Avoiding The 100% Utilization Fallacy Trap With Scrum

The 100% Utilization Fallacy

Many managers aim to maximize resource or team utilization, operating under the assumption that 100% utilization translates to optimal productivity. However, this push towards full utilization often leads to reduced throughput and slowing work due to increased bottlenecks and queueing.

Why Full Resource Utilization Leads to Bottlenecks

Trying to keep teams and individuals fully utilized at all times overloads the system’s capacity to process work. When resources become constrained at 100% utilization, any variability or additional work cannot be handled, leading to work piling up in queues. As queue length grows, cycle times stretch out, and throughput drops despite full utilization. The system bottlenecks and slows down due to a lack of available capacity to handle fluctuations.

Examples of How Multitasking Causes Slowdowns

Studies of multitasking show significant reductions in throughput when individuals switch between multiple tasks. For example, a study found that users regained focus on the original task less than 50% of the time after being interrupted. Multitasking also increases errors due to a lack of concentration and mental fatigue from constant context switching between tasks.

Beyond individuals, attempting to multitask across projects shows similar slowdowns at a team level. Teams trying to make progress on multiple projects at once rarely complete work as fast as focusing on one initiative at a time. The cognitive burden from switching business contexts leads to more than just the cost of the context switch itself.

Implementing Scrum to Optimize Flow

Scrum provides several mechanisms that can protect against pushing teams beyond sustainable utilization levels. Its focus on flow optimization, work-in-progress limits, and using cadence to establish reliable throughput allows teams to avoid getting overloaded.

Limiting Work-in-Progress to Maximize Throughput

A critical focus area in Scrum is to limit work-in-progress to maximize flow. Reducing the amount of work in process decreases queue lengths in front of individuals or teams and promotes faster cycle times. Shortened cycle times translate directly to increased throughput. Techniques like breaking large initiatives into small, time-boxed sprints further support smooth flow.

Additionally, the Scrum value of commitment focuses on selecting how much work can be completed within a sprint. By pulling in only enough work that the team can handle, Scrum helps prevent over-utilization that would risk achieving the sprint goal.

Using Pull Systems to Reduce Queueing

Scrum also serves as a pull system for bringing in new work rather than allowing unfettered push. As the team completes each sprint, they go to the product backlog and actively pull in the next set of highest priority items based on capacity. This pull approach ensures new work only enters the system at a sustainable pace rather than getting continually pushed onto the team without consideration of their throughput.

An agile Kanban system similarly uses explicit work-in-progress limits to facilitate pull. Because teams focus on finishing existing items before pulling new ones into play, work can flow smoothly through the system without extensive queueing at any stage.

Managing Capacity to Allow for Variability

In addition to work-in-progress limits, Scrum also provides general guidance around capacity planning and accounting for variability to avoid over-utilization. Intentional focus must go towards building in proper buffers and accommodations for uncertainty at multiple levels.

Planning for Fluctuations in Team Velocity

A cornerstone of Scrum lies around tracking team velocity to gauge throughput over time as a baseline for planning. However, velocity will likely vary to some degree from sprint to sprint. Tracking patterns over a rolling horizon allows estimation using an average over multiple sprints rather than expecting the team to deliver an exact number of story points each sprint indefinitely.

Sometimes a team takes on too much in a single sprint, over-utilizing themselves in the short-term trying to meet an unrealistic goal. While occasional overages happen, tracking trends provides feedback to prevent systemic over-commitment issue.Similarly, building in reasonable slack for vacation, illness, and unexpected issues proves necessary for long-term sustainable pace.

Accounting for Defects and Unplanned Work

Beyond planned project work, additional capacity must account for defects and technical debt. Scrum specifically calls for up to 10% of each sprint to go towards addressing defects and other unplanned work that arises. While this percentage threshold serves more as a guideline than a hard rule, it encourages acknowledgement that perfectly predictable utilization remains impossible.

Trying to eliminate all defects before moving to new functionality risks falling into a defect whack-a-mole Anti-Pattern with no end in sight. Similarly, teams that ignore defects and debt completely inevitably slow down later from the accrued issues. Budgeting for a reasonable buffer for the unexpected offers increased resilience without over-utilization.

Monitoring Cycle Time to Catch Bottlenecks

Scrum also facilitates monitoring of queueing and cycle time metrics that serve as early indicators teams may be approaching over-utilization. Tracking patterns helps detect constraints before they turn into bottlenecks that could significantly hinder throughput.

Measuring Cycle Time to Identify Constraints

Cycle time measures the total time for an item to proceed across each step needed for completion. Shortening and reducing variability in cycle time encourages flow. However, sudden jumps or additional variability could signal problems forming as queues start to build up.

Comparing work item age to typical cycle times helps filter normal variability from more systemic constraints threatening to impede flow. Reviewing higher-level board state can also quickly highlight where certain stages tend to bottleneck.

Techniques for Reducing Cycle Time

Various techniques exist to help optimize cycle time, prevent constraints from forming, and improve flow:

  • Reduce or split up large work items
  • Set work-in-progress limits per workflow state
  • Identify hand-offs creating delays
  • Build slack into timeframe estimates
  • Evaluate tools or technical platform constraints

Implementing some improvements may involve tradeoffs around resource utilization. However, allowing utilization to creep too high risks significant slowdowns from bottlenecks that require urgent intervention to resolve. Keeping utilization around sustainable levels helps avoid catastrophic workload issues.

Achieving Efficient Resource Utilization

While 100% utilization causes dysfunction, too much excess capacity proves equally wasteful. The right balance rests between these extremes to smooth flow while maximizing value delivery. Scrum offers guiding practices for productively utilizing resources without over-burdening them.

Balancing Utilization and Flow

Trying to eliminate all idle time destroys teams long-term due to mental fatigue and lack of flexibility to handle variability. However, teams that appear chronically under-utilized likely have more latent capacity to deliver additional value.

The most productive teams achieve a sustainable cadence matching workload to capacity with some reasonable slack. Occasional sprints may finish early or go over time, but the velocity trendline should show consistency avoiding either extreme scenario too frequently.

Keeping Some Capacity Available for Variability

Teams following agile methodology build planning workflows around capacity tradeoffs balancing feature requests, tech-debt, defects, and process improvements. While product owners may push for maximizing new features, teams must calibrate sustainable working pace.

Saving some utilization for non-feature work proves essential for long-term velocity stability and response agility. Scrum reinforces managing resource utilization for optimal flow rather than maximum utilization, helping teams learn patterns balancing productivity with sustainability.

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