Business intelligence for manufacturing operations

Get from ERP data to the answer faster.

ZxL Operations is an independent manufacturing business intelligence consultancy led by TJ Zingalis. I use SQL, Python, Excel, and Power BI to turn difficult-to-access ERP and operational data into the exact analysis your team needs—without hours of manual work.

Every engagement is scoped, built, and delivered directly by me.

Data to decision Automated
01
Reach the source
ERP · databases · offline files
SQL + Python
02
Shape the right cut
BOMs · demand · purchasing · finance
Modeled once
03
Answer what matters
What to buy · what can build · blockers
Decision-ready

The gap I close

The information exists. Getting to it should not take hours.

ERP systems capture enormous amounts of information, but the cuts people actually need are often buried behind rigid reports, difficult joins, exports, and repetitive spreadsheet work. I shorten the path from raw data to a trusted answer.

01

Data buried in the ERP

The answer requires multiple reports, exports, joins, and workarounds before anyone can begin analyzing it.

02

Analysis rebuilt by hand

Skilled employees lose hours refreshing workbooks, combining files, and recreating the same cuts every week.

03

Decisions without the full picture

Purchasing, production, warehouse, and finance cannot easily work from the same version of demand and supply.

What I deliver

The right data, in the right shape, for the decision in front of you.

I extract, model, automate, and present information around the way your team needs to use it—not the way a standard ERP report happens to return it. ZxL Operations does not sell prepackaged software; the service is hands-on consulting and custom analysis built around your systems and workflow.

SQL

ERP data access & modeling

Use SQL and Python to combine hard-to-reach ERP tables, operational files, and business rules into reliable datasets.

BI

Automated analysis & reporting

Replace recurring manual work with Excel, Power Query, Python, and Power BI reporting that refreshes consistently.

PI

Purchasing & inventory intelligence

Connect usage, demand, inventory, open POs, lead times, and supplier constraints to show what needs attention.

BOM

Build readiness & BOM analysis

Flatten complicated bills of material and evaluate thousands of components to show what can build and what is blocked.

High-value analysis

Know what you can build—and exactly what is blocking the rest.

For manufacturers with complicated, multi-level BOMs and thousands of components, a sales backlog alone does not show what can actually ship. I connect demand to the component-level supply picture so production, purchasing, and warehouse teams can act from the same answer.

My hands-on manufacturing and warehouse scheduling experience includes bringing customer priorities, scheduled dates, multi-level BOM requirements, on-hand components, open purchase orders, expected receipts, work orders, and practical capacity constraints together quickly. SQL and Python make it possible to evaluate the full schedule and respond to changing conditions without rebuilding the analysis by hand.

Explode multi-level BOM requirements across the open order book
Compare component demand with on-hand inventory, allocations, and open POs
Trace blocked orders to the exact parts and expected receipt dates
Prioritize what can move forward, what should be pulled in, and what purchasing must address first
Typical analysis combines
Customer demandOpen orders, quantities, priorities, and requested dates
Multi-level BOMsAssemblies, subassemblies, components, and usage quantities
Available supplyOn-hand inventory, allocations, work orders, and current availability
Incoming supplyOpen POs, expected receipts, lead times, and supplier constraints
Decision supported What can we build now, what is blocked, and what should purchasing address first?

How I work

Build the path once. Stop rebuilding the answer every week.

I learn the question, locate the source data, encode the business logic, and deliver the result in a format people can actually use.

01 / Define

Start with the question

Clarify the decision, the required detail, and why the current process takes so long.

02 / Extract

Reach the real data

Use SQL, Python, ERP connections, and source files to assemble the complete picture.

03 / Model

Encode the business logic

Turn complex relationships, exceptions, and operating rules into a repeatable dataset.

04 / Deliver

Put the answer in reach

Provide it through Excel, Power BI, automated reporting, or a purpose-built workflow.

Work directly with me

One accountable partner from the question to the finished solution.

I personally scope, develop, and deliver every engagement. You work directly with the person analyzing the business problem, writing the SQL and Python, and building the final reporting or workflow.

SQL & ERP extractionReach and join NetSuite or other ERP data that standard reports leave disconnected.
Python & Excel automationCompress repetitive data preparation and analysis into consistent, refreshable processes.
Power BI deliveryGive leaders and teams clear, interactive access to the cuts and exceptions they need.
Process improvementWhen data capture is the constraint, build practical Power Apps and SharePoint workflows—such as warehouse scanning and order-location visibility.

Start with one question

What information takes your team too long to get?

Bring the report, workbook, ERP question, purchasing problem, or production constraint that keeps consuming time. I will help you find the shortest practical path to a better answer.