Are We Measuring What Really Matters? A Different Way to Think About Asset Management Reporting and KPIs

Over the past few years, I've found myself thinking more about the reports we produce in asset management, and across the Council. Not because there's anything wrong with them, but because I'm starting to wonder whether we're measuring the things that really matter.

All businesses, organisations and councils collect an enormous amount of data these days. At the council, we have asset management systems, GIS, finance systems, customer request systems, inspection records and increasingly, business tools like Power BI that can pull all of that information together. We certainly are not short on numbers! But are we asking the right questions?

Welcome to the Iamdata Solutions Asset Management Newsletter – August 2026

Jill Singleton

Director - Asset Management Specialist & Data Analyst

It is something I've been reflecting on recently because the conversations I have with different people across a council can be quite different. An operational team might want to know how many work orders were completed this month, while an executive is often asking something completely different. They're usually more interested in whether risk is reducing, whether services are improving and whether the money being invested is making a real difference.

Neither perspective is wrong. They're simply answering different questions.

Activity Doesn't Always Equal Success

I still see a lot of reports that focus on things like the number of work orders completed, kilometres of road maintained or whether the maintenance budget has been fully spent. Those figures are useful and they absolutely have their place. Operations teams need that information to manage workloads and resources. But I sometimes wonder if those numbers tell the whole story.

Take work orders, for example. Imagine one department completes 12,000 work orders during the year while another completes 8,000. At first glance, it feels like the first department has been more productive.

Then you start digging a little deeper….

What if the second department had invested more in preventative maintenance? What if they renewed several ageing assets before they failed and, as a result, received far fewer emergency call-outs? Suddenly, completing fewer work orders might actually be a sign that things are improving rather than getting worse.

Are We Solving Problems or Just Responding to Them?

The same thought came to me when I was thinking about customer requests. We often celebrate completing thousands of customer requests each year, and that's definitely something worth recognising. But wouldn't an even better outcome be receiving fewer requests in the first place because recurring problems had actually been fixed?

Imagine two roads with ongoing pothole issues.

One road receives patches on the potholes every few months and records hundreds of maintenance jobs. The other receives a reconstruct on the worst section of road and eliminates the problem for years.

The maintenance numbers might actually go down, but most residents would see that as a much better result.

It makes me wonder whether we're sometimes measuring how well we respond to problems rather than whether we're reducing the number of problems that occur.

Looking Beyond the Budget

The same applies to budgets.

I've seen reports proudly showing that 99 percent of the maintenance budget was spent. That's certainly important from a financial perspective, but I've often wondered whether the more interesting conversation is what that spending actually achieved.

• Did asset condition improve?

• Did failures reduce?

• Did we make life easier for maintenance crews?

• Did customers notice a better level of service?

Those are much harder questions to answer, but they also feel much closer to what asset management is really trying to achieve.

Is Risk Showing Up in Our Asset Management Reporting KPIs?

Risk is another area that seems to be getting much more attention, and rightly so. Almost every council I've worked with has mature risk frameworks now, yet I don't always see risk reflected in performance reporting.

For example, rather than simply reporting the number of drainage inspections completed, would it be more meaningful to understand whether the highest-risk drainage assets were inspected on time and subsequently, risk reduced?

They're similar measures, but one tells us far more about whether we're focusing our effort where it matters most.

Thinking About the Community

Another thing I've been noticing is that communities don't really experience our KPIs. They experience the outcomes.

Residents don't know how many work orders were completed this month.

·        They know whether the street flooded.

·        They know whether the playground was repaired quickly.

·        They know whether the park is well maintained.

·        They know whether someone responded when they reported a problem.

Perhaps that's where some of our reporting should begin. Instead of asking what work we completed, maybe we should also be asking whether people are noticing an improvement in the services we provide.

Better Data Creates Better Conversations

One area where I think technology is really helping is our ability to bring information together. A few years ago, many of these datasets sat in completely separate systems. Now it is becoming much easier to combine GIS, inspection records, customer requests, financial information and maintenance history into a single view.

That opens up some really interesting possibilities.

Instead of simply reporting that we serviced 150 pumps this quarter, we can start asking whether pump reliability is improving. We can look at whether failures are becoming less frequent, whether maintenance costs are changing over time, or whether particular assets are costing far more than others to operate.

Those conversations feel much more useful than simply counting completed jobs.

Perhaps it is Time to Broaden the Conversation

I don't think this means we should stop measuring traditional operational KPIs. They remain incredibly valuable for managing day-to-day activities and making sure work gets done.

But perhaps they're only part of the picture.

The next generation of asset management reporting isn't about replacing those measures at all. It is about adding another layer that helps us understand the outcomes behind the activity. I don't think anyone's ultimate goal is to complete the most work orders or spend every dollar in the maintenance budget. The goal is to provide reliable services, reduce risk where we can, make sensible long-term investment decisions and ultimately improve the communities we serve.

