Shaping New Collaboration Models for the Future of Production

Our previous work with the World Economic Forum identified how imperative multilateral collaboration is to advance the future of production in ASEAN. In this article, we identified five ways to enhance the effectiveness of these collaborations.

Last fall in our paper Shaping ASEAN’s Future Readiness: Collaborations to Advance Manufacturing and Production, published in collaboration with the World Economic Forum, we assessed the opportunities to fuel the development of advanced manufacturing and production and examined the types of multilateral collaborations that could improve the chances of success. Although enhancing the manufacturing ecosystem initially appeared to be more of a country-specific issue, our work revealed that multilateral collaboration is imperative to capturing the opportunities presented by the future of production.

After identifying more than 30 opportunities for collaboration, we have honed our focus to six areas that can be transformed into initial showcases:

• Prototyping. Setting up 3D printing and prototyping centers of excellence
• Smart packaging. Jumpstarting the development of smart packaging capabilities
• Digital logistics. Supporting the development of digital logistics providers and solutions
• Academy. Establishing a learning and competence academy for small- and medium-size enterprises (SMEs)
• Circular economy. Launching an education and adoption platform for sustainable manufacturing
• Seamless data. Creating seamless data exchanges for the faster flow of goods

The World Economic Forum on ASEAN, held in Hanoi in September 2018, along with subsequent discussions created much interest from private and public stakeholders in ASEAN to implement these opportunities. However, it also raised questions about the types of collaboration models that will be required to establish multilateral public–private partnerships as effective vehicles that foster the accelerated development and adoption of Fourth Industrial Revolution (4IR) technologies and practices across a range of countries at various stages of development and with potentially competing interests.

In this article, we take a closer look at the six opportunities listed above to understand the constraints and develop new hypotheses about how collaboration models could evolve.

Constraints in Collaborations

Collaborations to accelerate the adoption of advanced manufacturing will need to be multilateral and based on public–private partnerships. This will require new forms of scale, speed, and use:

• Scale. Collaborations will need to be larger—involving more private companies, countries, and governments to strengthen production networks across value chains and harmonize ecosystems across countries. For example, taking advantage of opportunities for seamless data will require harmonizing ecosystems across 10 countries with significant involvement from the private sector to address the prevailing pain points.
• Speed. Collaborations need to be faster paced, more agile, and forward-looking in their execution and decision-making to be able to adopt rapidly changing technologies, globally competitive trends, and new capability requirements. For example, prototyping is not only about making prototyping facilities available, but also about speedily steering the development of new technologies and material development in ASEAN across a wide spectrum of industries, applications, and interests.
• Use. Collaborations need to intervene more in technology development to be able to develop locally relevant and affordable technologies, solutions, and capabilities. For example, smart packaging will require a focused technology development targeted at specific ASEAN food waste issues and adaptable to ASEAN’s manufacturing and plant setups.

However, an array of challenges is restricting existing and envisioned traditional collaboration models for governments and for companies:

• Scale. Governments often encounter difficulties aligning their interests and have to overcome conflicts in large, multilateral collaborations given the perceived encroachment on economic competitiveness. They also face difficulties in consolidating separate and possibly fragmented efforts and funding. For private companies, large-scale implementation across production networks is often deterred by a too-narrow focus on singular pain points and the high cost of new technologies. In addition, end-to-end global value-chain connectedness can be limited by gaps in management capabilities for broader collaborations, especially between multiple large enterprises and SMEs as well as potential competitive conflicts in export-oriented industries. For example, although seamless data is an issue that has been addressed for more than 15 years, progress is hampered by the difficulties in harmonizing bureaucratic practices and managing country-specific implementations.
• Speed. For governments, policy design struggles to keep up in a rapidly changing world because of political considerations and diverging interests across various government bodies. Many efforts are reactionary rather than preemptive. For private companies, a shortage of talent and the ensuing slow pace of adoption can deter an on-the-ground transformation. A short-term business case orientation (six to 18 months) and focus on use case pilot areas (sometimes resulting in “pilot paralysis”) can slow the pace of implementation. For example, even though digital logistics is a well-understood challenge for SMEs across all ASEAN countries, adoption is impacted by the lack of business case clarity for companies and limited government clarity on priorities (such as a focus on creating awareness rather than on building a platform for connectivity or developing specific logistics tools).
• Use. For most ASEAN governments, science and technology play a relatively small role in policies and funding and often do not get adapted into interventionist, forward-looking technology developments. For companies, many global solutions are not directly transferable to the region and require local adaptation. In addition, broad technological developments are often not focused on addressing local pain points, and clear constraints exist in required information technology and operational technology capabilities and the underlying data collection infrastructure. For example, although Singapore has established the National Additive Manufacturing Innovation Cluster (NAMIC) for 3D printing and prototyping, other ASEAN countries have been slow to identify locally relevant 3D printing solutions and funding models.

