SCOPEAUTOMATION
EXAMPLES + PORTFOLIO

THE APPROACH.
PUT INTO PRACTICE.

Real engineering experience, alongside worked examples of how I would approach common MSP problems.

REAL WORK / COMMERCIAL NETWORKS LTD

FROM THE MSP
ENGINE ROOM.

Selected work from my time in support and systems automation engineering at Commercial Networks. Customers are anonymised; prototypes and pilots are identified. These examples are my own account of the work, with no employer endorsement implied.

ILLUSTRATIVE SCENARIOS · FICTIONAL FIGURES

WHAT IMPROVEMENT
COULD LOOK LIKE.

These are hypothetical MSP situations, not clients I worked with or results I achieved. They show the method, the assumptions and how an outcome would be calculated.

WORKED EXAMPLE / 09

Reducing ticket noise

A fictional example of how better alert rules and escalation could change a service desk’s workload.

600 → 180Noise tickets / month

(600 − 180) × 5 assumed minutes ÷ 60 = 35 hours per month. All figures are fictional.

EXPLORE THE SCENARIO
WORKED EXAMPLE / 10

Improving patch compliance

A fictional 1,000-workstation estate demonstrates a controlled patch-compliance improvement plan.

74% → 96%Illustrative compliance

740/1,000 → 960/1,000 compliant devices. Same scope and criteria. All figures are fictional.

EXPLORE THE SCENARIO
WORKED EXAMPLE / 11

Automating repeat support work

A fictional repeat-ticket example connects service-desk evidence to detection, remediation and review.

90 → 30Eligible tickets / month

(90 − 30) × 12 assumed minutes ÷ 60 = 12 hours per month, before maintenance overhead. All figures are fictional.

EXPLORE THE SCENARIO
WORKED EXAMPLE / 12

Disk-space alert optimisation

A fictional example of turning repeated disk alerts into verified recovery and useful escalation.

240 → 60Illustrative tickets / month

(240 − 60) × 6 assumed minutes ÷ 60 = 18 hours per month, before maintenance overhead. All figures are fictional.

EXPLORE THE SCENARIO
WORKED EXAMPLE / 13

Processor-utilisation alert tuning

A fictional example of separating brief CPU spikes from sustained performance incidents.

180 → 45Illustrative tickets / month

(180 − 45) × 4 assumed minutes ÷ 60 = 9 hours per month, before maintenance overhead. All figures are fictional.

EXPLORE THE SCENARIO
LET’S LOOK AT YOUR PLATFORMLET’S MAKE IT USEFUL

GOT SOMETHING
WORTH AUTOMATING?

Tell me where your RMM is creating work.
Let’s look at what could run better —
and how to get there.

LET’S TALK