We value your privacy

We use cookies to analyse site traffic and improve your experience. You can accept all cookies or reject non-essential ones. See our Privacy Policy for details.

GR IT SERVICES
  • Contact
Get a quote
  2. Intune and MDM
  3. Endpoint analytics
Microsoft Intune Endpoint analytics, UAE

The laptops are slow. Now you can say which ones, by how much, against what a typical enterprise looks like.

Endpoint analytics scores your estate from 0 to 100, compares it against an anonymised median of all enrolled organisations, and produces a prioritised list of recommendations that each state how many points the score gains when completed. It also scores per device and per model, which is what turns a hardware refresh from a feeling into a case.

Book an endpoint experience reviewSee how the scoring works
Microsoft Intune Endpoint analytics for UAE organisations
  • 0 to 100Score range, lower means room to improve
  • Five devicesThe minimum before a score is produced
  • Median baselineCompare against a typical enterprise
  • Points per fixEach recommendation states its score gain
What it measures

Seven things that make this the most persuasive report in Intune.

Microsoft describes endpoint analytics as exposing score charts that include information about what affects the scores and how to improve them. The three concepts that make the reports readable are scores, baselines, and insights and recommendations, and each does something a raw performance metric cannot.

Scores from 0 to 100, where lower means room to improve

Microsoft states scores range from 0 to 100 and that lower scores indicate there is room for improvement, with the scores helping you understand how each metric affects your environment. A number on that scale is a fundamentally different artefact from a set of timings, because it can be tracked, compared and put in front of somebody who does not read performance data.

A baseline drawn from every enrolled organisation

Baseline scores appear on charts as triangle markers, and there is a built-in baseline for all organisations median which allows you to compare your scores to a typical enterprise. Microsoft anonymises and aggregates scores from all enrolled organisations to keep that baseline current, and notes you can stop gathering data at any time.

Recommendations that state their own value

Insights and recommendations is a prioritised list to improve your score, filtered to the context of whichever report you are in. The detail that makes it actionable is published plainly: the recommendation listed with each insight tells you how to increase the score, and how many points the score gains when the recommendation is complete.

Per device scores, which reach the problem before the helpdesk does

Microsoft describes reviewing scores per device to help find and resolve end user impacting issues before a call is made to the help desk. Selecting a device gives boot history and sign-in history under startup performance, plus an application reliability tab providing insight into potential issues with desktop applications on that machine.

Per model scores, which is the hardware refresh argument

Scores per device model are available in all endpoint analytics reports, and Microsoft states directly that reviewing model scores might help you project and prioritise your next hardware refresh cycle, and help you discover devices that no longer meet your organisation current hardware specifications. That is the report that gets a refresh budget approved.

Filters that turn a number into a diagnosis

Microsoft published example is instructive. In the device performance tab of the startup performance report, filter for devices with a high time to responsive desktop, then add a filter for high Group Policy sign-in time, and you can gauge the effect of Group Policy on user experience for the devices that take longest to become usable.

Five devices minimum, and two documented filter quirks

A status of insufficient data means you do not have enough devices reporting for a meaningful score, and Microsoft states at least five are currently required. Two filter limitations are also published: the disk type filter does not support the value unknown, and filtering on startup performance score from the device scores view returns devices with a score of two dashes.

Why this changes the conversation

A score of 61 against a median of 50 is an argument. Twelve seconds to desktop is a shrug.

Microsoft publishes a worked example, and it is worth reading because it demonstrates exactly how the scores are meant to be used.

  • Quoted: reviewing your startup score, you find that overall your score of 61 is higher than the baseline of 50 for all organisations. That single comparison converts an internal complaint into a position relative to a typical enterprise.
  • Quoted: examining the startup score breakdown, you find that your environment excels during the core boot phase with a score of 77. So the hardware and the boot path are not the problem, which immediately removes the most expensive hypothesis.
  • Quoted: based on the average time it takes to get to a responsive desktop, you suspect long running startup processes are lowering the core sign-in score to 46, and reviewing the top insights and recommendations entry confirms that long running processes are responsible.
  • That is the whole method in four sentences. A comparable score, a breakdown that isolates the phase, and an insight that names the cause and states how many points fixing it returns. It is the rare security or operations report that arrives with its own business case attached.
Ask us to run an endpoint experience baseline
How we approach it

Four things that stop endpoint analytics being another dashboard.

