Digital Transformation: Strategies and Pitfalls - Process Industry Informer

In the current manufacturing climate, which is shrouded in economic uncertainty, it can be tempting to prioritise initiatives with immediate ROI over digital transformation, which some say can typically take several years to yield full returns. However, the accelerated need for digital-first strategies in manufacturing – digitalisation over digitisation – CAN reap significant returns straight away (our view).

Arjun Chandar, Founder & CTO of IndustrialML looked at the pitfalls, benefits and strategies needed for unlocking digital transformation in the manufacturing sector for Process Industry Informer (10th Nov 23).

Consequently, manufacturers are dedicating substantial time and financial resources to fuel their digital transformation endeavors. According to McKinsey, due to these transformations, it’s common to see machine downtime decrease by up to 50%, throughput increase by 10-30%, labour productivity improve by 15-30%, and forecasting accuracy by an impressive 85%.

However, while these investments demonstrate positive results for a select few, the majority are still struggling to expand pilot programs or harness the full potential of technology, hindering their ability to realise substantial returns. Arjun dives into what’s causing these pitfalls before reviewing some changes manufacturers can make to avoid them.

Do bear in mind that automating can help to streamline, speed up and increase volume, whilst lasers and sensors help to ensure (better) accuracy and alignment, as shown by our range of machines and conveyors.
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Risk #1 – Automating Before Properly Analysing

Manufacturers can often get distracted by the allure of technology, discussing specifications and pricing without considering what the core business objectives are. While automation, such as welding or robotics, may be the end goal, it’s crucial to explore scalable steps that align technology adoption with overarching objectives, once you have defined what that objective is.

Often, when companies embark on digital transformations merely as a theoretical exercise, they unintentionally establish isolated delivery teams that lack integration with business leaders, site operations, manufacturing excellence, and central IT. Alternatively, some become overly fixated on replicating the experience of a single site, overlooking the broader complexities within their network.*

One approach to mitigate this issue is to consider designating a single leader to take ownership of the project, similar to how software companies utilise product managers. This leader will be responsible for managing various situations, establishing consensus to prioritise the project effectively, making critical decisions, and successfully guiding digital transformation to completion.

This avoids an unrelated team, such as marketing, procuring software without informing IT, utilising their functional budget, and testing corporate policies in the process. Ideally, a product manager should have a cross-functional skill set which allows them to coordinate across all of the relevant job functions, while having particular expertise in the technology to be adopted.

*It is again important to state that we have had proven success with the conceptualisation, design, testing and installation of a range of solutions that manufacturers have faced (or are currently facing). Testing in one site or facility can enable that the process for production is robust and accurate before being replicated into other sites. In short, you can work out the bugs and make sure it meets the requirements and objectives.
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Risk #2 – Starting Over and Fear of Failure

It can be easy to fall into the trap of believing that starting from scratch is necessary for a successful digital transformation. In reality, existing infrastructure should be leveraged. Advancements in APIs and distributed cloud systems should help manufacturers to retain elements that are working well for specific departments while addressing technology gaps in others.

There are plenty of long-term employees and executives who may resist change due to the perceived risk and delayed ROI associated with digital transformation. To alleviate these concerns, you should enable employees to contribute content to improve digital systems and use key performance indicators (KPIs) to track and demonstrate progress.

By emphasising iterative change and foundational system investments, companies can gradually build ROI while staying competitive in a rapidly evolving market.

Additionally, you could highlight which digital solutions contribute to business priorities and where they should be scaled. A value-oriented digital transformation roadmap will enable you to convince key stakeholders of your plan for digital transformation rollout.

You do need to keep a copy of the data being imported/inputted into a new system, not just for records (although that is super important too), but to ensure consistency and allow for evaluation. The data should be accurate, cleansed and filtered to allow for a seamless integration and ensure that the reports and processing of the data are correct and smooth. A system is only as good as the information in it. If a link is rusted, a machine won’t run as well as it otherwise could.
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Risk #3 – Drowning in Data and Missing the Human Touch

Manufacturers can often amass vast amounts of data in their quest for automation. And there are certainly areas where a lot of data is needed to train an AI model. For example, in quality inspection, you need thousands of images to determine good and bad products.

However, this excessive focus on data capture can lead to decision paralysis. Say a manufacturer just needs a few key data points to make a decision, but their analysts are working in overdrive to collect as much data as they can. In that scenario, you may not make the best decision because your data collection doesn’t match the specific objectives.

Despite the multitude of advances in automation and AI, human expertise remains absolutely fundamental in manufacturing. In fact, 70% of U.S. manufacturing processes rely on human decision-making.

Manufacturers who communicate effectively with human operators will ensure that everyone understands the logic behind automation decisions and will be able to leverage their expertise to work in harmony with automated processes.

Moreover, manufacturers can choose technologies which include humans in the automation loop if those technologies better suit their business objectives; for example, they can send out work instructions to employee mobile devices or headsets, but still expect employees to perform the underlying work.

Those who align technology adoption with business objectives, engage their workforce in the process, and ensure data collection remains purpose-driven will see the full potential of their initiatives. Tailoring the transformation to the manufacturing sector, leveraging existing resources, and embracing iterative change will lead to long-term success, positioning manufacturers for growth in the digital age.

Taking the leap to automate even elements of processing and production in manufacturing can be hugely beneficial. Our machines and production lines work alongside and in place of operators, with them acting mainly just to supervise or oversee, rectify and inspect, as well as maintenance, of course! Automating and programming to speed up a process can help to make more efficient, optimise volume and amount processed as well as increasing productivity and profitability.