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In a market flooded with cloud-based Enterprise Resource Planning\u00a0(<\/strong>ERP) SaaS solutions for machinery maintenance \u2013 seemingly with little differentiation \u2013 informed decision-making can be a major dilemma. There are no guarantees: products may not always deliver the desired outcome. Adoption of some can result in unintended consequences \u2013 failing to address the problem at all, or even worsening unplanned maintenance and equipment downtime.<\/p>\nHaving observed this impact on machinery reliability significantly, two experts from leading global software solutions provider,\u00a0麻豆原创<\/a>, advise asset and maintenance teams to apply due diligence when looking for suitable solutions. Mohamed Beradhi<\/a> is 麻豆原创 Value Prototyping I4.0 Global Portfolio & Programme Management, and Anthony Poltera<\/a> is 麻豆原创 Value Prototyping Lead and 麻豆原创 Enterprise Architect.<\/p>\n The two share experiences drawn from addressing heavy industry\u2019s specific needs in ERP SaaS in the Middle East and African region (MEA) with 麻豆原创\u2019s flagship solutions:\u00a0RISE with 麻豆原创<\/a>\u00a0and\u00a0GROW with 麻豆原创<\/a>. Through highlighting common challenges, they hope to raise awareness about steps industries can take to make informed purchasing decisions to ensure their cloud ERP software enables optimal machinery maintenance.<\/p>\n Heavy industry companies, such as those in mining or energy, often rely on critical machinery that must operate continuously even in remote or rugged environments. Moving to a cloud-based enterprise resource planning (ERP) system can deliver real benefits such as greater visibility, improved maintenance scheduling, and predictive insights.<\/p>\n However, this also introduces challenges that must be managed carefully. The transition may not always be as smooth as generally desired, states Beradhi, underlining the following common challenges encountered:<\/p>\n One of the biggest hurdles is adapting existing systems and processes to the standardised way software-as-a-service (SaaS) ERPs are designed to work. Instead of highly customised setups, these platforms encourage businesses to adopt best practices \u201cout of the box\u201d. While well-meaning, this can involve significant change management.<\/p>\n Integrating operational technology (OT) \u2013 such as sensors, industrial control systems, and machine data \u2013 with information technology (IT) systems also presents difficulties. Unfortunately, when companies adopt multiple technology vendors, protocols, and legacy systems for asset maintenance, integration issues often arise. These problems can lead to inconsistent data and disrupted workflows, which makes ensuring real-time visibility more complex. In addition, it results in increased costs for custom connectors and maintenance.<\/p>\n Remote locations with unreliable connectivity also pose problems. In such environments, field teams need offline capabilities to continue working without internet access. This challenge is particularly relevant in parts of Africa where infrastructure limitations can affect connectivity and system responsiveness.<\/p>\n Data quality is another sticking point. Firstly, without consistent, well-governed data models, it is difficult to obtain accurate analytics or build effective predictive maintenance strategies. Secondly, safety and cybersecurity must also be considered, especially when bridging IT and OT systems. Lastly, getting workers up to speed with new tools requires tailored training that reflects on-the-ground realities.<\/p>\n These abovementioned challenges are worsened when software developers make wrong assumptions about the needs of clients in heavy industry during product design. \u201cWhen building cloud-based asset management solutions for heavy industries, software developers sometimes overlook real-world conditions,\u201d Poltera points out, underlining oversights in the following areas:<\/p>\n i.\u00a0Data Quality and Connectivity Issues<\/strong> ii.\u00a0Mobile Application<\/strong> iii.\u00a0Generic User Experience<\/strong> iv.\u00a0Underestimating Change Management<\/strong> Evidently, based on these bottlenecks, it is paramount that end-users exercise prudence in procurement when selecting ERP SaaS maintenance solutions. With many vendors in the market, it is not easy to separate the wheat from the chaff from the products out there.<\/p>\n For this reason, Beradhi advises heavy industry players to go beyond feature checklists, as there is more to ERP than merely ticking boxes before procurement.<\/p>\n \u201cFor asset reliability managers, uptime is everything. So, any solution they adopt needs to improve how well they can monitor, maintain, and optimise equipment.<\/p>\n \u201cHence, when evaluating different systems, it is important to go beyond feature checklists and consider whether the solution supports the realities of heavy industry environments such as harsh field conditions, remote locations, complex safety requirements, and integration with operational systems,\u201d Beradhi explains, citing the following features as essential:<\/p>\n a.\u00a0Openness and Interoperability<\/strong> \u201cOrganisations should treat integration as a priority, not an afterthought. That means requesting clear documentation on application programming interfaces (APIs), data event schemas, and compliance with operational technology (OT) standards such as ISA-95. They should also define a standardised asset data model and governance framework to ensure consistency across systems. Selecting platforms that are designed to work together reduces the need for expensive custom integrations, and any request for proposals (RFPs) should include integration testing as a mandatory requirement,\u201d Beradhi says.<\/p>\nCommon Challenges<\/strong><\/h2>\n
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Wrong Assumptions Software Developers Make<\/strong><\/h3>\n
\nA common assumption is that clean, real-time machine data will be readily available. In practice, data quality varies widely, and connectivity issues can introduce delays. In addition, many systems assume uniformity in operational protocols, whereas heavy industry environments are often fragmented and vendor-diverse.<\/p>\n
\nMobile applications are another pain point. Developers may assume constant connectivity and uniform device usage. However, technicians frequently work in harsh, remote locations with limited network coverage and a range of mobile tools.<\/p>\n
\nUser experience is often treated as generic, yet the needs of field technicians, planners, and reliability engineers differ vastly. For instance, data governance \u2013 especially around asset master data \u2013 is often overlooked, yet it is vital for ensuring that analytics and AI tools function properly.<\/p>\n
\nFinally, developers often underestimate the change management involved in shifting processes, or neglect safety compliance and system integration testing during upgrades.<\/p>\nSelecting Maintenance Solutions<\/strong><\/h2>\n
Going Beyond Feature Checklists<\/strong><\/h2>\n
\nOpenness and interoperability are key. Ideally, any modern maintenance system should be able to integrate seamlessly with shopfloor equipment, Internet of Things (IoT) platforms, geospatial systems (GIS), and analytics tools. The best time to avoid integration problems is during the procurement phase by setting clear expectations around integration, testing, and data standards from the outset.<\/p>\n