i3solutions

The offshore Power Platform engagement ships fast for the first few quarters. Then ownership fragments, approval evidence doesn't exist, and incident response stalls across time zones. Internal risk teams start reviewing every release, and delivery timelines double.

The sequence is predictable because the root cause is the same each time: the delivery model was selected on cost.

In a regulated Microsoft 365 environment, Power Platform runs approvals, data movement, and compliance processes. Every flow, every connector, every automation change is a controlled change inside your tenant, whoever builds it.

That makes the delivery model a governance decision disguised as a cost decision, and it comes down to four structural requirements. Evaluate them before the contract, or discover them one compounded gap at a time.

Read the full article before your next delivery model review: https://i3solutions.com/insights-power-platform/onshore-vs-offshore-for-microsoft-power-platform-in-regulated-industries/

Your Power Platform delivery model was evaluated on hourly cost. In a regulated environment, it's a governance decision.

Every flow, every connector, every automation change is a controlled change inside your tenant. Who builds it, who reviews it, and who owns it in production is what you point to when auditors ask you to prove control.

Pick the model on rate alone, and you learn whether that proof exists during the audit, not before it.

Full video: https://youtu.be/twsE7VtijLw

Read the full article before your next delivery model review:
https://i3solutions.com/insights-power-platform/onshore-vs-offshore-for-microsoft-power-platform-in-regulated-industries/

Six months after a successful launch, exception rates are climbing, processing times are stretching, and users are quietly building workarounds. The automation hit every milestone and first-quarter ROI looked strong. Nobody budgeted for what happens after go-live.

Nothing was built wrong. Business requirements shifted and the workflow didn't shift with them. Without active monitoring, that's the path forty to sixty percent of deployed workflows take inside six months.

The organizations that sustain automation value treat deployment as the starting point, not the finish line, and they put three support layers behind it. That support costs thirty to fifty percent less than rebuilding after the decay compounds.Users lost confidence and went back to manual. The rebuild costs twice what the support would have.

Full video: https://youtu.be/xyREdTJtjyQ



Read the full article before your next planning cycle:
https://i3solutions.com/insights-workflow-automation/workflow-automation-support-services/

Half of unsupported automations become obsolete or problematic within eighteen months, and the first sign anyone acts on is someone asking about the ROI.

By then the numbers aren't describing a technical failure. Requirements kept shifting after go-live, and the workflow answered with exception rates instead.

Full video: https://youtu.be/xyREdTJtjyQ

Every automation in production is earning or eroding right now. Without a support model behind it, the answer gets decided for you.
Read the full article before your next planning cycle:
https://i3solutions.com/insights-workflow-automation/workflow-automation-support-services/

SharePoint sprawl has two causes. Address only one, and the cleanup doesn't hold.

Here is the pattern i3solutions sees when brought in to untangle it.
IT designs a logical structure with clear conventions. Business users immediately work around it: subsites, inconsistent naming, personal systems. Then Teams rolls out, and every new team spins up a new SharePoint site with no approval and no IT involvement. A department that should have one site now has fourteen.

The result is measurable. Knowledge workers spend an average of 2.5 hours a day searching for content they know exists but can't find. Compliance runs as a manual process that fails under audit pressure. Experienced people leave, and their work goes with them, not because it was deleted, but because no one can find it.

Address only half of it, and the same sprawl comes back inside a year.

Read the full article before your next SharePoint cleanup: https://i3solutions.com/sharepoint-software-development/controlling-sharepoint-content-management/


Full video: https://youtu.be/iKadSa3_Q6A

Your SharePoint problem has two causes. Address only one, and the sprawl regenerates.

Users create subsites, upload documents inconsistently, and build their own systems. That has been true since SharePoint launched. Then Teams accelerated everything. Every new team automatically generates a new SharePoint site, with no approval and no IT involvement. A department that should have one site now has fourteen.

Knowledge workers spend an average of 2.5 hours a day searching for content they know exists. The number climbs every week that new sites keep provisioning themselves.

Clean up the sites without addressing what's creating them, and they keep coming back.

Read the full article before your next SharePoint cleanup: https://i3solutions.com/sharepoint-software-development/controlling-sharepoint-content-management/

Full video: https://youtu.be/iKadSa3_Q6A

When an integration passes in development and fails in production, it didn't fail at go-live. It passed testing in the wrong place.

The environment it was tested in isn't the environment it runs in.

Development is tuned for speed with loose permissions, small datasets, and personal connections. Production is none of those, and the difference stays invisible until the first real transaction runs against it.

Testing proved the integration works somewhere it will never run.

Validate against a production-representative environment before you accept the build, or the failure is already scheduled.

The integration processed every test record. The logic checked out. The build was accepted.

Then production happened.

It ran against a list many times larger and reported success anyway. The results were incomplete, and there was no error or alert. Someone caught it weeks later when the missing data surfaced in a reconciliation.

The demo validated the logic. It never validated the scale, because the test data was too small to show what production would do.

At production scale, records get dropped and the run still reports clean.

The dashboard says it worked. The business already knows it didn't.

A SharePoint integration that ran clean in development starts failing in production, and the fix turns into a project.

The decision that caused it was made in week two, when it looked local and reversible. It was neither.

By the time the failure surfaces at month six, it is buried under everything built on top of it.

Three configuration choices decide this, and none are hard to get right as long as someone asks the question in time.

Follow for more SharePoint and Microsoft 365 architecture insights.

The enterprise SharePoint integration that fails at month six is not failing because of what broke.

The cause was set in week two and buried under everything built since.

So the team debugs the symptom, checking column names and connection settings for days, while the decision that actually caused it sits three layers down where nobody is looking.

It looks like a bug. It's a week two decision that was wrong the moment it was made.

Follow for more SharePoint and Microsoft 365 architecture insights.