In the fiercely competitive industrial landscape, the pursuit of operational efficiencies that minimise disruption, elevate productivity and drive growth is the ultimate aspiration.
Data solutions are fast becoming a lifeline for organisations that are striving to achieve these goals, and the concept of digital transformation has evolved from a futuristic dream into a tangible reality for many. However, embarking on the journey to successful transformation can be daunting and fraught with complexity. As a result, some organisations may be falling into the trap of going in big with large, high-cost projects , rather than focusing on the data they already have in abundance within the plant, and working on a plan to extract it to avoid disruption and downtime now, not at some point in the future.
The sheer magnitude of big data can indeed be daunting but by extracting the right measurements from asset-based modules, the process is more manageable and scalable, and efficiencies that lead to reduced operating costs can be achieved quickly. With a modular approach in place, these early benefits continue to accumulate and expand over time. But where to start in embarking on or expanding the digital transformation journey is the million-dollar question.
Navigating the maze of data solutions providers
The surge in service providers in recent times has made the case for digital transformation even more pressing for industrial operators who are being bombarded with messaging of how data, when wielded strategically, unlocks profound business insights capable of driving growth. With a crowded marketplace of traditional industrial automation companies and new emerging start-ups, all offering a multitude of services from monitoring and measurement through to AI-driven analytics – the abundance of options can be bewildering for industrial businesses seeking a path to digital transformation. How can they best choose a partner to take them on this important journey?
Not all data solutions providers are created equal, and sourcing one with industrial sector knowledge and experience is crucial. Knowing what to monitor, how to measure and how that information can best yield actionable insights is key – data alone is not enough. But even more fundamental to success is the ability of the software to successfully integrate an often diverse array of equipment brands and types, with different ages and data technologies. Seeking a solution that is brand agnostic is imperative.
As is the case across many sectors, there is a transience in the nature of start-ups. This could spell bad news for an industrial organisation that has put its investment and faith in a firm not yet fully established. Many start-ups emerge as a result of capital investment funding and these funding cycles can often experience delays or abrupt halts, potentially impacting the development or continuity of new solutions. This makes the longevity, credibility and sector-specific experience of a solutions’ provider key factors in the investment decision.
Pursue meaningful and effective transformation
Amid the fervour surrounding the Big Data movement, many industrial entities rushed to deploy sensors and monitoring systems. This has been exacerbated in recent years with the reduction in the cost of such technology, and not always to good effect. Data collection in manufacturing and industrial plants has definitely soared, but often without a coherent strategy for application. This glut of data sat in disparate silos has possibly hindered, rather than facilitated, informed decision-making. When a step-by-step approach is taken– identify a specific problem, extract the relevant data and gain insights to help solve the issue– the investment and risk are low and the approach scalable. Furthermore, this approach can be applied strategically for the prioritisation of the most critical assets.
It’s also important to work with a data solutions provider that can help in unlocking the low-hanging fruit existing in industrial environments. Collaborating with firms grounded in industrial engineering expertise – those which possess an in-depth understanding of the sector, coupled with proficiency in process control environments, IT integration, and digitally connection of both new and legacy assets – is key. The ability to pinpoint existing valuable data within the factory and identifying gaps requiring attention is something a firm with experience will be able to offer. This can be used to help optimise predictive maintenance, minimise production downtime and even achieve energy efficiency, which can aid sustainability goals. A consultative approach will also help organisations develop key performance indicators (KPIs) and objectives that they may struggle to develop without this input and expertise.
The cloud provides the scalability needed and the most cost-effective solution
For any industrial enterprise venturing into or expanding data solutions, deciding between cloud and on-premise options can present a real headache. However, as the industrial Internet of Things (IoT) often necessitates substantial data processing and storage capabilities, an on-premise approach can be cost-prohibitive due to hardware limitations, whereas cloud solutions offer scalable resources that can align with business requirements now, and in the future. Cloud-based solutions also eliminate expensive hardware maintenance and upgrades and do not require any support time from technical personnel
Cloud-based solutions offer unparalleled accessibility. As long as an internet connection is present, industrial IoT data can seamlessly traverse multiple departments and geographical locations, empowering organisations to harness the power of this to make real-time decisions based on information gleaned from multiple sources. Additionally, cloud solutions often exhibit greater compatibility with other software and systems compared to on-premise alternatives. This compatibility proves invaluable for integrating industrial IoT data with enterprise systems used in industrial environments like Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Manufacturing Execution Systems (MES).
Concerns about security often present a roadblock to cloud adoption, but cloud solutions typically have extremely robust capabilities to cater for the safeguarding of sensitive data linked to manufacturing processes and supply chain operations. It’s clear that in an Industry 4.0 landscape, cloud-based solutions are the unequivocal choice. The agility afforded by cloud services is paramount for survival in turbulent economic conditions, while the ability to scale resources in real-time, coupled with maintenance-free operations and state-of-the-art security, delivers significant savings.
Digital transformation is no longer a distant aspiration but a compelling necessity. As barriers to adoption are gradually broken down, the case for digitally connecting industrial assets becomes unequivocal, and the effectiveness of a modular approach can be tried and tested in phases. This can offer real peace of mind to those looking to either toe-dip or take their digital transformation journey to the next level. It’s as important to choose the right solutions provider as it is to take action. But the cost of inaction in a rapidly evolving landscape will be to the detriment of any industrial operator.