ACM Interactions

In the year of the AI, as defined by Melissa Heikkilä [1], it is more urgent than before for asset-intensive manufacturing (AIM) companies to find their way through the maze of digitization. Their success in this process will ensure resilient business growth while reducing individual uncertainty and—in some cases—dystopian images about the future.

AIMs includes oil and gas, aerospace, and pharmaceutical businesses that rely on intensive productivity and high-value and complex assets [2]. Implicitly, when referring to AIMs, we often consider a set of functions that make things possible: from people services to finance and research and development to production. Compared with flexible and consumer driven e-economy, AIMs depend on interrelated activities that require greater coordination and strategic effort to sustain and enhance market competitiveness [3]. Moreover, digital transformation influences how these organizations shape their processes, depending on how they collect, store, operate, and utilize data across different devices, platforms, and services. 

If on one side digitalization aims to enhance business operation via process automation, optimization, and reconfiguration, on the other side it drives innovation by triggering product and service development. Hence, the challenge behind the rise of digitalization is often tied to employees’ ability to independently keep pace with ongoing transformations. To paraphrase Christian Matt et al. [4], the success of digital transformation is about balancing four dimensions: the adoption of technology, the expected value, the structural changes, and the financial dimension. A fifth, and perhaps core, dimension that we often take for granted is the impact on employees’ work-life balance.

Digitalization in AIM, namely the introduction of digital technologies to increase productivity or to boost product development, succeeds when employees are actively involved in the process. It’s a type of involvement that overcomes hierarchical barriers and involves everyone. In fact, digitalization isn’t limited to the adoption of the latest fancy AI-powered enterprise resource planning systems (ERP) or the flashy real-time performance analytics of service delivery software. Digitalization in AIM embeds “agility, efficiency, flexibility, collaboration, automation, innovation, and productivity, [while increasing] ambiguity, security concerns, employee anxiety, privacy issues” [5]. The question is how AIM companies can embrace stepping into the fastest spinning digitalization year(s) ever?

Equipping AIMs for Intensive Digital Transformation
Example 1: Revamping a cross-functional team. To address this challenge, all the PD/HCI/agile tricks of the trade had been leveraged, but the team’s mood remained grim. Members were applying for other roles, the moral was low, and gossip was flowing. It took a few months to get to the core of the problem: The team members were overwhelmed and stretched too thin. Digital tools were adopted hastily, much like applying band aids to a knife wound. In order to solve the problem, the team was asked to become an active participant in the digitalization, which resulted in a standardized flow that rebalanced the impact of mundane tasks and collaborative governance. Effective actions enabled consistent and robust knowledge-exchange opportunities. All the ideas came from the team, which only needed an initial collaboration kick-off. 

Collaboration and knowledge sharing fueled the digital engine, driving successful technology adoption. By the end of the experience, the team had developed an entirely new mindset. One member said that her “life was ruined,” since she now knows that a different way of working is possible. The takeaway here is that even the best tools on the market are ineffective without collaborative, inclusive governance and a receptive culture, both from the bottom-up and top-down.

Example 2: Knowledge sharing. One of the many challenges AIMs face is advancing a knowledge infrastructure that fosters the growth and establishment of connections among people, artifacts, and contexts, enabling the maintenance and development of organizational knowledge. The core challenge of knowledge in AIM lies in the traditional adoption of a rigid stage-gated approach to production and service maintenance, leaving little to no room for creativity and knowledge development. Accepted knowledge is formalized and excludes informal know-how. Knowledge is formally captured in silos and often duplicated. It can be difficult to access, and information is difficult to navigate, as data may be outdated, unrecorded, or impossible to extract due to obsolete technologies. As a result, knowledge dissemination frequently depends on employees’ organizational memory and technical knowledge. Some technical and “historical know-how” may retire or leave businesses with limited time to transfer competencies. 

An organization we’ve worked with stored information in multiple repositories, making it difficult to determine what to look for, when, where, and how. Consequently, measures were implemented to reduce fragmentation, silos, and mundane tasks by, for example, using a tailored intelligent search engine. As advanced digital solutions found their place within the organization, the risk of digital resistance grew. New challenges arose, focusing on the ability to bring employees together in a constructive collaborative governance framework and ensuring that the digital tools were suitable for specific needs, rather than creating new scopes to justify further implementations. 

It soon became clear that a one-size-fits-all digital solution would likely be insufficient for knowledge transfer, as learning style preferences and accessibility needs vary among different employee groups. Ultimately, digital transformation needs to balance technological solutions and a human-centered approach to address the challenges of the future.

Conclusion
A lot has been written around digitalization in asset-intensive manufacturing. However, as insiders, we bring a different perspective on the potential effectiveness of digital adoption. Over the years, we came across both successful and unsuccessful digitalization processes. The successful initiatives embraced a collaborative and training-oriented journey that focuses not only on technology but also on fostering cultural change and encouraging technology acceptance.

Among the successful stories of digitalization, a common thread is collaboration and knowledge sharing, coupled with opportunities to upskill and reskill employees based on the required technology. Unfortunately, there is no one single solution to the challenges of this revolutionizing era. However, we can say that the key to success lies in aligning organizational needs, technology availability and readiness, and employee needs.

Endnotes
1. Heikkilä, M. What to expect from the coming year in AI. MIT Technology Review. Jan. 9, 2024; https://www.technologyreview.c...
2. Loonam, J., Eaves, S., Kumar, V., and Parry, G. Towards digital transformation: Lessons learned from traditional organizations. Strategic Change 27, 2 (2018), 101–109.
3. Verhoef, P.C. et al. Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research 122, 2021, 889–901.
4. Matt, C., Hess, T., and Benlian, A. Digital transformation strategies. Business & Information Systems Engineering 57, 5 (2015), 339–343.
5. Kraus, S., Ferraris, A., and Bertello, A. The future of work: How innovation and digitalization re-shape the workplace. Journal of Innovation & Knowledge 8, 4 (2023). 

Teresa Macchia

Amelia Bourton