A controlled financial engine that turns complete transactions, product economics and people administration into reliable management information, protects cash and exposes the decisions IKON must make to scale.
Source: Finance Architecture MeetingWorking vision for leadership validation
Engine purpose
Give IKON financial control and commercial visibility at R110 million scale, while building the disciplines and capability needed for the R500 million ambition.
Give leadership a fast, reliable view of business performance so decisions are made from current financial truth.
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1. Purpose
Turn complete, accurate financial data into timely management information that shows how IKON is performing and where action is required.
Agreed direction
2. One-year finished state
Finance owns the complete reporting cycle from source data to a consistent management pack.
Leadership can see P&L performance, EBITDA, project profitability, work in progress and stock value without waiting weeks.
Cost centres are visible and assigned to the relevant leaders.
Weekly and monthly reporting rhythms are defined, repeatable and trusted.
Working proposal
3. Current reality
IKON does not yet have reliable click-of-a-button visibility of weekly performance, WIP, stock and profit by project.
Financial information is spread across invoices, Zoho, Bizman Tools, EVA and existing finance processes.
Finance still carries temporary work outside the future engine.
Source confirmed
4. Problems & constraints
Reporting is delayed by fragmented data and manual preparation.
Information must be reconciled across systems.
A report cannot be trusted if transactions, stock, WIP or project allocation are incomplete.
5. What must be resolved
Define the minimum weekly and monthly management pack.
Decide the central financial package and cost-centre structure.
Define source, cut-off, reconciliation and approval rules for material numbers.
Establish reporting lead-time and data-quality baselines.
Leadership decision required
6. Operating model
Capture at source → validate and reconcile → allocate to project and cost centre → close period → produce management pack → review exceptions → assign action → improve source data.
7. Capabilities & training
Management accounting and financial interpretation.
Reconciliations, close and variance analysis.
WIP and stock accounting.
Project profitability analysis.
Data quality and commercial communication.
8. Roles & accountability
One accountable Finance owner is required for management-information integrity and delivery. Department leaders remain accountable for operational data and spending within their cost centres. Final Seats follow engine approval.
Engine before people
9. Systems, tools & documents
Central financial package, still to be confirmed.
EVA, Zoho and Bizman Tools where relevant.
Weekly flash report and monthly management pack.
Close checklist, reconciliations and variance commentary.
Controlled chart of accounts and reporting definitions.
10. Standards
One version of the financial truth.
Every material number has a source, definition, cut-off and reconciliation.
Reports separate fact, estimate and unresolved variance.
Errors are corrected at source.
11. Measurables
Time from period end to trusted pack.
Unreconciled items and material exceptions.
Availability of P&L, EBITDA, WIP, stock and project-profit views.
Report corrections after issue.
Input to Data GPT · baseline before targets
12. Dependencies
Operations supplies accurate stock, production, dispatch and WIP movements.
Technical hands over complete product and BOM logic.
Client Development supplies accurate sales and order data.
Creditors and Costing supply clean transaction and project data.
13. Risks
Automating incomplete or incorrect data.
Treating system output as accurate without checks.
Finance becoming the manual clean-up department for every engine.
Building reports before agreeing definitions and ownership.
14. Immediate priorities
Map required management numbers to source and current reliability.
Define the proposed management pack for leadership challenge.
Establish reporting and close baselines.
Remove remaining non-Finance work through trained handovers.
Input to Rocks GPT · not an approved Rock
15. Definition of Done
IKON has a repeatable close and reporting system that produces timely, reconciled and decision-useful information, with visible P&L, EBITDA, cash, stock, WIP, project profitability and material variances.
02 · Control
Debtors, Creditors & Cash Control
Control money owed to IKON, money IKON owes and the cash consequences of both.
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1. Purpose
Protect IKON’s cash and relationships through controlled customer collections, supplier payments, reconciliations and cash visibility.
Agreed direction
2. One-year finished state
Customer invoices, receipts, ageing and collection actions are current and visible.
Supplier invoices are captured, allocated and reconciled before payment preparation.
Finance prepares complete debtor and creditor control packs, with final releases separately approved.
Short-term cash requirements, overdue accounts, disputes and exceptions are visible early.
Working proposal
3. Current reality
Meegan is expected to own debtors and creditors from start to finish up to final payment release.
Creditor preparation already exists, but central capture and cost-centre allocation still need development.
Debtor, creditor and cash information is not yet integrated into the desired weekly management view.
