Can WizEmp reconcile PI System data with SAP for plant performance reporting?

Yes. PI to SAP reconciliation is the signature problem of petrochemical reporting. WizEmp's discovery names every metric where the two systems diverge — energy per ton, yield per feedstock, availability — and the Power BI Cockpit shows both numbers in the same view, with the variance flagged. The KPI Definition Register is signed under Shield of Truth before any report is built.

How does WizEmp approach ESG and Scope 1/2/3 reporting for a parent-company audit?

Scope 1/2/3, PRTR, water and flare are treated as first-class data domains at discovery, not after-thoughts. The Data Source Map names every input — process historians, lab systems, fuel records, electricity invoices, freight bills — and the disclosure architecture is signed before the audit window opens. Parent-company definitions (Tokyo, Houston, Düsseldorf) are mapped to local data sources explicitly.

Is the Wit discovery process compatible with safety-critical operations?

Wit is designed for environments where safety is non-negotiable. Anonymous async interviews preserve face-protection discipline and surface what shift supervisors cannot say in a meeting. No process data is changed during discovery — Wit produces a Data Source Map and KPI Definition Register, not a live integration. The change management discipline (MOC) is respected throughout.

What does the Shield of Truth contain for a petrochemical engagement?

Beyond the standard signed scope, priorities and success metrics, a petrochemical Shield of Truth carries explicit signal sections for PI-SAP Reconciliation Map, KPI Definition Register for multi-plant benchmarking, ESG and Scope 1/2/3 Data Source Map, HSE Leading Indicator Architecture, and Gateway Architecture Standard for refresh integrity. Each is signed before go-live.

Does WizEmp handle multi-plant benchmarking when KPI definitions differ?

Yes. Multi-plant benchmarking with divergent definitions is the standard reality of group operators. WizEmp does not impose one definition; we surface the differences and reconcile them in the KPI Definition Register signed by each plant. The Cockpit shows the harmonised number AND each plant's native number, with the translation explicit. Operations directors keep their working definitions; the CEO gets one comparable view.

When PI says one thing and SAP says another, who does the plant manager believe?

Your PI System holds ten thousand tags per plant. Your SAP holds the financials. The plant manager makes calls on data that lives in both. The two systems rarely agree on the number that matters.

We speak process safety. Not just BI.

In petrochemicals, a number that affects a turnaround decision must be defensible to your operations director, your HSE officer, your parent company's audit team and the Industrial Estate Authority of Thailand. Same number, different audiences, different definitions. Your existing reports satisfy one. The others ask for another report.

Your data landscape is bifurcated: PI System (OSIsoft / AVEVA) is the source of truth for the plant; SAP is the source of truth for the business. They were never designed to converse. Energy per ton of product is calculable from both systems. And the two numbers do not match. The gap is where your CFO and your plant manager lose alignment.

Environmental reporting (PRTR, Scope 1/2/3, water, flare) has moved from compliance footnote to board-level demand. Your parent company audit teams in Tokyo, Houston or Düsseldorf expect data your infrastructure was not built to produce.

WizEmp has worked with SAP-centric, PI-rich industrial environments. We know what it takes to produce a single number a process engineer, a plant accountant and a Tier-1 parent company auditor can all stand behind.

PI System and SAP show different versions of the same plant

Process data is time-series. Business data is transactional. The reconciliation lives in a senior engineer's Excel model. And they retire next year.

Turnaround planning runs on inherited spreadsheets

Your TAR Excel was built in 2008. It has been improved by three engineers. It works. Nobody knows exactly why. The next TAR starts in eighteen months.

ESG and Scope 1/2/3 are now board-level, your infrastructure was not built for it

Your parent company audit committee wants the numbers. Your environmental team is collecting them manually across plants. The audit window starts in March.

HSE leading indicators are tracked but never analysed predictively

Near-miss reports, permit-to-work compliance, behaviour-based safety scores. You have the data. You do not have the architecture that turns it into a leading signal before the next incident.

Multi-plant benchmarking is desired, and impossible

Three plants. Three different KPI definitions. Three operations directors who each believe theirs is correct. Your CEO wants one number. There is not one.

Wit · Discovery Process

Discovery that bridges OT and IT.

