Data protection sounds simple until you sit in front of the Purview admin centre with a blank policy and a business that hasn’t slowed down to wait for you. I’ve deployed DLP across enough tenants now to have opinions about what works and what quietly causes chaos six weeks later. Here they are.

Don’t start with policies. Start with looking.

The single most common mistake I see is someone jumping straight into policy creation before they’ve spent any real time in Content Explorer.

You can’t protect what you haven’t found. Before you write a single rule, go and look at where sensitive data actually lives, who’s touching it, and how it’s currently being shared. Most of that sharing is legitimate. Some of it isn’t. You won’t know which is which until you look.

Ask yourself the boring but essential questions:

• Where does personal data actually sit?
• Who in the business handles financial information day to day?
• Is anything sensitive leaking out externally right now?
• Which Teams or SharePoint sites are quietly holding regulated content nobody’s thought about?

This discovery phase is unglamorous. It’s also the difference between a DLP programme people trust and one they route around.

Get your labelling sorted first

DLP on its own is decent. DLP paired with Purview Information Protection is genuinely useful.

Roll out sensitivity labels, turn on auto-labelling for existing content, and use mandatory labelling with inheritance where it makes sense. A typical label set looks something like Public, General, Confidential, Highly Confidential, and Highly Confidential – Restricted.

Once labels are in place, your DLP policies get a lot smarter. Instead of relying purely on pattern matching, you can build conditions around the label itself. A policy blocking anything marked “Highly Confidential” from leaving the tenant doesn’t care whether the content matches a regex — it just knows the label says no.

Custom Sensitive Information Types are worth the investment too, especially for anything business-specific. They catch data that generic patterns miss, and you can feed them into auto-labelling so files get tagged correctly without someone doing it by hand.

Audit mode isn’t optional — it’s the whole point

Please don’t flip a policy straight to enforcement. I’ve seen it done, and it’s rarely pretty.

Purview lets you run policies in simulation or audit mode first, and that time is worth every minute. You’ll see false positives you didn’t expect, get a real sense of alert volume, and gather feedback before anyone’s inbox gets blocked mid-deal.

A deployment sequence that actually holds up in practice:

1. Discover and assess.
2. Deploy in audit mode.
3. Review the incidents that come in.
4. Fine-tune the conditions.
5. Turn on user notifications.
6. Move to enforcement.

Skip steps and you’ll spend your first week of enforcement fielding complaints instead of reviewing genuine risk.

Protect the data that actually matters, first

Trying to lock down every category of sensitive information on day one is a recipe for an alert queue nobody will ever clear. Pick your highest-risk data and start there:

• Intellectual property
• Payment card information
• National Insurance and Social Security numbers
• Passport details
• Banking information
• Healthcare records
• Customer personal data

Getting this right early builds confidence in the programme. Getting it wrong — trying to boil the ocean — burns goodwill you’ll need later.

Built-in SITs are a good starting point, not a finish line

Microsoft ships hundreds of pre-built Sensitive Information Types — UK National Insurance numbers, credit card numbers, IBANs, passport numbers, NHS numbers, tax IDs, and plenty more. They’re updated regularly, and they get you moving quickly.

They also throw up more false positives than you’d like. That’s just the nature of pattern matching at scale. Check the accuracy before you enforce anything based on them, and where you’ve got genuinely business-specific data, build custom SITs, Exact Data Match classifiers, or trainable classifiers instead. The accuracy improvement is worth the setup time.

Policy Tips do more work than people give them credit for

DLP isn’t only about blocking. A lot of its value comes from simply telling people what’s going on, in the moment, before they make a mistake.

Policy Tips do exactly that — a quiet warning when someone’s about to email something sensitive externally, with a nudge towards the secure alternative. Users who understand why something’s restricted tend to adjust their behaviour. That means fewer repeat alerts and less friction down the line.

Alert fatigue will kill your programme faster than any misconfiguration

I’ve walked into tenants generating thousands of DLP alerts a month that nobody has looked at in weeks. That’s not a security control — it’s noise.

Tune severity levels properly, route incidents to whoever can actually act on them, and connect things into Microsoft Defender XDR where it makes sense. Review trends regularly. A DLP policy that nobody’s watching isn’t protecting anything.

