Faculty Member at The University of Texas at Austin McCombs School of Business
Answered 23 days ago
Name: Joe Sagrilla Title: CEO & Principal Consultant Company: Horizon Business Consulting LLC 1.What would you change first if you saw a team you were advising was burnt out? RESPONSE: "Even great teams burn out trying to deliver the impossible. The first thing I do is pressure-test whether expectations are realistic - usually by mapping what's been promised against actual funding, skills available, and whether anyone defined success criteria. A lot of the burnout I see stems from this mismatch." 2. As a consultant, how do you assess whether a team is actually ready for AI? RESPONSE: "Most teams can't connect their AI use case to the P&L - that's the first red flag. I also test whether the process can tolerate errors or needs human review that doesn't just duplicate the original work."
1. What would you change first if you saw a team you were advising was burnt out? When I see a team member starting to burnout, the first thing I will look at is whether they have a a managable workload. Unrealistic workloads combined with shifting objectives will take their toll on a person's energy and motivation. The first thing action I will take is is to re-evaluate delivery expectations with other stakeholders, and try to create some breathing space for the person suffering from burnout. Another measure I take is giving regular feedback on project results and outcomes, and the responses of wider stakeholders. It is motivational and prevents my team from feeling like a cog in a machine. I would definitely not instantly try to offload some of their work with an AI tool. 2. As a consultant, how do you assess whether a team is actually ready for AI? I start by evaluating processes: if process workflows are neither well documented nor approached with consistency, then adding AI is folly and will create confusion rather than add value. A team is ready for AI once they have established clear and consistent processes, allowing them to gauge how AI improves their work, rather than blurring processes and subsequently, their outcomes. 3. What are the AI use cases teams ask for the most and how do they compare to the ones you actually recommend? AI tools that automate reporting and status updates are popular requests. But, I usually recommend starting with tools that support decision making: for example, in areas such as risk identification and data analysis. These tools will faciliate decision taking but will keep people close to the impact of their decisions (as I said above, being able to see tangible results and outcomes is highly motivating) meaning they feel in control, and empowered, rather than feel that AI automation is replacing them.
1. My first priority would be to put a hold on the roadmap and take stock of the "invisible" work that isn't being captured. Generally speaking, burnout comes from the amount of effort required to switch gears as a result of poor or unclear requirements, not necessarily the amount of code written. 2. Before I take any kind of look at the technology being used by a team, I always look at how well they are handling their process right now. If a team has a lot of manual, untracked processes, having AI to automate those untracked processes will lead to creating a larger backlog of technical debt due to the chaotic nature of those processes. 3. Teams tend to request "magic" (aka autonomous agents) to completely build new features; however, I normally recommend starting with "mundane" (aka) type tasks such as automated PR review and automated unit test creation. By reducing the amount of cognitive effort required on a daily basis to do their jobs, developers will achieve a far greater return on investment than if they were trying to automate decisions regarding the high-level architecture of their systems.
I find it helps to automate those annoying repetitive tasks. At ShipTheDeal, we set up an automatic weekly report and suddenly everyone just felt lighter. Burnout with remote work sneaks up on you, so I ask my team directly if they're okay. Honest, regular talks work better than any magic bullet. If you have any questions, feel free to reach out to my personal email
I tell if a team is ready for AI by watching them. Are they actually open to what the data says? Do they complain about the boring stuff they have to do over and over? I've found a direct conversation uncovers more problems than any formal assessment. If they're still fighting with the tools they have, automation will just make things worse. Fix that first. If you have any questions, feel free to reach out to my personal email