This is a genuinely good report that a large number of organisations have switched on and never used. The gap is not data quality, it is that nobody owns any of the recommendations.

We work the insights in order of stated point value

Microsoft publishes the recommendation alongside each insight, telling you how to increase the score and how many points the score gains when it is complete. That is an unusually clear prioritisation signal and it is right there in the interface. Working the list in that order, rather than by whichever finding somebody noticed, is what produces visible movement.

We put model scores in front of whoever buys hardware

Microsoft states directly that reviewing model scores might help project and prioritise the next hardware refresh cycle, and discover devices that no longer meet current hardware specifications. Most organisations decide refresh by age. Deciding it by measured user experience per model is both cheaper and considerably easier to justify.

We create a custom baseline on day one

The built-in all organisations median tells you where you stand relative to a typical enterprise. A baseline created from your current metrics tells you whether you are improving, which is the question that matters after the first month. Creating it before any remediation is what makes the improvement provable rather than asserted.

We give the helpdesk the per device view

Boot history, sign-in history and application reliability for a named device, reachable from the user experience page. Microsoft frames per device scores as helping find and resolve end user impacting issues before a call is made. In practice it changes the call itself, because the technician opens the ticket already knowing what the machine has been doing.

Where this matters most

Six UAE situations where measured endpoint experience settles an argument.

The common thread is a disagreement that nobody can resolve with evidence: whether the machines are slow, whether it is getting worse, and whether new hardware would actually help.

A business being asked to justify a hardware refresh

Scores per device model, available across all endpoint analytics reports, with Microsoft explicitly framing them as helping project and prioritise the next refresh cycle and discover devices that no longer meet current hardware specifications. A refresh proposal built on measured user experience per model is a different document from one built on purchase date.

An organisation where users say it is slow and IT says it is not

The score against the all organisations median settles the first half of that argument, and the breakdown between boot and sign-in phases settles the second. Microsoft own worked example shows a boot phase scoring 77 and a sign-in phase scoring 46, which points at long running startup processes rather than at the hardware everybody assumed.

A firm that has just migrated to Intune and needs to show value

A custom baseline created at go-live, with the score tracked monthly against it, produces a straightforward before and after. Combined with insights that each state the points gained on completion, it gives a programme something to report that is neither a project milestone nor a device count.

An operator whose sign-in times are hurting shift changeover

Where staff sign in and out repeatedly through a day, sign-in time is not a comfort issue, it is a productivity one. The startup performance report with filters on time to responsive desktop and Group Policy sign-in time, which is Microsoft own published example, isolates whether policy processing is the cause and how many devices it affects.

A healthcare organisation with shared clinical workstations

Shared machines take the worst of every startup and sign-in problem because the cycle repeats all day. Per device scores identify the specific machines, and application reliability per device gives insight into potential issues with the desktop applications running on them, which on a clinical workstation is usually where the real complaint sits.

An institution with a large and varied device estate

Many models, many ages, many procurement decisions made by different people over years. Model scores available in every report turn that into a ranked list, and filters let you find what the worst affected devices have in common rather than treating each complaint as an isolated incident.

Three positions

How UAE organisations know whether their devices are any good.

