What is a device health score?

The definition

A device health score condenses a machine's telemetry — storage wear, uncorrected drive errors, battery capacity and charge cycles, thermal throttling, application crashes, patch age, network quality and workload pressure — into a single number or band that a human can act on. Instead of reading twelve graphs per laptop, you read one score per fleet and drill into the machines that need attention.

MSPs use health scores to decide three things: which devices need attention now, which belong in next quarter's refresh budget, and which are fine — and to prove all three to a client who is about to be asked for money.

What signals actually matter

The signals that predict real cost live below the operating system's surface, and most of them never reach an RMM dashboard:

• Storage wear and uncorrected errors — the strongest hardware signal there is. A drive logging uncorrected errors is telling you something; listen before the data does.
• Battery capacity and cycle count — a laptop at 60% design capacity is a productivity problem long before it's a failure.
• Thermal throttling and power-on hours — the difference between "slow laptop" and "cooked laptop".
• Per-application crash counts and patch age — because very often the device is fine and one application is the problem.
• Network quality and workload pressure — a dead Wi-Fi zone and three VMs on an 8 GB machine both masquerade as "failing hardware".

What makes a score trustworthy

It shows its working. A score you can't explain to a client is a liability in a QBR. Every point should trace to a named rule: storage uncorrected errors in the last 7 days → −22 points is an argument; "the AI thinks it's bad" is not.

It's deterministic. Same inputs, same score, every time. If the number can drift without the device changing, nobody will budget against it.

It admits what it can't see. A device with missing signals should say Not assessed — never be shown as a zero or quietly averaged in. A wrong score in front of a client is worse than no score.

It doesn't pretend to predict failures. Google's study of over 100,000 drives found that a large share of failures showed no SMART warning at all, while healthy drives showed the same "warning" signals — and Backblaze's published drive stats keep confirming it. Treat any score with a "failure probability: 92%" badge with suspicion; a condition band with evidence is what the data actually supports.

It diagnoses before it recommends. A useful score distinguishes a degrading SSD (hardware) from a crashing app (software), a Wi-Fi dead zone (network), and an overloaded spec (usage) — because three of those four don't need a new machine.

A worked example

Here is how a rule-based score actually lands on a number. One warehouse laptop, five signals, each tied to a named rule:

Illustrative rules and weights. The point is the shape: every deduction has a name, a reading and a threshold someone can check.

Device health score vs device age

Most refresh lists are still ranked by age: everything over four years gets replaced, everything under it stays. Age is cheap to measure and weakly correlated with the thing you care about. A four-year-old desktop that has spent its life in an air-conditioned office browsing spreadsheets is usually fine; a two-year-old laptop with a cooked battery, worn SSD and three VMs on an 8 GB spec is a ticket factory.

A measured health score reorders that list. In practice it does two commercially interesting things at once: it rescues devices an age policy would have replaced (the biggest hidden saving), and it catches the young machines an age policy would have missed — the ones that generate the angriest tickets. Age still matters as one input; it just stops being the whole policy.

Common questions

How Lilo does it

Lilo runs a lightweight agent on Windows, macOS and Linux, feeds a fixed, published set of signals into a deterministic rules engine, and produces a banded 0–100 score with every point traceable to a named rule — plus the four-category diagnosis, the refresh budget, and a white-label client report. Free up to 25 devices — a commitment, in writing — with published pricing after that.