ITP, InTech Partner

28/08/2026

A successful S/4HANA migration in pharma isn’t just about moving to a new system.

In a regulated environment, the decisions made before and during the migration can matter just as much as the technology itself.

From our experience working on pharmaceutical transformation projects, five lessons consistently stand out:

→ Design around regulated processes, not just SAP modules
→ Define validation scope early
→ Give data migration clear ownership
→ Test exceptions, not only the happy path
→ Treat user adoption as part of maintaining control

Compliance shouldn’t be something you try to prove at the end. It should influence how the migration is designed from the start.

Swipe through the carousel for the five practical lessons ➡️

Tell us the compliance risk you’re most concerned about. Our pharma team would be happy to discuss it.

GxP ITP

27/08/2026

Your best engineers shouldn’t spend hours rebuilding routing cards.
Yet that’s still part of the daily workload for many manufacturing teams — reviewing drawings, checking old projects, repeating calculations, and turning the same engineering knowledge into new documentation.

AI can take some of that repetitive work off the team’s plate.
Technical drawings and manufacturing parameters can be used to create structured draft process plans and routing cards, with engineers reviewing and approving the results.

💬 Comment “AI Workflow” if you’d like to see how this workflow can work in practice.

27/08/2026

22/08/2026

Your SAP project success depends on the questions you ask first.

From KPIs and production to procurement, logistics, data, and automation — the right discovery approach creates the foundation for transformation.

💬 Comment “Checklist” to get the complete checklist.

13/08/2026

How much delivery cost is already locked in before the first truck leaves?
Route-planning inefficiency often starts long before dispatch.
Manual sequencing.

Incomplete addresses.
Missed time windows.
Unused vehicle capacity.
Slow replanning when something changes.

None of these problems looks dramatic on its own. But repeated across every planning cycle, they can quietly add kilometres, planner hours and avoidable cost.

The first step is not necessarily replacing your planning process.
It is understanding where the leakage is happening today.

Swipe ➡️ for five areas worth checking with your dispatch team.
Use our route-planning baseline checklist to review your current process and identify where optimisation could create value.

10/08/2026

The same deliveries. Fewer kilometres.

Up to 10% lower delivery mileage, with a full order set planned in under five minutes.

The opportunity isn’t always about adding more vehicles or changing the fleet. Sometimes, it starts with building better routes.

Our logistics optimisation approach works with the data companies already have. Orders, vehicles and operational constraints can come directly from existing ERP exports.

From there, the process validates the data, geocodes delivery addresses and generates optimised, editable routes.

And importantly, the planner stays in control.
AI handles the heavy calculation. The logistics team keeps the operational knowledge and final decision-making.

In one of our business cases, this approach delivered 5–10% lower mileage on historical orders while reducing route planning from hours to minutes.

Want to see where the hidden cost may be in your current route planning process?
Test your historical orders and measure the opportunity against your own baseline.

🌐 Read the full article:
https://lnkd.in/dj2FXM6k

04/08/2026

When warehouse teams rely on manual checks, disconnected updates, and workarounds, even small issues can create delays across the operation.

Connecting SAP EWM, SAP QM, and SAP PP can give teams a clearer view of stock, quality status, production staging, and shipment progress.

Check these seven signs to see whether your warehouse processes need a closer look ⬇️

Request an EWM/QM readiness review to identify where improvements could have the greatest impact.

Read the full article:
https://itp.biz/ai-ready-warehouses-with-sap-ewm-qm-and-pp/ 🌐

SupplyChain

23/07/2026

Is your manufacturing planning process truly connected – or still driven by spreadsheets and urgent fixes?
Swipe through the carousel to discover five common warning signs and how SAP IBP + SAP PP help close the gaps

SAP IBP aligns demand, supply, inventory, and finance, while SAP PP turns the plan into executable production requirements.
The goal is one connected cycle:

Forecast → Supply Plan → Production Plan → Warehouse Readiness → Ex*****on Feedback

See how one of our clients used SAP IBP to manage demand volatility and production capacity: https://itp.biz/sap-ibp-production-planning-demand-volatility/

Comment “Planning” to receive our short planning diagnostic checklist.

15/07/2026

Do We Need Clean Core Before Using SAP AI?

Many organizations are asking this as they explore SAP Business AI.
McKinsey’s 2026 AI Trust Maturity Survey found that nearly two-thirds of respondents see security and risk concerns as the top barrier to fully scaling agentic AI.

For SAP customers, AI can only be trusted and scaled when the foundation is strong: reliable data, controlled custom code, connected processes, up-to-date integrations, clear permissions, and strong governance.

In pharma, inconsistent batch data and manual quality approvals can reduce the reliability of AI recommendations.
In mining, disconnected maintenance, procurement, and warehouse systems can leave AI without the full operational picture.
In manufacturing, plant-specific custom code and fragmented production and quality processes can make AI difficult to trust and scale across the business.
You do not need a perfect SAP landscape to begin exploring AI.

But once SAP Business AI moves from giving answers to influencing or taking action in SAP S/4HANA, a strong and reliable foundation becomes essential.
That is why clean core is more than an IT architecture principle.

It is a business requirement for making AI trusted, scalable, and ready to act.
Comment “Clean Core” to request our short SAP AI-readiness checklist.

13/07/2026

The next phase of pharma transformation will be shaped by AI.
But it must first be built on trusted data, controlled processes and accountable governance.

In our Adalvo case study, ITP supported a 7.5-month migration from SAP ECC to SAP S4/HANA on Azure, helping build a modern digital core for pharma growth.

Swipe through the carousel to explore 5 practical lessons we learned from this Pharma SAP project.

Read our full article, where we go deep in the solution, result and lessons learned: https://lnkd.in/dmYpKyzt