The contract says "queries must be resolved within 48 hours." That sounds precise. But does anyone actually check? When was the last time someone measured whether queries are actually being resolved in 48 hours—or whether it routinely takes two weeks while everyone pretends the SLA is being met?

Service level agreements are only as good as their enforcement. Without measurement, they're aspirational statements rather than operational requirements. And without automated measurement, they're probably not being measured at all.

The Measurement Gap

Most organisations have service level agreements with their suppliers. Delivery times. Response times. Quality thresholds. Uptime guarantees. The contracts are full of specific, measurable commitments.

But the measurement often doesn't happen. The SLAs were negotiated by contracts, implemented by operations, and monitored by—nobody in particular. The requirements exist in documents that nobody refers to. Performance happens without anyone checking whether it meets the commitments.

This gap is surprisingly common. A contract might specify 99% on-time delivery, but nobody is calculating the actual percentage. A service level might promise four-hour response, but nobody is timing responses. The commitment exists; the verification doesn't.

The result is that SLAs don't drive behaviour. Suppliers learn that the requirements aren't actually enforced. Internal teams don't know whether they're receiving what was promised. The negotiating leverage created by the SLA goes unused.

Automating the Tracking

Automated SLA tracking solves this problem by building measurement into the systems that manage supplier interactions.

When an issue is raised, the clock starts automatically. The system knows the priority level, looks up the applicable SLA, and begins tracking time. As the issue progresses—or doesn't progress—the system compares elapsed time against targets.

At defined thresholds, actions trigger. At 80% of SLA time, perhaps a warning goes to the assignee. At 100%, the issue is flagged as breaching. At 150%, escalation activates. The response is proportionate and automatic.

Reporting aggregates performance over time. What percentage of issues met their SLA? What's the average resolution time compared to target? Which suppliers or issue types have the worst performance? The data enables management rather than assumption.

Setting Appropriate Levels

SLA definitions must balance ambition with reality. Unrealistically aggressive targets—where breach is normal—become meaningless. Excessively loose targets—where compliance is trivial—don't drive improvement.

Good SLAs reflect what should be achievable with reasonable effort. They're stretching but not impossible. Compliance should be the norm, with breaches being exceptions that warrant attention.

Differentiation by priority is essential. Not every issue warrants the same urgency. A Priority 1 issue affecting production needs rapid response. A Priority 3 administrative query can wait longer. SLAs should reflect these different urgency levels.

Differentiation by issue type may also make sense. Complex issues that require investigation naturally take longer than simple queries. Setting the same target for both creates either impossibly tight deadlines for complexity or meaninglessly loose deadlines for simplicity.

The Supplier Conversation

SLA tracking changes supplier conversations. Instead of general impressions—"response feels slow"—you have specific data. "Your average resolution time last quarter was 4.3 days against a 2-day SLA, with 67% of issues breaching."

This specificity enables improvement discussions. Where are the failures occurring? What causes delays? What would it take to improve? The conversation becomes collaborative problem-solving rather than vague complaint.

For suppliers consistently meeting or exceeding SLAs, the data provides positive reinforcement. Recognition that they're delivering on commitments. Evidence to support contract renewal or expansion. Validation that their investment in service capability is paying off.

When SLAs are genuinely unachievable, the data reveals this too. If every supplier in a category breaches the same SLA, perhaps the SLA is wrong rather than the suppliers. Data-driven recalibration is better than maintaining fiction.

Internal Application

SLA tracking isn't only for supplier performance. Internal teams have performance expectations too—how quickly procurement responds to requisitions, how fast contracts are reviewed, how promptly supplier queries are addressed.

Applying the same measurement discipline internally ensures consistent service. Internal customers know what to expect. Teams have clear targets. Performance becomes visible and manageable.

This internal application can be uncomfortable. Departments that have avoided scrutiny may resist measurement. But the benefits of consistent service levels and clear expectations outweigh the discomfort of transparency.

Connecting to Consequences

Measurement without consequence is just observation. SLA tracking becomes powerful when connected to outcomes that matter.

Commercial consequences might be built into contracts. Service credits when SLAs are missed. Payment adjustments tied to performance metrics. Termination rights if breaches persist. These mechanisms create financial incentive for compliance.

Relationship consequences matter even without commercial mechanisms. Suppliers who consistently breach SLAs should face scrutiny at business reviews. Their position on preferred supplier lists should be questioned. Future opportunity should depend on reliable performance.

Recognition for excellence is equally important. Suppliers who exceed SLAs deserve acknowledgment. Performance data should inform decisions about contract renewal and expansion. Being an excellent performer should be visibly rewarded.

Avoiding Gaming

Any measurement system invites gaming. If resolution time is measured from issue logging, suppliers might discourage logging. If the clock stops when they respond, they might send hollow responses that don't actually resolve anything. If priority affects targets, disputes about priority might delay issues further.

Good system design anticipates gaming and builds in countermeasures. Resolution should be verified rather than just claimed. Priorities should be defined by objective criteria rather than negotiated case-by-case. Multiple metrics should balance each other so gaming one doesn't improve overall performance.

Human oversight remains essential. Automated systems measure; humans interpret. An issue technically meeting SLA but leaving the customer unhappy hasn't really succeeded. Blending automated metrics with qualitative assessment provides complete picture.

The Cultural Shift

Implementing SLA tracking often requires cultural change. For organisations that have operated on informal understanding rather than measured performance, introducing metrics can feel bureaucratic or distrustful.

Framing matters. SLA tracking isn't about distrust—it's about clarity. It protects good performers from unfair criticism. It identifies where improvement is needed. It creates shared understanding of expectations and performance.

Gradualism can help. Starting with a few high-priority issue types and expanding over time gives everyone space to adapt. Celebrating successes and handling failures constructively builds confidence in the approach.

Eventually, SLA tracking becomes normal—expected infrastructure for managing supplier relationships rather than exceptional oversight. Organisations that have embedded this discipline wonder how they ever managed without it.

From Enforcement to Partnership

The mature use of SLA tracking is less about enforcement and more about continuous improvement. When both you and your suppliers can see the same performance data, the relationship becomes more collaborative.

Joint problem-solving focuses on improving metrics that both parties can see. Root cause analysis of breaches leads to process improvements. Targets evolve as capabilities develop. The SLA becomes a tool for improvement rather than just a stick for punishment.

This partnership approach requires trust that the data is accurate and the interpretation is fair. Building that trust takes time and consistent behaviour. But the result—mutual commitment to measured, improving performance—is worth the investment.