Slicing through the watermelon effect: Why green SLAs can hide red problems

Here are some classic examples:

• Customer service tickets:
  SLA: Resolve tickets within 48 hours.
  Reality: 95% compliance, but critical issues often take longer than minor ones, leaving customers fuming.
• Call centres:
  SLA: Average call time is under 4 minutes.
  Reality: Agents rush through calls to hit the target, leaving customers with unresolved issues that require repeat calls.
• IT incident management:
  SLA: 99% server uptime.
  Reality: The server is up, but key applications are sluggish or non-functional, causing business disruptions.
• Delivery services:
  SLA: Deliver 98% of orders on time.
  Reality: Sure, the majority are on time, but high-priority shipments are consistently delayed, frustrating key clients.

Read more about the do's and don'ts of metrics here >

• Misaligned priorities: SLAs focus on metrics that are easy to measure, not those that reflect true performance.
• Siloed thinking: Teams work in isolation, focusing on their specific metrics without understanding the bigger picture.
• Over-reliance on averages: Outliers and chronic issues are buried in a sea of "good enough" data.
• Customer detachment: SLAs measure process efficiency rather than actual customer satisfaction.
• Outdated SLAs: Metrics that worked five years ago may no longer align with current business goals.

• Align metrics with organisational goals: Your SLAs should support the bigger picture and align to business metrics. For instance, if your goal is customer retention, measuring satisfaction post-interaction is far more valuable than simply tracking call duration.
• Focus on SMART goals: Ensure your SLAs are Specific, Measurable, Achievable, Relevant, and Time-bound. For example, instead of “reduce delivery issues,” go for “achieve 99% on-time deliveries for high-priority shipments within the next quarter.”
• Drill into the data: Look beyond averages to spot patterns and recurring issues. For instance, if 90% of calls are resolved quickly but the same 10% of customers are repeatedly calling, it’s time to dig deeper.
• Balance quantity and quality: Metrics should measure efficiency and effectiveness. For example, track both ticket resolution times and the percentage of tickets resolved on the first attempt.
• Include the customer’s voice: Measure satisfaction with tools like post-service surveys or Net Promoter Scores (NPS). For example, instead of just measuring incident response time, also gather customer feedback on the resolution process. In other words, use both quantitative and qualitative metrics to get a well-rounded view.
• Encourage collaboration across teams: Break down silos by having regular cross-department meetings to discuss SLA performance and identify shared goals. For instance, link IT response times with customer service satisfaction to understand the broader impact.
• Use real-time monitoring: Dashboards that highlight emerging problems can help you address issues before they escalate. For instance, flagging a spike in unresolved high-priority tickets can trigger immediate intervention.
• Regularly review and adjust SLAs: Don’t let your SLAs gather dust. For example, if customer needs shift toward faster response times during peak periods, your metrics should reflect that.
• Train your teams: Help employees understand why metrics matter. For example, show how ticket resolution speed impacts customer loyalty.
• Communicate outcomes clearly: Share SLA performance transparently with stakeholders. For instance, instead of saying, “We met our uptime target,” explain, “We achieved 99% uptime, ensuring critical applications were available during business hours.”