.png)
In brief: Choose a Dynamics 365 manufacturing partner by testing industry process knowledge, the proposed delivery team, integration and data capability, implementation governance, adoption and support. An unsupported “top partner” list is not a safe basis for selection.
Manufacturing ERP projects succeed when the implementation partner understands how planning, production, quality, maintenance, inventory, costing and customer demand connect. Product knowledge matters, but it does not replace operational fluency or delivery discipline.
What Dynamics 365 can cover in a manufacturing environment
Depending on the selected applications and design, the Microsoft stack can support finance, supply chain planning, procurement, production control, warehouse operations, asset management, quality, sales, service, analytics and workflow automation. The partner must determine which capabilities belong in the core ERP and which should remain in an MES, product lifecycle, ecommerce, logistics or specialist system.
Why manufacturing experience matters
A general ERP team may understand configuration but miss the consequences of a design decision on the shop floor. Manufacturing-specific discovery should cover:
- discrete, process, lean or mixed-mode production;
- bill-of-material and formula control;
- routes, resources, capacity and scheduling;
- material planning, substitutes and shortages;
- quality orders, non-conformance and traceability;
- work-in-progress, standard cost and production variance;
- maintenance, downtime and asset history;
- warehouse, batch, serial and expiry controls;
- customer forecasts, order promising and after-sales service.
Ask the partner to explain one of your real production scenarios. A capable team should be able to map the process, identify data dependencies and discuss standard versus extended design without retreating into generic product language.
Seven criteria for selecting a manufacturing partner
1. Relevant client evidence
Request examples at a comparable scale, production type and integration complexity. Evidence should explain the initial problem, scope, delivery decisions, data and adoption challenges, and operational outcome. A logo list is not enough.
2. Named manufacturing delivery team
Review the people who will lead process design, solution architecture, data, integration, testing, change and support. Confirm availability and whether delivery depends on subcontractors not introduced during selection.
3. Discovery and fit-to-standard method
The partner should map current decisions and pain points, demonstrate standard capability, document gaps and challenge requests that recreate legacy complexity. Customisation should be justified by legal need, customer obligation or differentiated value.
4. Data and integration capability
Manufacturing projects depend on item, BOM, route, resource, inventory, supplier, customer and cost data. Evaluate the partner’s migration profiling, cleansing ownership, reconciliation and cutover method. Also assess integration experience with MES, machines, IoT, product lifecycle, ecommerce, transport, payroll and banking systems where relevant.
5. Testing and cutover discipline
Testing should follow end-to-end production scenarios, including shortages, substitutions, rework, scrap, quality holds, subcontracting, returns and financial posting. The cutover plan must address open production orders, inventory balances, master-data freeze, interfaces and fallback.
6. Adoption and operational ownership
Role-based learning should reflect real work for planners, buyers, production supervisors, warehouse teams, quality users, finance and managers. The partner should establish super users and transfer process and configuration knowledge before go-live.
7. Support and continuous improvement
Confirm service hours, severity levels, response targets, release management, manufacturing expertise and how enhancements are prioritised after stabilisation.
UAE and GCC requirements to test
- VAT, invoicing and document requirements;
- multi-entity, multi-currency and regional reporting;
- Arabic or bilingual documents and user needs where applicable;
- local banking, payroll, logistics and customer integrations;
- data residency, access and security expectations;
- support coverage across sites and countries.
Do not accept “we have a local office” as proof. Ask which requirements the named team has delivered and how they were validated.
A practical manufacturing partner scorecard
- Manufacturing process and industry fit — 25%.
- Proposed team and relevant references — 20%.
- Discovery, design and governance — 15%.
- Data, integration and architecture — 15%.
- Testing, cutover and adoption — 15%.
- Support and commercial clarity — 10%.
Record the evidence, concern and assumption behind every score. This makes the decision auditable and exposes where a polished proposal is not supported by delivery detail.
Questions to include in the RFP or working session
- Which manufacturing processes in our scope should remain standard?
- How will the solution exchange data with MES, machines or specialist systems?
- Who owns master-data cleansing and acceptance?
- How will production, inventory and finance be reconciled at cutover?
- Which scenarios will be used for end-to-end testing?
- What design decisions create the greatest upgrade or support risk?
- How will supervisors and shop-floor users be trained without disrupting operations?
- What support skills will be available after go-live?
Red flags
- The proposal recommends modules before understanding the production model.
- The team cannot explain BOM, routing, planning, quality or production costing.
- Integration and data are broad exclusions.
- Customisation is offered as the first answer to every gap.
- Testing focuses on screens instead of end-to-end production scenarios.
- Training and support are treated as optional add-ons.
Final recommendation
Select the partner that reduces uncertainty before implementation. The strongest team will show how your manufacturing decisions, data and controls fit the platform, identify what should not be customised and provide a credible path from discovery to stable operations.
.png)
.png)
.png)
.webp)
