Better decisions for ageing public infrastructure.
Daphron Consulting helps public infrastructure owners manage their assets better. Our main goal is to assist asset owners to optimise their networks or portfolios of physical assets, by better understanding their infrastructure and how to scientifically manage it to maximise Return on Investment.
Infrastructure managers rarely have the luxury of asking only whether an asset is old or in poor condition. The real question is: given what we know about the asset today, what is the most economically sensible way to manage it over the planning period, and how can we manage the uncertainty in that answer?
Daphron is a specialist consulting service that operates primarily in the public infrastructure sector. Its focus is on answering the above question. We have developed a methodology, the Integrated Infrastructure Intervention Decision Methodology (I³DM), supported by a tool, Daphris, to implement the methodology and carry out the required analyses.
The question is not “which assets are old?”
It is which intervention, for which component, at what time, gives the strongest lifecycle value, and how uncertain is that answer.
Ranking by age or condition alone hides the economics. A cheap intervention today can be the most expensive option over a component’s life.
I³DM and Daphris
A methodology and a decision-support tool for planning large, ageing and data-scarce public infrastructure portfolios. The methodology defines the logic. Daphris makes it repeatable at portfolio scale.
I³DM, the decision methodology
The Integrated Infrastructure Intervention Decision Methodology combines established reliability, lifecycle-economic and uncertainty-analysis techniques into one component-level framework. It is built for varied portfolios where long deterioration records and analytical resources are limited.
Daphris, the execution engine
Daphris applies I³DM to every component in a portfolio. From minimal input data it runs the full lifecycle calculation for each option, repeats it across thousands of simulated futures, and produces auditable recommendations, five-year budgets and risk outputs.
From condition to lifecycle position
A condition score becomes useful for planning once it is translated into an effective age and remaining life. Move the sliders.
P is the target probability of failure (PoF) at EUL. η = EUL / [−ln(1 − P)]1/β, and effective age = η · [−ln(condition)]1/β. Condition is used as a practical proxy for a consistent deterioration age, not as a literal failure probability.
Four strategies, one starting point
Every option starts from the same observed Year-0 condition, so the economic comparison is fair. Daphris compares the whole future consequence of each strategy, not only the first cost.
Do nothing
Accept faster deterioration and the condition-dependent consequences that follow.
Planned maintenance
Maintain the existing component and preserve its maintained-life basis.
Rehabilitate, then maintain
Restore condition now, then maintain from the improved state.
Replace, then maintain
Renew now, reset to new condition, then maintain.
Lifecycle present cost
Which option has the strongest whole-life economic position, including maintenance, disruption, consequential damage and residual value?
Benefit–cost ratio
How much measured benefit does each option deliver per unit of lifecycle cost?
Incremental benefit–cost
Once dominated options are removed, is each step up in spending economically justified?
Ruling out false choices
Before any incremental comparison, a strategy is removed if another delivers at least as much benefit for no more cost, and is strictly better on at least one of the two. This stops inferior options from distorting the decision.
In this example
Do nothing (A) costs more than Replace + PM (D) and delivers less benefit, so it is excluded before the incremental comparison.
Incremental step 1: D against B
Planned maintenance adds R3.90m of benefit for R564k of extra cost, an incremental benefit–cost ratio of 6.91. Above 1.0, so B becomes the defender.
Incremental step 2: B against C
Rehabilitate + PM adds R179k of benefit for R487k of extra cost, a ratio of 0.37. Below 1.0, so B remains the defender.
Recommended
(B) Planned maintenance
Illustrative single-component example. The solid line joins the non-dominated options in order of cost. Swipe the chart sideways to see all of it. PM = planned maintenance; PV = present value.
Inputs are estimates. Budgets should say so.
In Monte Carlo mode, Daphris repeats the complete engineering and economic model across 5,000 simulated futures. Shared uncertainty is kept through correlation across the asset hierarchy, so risk does not diversify away unrealistically fast in a large portfolio.
The result is a funding range for the five-year budget horizon, not a single number presented as certain.
Illustrative relative index, not client data. Choose the percentile to match affordability and risk appetite.
Where to send limited inspection capacity
Each asset is banded by its simulated probability of needing intervention within five years.