Source confirmed
4. Problems & constraints
Late invoicing or weak follow-up can delay cash collection.
Missing supplier evidence or incorrect allocation weakens control.
Unclear handoffs can create overdue accounts, duplicate work and cash surprises.
Preparation, approval and release boundaries require clarity.
5. What must be resolved
Approve end-to-end debtor and creditor workflows.
Define collection cadence, escalation and credit-control rules.
Define payment authority, evidence and exception rules.
Define supplier and customer master-data controls and cash forecasting rhythm.
Leadership decision required
6. Operating model
Raise and verify customer invoice → monitor receipt and ageing → follow up and escalate → receive and validate supplier invoice → allocate and reconcile → compile payment pack → approve and release → update cash view → resolve exceptions.
7. Capabilities & training
Debtor collection and customer-account reconciliation.
Creditor processing and supplier reconciliation.
Cash-flow forecasting and working-capital control.
Fraud awareness, VAT and supporting-document checks.
Professional dispute and exception management.
8. Roles & accountability
Finance owns debtor and creditor controls, collection visibility, reconciliations and payment-pack preparation. Sales and Operations supply accurate billing triggers and evidence. Final payment release remains separately controlled. Seats follow approval.
Engine before people
9. Systems, tools & documents
Customer and supplier masters in the central finance package.
Invoice, receipt, ageing and collection registers.
Supplier invoice intake, reconciliations and payment pack.
Cash forecast, approval matrix and exception register.
Bank-detail verification and audit evidence.
10. Standards
Invoices are raised promptly from approved commercial evidence.
Overdue customer accounts receive consistent follow-up and escalation.
No supplier payment without valid evidence and approval.
Bank-detail changes are independently verified.
Debtor, creditor and bank positions reconcile to the financial truth.
11. Measurables
Debtor ageing and overdue value.
Collection actions completed and disputes unresolved.
Invoices awaiting capture or allocation.
Unreconciled creditor and bank items.
Cash forecast accuracy and off-cycle payments.
Input to Data GPT · baseline before targets
12. Dependencies
Client Development supplies accurate commercial terms and collection support.
Operations confirms billing, delivery and receipt events.
Data & Analytics consumes reconciled working-capital information.
Systems preserve evidence, workflow and audit history.
13. Risks
Revenue is recorded but cash is not collected.
Supplier fraud or incorrect bank details.
Late capture creates surprise cash requirements.
Over-control delays supply or damages customer relationships.
Disputes remain unresolved because ownership is unclear.
14. Immediate priorities
Map debtor and creditor processes end to end.
Baseline ageing, disputes, unreconciled items and off-cycle payments.
Define collection and payment escalation rules.
Confirm cash-forecast and master-data controls.
Input to Rocks GPT · not an approved Rock
15. Definition of Done
IKON knows who owes it, what it owes, when cash will move and what requires intervention; customer collections and supplier payments are controlled, reconciled, timely and auditable.
03 · Enable the Engine
Systems, Automation & AI
Own the digital backbone that connects Finance, protects data integrity and removes repetitive administration without losing control.
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1. Purpose
Build and govern the connected systems, automation and AI capability that makes Finance faster, more accurate, auditable and scalable.
Agreed direction
2. One-year finished state
A clear systems architecture defines the role of the finance package, EVA, Zoho, Bizman Tools and connected data.
Finance owns system oversight, controls and financial audits without becoming the developer of technical product logic.
Priority repetitive administration is automated safely using AI or workflow automation.
System changes are scoped, tested, trained, launched and audited through a controlled process.
Capacity exists to champion AI and systems without weakening core Finance delivery.
Working proposal
3. Current reality
EVA implementation is consuming material time and the first launch will not complete the full programme.
Further phases include machine integrations, tablets, sensors, barcoding and installation processes.
Meegan is willing to oversee systems but does not want responsibility for inventing technical product calculations.
AI was explicitly identified as a way to remove repetitive work, but learning time, accuracy and capacity are constraints.
Source confirmed
4. Problems & constraints
Software projects have not always been broken into sufficiently clear phases and milestones.
Finance can receive incomplete technical logic and then be expected to resolve it.
Multiple systems can create duplicate data, weak ownership and inconsistent truth.
AI can produce inaccurate work if controls, training and review are weak.
One person cannot simultaneously perform Finance, EVA audits, software oversight and AI championing without capacity design.
