inventory management

The Future of Asset Management: Insights from mendrhub’s Founder on AI, Data and Smarter Decisions

July 28, 2026 by Mendrhub

As AI continues to rapidly speed up what’s possible for asset-centric platforms, businesses are increasingly moving away from reactive servicing and towards intelligent decision-making. But according to mendrhub founder, Glen Barkhan, the future of asset management isn’t just automation, dashboards or predictive maintenance.

It comes down to one thing: data, and what organisations do with it.

Data as a core driver of business decisions

Collecting data isn’t a new concept for most organisations. However, analysing it previously required specialist expertise and significant manual effort. It would take a data analyst days or weeks to extract useful insights from sources like service histories or downtime reports – something that AI can now do in a fraction of the time.

This doesn’t mean that AI will replace analysts. Instead, AI can handle the “grunt work” while analysts use their expertise to interpret the actionable insights. As Glen explains, “The key word with all clients is data, and being able to use that data to identify historical trends and predict what will happen in the future.”

For asset management, it means a shift from simple record-keeping to in-depth analysis and forecasting.

Data-capture intelligence

Modern asset platforms are becoming increasingly intelligent in the way they capture data. Whereas previously a technician would simply log that they replaced a thermostat, systems can now record asset-specific details like:

the exact model
the specific serial number
the compatible part used
the performance outcome

This matters because each asset behaves differently. Even identical machines operating in different environments or used differently by staff will experience different wear patterns and issues. Smart asset-centric systems now offer detailed serial-level tracking that helps organisations understand failure trends, identify weak components and improve first-time-fix rates.

Uptime as a financial metric

Asset uptime has long been considered an engineering KPI. Now, with broader data available through modern asset platforms, organisations can combine downtime duration with transaction volumes and performance data to estimate the financial impact of equipment failures. The future of asset management will see uptime become a revenue metric – not just an engineering one.

In practice, it means if a key machine fails across multiple restaurant locations, the asset management system can provide an estimate for how much revenue is potentially lost during the downtime. Multiply this across hundreds of sites, thousands of assets and multiple failure events, the financial impact of downtime is clear.

This is where asset management becomes business strategy.

How AI will shape the future of asset management

AI-powered tools are now capable of everything from identifying equipment faults before they happen to capturing vast amounts of data instantly. For example, mendrhub’s asset auditing capability uses AI to capture serial code information automatically, reducing work that previously took days or weeks into a much faster process.

It’s an exciting leap ahead for asset management innovation, but the question remains: what does AI mean for jobs?

According to Glen, the shift is already underway.

“The reality is that over time, jobs change. There will be plenty of opportunities to upskill as AI becomes more prevalent, which I think is important – so you don’t risk being left behind.”

But Glen still believes that one of the biggest misconceptions about AI in asset management is that it will completely replace human expertise.

“It doesn’t necessarily replace humans. It becomes an enabling tool to allow them to do tasks quicker. This means that smart business operators can grow without a corresponding increase in overhead.”

The future of asset management is predictive and insight-led

As we look ahead, Glen predicts that the organisations that will succeed are the ones taking advantage of smart asset management platforms that are:

Data-rich
AI and automation enabled
Model-aware
Uptime-focused

Organisations that can capture detailed asset data and predict performance will reduce downtime, have happier customers and enjoy the boost to their bottom line. Because the future of asset management isn’t just about getting things done faster – it’s about understanding each asset enough to prevent failure before it happens.

What is OCR (Optical Character Recognition) & How Does It Work?

July 28, 2026 by Mendrhub

As workplaces evolve with new technologies and with automation becoming the norm, manual data entry is no longer a sustainable work process. That’s why OCR (Optical Character Recognition) has become such a powerful tool. This not-so-new technology is changing the way businesses operate and increasingly saving them time and money. Let’s take a look at what it is, where it came from, and why it can help your business.

What is OCR?

