Operational Intelligence for Manufacturers
Most manufacturing operations run on institutional memory, tribal knowledge, and whoever has the most tenure. When that person leaves, the system breaks. NX Advisory Group builds the systems, frameworks, and automation that make operations work regardless of who’s in the seat.
Work is project-based. No retainers, no ambiguity about what you’re paying for.
Competency Architecture
You can’t train your way out of a documentation problem.
Most manufacturers don’t have a training problem — they have a knowledge system problem. Operators learn on the job from whoever happens to be available, qualifications are informal or nonexistent, and there’s no mechanism to verify that someone actually knows what they’re supposed to know. When that person retires or leaves, the knowledge walks out with them.
Competency Architecture builds the underlying structure your training needs to actually function: defined competency standards, role-based qualification pathways, and a documented progression from onboarding through certification and recertification. The output is a system, not a course.
What this includes:
- Role-by-role competency mapping tied to actual job requirements
- OJT frameworks with observable, verifiable performance standards
- Qualification and certification structures with defined pass/fail criteria
- Recertification schedules that reflect real operational risk, not calendar convenience
- Document templates and format standards your team can maintain without outside help
The result: a new operator knows exactly what they need to learn, in what sequence, and what “qualified” looks like. Your leads know what to teach. Your managers can verify it happened.
Deliverable-based engagement. Typical scope: 4–12 weeks depending on role complexity and document volume.
Workforce Intelligence Systems
You can’t manage what you can’t measure — and most workforce data is a mess.
Headcount reports that don’t match reality. Skill data that lives in spreadsheets nobody trusts. Succession plans built on assumptions instead of evidence. Most organizations don’t lack people data — they lack organized, queryable people data that connects to actual operational decisions.
Workforce Intelligence Systems builds the infrastructure to answer the questions that matter: Who can actually run Line 4? If the shift supervisor on nights leaves, who’s qualified to step in — and are they on the bench or still two months from certification? What’s the attrition trajectory on the machining floor, and what does that mean for Q3 capacity?
What this includes:
- Workforce data architecture connecting HR records, training status, and operational assignments
- Skill and qualification mapping at the position and individual level
- Attrition risk modeling and headcount scenario analysis
- Dashboard infrastructure (Power BI) built for shift leads and ops managers, not HR
- Succession readiness scoring against defined role requirements
The result: decisions about people get made on data instead of gut feel. Gaps surface before they become emergencies.
Deliverable-based engagement. Requires access to existing HR and operational data sources. Typical scope: 6–16 weeks.
Operational Stress Testing
Your operation looks fine until it doesn’t.
Most manufacturing operations have single points of failure they don’t know about — a process that only two people understand, a critical role with no bench depth, a workaround that became standard practice and never got documented. These aren’t visible until something breaks: a key resignation, an audit, a production ramp that exposes every assumption the floor was running on.
Operational Stress Testing maps those vulnerabilities before reality does. The engagement is structured as a deliberate diagnostic — not a feel-good review, but a systematic pressure test of your operation’s actual resilience across workforce, process, and system dimensions.
What this includes:
- Critical role identification and bench depth assessment (succession readiness by position)
- Single-point-of-failure mapping across process, knowledge, and personnel
- Scenario modeling: what breaks if X happens, and how fast
- Process dependency analysis — what has to work for the rest of the operation to work
- Prioritized risk register with remediation paths, not just a list of problems
The result: a clear picture of where your operation is fragile and a sequenced plan to address it before the fragility becomes a failure.
Diagnostic-first engagement. Findings delivered as a risk register with prioritized remediation. Typical scope: 3–6 weeks for initial assessment.
Process Automation
If someone is doing it manually, it’s a candidate for automation.
Scheduling built in spreadsheets. Status updates that require three systems and a phone call. Reports that take two hours every Monday morning. The manual work isn’t just inefficient — it introduces error, creates bottlenecks, and puts your operation’s continuity in the hands of whoever built the spreadsheet.
Process Automation replaces manual workflows with systems that run on data instead of effort. The work is built on the Microsoft stack (Power Apps, Power Automate, Power BI, SharePoint, Azure) — tools most manufacturing operations already have access to and don’t fully use. No expensive new platforms, no IT dependency that takes six months to approve.
Reference implementation: an AI-driven production scheduling engine integrating real-time shop floor data with ERP outputs across multiple production environments — eliminating manual scheduling and delivering shift-level schedule accuracy. Built and deployed in an active manufacturing operation.
What this includes:
- Current-state workflow mapping to identify automation candidates and ROI
- Power Apps application development (custom, production-ready, not demos)
- Power Automate flows replacing manual handoffs, notifications, and approvals
- Power BI reporting infrastructure replacing manual report generation
- Azure/SharePoint integration for data connectivity across systems
- ERP and legacy system integration (including AS400/JDE environments)
The result: the work gets done by the system, not by the person who built the habit of doing it manually.
Scoped by project. Applications built to production standards — tested, documented, and deployable without ongoing outside support.
Ready to talk specifics?
Engagements start with a scoping call. No proposal before the conversation. If the work is a fit, you’ll know what it costs and what you get before anything gets signed.