5. What must be resolved
Approve the target systems architecture and system of record for each data type.
Define Technical-to-Finance handover requirements for product and costing logic.
Define ownership of development, implementation, administration, audit and support.
Define AI-use controls, approval boundaries and priority use cases.
Decide capacity or Seats required to deliver the systems responsibility.
Leadership decision required
6. Operating model
Identify business problem → simplify process → define owner and requirements → receive technical logic where required → configure or develop → test known cases → approve → train → launch → audit accuracy and adoption → improve.
7. Capabilities & training
Financial-systems administration and process mapping.
Software project scoping, testing and implementation oversight.
Data integration, audit trails and access control.
AI prompting, workflow design and human verification.
Change management, training and adoption measurement.
8. Roles & accountability
Finance requires one accountable owner for systems governance, financial data integrity, automation and AI enablement. Technical owns physical product logic. System developers build to approved requirements. Users own correct execution. Final Seats and capacity follow engine approval.
Engine before people
9. Systems, tools & documents
Central financial package, still to be selected or confirmed.
EVA, Zoho and Bizman Tools.
Integration map and system-of-record register.
Requirements brief, test script, known-case library and sign-off checklist.
Access matrix, change log, audit schedule and training records.
AI use-case register, review controls and automation exception log.
10. Standards
Simplify the process before automating it.
No system change launches without defined ownership, testing, sign-off and training.
Technical logic is handed over complete, documented and teachable.
AI output affecting money, people or commitments is verified by an accountable human.
Access follows role need and changes promptly when people join, move or leave.
System output is audited against real evidence.
11. Measurables
System implementation milestones on or off track.
Data exceptions and audit failures by system.
Manual hours removed through approved automation.
AI workflows in use and exceptions found.
User adoption, training completion and support demand.
Duplicate capture or reconciliation effort.
Input to Data GPT · baseline before targets
12. Dependencies
Technical supplies validated product and formula logic.
Operations and Client Development define user requirements and execute source processes.
Data & Analytics defines required outputs and control definitions.
External developers and vendors deliver approved technical work.
HR & Office Administration supports access and training controls.
13. Risks
Automating a broken or unclear process.
AI creates plausible but incorrect financial work.
System development becomes dependent on one individual.
EVA phases continue without clear scope, milestones and Definition of Done.
Integrations create multiple versions of the truth.
Finance becomes responsible for technical product design.
14. Immediate priorities
Map the current systems architecture and data ownership.
Define EVA phases still required after initial launch.
Create the Technical-to-Finance logic handover standard.
Identify a small set of safe, high-value AI automation use cases.
Baseline manual effort, system exceptions and required capacity.
Input to Rocks GPT · not an approved Rock
15. Definition of Done
IKON has a controlled and connected Finance technology environment; system ownership and data truth are clear; EVA and other implementations follow disciplined phases; AI removes verified repetitive work; and Finance can audit performance without owning technical product development.
04 · Know
Costing & Profitability
Know what every product and project truly costs so pricing, margins and improvement decisions use controlled commercial logic.
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1. Purpose
Create confidence in IKON’s product and project economics by controlling costing logic, auditing actual cost and exposing margin variance.
Agreed direction
2. One-year finished state
Finance can explain approved cost logic without depending on informal technical knowledge.
New and changed products arrive from Technical with a complete documented costing handover.
Expected versus actual project cost and profitability are visible.
BOM, material, labour, overhead and consumption assumptions are reviewed when variance appears.
Working proposal
3. Current reality
Technical calculation questions have reached Finance without a complete formal handover.
EVA development is exposing the boundary between technical definition and financial audit.
Technical defines physical logic, then Finance understands, controls and audits the financial result.
Project profit is not yet visible at the desired speed.
Source confirmed
4. Problems & constraints
Finance cannot audit a cost it does not understand.
Costing formulas can be handed over half-built.
Incorrect silicone, hardware, labour or material logic can silently erode margin.
Actual usage, stock and WIP data may not support reliable variance.
5. What must be resolved
Approve the Technical-to-Finance costing handover pack.
Define the boundary between technical logic and financial control.
Define standard cost, actual cost and variance-review methods.
Prioritise products and projects for validation.
Leadership decision required
6. Operating model
Technical defines validated physical logic → formal handover and training → Finance controls financial logic → implement in system → test known cases → monitor expected versus actual → investigate variance → correct at source.
7. Capabilities & training
Product-cost architecture and BOM interpretation.