OCR or Optical Character Recognition, is a technology that automatically extracts data to convert printed text or images of text into a machine-readable format. This means that images of invoices or PDF’s can be read by a computer and digitised, with different sections of the invoice identified to instantly match relevant data to a purchase order or a job, saving countless hours of admin time. You can also scan and instantly digitise text from:

Receipts
Delivery dockets
Contracts
Maintenance reports
Compliance forms

How does OCR work?

OCR software requires either a digital document such as a PDF or a digital image to be able to process text. Thankfully, we all have access to a quick way to digitise information via our smartphone cameras! The actual OCR processing involves multiple steps including:

Image acquisition – the OCR program identifies dark areas as characters to recognise and light areas as background
Preprocessing – the digital image is stripped to remove extra, irrelevant pixels
Text recognition – the darker parts of the image are processed to look for alphabetic letters, symbols or numbers
Pattern recognition – the OCR software is previously trained on text in specific fonts and formats
Feature recognition – when analysing a font that the OCR software hasn’t been trained on, it will look for rules relating to the features of a specific letter or number to recognise the characters
Layout recognition – the OCR software will analyse the entire structure of a document and divide it into elements like blocks of text or tables
Postprocessing – the gathered data is stored as a structured and editable digital file, which can then have the specific data you want sent through to

How has OCR evolved?

OCR has been around for more than a century, but the technology has changed dramatically over time. What started as a way to recognise simple printed characters has evolved into intelligent software that can extract, interpret and route information from complex business documents.

1. Early experiments

The earliest OCR-like systems appeared in the early 20th century. These were mechanical and optical devices designed to recognise typed or printed characters. They were limited, experimental and usually required very specific fonts or document formats to work reliably.

2. Commercial OCR

By the 1950s and 1960s, OCR began to be used commercially, particularly in banking, government and large-scale administration. These systems could read clearly printed text, but they usually relied on standardised fonts and highly structured documents. They were useful, but not flexible.

3. Digital OCR

From the 1990s onwards, OCR became widely available through desktop scanners, document management systems and searchable PDFs. Businesses could digitise paper records, search document archives and extract basic information from forms, invoices and reports. This made OCR much more practical for automation and everyday office use.

AI-powered OCR

Today’s OCR systems use artificial intelligence, machine learning and, increasingly, large language models to do much more than recognise characters. Modern OCR can identify document types, understand context, extract key fields, read tables, handle different layouts and validate information against business systems. This means OCR is no longer just about turning images into text — it is becoming part of broader document automation and intelligent workflow systems.

What can modern OCR actually read?

For most businesses, the important thing to understand is what an OCR system can actually do with your documents.

Basic OCR reads printed text from an image or scanned document and turns it into editable, searchable text. This is useful for digitising paper records, making PDFs searchable, or extracting simple information from clean, standardised documents.

More advanced OCR can recognise handwriting, checkboxes, tables, forms, logos, signatures and document layouts. This is useful for invoices, delivery dockets, maintenance reports, compliance forms and other documents where the information is not always presented in the same way.

Finally intelligent OCR goes a step further. Instead of simply reading text, it can help identify what the document is, where the important information sits, and how that information should be used. For example, an intelligent OCR system might read an invoice, identify the supplier, extract the invoice number and total, match it to a purchase order, and send the information into the right workflow for approval or payment.

What are the benefits of OCR?

OCR can deliver significant benefits for businesses that still rely on emailed documents, manual data entry or paper records:

Less manual data entry

One of the biggest advantages of OCR is that it reduces the need for people to manually type information from invoices, forms, receipts or reports into another system. This saves time, lowers admin costs and frees staff to focus on higher-value work.

Fewer errors

Manual data entry is slow and prone to mistakes. OCR can help reduce errors by extracting information directly from the source document and applying validation rules, such as checking invoice details against a purchase order or matching a job number to an existing record.

Faster document processing

OCR can speed up processes that rely on paperwork, such as invoice approval, job matching, asset registration, compliance reporting or warranty claims. Instead of waiting for someone to read and enter the information manually, documents can be scanned, read and routed automatically.