Don’t forget the endpoint

Sensitive data doesn’t stay neatly inside Microsoft 365. Endpoint DLP extends control out to endpoint devices, covering things like:

• USB transfers
• Printing
• Copying to network shares
• Clipboard activity
• Uploads to unapproved cloud services

If you’re working towards Zero Trust, endpoint protection isn’t an add-on to your DLP deployment — it’s part of it from the start.

Talk to the business before you write the policy

Security teams have a habit of designing policies around technical requirements and forgetting the business workflows sitting underneath them.

Bring in legal, compliance, data owners, and information governance early. Finance might have a completely legitimate reason to send payroll data to a trusted third party — block that without understanding it first, and you’ll be firefighting an exception request within the week. Understanding legitimate use cases up front saves you from a pile of exceptions later, and it gets the business on side rather than working around you.

Make it risk-aware, not just rule-aware

Modern DLP shouldn’t treat every user the same. Purview can integrate with Insider Risk Management and Adaptive Protection, which lets enforcement flex based on actual risk signals — tighter controls for high-risk users, closer monitoring during someone’s notice period, extra restrictions when risky behaviour shows up.

This gives you stronger protection where it’s needed, without piling controls onto everyone regardless of risk.

Test it like it’s real, because it will be

Lab testing tells you a policy technically works. It doesn’t tell you how it behaves in the hands of an actual user. Test against realistic scenarios — external sharing, Teams messages, email attachments, USB copying, SharePoint uploads, and increasingly, AI-assisted content generation. Pull in real users from different departments before go-live, not just your own team.

Measure it, or you’re just guessing

A DLP programme needs numbers behind it. Track the reduction in sensitive data exposure, the number of policy matches, how often users override a block, external sharing trends, incident response times, and activity from high-risk users. Purview’s analytics and reporting give you a genuine read on whether the programme is working — use them.

The bigger picture

DLP works best as part of something larger, not on its own. Tied into the rest of the Purview suite and the wider Microsoft Security stack, it becomes part of a proper Zero Trust data security strategy rather than a standalone control that catches some things and misses others.

My Final Thoughts

Microsoft Purview DLP is a strong capability, but the deployment is what makes or breaks it. Start with discovery, get classification right, run everything through audit mode before enforcing, use Policy Tips to educate rather than just block, and keep refining as the business changes.

The point of DLP was never to stop people working. It’s to let people keep collaborating while the sensitive stuff stays where it should. With hybrid working, AI tools, and regulatory requirements all moving at once, that balance matters more than it used to — and Purview DLP, deployed properly, is still one of the better ways to strike it.

Insider threats are often among the hardest security risks to detect. Unlike external attackers, insiders already have access to systems, applications, and data. Whether the result of malicious intent, poor judgement, or simple human error, insider activities can lead to data loss, intellectual property theft, compliance violations, and significant reputational damage.

Microsoft Purview Insider Risk Management (IRM) helps organisations identify potentially risky user behaviour by analysing signals from across Microsoft 365, endpoint devices, Microsoft Defender, and other connected services. When configured correctly, it provides security and compliance teams with valuable insights into activities that might otherwise go unnoticed.

The challenge, however, isn’t deploying IRM—it’s tuning it effectively. A poorly configured implementation can overwhelm analysts with alerts, making it difficult to distinguish genuine risks from normal business activity. In this article, we’ll look at how to configure IRM policies and, more importantly, how to tune them to produce meaningful, actionable results.

Understanding Insider Risk Management

Microsoft Purview IRM correlates signals from multiple Microsoft services to build a picture of user behaviour and identify activities that may need investigation.

Common scenarios organisations use IRM to detect include:

• Employees copying sensitive information before leaving the business.
• Unauthorised sharing of confidential files.
• Excessive downloading or copying of corporate data.
• Uploading business information to personal cloud storage platforms.
• Printing or exporting high-value documents outside normal working patterns.

Rather than relying solely on predefined rules, IRM incorporates behavioural analytics and machine learning to help you identify activity that deviates from the norm.

Why Tuning Matters

One of the most common mistakes I see during deployments is the assumption that IRM will deliver high-quality results immediately after being enabled.