I'd be interested to know whether you've noticed a similar shift. Are the conversations in your organisation changing as well? Are executives asking different questions than they were five or ten years ago? I suspect the way we measure success will continue to evolve over the coming years.

OK, but Where Does This Data Come From?

One question I'm often asked after demonstrating an Asset Management Reporting Power BI report like this is, ‘Where does all of this data actually come from?’

The answer is that very little of it usually comes from a single system.

Take the example KPIs in this post. They would typically be built from information spread across several different business systems.

For example:

• Asset Management System (AMS): Asset registers, condition assessments, maintenance history, work orders, asset hierarchy and service levels.

 

• GIS: Asset locations, spatial relationships, catchments, service areas and network connectivity.

 

• Customer Request Management (CRM): Customer requests, response times, repeat requests and customer interactions.

 

• Finance System: Operational expenditure, capital expenditure, renewal programs and lifecycle costs.

 

• Inspection Systems: Asset inspections, defects, risk assessments and compliance activities.

 

• Document Management Systems: Drawings, inspection reports, photographs and supporting documentation.

 

Each system plays an important role, but they were generally designed to support day-to-day business processes rather than executive reporting. They often use different identifiers, different structures and sometimes even different definitions for what appears to be the same piece of information.

That's where the real work begins.

Preparing the Data for Asset Management Reporting in Power BI

Before this information can be presented in a Power BI report, it usually needs to be extracted, validated and combined into a single, consistent source. This is where SQL databases / warehouse / lakehouse's are key.

Typical preparation activities include:

• Standardising asset identifiers across systems.

• Cleansing duplicate or incomplete records.

• Validating spatial data and asset relationships.

• Combining maintenance, inspection and financial information into a common asset model.

• Calculating business measures such as service levels, risk scores and data quality indicators.

• Creating consistent time-series data for trend reporting.

• Applying business rules so that KPIs are calculated consistently every time the report is refreshed.

This preparation is often referred to as ETL (Extract, Transform and Load)

Why This Work Shouldn't Be Done in Power BI

One of the biggest mistakes I see is organisations trying to perform all of this preparation inside Power BI using Power Query or DAX.

Power BI is an excellent reporting and analytics platform, but it wasn't designed to be the primary location for complex data engineering.

As reports become more sophisticated, this approach often leads to duplicated business logic, slower refresh times and different reports calculating the same KPI in different ways.

A much more sustainable approach is to perform the heavy lifting upstream within a data warehouse or lakehouse.

Within the data warehouse or lakehouse, data from each business system can be cleansed, validated and transformed into reporting-ready tables before Power BI ever connects to it.

This provides several important benefits:

• A single source of truth for reporting.

• Consistent KPI calculations across every report.

• Faster Power BI datasets and refresh times.

• Simpler report development and maintenance.

• Easier governance, auditing and troubleshooting.

• The ability to reuse the same trusted data across multiple dashboards and business areas.

I'll be covering more of this subject in my September 2026 blog post, 'The Hidden Complexity Behind a Simple Power BI Report'.

The Power BI Report Is the Final Step

When people see a clean, executive Power BI Report, it's easy to assume that most of the work happened inside Power BI. In reality, Power BI is really the final presentation layer.

The real value comes from the work completed beforehand, integrating data from multiple business systems, improving data quality, applying consistent business rules and building a reliable reporting model that decision-makers can trust. That's why the most effective Power BI reports rarely start with Power BI. They start with well-managed data.

Where Does the Data for These Asset Management Reporting KPIs Come From in Your Organisation?

Although these visuals appear quite simple, each one is likely to draw on information from several different business systems. One of the strengths of modern reporting platforms like Power BI is their ability to bring these datasets together to tell a much more meaningful story than any individual system could on its own.

Risk Reduced

This KPI would typically combine information from the Asset Management System, inspection records and risk assessments. The underlying calculation might compare the number of assets classified as high or extreme risk over time, allowing management to see whether maintenance and renewal programs are genuinely reducing organisational risk.

Service Levels

Service level reporting is generally derived from the Asset Management System using condition assessments, asset performance measures or levels of service defined within the asset management plans. In some organisations, operational data from SCADA systems, IoT sensors or other monitoring systems may also contribute to measuring whether service targets are consistently being achieved.

Customer Outcomes

This information is commonly sourced from the Customer Request Management (CRM) system and linked back to the Asset Management System. Rather than simply counting how many requests have been completed, this KPI focuses on whether the underlying issues have been resolved by measuring repeat requests, recurring defects or customer satisfaction over time.

Asset Reliability

Asset reliability is usually calculated from work orders, maintenance history and asset defect and failure records stored within the Asset Management System. Planned maintenance activities, breakdown history and inspection results can all be combined to understand whether assets are becoming more reliable as maintenance and renewal programs are delivered.

