Yemen Telecom Customer Trust Reset: SLAs, Complaint Operations, and “Trust KPIs”

Why this is a board-level issue

In a post‑peace operating environment, customers don’t judge a telecom operator only on performance. They judge it on predictability. When service is variable, the brand differentiator becomes clarity: what you promise, how you communicate, and how reliably you resolve issues.

“In fragile markets, trust is not a brand attribute. It is the product.”

For Yemen telecom leaders, a trust reset is not a marketing campaign. It is an operating model: an explicit set of service promises, a disciplined complaint-to-root-cause loop, and a scorecard the CEO can review weekly.

Executive summary (what to do in 30–60 days)

1. Publish realistic SLAs (consumer and enterprise) aligned to your “Minimum Viable Network” priorities.

2. Run complaints like an operations signal, not a call‑center activity: taxonomy, root cause mapping, and closure discipline.

3. Implement “Trust KPIs” that connect network stability, billing integrity, and resolution times into one board view.

4. Standardise communications: incident updates, restoration ETAs, and clear customer compensation rules (especially for enterprise).

“Your SLA is not a contract clause. It is your public operating discipline.”

The core decision: What are you willing to promise—and consistently deliver?

The most common failure mode is promising international‑grade SLAs while operating with recovery‑phase constraints. The second most common failure mode is promising nothing, which invites churn and reputational damage.

A practical approach is to define three tiers of promises:

• Tier 1 (Critical services): emergency/critical corridors, core dependencies, priority enterprise sites

• Tier 2 (Primary commercial demand): high-usage areas, major business districts, dense residential corridors

• Tier 3 (Coverage expansion / long tail): lower demand, less dependency, delivered as capacity allows

Y

ou do not need to publicly label them Tier 1/2/3. You do need to operate that way internally.

Step 1 (Weeks 1–2): Build “SLA truth” before you publish anything

Before you write an SLA, define what “available” means across your service portfolio:

• Mobile: attach success rate, session retainability, data throughput bands, voice call completion

• Fixed: line availability, packet loss, latency bands, mean time to repair

• Top‑up/recharge: success rate and average completion time

• Billing: dispute cycle time, refund/adjustment policy and timeline

Then choose a small set of external promises that you can meet.

A credible consumer SLA set (example categories)

• Fault acknowledgement time (e.g., within X hours)

• Update cadence (e.g., every X hours during major incidents)

• Restoration target bands (not fake precision)

• Complaint resolution targets by category (billing vs coverage vs service outage)

A credible enterprise SLA set

• Incident response time by severity (P1/P2/P3)

• Restoration target bands + escalation ladder

• Planned maintenance notice period

• Service credits rules (standardised, not negotiated ad hoc)

“If you cannot measure it daily, don’t promise it publicly.”

Step 2 (Weeks 2–4): Turn complaints into an engineering signal

In high-variability environments, complaints are the most underutilised diagnostic data source.

“Every unresolved complaint is a hidden network ticket.”

Build a complaint taxonomy that engineering respects

Most complaint systems fail because they are categorised for call‑centre reporting rather than root cause.

A Yemen telecom-ready taxonomy should map directly to technical and commercial workstreams:

• Network availability: site outages, weak signal, congestion

• Transport/backhaul: intermittent data, high latency, dropouts

• Power-related instability: recurring downtime patterns by site cluster

• Top‑up/recharge failures: channel outages, confirmation delays, duplicate deductions

• Billing/rating issues: unexpected deductions, bundle entitlement problems, failed renewals

• Device/SIM/account: provisioning, SIM swap issues, ID/KYC friction (where applicable)

• Enterprise SLA incidents: last-mile faults, CPE issues, access constraints, planned works disputes

Add a “Root Cause Owner” to every complaint category

Assign each category to a named owner in:

• Network Ops

• IT/BSS

• Distribution/Channels

• Enterprise Service Delivery

Make those owners review weekly patterns and publish corrective actions.

Step 3 (Weeks 3–6): Create the “Trust Loop” operating rhythm

A trust reset requires one meeting and one dashboard that the CEO can rely on.

Weekly Trust Loop (60 minutes)

• Inputs: complaint trends, top 10 repeat incidents, enterprise escalations, billing disputes

• Decision outputs: which clusters get fuel/spares/field teams, which product rules get fixed, what customer comms gets published

• Closure discipline: each recurring issue must have a fix owner and a closure date

A high-functioning trust loop does not look like a “customer experience” meeting. It looks like an operations meeting with customer data.

“Customer experience is operations—measured in public.”

Step 4 (Weeks 4–8): Standardise communications so you stop negotiating trust case-by-case

In post‑peace contexts, inconsistency is reputational poison. Customers forgive outages more easily than they forgive opacity.

Minimum communication standards (practical, not aspirational)

• Major incident updates: a fixed cadence (e.g., every 4 hours)

• ETA language: use time bands, not false precision (“within 24–48 hours” rather than “3pm”)

• Public restoration principles: what you prioritise and why (critical services, national corridors, enterprise dependencies)

• Single source of truth: one page/channel where updates live consistently

• Enterprise comms: named owner + written incident summary within 24 hours of restoration

The Trust KPI set (what the CEO should track weekly)

You will be tempted to include 30 metrics. Don’t. Use a balanced Trust KPI set that connects service reliability to customer and revenue outcomes:

Reliability + service integrity

• Network availability (overall and priority clusters)

• Major incidents: count, duration, repeat rate

• Top‑up success rate

• Billing disputes per 10,000 subscribers

Customer experience

• Complaints per 10,000 subscribers (trend)

• First-contact resolution rate

• Complaint resolution time (median + 90th percentile)

• Enterprise escalations: count and time-to-restore

Commercial outcomes

• Churn proxy (disconnects / inactivity trend)

• Adjustments/refunds as % of revenue (watch for billing integrity issues)

“If your trust KPIs don’t change operational decisions, they’re not KPIs. They’re decoration.”

Common failure modes (avoid these)

• Publishing SLAs that operations cannot meet (creates legal and reputational risk)

• Treating complaints as “call centre noise” (you lose your most valuable diagnostic feed)

• No service credit rules for enterprise (you end up negotiating under pressure)

• Too many channels for updates (customers don’t know what to believe)

• No closure discipline (repeat incidents become “normal”)

What “good” looks like by Day 60

• Published, measurable consumer and enterprise SLA commitments

• Complaint taxonomy mapped to root cause owners

• Weekly Trust Loop meeting with documented corrective actions

• Visible improvement in repeat incidents and resolution time

• A CEO-level Trust KPI dashboard with trends and thresholds

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