The middle column is nearly universal. IT knows from tickets that something is slow, users know it is slow, and nobody can say by how much, on which machines, or whether it is getting better.
Startup experience measured
Measured with endpoint analyticsYes
Anecdote and ticket volumeNo
No visibility at allNo
Application reliability measured
Measured with endpoint analyticsYes
Anecdote and ticket volumeNo
No visibility at allNo
Comparable to other organisations
Measured with endpoint analyticsYes
Anecdote and ticket volumeNo
No visibility at allNo
Improvement tracked over time
Measured with endpoint analyticsYes
Anecdote and ticket volumeNo
No visibility at allNo
Recommendations quantified
Measured with endpoint analyticsYes
Anecdote and ticket volumeNo
No visibility at allNo
Worst devices identifiable by name
Measured with endpoint analyticsYes
Anecdote and ticket volumeBy complaint
No visibility at allNo
Hardware refresh evidence available
Measured with endpoint analyticsYes
Anecdote and ticket volumeNo
No visibility at allNo
Problems found before the helpdesk call
Measured with endpoint analyticsSometimes
Anecdote and ticket volumeNo
No visibility at allNo
Reportable to a business audience
Measured with endpoint analyticsYes
Anecdote and ticket volumeNot credibly
No visibility at allNo
Cost to obtain
Measured with endpoint analyticsConfiguration
Anecdote and ticket volumeNot applicable
No visibility at allNot applicable
Feature
Measured with endpoint analytics
Anecdote and ticket volume
No visibility at all
Startup experience measured
YesNoNo
Application reliability measured
YesNoNo
Comparable to other organisations
YesNoNo
Improvement tracked over time
YesNoNo
Recommendations quantified
YesNoNo
Worst devices identifiable by name
YesBy complaintNo
Hardware refresh evidence available
YesNoNo
Problems found before the helpdesk call
SometimesNoNo
Reportable to a business audience
YesNot crediblyNo
Cost to obtain
ConfigurationNot applicableNot applicable
The three views

Organisation, device and model, and what each is for.

Views as published. Each answers a different question, and using the wrong one is why some organisations conclude the reports are not useful.
ViewWhat it showsThe question it answers
Organisation scoreOverall scores from 0 to 100 with breakdowns, against the all organisations median baselineAre we better or worse than a typical enterprise, and in which phase
Custom baselinesBaselines created from your current metrics, shown as triangle markers on chartsAre we improving or regressing against where we were
Insights and recommendationsA prioritised list, filtered to the report context, each stating the points gained on completionWhat should we fix first, and what is it worth
Device scoresIndividual device scores, sortable, with boot and sign-in history and application reliability per deviceWhich specific machines are giving users a bad experience
Model scoresScores per device model, available in all endpoint analytics reportsWhich hardware should be refreshed first, and what no longer meets specification
Report filtersMultiple stacked filters on report tables, such as time to responsive desktop plus Group Policy sign-in timeWhat do the worst affected devices have in common
User experience pageEndpoint analytics, startup performance and application reliability for one deviceWhat is happening on the machine this user is complaining about
How an engagement runs

Five steps, and the baseline has to come before the fixes.

Typically four to eight weeks for a first cycle, then a monthly rhythm. Getting data is quick. Assigning owners to recommendations, and reporting the trend, is what makes it a practice.
  1. 1

    Confirm data is arriving and is meaningful

    At least five devices reporting, since Microsoft states below that the status is insufficient data and no meaningful score is produced. Windows health monitoring configured so event data reaches endpoint analytics. And a check that the populations reporting are representative, since the scores reflect the devices that report rather than the devices that exist.

  2. 2

    Create a custom baseline before changing anything

    The built-in all organisations median baseline shows where you stand against a typical enterprise. A baseline created from your current metrics is what lets you demonstrate improvement or spot regression later. Creating it after remediation has started makes the improvement unprovable, which is a small mistake with a lasting consequence.

  3. 3

    Work the insights in stated point order

    Each recommendation tells you how to increase the score and how many points the score gains on completion. Working them in that order, with an owner named against each, is what produces movement. Insights are filtered to the context of the report you are in, so the same discipline applies within startup performance and application reliability separately.

  4. 4

    Use the device and model views for the two other audiences

    Per device scores handed to the service desk, so boot history, sign-in history and application reliability are available before a technician picks up a ticket. Per model scores handed to whoever makes hardware decisions, as the evidence for refresh sequencing and for identifying models that no longer meet specification.

  5. 5

    Establish the monthly review and the reporting line

    Score against the custom baseline and against the median, the top insights and who owns them, and the model ranking. The score presents unusually well to a non-technical audience, which makes it one of the few operational metrics worth putting in a monthly business report rather than an IT one.