Lifecycle Cost

This KPI typically brings together financial information from the finance system with asset information from the Asset Management System. Instead of reporting how much money was spent, it focuses on whether maintenance and renewal investments are improving long-term value by reducing operating costs, extending asset life or improving service outcomes.

Data Confidence

Data confidence is often generated by assessing the quality of the asset register itself. It may draw on information from the Asset Management System, GIS and inspection systems to measure attributes such as completeness, accuracy, location quality, inspection coverage, photographs and missing asset information. While it isn't a traditional operational KPI, it provides valuable insight into how much confidence decision-makers can place in the information supporting their reports.

In my blog post: https://www.iamdata.solutions/post/the-hidden-cost-of-dirty-data I discuss how to build a Power BI report specifically check that your data is current, complete, and correct.

High Risk Assets Trend

High Risk Assets would typically be calculated from the Asset Management System, where each asset is assigned a risk rating based on factors such as condition, likelihood of failure and consequence of failure. This visual provides a simple snapshot of the number of assets currently classified as high risk, while the month-on-month change shows whether maintenance, renewal and risk mitigation programs are reducing that number over time. Rather than measuring how many inspections or work orders have been completed, it measures whether those activities are actually reducing organisational risk.

Critical Assets

Critical Assets are typically identified within the Asset Management System using an asset criticality framework that considers factors such as service impact, public safety, environmental consequences and operational importance. This KPI highlights the number of assets considered critical to service delivery and helps ensure they receive appropriate maintenance, inspection and renewal attention. Rather than treating every asset equally, it helps organisations focus resources where failures would have the greatest consequences.

Inspection Compliance %

Inspection Compliance is usually calculated from inspection schedules and completed inspections stored within the Asset Management System or a dedicated inspection management system. Instead of simply reporting the number of inspections completed, this KPI measures whether inspections are being carried out within their required timeframes, providing confidence that high-risk assets are being monitored and managed in accordance with the organisation's maintenance and risk management strategies.

Assets with Unknown Risk

This KPI is derived from the Asset Management System and highlights assets that cannot currently be assigned a reliable risk rating because essential information is missing. This may be due to incomplete condition assessments, missing asset attributes, insufficient inspection history or unknown asset characteristics. Monitoring this figure helps organisations identify gaps in their data quality, as reducing the number of assets with unknown risk improves confidence in maintenance planning, renewal prioritisation and long-term investment decisions.

Effort Versus Results by Asset Class

This visual combines information from several business systems to compare operational effort with the outcomes being achieved for each asset class. Work order volumes and maintenance activities would typically come from the Asset Management System, while service levels, condition improvements, risk assessments or asset performance measures are used to calculate the resulting benefit. By combining these datasets, the report highlights where maintenance effort is delivering strong outcomes and where significant effort may not yet be translating into improved asset performance.

Producing a measure like this usually requires more than simply extracting data from operational systems. Business rules need to be developed to define what constitutes both ‘effort’ and ‘results’, with those calculations ideally performed within a data warehouse or lakehouse so that every report measure performance consistently.

Asset Performance Matrix

This visual brings together data from the Asset Management System, inspection records and customer or operational performance measures to compare workload against service outcomes for each asset class. Work order history provides an indication of operational effort, while portfolio compliance, condition targets or service level measures indicate whether that effort is delivering the expected results.

The reference lines divide the chart into four distinct performance zones. Asset classes appearing in the upper left are delivering strong outcomes with relatively little operational effort, while those in the lower right represent areas where significant resources are being invested but desired service outcomes are not yet being achieved. This type of analysis helps shift conversations away from simply asking 'How much work did we complete?' and towards 'Are we investing our effort where it delivers the greatest benefit?'

Good reporting isn't really about building more reports. It's about helping people make better decisions. The data to answer many of these questions already exists within most organisations, but it often sits across multiple systems and needs to be brought together in a meaningful way. When we shift our focus from measuring activity to measuring outcomes, our reports become much more than a collection of numbers, they become tools that help guide investment, reduce risk and improve the services we provide to our communities.

If this has sparked a few ideas about the way your organisation measures performance, or you're wondering how your existing data could be transformed into more meaningful Asset Management reporting, I'd love to have a conversation. Whether you're looking to build executive Power BI reports, improve your asset data, develop a reporting data warehouse, or simply make better use of the information you already have, feel free to get in touch. I'm always happy to discuss ideas and explore how we can turn your data into insights that support better decisions.

I have worked on many different projects with my Local Government clients, from designing and developing Power BI Reports, to building SQL Server databases for spatial data, to managing and maintaining GIS and the Asset Management systems. If you'd like to discuss how we might work together, then please email Jill at ➡️ jill.singleton@iamdata.solutions

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