to know! “Why does enterprise software we use at work suck?”
While Lauren Maffeo initially demurred, this question is certainly not above her pay grade. Maffeo articulated:
Lack of Investment: Cash is king. When 30-50% of Corporate IT budgets are wrapped up triaging Shadow IT emergencies, who has the money to invest in better and more flexible tools?
Too Old to Touch: For companies that have been around for decades, their infrastructure is a hodge podge of solutions built on top of legacy systems. “Legacy” means super old, and is usually accompanied by the assumption that touching it will bring down the house of cards. This is because none of the original builders of said legacy systems aren’t around anymore, which brings me to the next point.
Poor Documentation: There are a few reasons why many companies have spotty documentation; we can point primarily to the lack of incentive for documentation and high-paced business environments with shifting priorities. There’s not enough time to keep documentation up-to-date so it becomes outdated and inaccurate quickly.
Lack of Transparency: Without clear documentation, it’s difficult to understand the data each system holds, how it’s supposed to be used, and who can access it. In the absence of this essential information, corporate IT may make the system more restrictive, which in turn, makes your job harder to do.
Ignoring the People: Frequently, more time and investment are given to the backend of technology systems while very little thought is given to the interface and the user.
If enterprise software at work sucks for all of the above (and more) reasons, will AI initiatives help or hurt us? If we focus on the problem, use AI as a tool only when it is the best solution, and build more flexible and composable infrastructure (like Legos!), then the potential is great.
Together, Lauren Maffeo and I also talk about:
- The need to prioritize data comprehension over data accumulation
- Her transition from a journalist reporting on tech to an award-winning innovator
- How incremental improvements will be a better bet over chasing technology fads
Reference the full show notes below
Choice Quote
“Data governance is a team sport. You can’t implement data governance throughout your organization without the buy -in from your sponsors and senior leadership, and your colleagues across sales, marketing, and customer care.”
– Lauren Maffeo, Author of “Designing Data Governance from the Ground Up”
Buck the media hype cycle. Calm the fear-mongering. Laugh at the inanity of Tech CEO “hero culture.” Be the smartest person in your peer’s LinkedIn feed:
Key Takeaways with Lauren Maffeo
Here are Al’s takes from the segment Crystal Ball: What does the future hold?
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The fear of AI taking everyone’s jobs will continue to grow: Yes [2:22]
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Better AI guardrails and encryption for customer data: Yes [4:27]
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Data Comprehension Will Get Priority over Data Accumulation: Probably a “nay”. [10:03]
Show Notes
00:00 Introduction and Overview
03:00 The Fear of AI Taking Jobs
04:16 Better AI Guardrails
10:52 Prioritizing Data Comprehension over Accumulation
15:35 The Importance of Data Governance and Involving Stakeholders
20:00 Segment 2: Who Needs a Safety Net? From Journalist to Award-Winning Innovation Leader
32:00 Segment 3: Deep Dive – Enterprise AI Strategy
35:02 The Role of AI in Improving Enterprise Software
45:19 The Power of Incremental Improvements in Enterprise AI
Where to find Lauren Maffeo
Lauren Maffeo is an award-winning author, analyst, and designer of data systems for the U.S. Federal government. Her first book, “Designing Data Governance from the Ground Up“, was published by The Pragmatic Programmers and adapted into a LinkedIn Learning course.
Lauren is a founding editor of Springer’s AI and Ethics journal and a former area editor for Data and Policy, an open-access journal with Cambridge University Press. She has presented at venues/with partners including Princeton and Columbia Universities, the U.S. State Department, and Twitter’s San Francisco headquarters.
Lauren was an associate principal analyst at Gartner, where she covered the impact of emerging tech like AI and blockchain on small business owners. Lauren has written for Harvard Data Science Review, Financial Times, and The Guardian, among other publications. She has also peer-reviewed technology research and books published by the GovLab at NYU, O’Reilly Media, and The Atlantic Council.
Lauren is a fellow of the Royal Society of Arts, a former member of the Association for Computing Machinery’s Distinguished Speakers Program, and a member of the International Academy of Digital Arts and Sciences, where she helps judge the Webby Awards. She is on 2 nonprofit boards and volunteers with The Linux Foundation.
LinkedIn: https://www.linkedin.com/in/laurenmaffeo/
Where to find Lindsay Tabas
LinkedIn: https://www.linkedin.com/in/lindsaytabas
YouTube: https://www.youtube.com/@LindsayTLadyEngineer
Instagram: https://www.instagram.com/lindsaytladyengineer
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