Straight answers

What organisations ask about endpoint analytics.

Microsoft states endpoint analytics scores range from 0 to 100 and that lower scores indicate there is room for improvement, with scores helping you understand how each metric affects your environment. The value is comparative rather than absolute: against the all organisations median baseline, and against a baseline created from your own earlier metrics.

Not enough devices are reporting. Microsoft states that a status of insufficient data means you do not have enough devices reporting to provide a meaningful score, and that at least five devices are currently required. In a small pilot that is the first thing to check before concluding anything about the environment.

A built-in baseline that lets you compare your scores to a typical enterprise, shown on charts as a triangle marker. Microsoft states it anonymises and aggregates scores from all enrolled organisations to keep that baseline up to date, and that you can stop gathering data at any time if you would rather not contribute.

Yes, by creating custom baselines based on your current metrics, which Microsoft describes as letting you track progress or view regressions over time. Doing this before any remediation work begins is important, because a baseline created afterwards makes it impossible to demonstrate what the work actually achieved.

The insights and recommendations list, which Microsoft describes as a prioritised list to improve your score. The part that makes it genuinely actionable is that the recommendation listed with each insight tells you how to increase the score and how many points the score gains when the recommendation is complete. Very few operational reports come with that.

Yes, through the device scores tab on the main endpoint analytics page, which can be sorted to find devices needing attention. Selecting a device gives boot history and sign-in history under startup performance, and an application reliability tab providing insight into potential issues for desktop applications on that machine. The same information is on a device user experience page.

That is one of its stronger uses, and Microsoft says so directly. Scores per device model are available in all endpoint analytics reports, and reviewing model scores might help you project and prioritise your next hardware refresh cycle, as well as discover devices that no longer meet your organisation current hardware specifications.

With stacked filters. Microsoft published example uses the device performance tab of the startup performance report, filtering to identify devices with a high time to responsive desktop, then adding a second filter for high Group Policy sign-in time, which lets you gauge the effect of Group Policy on user experience for the devices that take longest to become usable.

Two published filter limitations. The disk type filter does not support the value unknown, and filtering on startup performance score from the overview device scores view returns devices with a score of two dashes. Microsoft also notes you may see small differences in values when comparing detailed reporting to the less granular scores for devices and models.

Endpoint analytics is designed around Intune-managed and co-managed estates, and the specific enablement path depends on how devices are managed and whether Windows health monitoring is configured. That is one of the first things we establish, because the answer determines whether the scores reflect your whole estate or only part of it.

No, and that is worth being clear about. It measures user experience: startup performance, application reliability and related metrics. It is genuinely useful alongside a security programme, because slow devices are a real driver of workaround behaviour, but the reports answer questions about experience and hardware rather than about threats or compliance.

Three audiences with three views. The service desk uses per device scores to understand a machine before a technician picks up the ticket. The engineering team works the insights list. And whoever makes hardware decisions uses model scores. Giving each of them the view that answers their question is what stops it being a dashboard nobody opens.

Monthly, against your custom baseline. The value is in the trend rather than in any single snapshot, and a monthly cadence is frequent enough to notice a regression and infrequent enough that the review remains worth attending. It also fits the natural rhythm of insight work, since most recommendations take more than a fortnight to complete.

That is a useful finding and it does not mean there is nothing to do. Microsoft own worked example has an overall startup score of 61 against a median of 50, with a boot phase scoring 77 and a sign-in phase scoring 46. Being above the median overall while a specific phase is well below it is exactly the pattern the breakdown is designed to expose.

We scope per organisation, driven by estate size and whether you want the remediation work run or only the analysis delivered. The first cycle, establishing data quality, creating a baseline and working the top insights, is typically four to eight weeks, after which most organisations run the monthly review themselves.
Making it useful

Fifteen questions that turn scores into decisions.

The first group is getting meaningful data, the second is reading it correctly, and the third is the part organisations skip: doing something with it on a schedule.