Searchable digital records

OCR makes scanned documents searchable. This means teams can quickly find an invoice, contract, delivery docket, maintenance report or compliance form by searching for a supplier name, job number, asset number or keyword.

Better visibility and reporting

Once information has been extracted from documents, it can be used in dashboards, reports and business systems. This gives teams better visibility over operations, costs, jobs, assets and compliance requirements.

Easier automation

OCR is often the first step in a broader automation workflow. Once a system can read and understand a document, it can trigger the next action — such as matching an invoice to a job, sending a form for approval, updating an asset record, or notifying the right team member.

To Wrap Up

For businesses dealing with high volumes of invoices, forms, reports or service documents, OCR can make everyday operations faster, more accurate and easier to manage.

OCR certainly isn’t a new technology, but as it continues to evolve, it continues to make manual data processing a practice of the past. With its numerous benefits and potential to increase productivity and profitability, it’s no wonder that so many companies are already on board – including us.

Intelligent OCR technology is integrated into our system to learn the custom format of invoices and instantly match any relevant data to a certain job. It automates billing and saves on admin hours, so we can say with certainty that this technology is worth looking into.

4 Best Practices for Asset and Inventory Management

June 21, 2024 by Mendrhub

Whether you’re working in the equipment manufacturing, distributing, or field service sectors, managing your assets and inventory effectively is critical for maximising profit margins. Proper management can also save on costly mistakes, improve overall productivity, and ensure everything is tracked and valued in real-time. Having worked with clients across these industries, we’ve identified several best practices for asset and inventory management that have fuelled their growth.

Conduct Regular Audits

Auditing may be a standard operation in most (if not all) businesses, but it can easily be overlooked when other priorities arise. Unfortunately, it’s when audits get skipped that problems occur. Regular auditing of your equipment and part inventory will help identify any discrepancies, faults, maintenance issues, or mix-ups, so you can address obstacles before they become larger, more costly problems. Regular audits will also help you determine the actual value of your assets and usage frequency of parts, helping you forward plan, and effectively manage capacity.

Label All Assets

Another best practice businesses should consider adopting is labelling their assets using unique identification numbers. Scannable, unique QR codes are perfect for quickly identifying assets, verifying their location, and determining their status. In addition, for manufacturers and distributors, placing QR codes on either your assets or asset packaging can provide your end users with a seamless way to register their new purchase for warranty and book after-sales servicing. Asset and facility management software like mendrhub stores all QR codes linked to equipment details, along with supporting integrated customer registration and after-sales servicing, making the addition of these labels an affordable way to add significant value.

Implement a Just-In-Time (JIT) System

The Just-In-Time system is a type of inventory management where you work closely with your suppliers to ensure raw materials arrive precisely when production begins, not any sooner. The goal here is to have the absolute minimum amount of inventory on hand to meet current demand. Adopting JIT practices has been shown to reduce excess inventory and the associated holding costs. It also helps you maintain a strong relationship with each supplier, which is required to ensure inventory is delivered as needed.

Use a Centralised Asset Management System

Using a centralised asset management system to track all assets and parts from factory to warehouse to end user can transform the operational efficiency and overall experience of your procurement, warehouse, and service facilitator teams. A system like mendrhub will provide detailed reports of asset service and logistics history and whole-of-life costs to help you determine economic viability and proactively manage your assets.

You can even monitor and move spare parts between locations and technician’s van stock, or create purchase orders to refresh inventory shortages. Workflow automation and technician scheduling also help to ensure your assets are managed efficiently and effectively.

Running a successful business means having a full view of company operations – especially your assets. By following these best practices, you’re setting yourself up for success. Are you interested in how an asset and facility management system like mendrhub could work for your business? Get in touch today to have a chat.

The Future of Asset Management: Insights from mendrhub’s Founder on AI, Data and Smarter Decisions