Material, labour and overhead costing.
Project accounting and margin analysis.
Formula auditing and controlled test cases.
Cross-engine variance investigation.
8. Roles & accountability
Technical owns the physical truth. Finance owns financial costing control after complete handover and must understand the calculation it audits. Operations owns actual usage evidence. Final Seats follow approval.
Engine before people
9. Systems, tools & documents
EVA and Bizman Tools costing logic.
Approved BOM and calculation-logic handover pack.
Standard-cost sheets and formula register.
Known-case test library.
Expected-versus-actual report and variance register.
10. Standards
No costing logic enters use without documented technical handover and financial validation.
Finance understands the mathematics it audits.
Product changes trigger costing review.
Material, labour and overhead assumptions are explicit and versioned.
Variance is corrected in the responsible engine.
11. Measurables
Products with complete costing handovers.
Expected versus actual material and labour variance.
Project profit variance.
Open costing exceptions and age.
Costing errors found after quotation or manufacture.
Input to Data GPT · baseline before targets
12. Dependencies
Technical supplies validated product, BOM and formula logic.
Operations supplies actual usage, labour, stock and WIP.
Client Development applies approved pricing.
Financial Data reports profitability.
13. Risks
Finance is expected to invent technical consumption logic.
Technical remains permanent owner of financial checking.
System formulas are trusted without known-case testing.
Margin leakage stays hidden in aggregate results.
14. Immediate priorities
Define the costing handover from Technical.
Select known products for end-to-end testing.
Map expected-versus-actual data availability.
Document unresolved EVA calculation and integration issues.
Input to Rocks GPT · not an approved Rock
15. Definition of Done
Every priority product has documented, tested and controlled costing logic; Finance understands and audits it; actual performance can be compared with expected cost; and variance triggers a clear correction in Technical, Operations, pricing or financial control.
05 · Enable
HR & Office Administration
Provide scalable people and office administration while keeping day-to-day leadership accountability inside each department.
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1. Purpose
Protect IKON and enable its leaders through consistent people administration, payroll inputs, office coordination, controlled records and employee lifecycle support.
Contracts, confidentiality obligations, access changes, payroll inputs and disciplinary records are complete.
Managers and supervisors handle defined basic discipline within a clear framework.
HR administration supports leaders without taking over their responsibility to lead.
Working proposal
3. Current reality
Finance currently holds significant HR documentation and administration.
Existing checklists and files have improved, while the meeting identified further scaling and control gaps.
Managers can pass recruitment, discipline or administration into Finance when accountability is unclear.
The disciplinary software already structures offences, evidence and escalation.
Source confirmed
4. Problems & constraints
HR administration can become involved in every basic people issue.
Recruitment screening and onboarding are not consistently designed end to end.
System access, confidentiality and restraint reminders can be missed at exit.
Sensitive salary and employee information limits delegation.
5. What must be resolved
Define the boundary between central HR administration and line leadership.
Approve recruitment, onboarding, discipline, payroll-change and exit workflows.
Define which actions supervisors may handle and when HR or legal support is required.
Confirm confidentiality and delegation rules.
Leadership decision required
6. Operating model
Leader raises approved people event → central administration runs process and records → manager owns leadership decision → approvals occur → systems, payroll and files update → exception escalates → completion is audited.
7. Capabilities & training
South African labour-law and disciplinary fundamentals.
Structured screening and interview administration.
Payroll-input control and confidentiality.
Employee evidence management.
Manager and supervisor training on warnings and escalation.
8. Roles & accountability
Central HR and Office Administration owns process, records, office coordination, advice and completion controls. Department leaders own hiring decisions, performance management and discipline within the framework. Major matters escalate. Seats follow engine approval.
Engine before people
9. Systems, tools & documents
Secure employee master file and office administration register.
Recruitment and interview checklists.
Contract, NDA, restraint and policy acknowledgements.
Onboarding, access and exit checklists.
Disciplinary software and escalation framework.
Payroll change forms and approvals.
10. Standards
Every employee event follows the approved checklist.
Confidential access is limited to need.
Managers do not outsource leadership to HR administration.
Discipline follows approved process and evidence standards.
Departing employees lose access promptly and receive required reminders.
11. Measurables
Incomplete files or onboarding actions.
Recruitment administration lead time.
Payroll corrections and late changes.
Outstanding disciplinary documents.
Exit controls not completed on time.
Leaders trained in the approved process.