Getting data

  • Do you have at least five devices reporting?
    Below that, the status is insufficient data.
  • Is Windows health monitoring configured?
    It feeds event data to endpoint analytics.
  • Are the right device populations enrolled?
    Scores reflect what reports, not what exists.
  • Do you want to contribute to the median?
    You can stop gathering data at any time.
  • Has a custom baseline been created?
    It is how you measure your own progress.

Reading it

  • How do you compare to the median?
    That is the built-in baseline.
  • Which phase is dragging the score?
    Boot and sign-in score separately.
  • What do the top insights say?
    Each states its own point value.
  • Which models score worst?
    That is the refresh priority list.
  • Which individual devices are outliers?
    Sort the device scores tab.

Acting on it

  • Who owns the highest value recommendation?
    An insight without an owner is a chart.
  • Is the score reported to anybody?
    It presents unusually well to a business audience.
  • Is it reviewed monthly?
    The value is the trend, not the snapshot.
  • Does the helpdesk use per device scores?
    They can pre-empt the call.
  • Does procurement see model scores?
    That is the hardware evidence.
Related reading

The pages around this one.

Windows Autopatch

Update management, which is frequently where a startup or reliability finding leads.

Learn more

Intune configuration profiles

Where a Group Policy sign-in finding usually gets resolved.

Learn more

Microsoft Intune

The product overview and where endpoint analytics sits within it.

Learn more
Next step

Look at your score against the median. It takes a minute and it usually surprises somebody.

Either you are above it, which is worth knowing and reporting, or you are below it, which is the start of a much more productive conversation than the one about whether the laptops are slow.

Book an endpoint experience reviewCall +971 56 613 2743

Related Services

Explore more solutions that work great with this service

Windows Autopatch

Security updates without a restart, and Business Premium has it

Learn more

Intune Configuration Profiles

Settings catalog, templates and conflict management

Learn more

Microsoft Intune

Device management and endpoint security

Learn more

MDM Solutions Dubai

Device management across Windows, Apple and Android

Learn more

Managed IT Services

Complete outsourced IT department

Learn more

Windows Autopilot Dubai

Zero-touch laptop deployment, supplier registration onward

Learn more

IT Support Dubai

24/7 on-site and remote IT support

Learn more

Win32 App Packaging

Packaging, detection rules and deployment that works

Learn more
GR IT SERVICES

Leading IT services provider in Dubai,
delivering enterprise-grade solutions
for businesses across the UAE.

Microsoft CSP PartnerCISGuard

Get the Helpdesk app

Raise and track IT tickets from your phone.

Download on the App StoreGet it on Google Play
Learn more about the app

Microsoft 365

  • Microsoft 365 Administration
  • M365 Reporting & Auditing
  • Microsoft 365 Licensing
  • Microsoft Copilot
  • Microsoft 365 Apps
  • Windows 365 Cloud PC
  • Microsoft SharePoint
  • Outlook & Exchange

Security

  • Microsoft Defender
  • Microsoft Purview
  • Microsoft Intune
  • Microsoft Entra
  • Compliance Manager
  • Cybersecurity Audits
  • Copilot for Security
  • Microsoft Sentinel
  • Microsoft Priva

Infrastructure

  • Google Workspace
  • Cloud Migration Services
  • Data Analytics & BI
  • Active Directory
  • Server Management
  • Apple Business
  • Apple Jamf Pro
  • IP Telephone
  • Data Backup
  • Website Development

IT Services

  • Managed IT Services
  • IT Support Dubai
  • IT AMC Dubai
  • New Office IT Setup
  • IT Relocation
  • Remote IT Support
  • On-Call IT Support
  • Startup IT Business Kit
  • Disaster Recovery & BC

Company

  • About Us
  • Careers
  • Contact
  • Blog

Contact

  • Iris Bay Tower, Office 903,
    Business Bay, Dubai, UAE
  • +971 56 613 2743
  • hello@gritservices.ae
  • gritservices.ae

© 2026 GR IT Services. All rights reserved.

Privacy PolicyTerms of UseCookie Policy