What is Process Drift?
Process drift is the gradual, often unintentional deviation of operational processes from their designed intent. Unlike sudden process failures or deliberate changes, drift accumulates slowly over time, making it difficult to detect through traditional monitoring.
Think of it like a river gradually changing course. Day to day, the change is imperceptible. But over months or years, the river may be flowing in an entirely different direction than it once was.
The Mechanics of Drift
Process drift typically follows a predictable pattern:
Exception introduced
A team member encounters an edge case and creates a reasonable workaround to handle it.
Exception normalized
The workaround is applied to similar situations. It becomes "how we do things around here."
Knowledge transferred
New team members learn the drifted process as the standard. Original design is forgotten.
Baseline shifted
The drifted process becomes the new baseline. Further exceptions build on this shifted foundation.
Common Causes of Drift
System limitations
Tools that don't quite fit the process lead to workarounds
Volume pressure
Shortcuts taken during peak periods become permanent
Staff turnover
Knowledge gaps filled with improvised solutions
Process complexity
Complicated processes get simplified unofficially
Lack of feedback
No mechanism to detect when drift is occurring
Distributed teams
Different locations develop different variations
Why Drift Matters
Process drift creates several operational risks:
- Efficiency loss: Drifted processes often contain unnecessary steps or redundancies
- Quality degradation: Controls designed into the original process may be bypassed
- Compliance risk: Processes may no longer meet regulatory or policy requirements
- Scaling difficulty: Undocumented variations make it hard to replicate or scale operations
- Training complexity: Multiple process variations create confusion for new team members
Detecting Drift Early
Traditional process monitoring looks at outcomes – cycle times, error rates, throughput. But these metrics often don't move until drift has significantly accumulated.
Operations Listening takes a different approach, monitoring the signals that indicate drift is occurring:
- Step sequence variations from designed flow
- Increasing process bypass frequency
- Time distribution changes within process stages
- Emerging patterns in exception handling
- Divergence between teams or locations
By detecting these signals early, organizations can address drift before it compounds into visible performance impact.
A Preventative Approach
Drift is inevitable in complex operations. The goal isn't to prevent all process variation – some variation is adaptive and valuable. The goal is to maintain visibility into how processes are actually operating, so drift can be assessed and addressed intentionally.
Operations Listening provides this visibility without requiring teams to change how they work or adding reporting overhead. It observes operations as they actually function, surfacing signals that indicate when drift needs attention.