# Execution trap *Too much work in flight* --- You've just taken over an operations team. Forty people, good talent, strong individual track records. The board's verdict is blunt: execution failure. Deadlines slip, quality is inconsistent, two product launches came in late last quarter. Your predecessor responded by tightening reporting cadence and adding weekly status reviews. It didn't help. Your instinct is to push harder. Shorter deadlines, more oversight, clearer accountability. Before you do, count something. --- You ask each team lead to list every active commitment: projects in flight, requests being worked, items waiting for someone's input. You expect fifteen or twenty. The list comes back at forty-seven. Forty-seven active items across a team that, based on last quarter's completion data, finishes about six things a month. | What you count | What it says | |---|---| | Active items (WIP) | 47 | | Monthly completions (throughput) | 6 | | Implied lead time | 7.8 months | If you have forty-seven things in flight and finish six a month, everything takes nearly eight months on average, purely because the queue is that long. There's a simple relationship from queueing theory ([[Flow and bottlenecks|Little's Law]]) that formalises it: lead time equals work in process divided by throughput. The maths doesn't care whether the work is manufacturing parts or reviewing contracts. More items in the system means longer waits for all of them. The two late product launches weren't execution failures. They entered a queue of forty-seven and took roughly as long as the maths predicted. --- Where did the forty-seven come from? Not all at once. A board member requested a competitive analysis, marketing kicked off a positioning refresh, sales needed a new demo environment, finance asked for a revised forecast model. Each request, individually, seemed reasonable. Nobody tallied the running total. Somebody's job, at this size, is to sit on ideas and release them at a rate the organisation can absorb. You pull up last quarter's data and count starts against finishes. | | Q3 | |---|---| | New items started | 19 | | Items completed | 6 | | Net WIP increase | +13 | Nineteen new commitments entered the system and six left. The queue grew by thirteen in a single quarter. The organisation was starting work faster than anyone could finish it. --- You trace three of the stalled items back to their origin. Each one hit the same wall: a decision that needed sign-off from someone senior. The competitive analysis needed a VP to confirm scope, and the request sat in her inbox for eleven days. The positioning refresh required the CMO to choose between two directions; he asked for more data, diaries aligned two weeks later, and he picked a direction in the meeting within ten minutes. The forecast model needed the CFO to agree the assumptions, and she was travelling. None of these delays show up in any project tracker. No ticket says "waiting for decision". But across three items, seven weeks of elapsed time were consumed by decisions rather than work. The bottleneck was decision speed. --- The team you inherited isn't undisciplined. They're working inside a system that fights them: too much work in flight, more starting than finishing, and decisions that take weeks to arrive. Each problem feeds the others. Slow decisions leave half-blocked work sitting in the queue, which lengthens lead times, which makes everything feel late, which triggers more status meetings and tighter reporting, which consumes the time that could have gone to finishing things. Your predecessor's response, more oversight and shorter deadlines, made every one of these dynamics worse. --- The fix starts with the queue, not the people. You cap active work at fifteen items. That means saying no, or more precisely "not yet", to thirty-two existing commitments. A few genuinely can't wait (a compliance deadline doesn't negotiate), but most go to a backlog and some get killed. The team leads push back at first, because every item has a sponsor who thinks theirs matters most. But the team finishes six things a month, and forty-seven in flight means nothing moves quickly, whoever is sponsoring it. | | Before | After (month 2) | |---|---|---| | Active items | 47 | 14 | | Monthly completions | 6 | 8 | | Implied lead time | 7.8 months | 1.8 months | Completions actually increased. People spent less time switching between tasks, less time waiting for inputs across too many workstreams, and less time in status meetings about items that weren't moving. --- The decision bottleneck needs a different fix. You sit with the three senior leaders whose approvals created the longest delays and ask each a version of the same question: what would you need to see to say yes? The CFO describes the three assumptions she checks in any forecast. The VP explains her scoping criteria. The CMO lists the two questions that determine his positioning calls. None of this was secret. They'd just never written it down, so their teams were guessing at the criteria and losing rounds of work to revision. Once the logic is written down, most of these decisions stop requiring sign-off at all: the team applies the criteria themselves and escalates the genuine exceptions, and most decisions start moving in days rather than weeks. It works because the criteria already existed in each leader's head. Where a leader is still working out what they think, writing it down is a different and harder conversation. --- Six months in, the board reviews the same team. Two product launches shipped early, the backlog is shorter than it has been in two years, and quality complaints have dropped. Nobody was fired and nobody was hired: the same forty people, producing different results, because the system around them changed. When you inherit a team that can't execute, count the queue before you tighten the screws. ---