Day 231
Week 33 Day 7: Assignment: List Your Team's Top Three Recurring Fires
This week's assignment starts the diagnostic process: identify the three recurring problems that consume the most of your team's unplanned time, and calculate the cost of each.
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Without looking at data, write down the three problems that you believe cause the most unplanned work on your team. Then validate against reality: check your incident log, your support tickets, your Slack channels, or your email for the past 30 days. How close was your intuition to the data?
Here is the assignment process. Step one: write your intuitive top three. What are the three recurring problems that you believe consume the most of your team's unplanned time? Be specific: not 'deployment issues' but 'deployment failures caused by configuration drift between staging and production.' Step two: gather data. Check your incident tracking system, support ticket queue, Slack channels, email threads, and calendar (look for unplanned meetings). List every unplanned work item from the past 30 days. Step three: categorize and count. Group the unplanned work items into categories, count the occurrences, and estimate the person-hours per category. Step four: compare. How well did your intuitive top three match the data-driven top three? In my experience, leaders get one of the three right and are surprised by the other two. The intuitive top three are biased toward recent and dramatic events. The data-driven top three often reveal chronic, low-drama problems that consume significant time because of their frequency. Step five: for each of the data-driven top three, estimate the annual cost (occurrences per month times person-hours per occurrence times 12). This number is the budget you have available for system-building without spending a dollar more than you are already spending. Step six: for each, brainstorm one system that could prevent or reduce the occurrences. A system does not need to be software. It could be a documented checklist, a scheduled review process, a cross-team agreement, or an automated alert. Step seven: pick the one with the best return (highest annual cost, lowest system-building cost) and commit to building it next quarter. Add your fire analysis and system proposal to your Leadership Operating Manual under 'Systems.'
The intuition-versus-data comparison in step four implements what Kahneman (2011) calls the 'competition between System 1 (fast, intuitive) and System 2 (slow, analytical) thinking.' His research demonstrates that intuitive problem assessment (System 1) is biased by availability heuristic (recent and memorable events receive disproportionate weight) and affect heuristic (emotionally charged events are perceived as more frequent). The data-gathering step activates System 2 thinking, which corrects these biases through empirical evidence. Research by Bazerman and Moore (2013) on 'judgment in managerial decision-making' found that managers who supplemented their intuitive assessments with data improved their diagnostic accuracy by 40-60%. The annual cost calculation implements what accountants call 'annualized loss expectancy' (ALE) -- a risk management metric that converts recurring losses into an annualized figure to enable comparison with preventive investment costs. Research by Gordon and Loeb (2002) on information security economics demonstrates that the optimal investment in prevention is approximately 37% of the annualized loss, which provides a useful heuristic for sizing system-building investments: if the annual cost of a recurring fire is 200 person-hours, investing up to approximately 74 person-hours in prevention is economically justified. The one-system commitment in step seven implements what Heath and Heath (2010) call 'shrinking the change' -- making the initial action small enough to be non-threatening, which increases the probability of follow-through from approximately 20% (for large, ambitious improvement plans) to approximately 65% (for small, specific commitments).
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