Input to Data GPT · baseline before targets
12. Dependencies
Department leaders initiate and complete their responsibilities.
Finance and payroll need approved employee changes.
System owners action access changes.
External labour or legal expertise supports major matters.
13. Risks
Central HR becomes the manager for everyone.
Untrained supervisors create labour-law exposure.
Confidential information is over-delegated.
Incomplete exits expose IKON’s IP or systems.
Process becomes bureaucratic instead of enabling.
14. Immediate priorities
Map the employee lifecycle and current owners.
Clarify leader versus central HR responsibility.
Validate discipline framework and supervisor training requirements.
Audit onboarding, file and exit-control completeness.
Input to Rocks GPT · not an approved Rock
15. Definition of Done
IKON has a simple, legally sound and scalable people-administration system; records and controls are complete; managers execute their responsibilities; and Finance supports the process without becoming default owner of every people matter.
Leader guide · from vision to traction
How to use the Engine Builder
The Engine Builder turns leadership thinking into a shared departmental vision, then gives the Seats, Data and Rocks GPTs the right context to convert that vision into execution.
What this tool is
A living vision and workshop platform. It shows what each departmental engine must become, what is missing today and what leadership may choose to build next.
What this tool is not
It is not the project-management system and it does not replace Strety. Seats, measurables, Issues and Rocks move into the appropriate GPT and then into the execution rhythm.
01
Vision Meeting
Define the department’s one-year vision: its purpose, desired future state, current reality, problems, capabilities and dependencies. Record the meeting.
02
Draft the Engine
Use the transcript to build the engine visual, component blueprints and proposed one-year finished state.
03
Pre-Quarterly Workshop
Leadership reviews each component, challenges the thinking and decides what must be built within the next 12 months or sooner.
04
Edit and Record
Edit the workshop blocks live. Add missing points, remove what does not belong and record the complete discussion.
05
Approve the Vision
Combine the original transcript, workshop transcript and edits. Update the engine and separate decisions from unresolved issues.
06
Build the Seats
Define the Seats and accountabilities required by the approved engine before discussing who should occupy them.
07
Build Data and Rocks
Choose the numbers that prove the engine works, then select the few quarterly Rocks that close the most important gaps.
08
Execute and Improve
Run the quarter in Strety, surface Issues, capture learning and feed material changes back into the engine vision.
The GPT sequence
Seats → Data → Rocks
Always follow this order. Rocks cannot be assigned properly until accountability is clear, and priorities should be informed by the numbers that expose the biggest gaps.
First
Seats GPT
Upload the approved engine pack and transcripts.
Define the Seats required
Set five major accountabilities
Clarify handoffs and capacity gaps
Define the Seat before the person
Output: approved Seats and accountabilities
Second
Data GPT
Add the approved Seats output to the engine context.
Select leading and lagging indicators
Give every number an owner
Set reporting frequency
Identify where baselines are required
Output: departmental Scorecard and outcome measures
Third
Rocks GPT
Use the engine, Seats and Data outputs together.
Identify the most important gaps
Select only a few quarterly priorities
Give every Rock one owner
Write a measurable Definition of Done
Output: focused 90-day Rocks ready for Strety
Do not try to build the whole engine in one quarter. The pre-quarterly identifies the 12-month destination. Quarterly planning selects the few parts that matter most now.
What leaders need
Workshop handoff checklist
Before the workshopRead the engine vision and relevant component blueprints. Bring corrections, missing issues and practical evidence.
During the workshopChallenge the content, edit the blocks and agree what the engine must look like within one year.
After the workshopProvide the original Architecture transcript, workshop transcript, edited blueprint and approved engine context.
Before executionComplete Seats first, Data second and Rocks third. Transfer the approved outputs into Strety.
Source documents
Documents
The transcript is the controlling source. This draft does not convert working proposals into approved decisions, Seats, targets or Rocks.
Finance Engine Vision Architecture Transcript
Meeting held on 19 August 2026 with Dominic Pedreiro, Meegan Campbell, Gordon Harrison and Angie Pedreiro.
Architecture conclusion
Financial Data & Analytics · Debtors, Creditors & Cash Control · Costing & Profitability · Systems, Automation & AI · HR & Office Administration
Systems, Automation & AI is an approved full Finance Engine component.
Source control
Source loaded: 08-19 Finance Engine Vision (Architecture) transcript, 19 August 2026. The original transcript remains controlling evidence for workshop validation.