Committed
Intervention appears unavoidable.
Likely
Strong evidence it falls in the horizon.
At risk
Material uncertainty. Inspect or monitor.
Beyond
Probably outside the five-year horizon.
What Daphris does not claim
A credible decision-support tool is clear about its boundaries. Engineering judgement stays accountable; Daphris makes it visible and testable.
- Condition equals failure probability
- Weibull reliability is a practical proxy for a consistent effective deterioration age.
- EUL is a guaranteed failure date
- EUL is an engineering reference value, not a guarantee.
- Monte Carlo predicts the future
- It quantifies the consequences of the uncertainty assumptions supplied.
- P95 is “the budget”
- Percentiles express different levels of planning confidence and risk appetite.
- Correlation is known precisely
- It is an engineering modelling judgement and should be tested.
- The recommendation overrides constraints
- Statutory, feasibility, service-standard and local-knowledge constraints still apply.
Getting started
Start with decision usefulness and improve calibration as evidence accumulates. There is no need to wait for perfect records.
Define the taxonomy
Agree asset type, component group and component, and who owns each parameter.
Load minimum viable data
Condition and replacement cost per asset, with governed defaults by class.
Calibrate and validate
Review useful lives, deterioration, costs and consequences with engineering specialists.
Run a deterministic baseline
Establish lifecycle strategies and surface data-quality issues.
Run the portfolio simulation
Quantify uncertainty, shared risk and five-year funding distributions.
Embed the governance cycle
Use outputs in AMPs, budget prioritisation, inspection planning and annual parameter review.
Advisory services
Support for public and private infrastructure owners at every level of asset management, from board-level strategy to the component register.
Strategic
Are we investing in the right things?
- Asset management policy and strategy
- ISO 55001 maturity and gap assessments
- Long-term investment planning and prioritisation
- Climate adaptation investment prioritisation
Tactical
What should we plan and fund, and when?
- Asset registers and component classification
- Asset management plans and lifecycle plans
- Lifecycle cost analysis and budget forecasting
- Road asset management system support
Operational
What is the real state of our assets?
- Condition assessment programmes
- Maintenance strategies, norms and standards
- Technical due diligence of facilities
- Scan-to-BIM models resolved into asset registers
Sectors: roads, water, sanitation, energy, solid waste and building facilities.
Dave Coetzee
Founder and physical asset management specialist
Dave has 38 years’ experience in infrastructure: municipal construction, structural design, a decade of project and programme management, and the last twenty-one years specialising in physical asset management. His focus is public infrastructure and utilities in developing countries.
He believes asset knowledge, knowing what you have, is the foundation of good asset management. He has worked in South Africa, Namibia, Mozambique, Malawi, Kenya, Morocco, Sri Lanka and Indonesia, and remotely on projects in Austria, Senegal and elsewhere in Asia.
- Registration
- Pr. Tech (Eng), Engineering Council of South Africa
- Certification
- Certified Senior Principal in Asset Management (CSAM); Certified Asset Management Assessor (CAMA2)
- Qualifications
- MSc Technology Management (Pretoria); M Dip Tech (Structural Engineering); MBA (Wales); Diploma in Asset Management, IAM
- Membership
- South African Asset Management Association (SAAMA); Institute of Municipal Engineers of South Africa (IMESA); Institute of Asset Management (IAM) UK, full member; Institute of Public Works Engineers Australia (IPWEA), international member
Selected work
- eThekwini Metropolitan MunicipalityAsset management specialist on the capital asset management ERP implementation: around 5 million components, estimated replacement cost US$30 billion.
- National Water Supply and Drainage Board, Sri LankaInstitutional capacity strengthening for the Asian Development Bank.
- Lilongwe Water Board, MalawiInvestment plan and framework, funded by the World Bank.
- Resilient transport, Kenya and SenegalClimate adaptation investment prioritisation for the Global Center on Adaptation.
- North West Department of Public Works and TransportAsset management lead for a road asset management system implementation.
- National Department of HealthFacilities and infrastructure lead for the national public health facilities maintenance strategy.
Let’s talk about your infrastructure portfolio.
A demonstration of Daphris on a sample of your own register is usually the quickest way to see whether it fits.
© 2026 Daphron Consulting, South Africa