Wit, WizEmp's smart discovery process powered by AI, runs structured anonymous interviews across all stakeholders before any report is built. Wit is tool-agnostic. The Shield of Truth, Data Dictionary and Metrics Dictionary work regardless of whether your organisation runs Power BI, Tableau, Qlik or Looker.

Vocabulary Wit uses in your environment:

cracker feedstock turnaround (TAR) HAZOP SIL MOC PRTR Scope 1/2/3 plant availability permit-to-work RBI

Adaptation 01

Process Reality Gate fires early

Shift supervisors and control room operators who 'feel' the process are interviewed in Round 1. They hold knowledge no historian database captures. Wit surfaces it before the architecture is decided.

Adaptation 02

PI-SAP reconciliation surfaced as a primary scoping question

Wit asks: when PI shows X and SAP shows Y, which does the plant manager believe? The answer drives the semantic model boundary.

Adaptation 03

ESG and Scope 1/2/3 mapped at discovery, not bolted on later

Carbon, water, flare, PRTR. Wit treats them as first-class data domains, not after-thoughts. The Data Source Map names every input from intake to disclosure.

Adaptation 04

Safety performance treated as a leading indicator candidate

Near-miss density, PTW compliance, BBS scores. Wit asks: which of these currently influences operational decisions? The honest answer drives the leading-indicator architecture.

Adaptation 05

Multi-plant KPI harmonisation flagged before architecture

Three plants with three definitions cannot be benchmarked. Wit surfaces the definition gaps; the KPI Definition Register reconciles them under Shield of Truth signature.

A Necessary and Sufficient Architecture for process-industry reporting.

WizEmp delivers in Microsoft® Power BI®. Once the Shield of Truth™ is signed and the architecture defined, our team builds a Microsoft® Power BI® Cockpit: the navigation hub connecting all reports in your workspace. For a petrochemical operator, the Cockpit links to reports that serve three master requirements: operational reliability, safety and environmental compliance, and financial truth.

If your organisation already runs Tableau, Qlik or Looker, the Shield of Truth™ still applies. The discovery output (Data Dictionary, Metrics Dictionary, report architecture, signed stakeholder alignment) is platform-independent. You take it to your existing team or preferred integrator. WizEmp can support that path too.

Every Microsoft® Power BI® report WizEmp builds follows the Overview-Exploration-Detailed structure. A site director sees plant availability in 10 seconds. An HSE manager drills to a specific PTW exception in 2 minutes. The same report. The same data. Two different entry points.

Power BI Cockpit · Petrochemical Configuration

Your navigation hub: connecting every report in your workspace

Plant Performance

Energy per ton of product Yield per feedstock Plant availability & run length

Turnaround Readiness

TAR planning vs actual progress Post-TAR performance vs pre Critical path & resource load

HSE & Safety

Near-miss density & trend PTW compliance rate BBS score by area

Environmental & ESG

Scope 1 / 2 / 3 by plant PRTR & flare consent status Water & effluent monitoring

Financial HUD

Margin per ton Energy cost variance vs plan Cost per barrel-equivalent

Asset Reliability

MTBF & MTTR by unit RBI inspection status Critical-equipment age curve

"Energy consumption in your PI System is not the energy in your SAP cost report. Wit surfaces these definitional conflicts before any architecture is decided. The Data Dictionary and Metrics Dictionary are the first deliverables. Every report that follows draws from them."

Every function in your plant. One coherent data architecture.

⚗️

Operations & Process Engineering

Energy per ton, yield per feedstock, plant availability. Operational data finally reconciled to financial impact in the same view.

🛡️

HSE / Safety / Sustainability

Near-miss trend, PTW compliance, Scope 1/2/3, PRTR. The leading indicators your safety council can act on before the next incident.

🔧

Maintenance & Reliability

MTBF, MTTR, RBI status, critical-equipment age. The asset performance picture your reliability engineers can defend in the next budget review.

💰

Finance & Controlling

Margin per ton, energy cost variance, cost per barrel-equivalent. When the financial HUD matches the plant report, your CFO stops asking for parallel models.

Let's talk about your reconciliation problem.

Your data already holds the answer. Most operators never find it because no one built the architecture to bridge process data and business data in the same view.

Schedule a Discovery Call

Just a conversation. Specific to process industries.

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