In reality, every organisation has different working practices, risk tolerances, and data protection requirements. What may be considered suspicious behaviour in one environment could be completely normal in another.

For example, a software development team may legitimately access large numbers of files every day, while a finance department may regularly transfer sensitive spreadsheets between systems. Without appropriate tuning, these everyday activities can easily generate false positives.

The objective should never be to generate the highest number of alerts. The goal is to highlight the activities that genuinely deserve investigation while keeping alert volumes manageable for analysts.

Creating an Insider Risk Management Policy

Creating a policy is straightforward. Within the Microsoft Purview portal, navigate to:

Insider Risk Management → Policies → Create Policy

Microsoft provides several built-in templates covering common risk scenarios, including:

• Data theft by departing employees
• Data leaks
• Data leaks by risky users
• Data leaks by priority users
• Risky AI usage
• Security policy violations
• Industry-specific templates for healthcare (in Preview)
• Risky browser usage (in Preview)

These built-in templates provide an excellent starting point. They show the prerequisites for each template, including optional, recommended and required connectors and configurations.

Be Careful with User Scope

Determining who should be monitored is one of the most important decisions you’ll make during implementation.

Although it may be tempting to monitor every user from day one, doing so often creates unnecessary noise and makes it harder to assess how well policies are performing.

A better approach is to begin with a controlled pilot group, such as:

• IT administrators
• Finance personnel
• Research and development teams
• Users handling highly sensitive data

This allows security teams to validate policy effectiveness and establish behavioural baselines before expanding coverage across the wider organisation.

Focus on High-Value Indicators First

Insider Risk Management offers a wide range of indicators covering Microsoft 365 activity, endpoint activity, browser usage, and Microsoft Defender signals.

While flexibility is useful, using every available indicator rarely delivers the best results.

In most deployments, I recommend initially focusing on high-confidence activities such as:

• External sharing of sensitive information
• High-volume file downloads
• Large-scale file access events
• USB transfers
• Activity associated with departing employees

Starting with a smaller set of meaningful indicators makes it easier to understand alert quality and significantly reduces analyst fatigue during the early stages of deployment.

Improve Detection Quality with Content-Based Signals

Not all files carry the same level of risk.

Monitoring every document equally often creates unnecessary alerts and reduces the effectiveness of investigations. Instead, organisations should focus on content that has already been identified as valuable or sensitive.

This can include content protected by:

• Sensitivity labels
• Sensitive Information Types
• Trainable classifiers
• Data Loss Prevention policies

Examples may include customer records, financial information, source code, intellectual property, healthcare data, or legal documentation.

By prioritising sensitive content, organisations can dramatically increase the relevance of generated alerts while reducing false positives.

Departing Employee Policies Often Deliver the Greatest Value

In many organisations, departing employee policies generate some of the most valuable IRM alerts.

Employees approaching resignation or termination may begin collecting information they believe could be useful in future roles. While the majority of users act legitimately, this period often represents increased organisational risk.

When configuring these policies, focus on activities such as:

• Uploading files to cloud storage providers.
• External sharing.
• Downloading large volumes of sensitive content.
• Accessing repositories that the employee does not normally use.

At the same time, avoid assigning excessive weight to routine activities that form part of an employee’s normal workload.

Review and Refine Continually

IRM should be treated as an ongoing programme rather than a one-time deployment exercise.

Regular reviews are essential. A monthly review should examine:

• Alert volumes
• False positive rates
• Frequently triggered indicators
• Repeat offenders
• Investigation outcomes
• Case closure reasons

These metrics provide valuable insight into whether policies are generating genuine security value or simply creating additional workload for analysts.

Final Thoughts

Microsoft Purview IRM can be an exceptionally powerful capability when implemented thoughtfully. However, its effectiveness depends far more on tuning and operational maturity than on the initial policy deployment itself.

Organisations that take the time to pilot policies, focus on high-value indicators, leverage sensitivity labels, and regularly review outcomes typically achieve far better results than those that attempt to monitor everything from the outset.

When combined with Microsoft Defender and Adaptive Protection, IRM becomes much more than an alerting tool. It becomes a proactive security capability that helps organisations identify emerging insider threats, protect sensitive information, and reduce risk before incidents escalate into major security events.