If these constraints persist, collaboration models will struggle to deliver and maintain alignment and trust over time. Three obstacles will be especially challenging:

• Not broad or stable enough to remove major pain points in ecosystems or create broader regional opportunities through more integrated production networks
• Not fast or agile enough to catch up with faster-moving companies and countries in developed regions
• Not concentrated or forward-looking enough to create a distinctive competitive advantage for local and regional companies

This will have implications on how to rethink not only the governance model for collaborations, but also the underlying commercial and funding models and engagement platform constructs.

New Collaboration Models Can Shape the Future of Production

Based on these constraints, we identified five ways to enhance the effectiveness of collaborations in ASEAN production:

1. Government-led initiatives. Governments must be interventionists that manage fragmented efforts and are prepared to lead the initial funding and coordination of private-sector efforts to overcome initial barriers to collaboration, such as the private sector’s short-term business case orientation, lack of clarity on technology use cases, and low mutual trust among potential partners.
2. Government-led models could improve the scale of efforts—transitioning from piecemeal pilots to large-scale orchestrated transformations.
3. In Germany, the Fraunhofer Society for the Advancement of Applied Research offers some compelling examples of how a government initiative can launch collaborative efforts across production value chains to drive win–win technology applications. Following are some examples of the country’s industry alliances:

• Fraunhofer Additive Manufacturing Alliance collaborates with local and multinational engineering companies to develop new strategies, concepts, technologies, and processes in additive manufacturing.
• The Innovation Alliance Green Carbody Technologies works with major automotive original equipment manufacturers and their component suppliers to optimize processes and reduce waste in the manufacturing process.
• Kompetenzzentrum engages local mechanical engineering companies in the Saxony region to drive technology collaboration and help overcome inhibitive cost structure to SME growth.

1. Another example is the Manufacturing USA initiative, which was created in 2012 to develop and apply advanced manufacturing technologies through public–private partnerships. The initial program, America Makes, pulled together a community of more than 200 partners, including public agencies, universities, research institutions, and private companies to support the transformation of manufacturing in the United States through additive manufacturing and 3D printing. Initially set up with support from public funding, America Makes is intended to become a financially self-sustaining platform for ongoing public–private collaboration.
2. In ASEAN, Singapore is leading the region in a series of government-led efforts. For example, the National Additive Manufacturing Innovation Cluster (NAMIC) was set up to jumpstart multi-stakeholder collaboration and nurture additive manufacturing technologies. Another government-led effort, called SkillsFuture, was launched to promote lifelong learning and employability.
3. New commercial models. Commercial models must be redesigned to support the initial government funding and unleash long-term private sector funding. Rather than being capex-centric, models could be asset-light—providing access to 4IR assets through an assets-as-a-service business model (for example, uberizing the network of underutilized 3D printers across the region). Asset-light, open source, and crowdfunded models will also help develop new approaches to on-demand automation, which are crucial to SMEs.
4. New commercial models could also increase the scale of a transformation by lowering the barriers posed by the high cost of technologies and other investments.
5. The Hyperloop Transportation Technology (HyperloopTT) combination of a crowd-powered ecosystem and equity participation mechanisms for value chain partners provides an inspiring approach for how collaboration can create a new asset-light commercial model. HyperloopTT leverages in-kind human resources and capital investments from individual contributors and value chain partners. In exchange, the contributors and partners secure equity stakes in the organization, positioning themselves to capture value by commercializing the technology. This enables HyperloopTT to obtain a wide range of expertise and maximize the potential for growth with a cash- and asset-light approach. This is in contrast to Virgin Hyperloop One, a competing technology company that relies on a conventional venture capital fund financing model to drive growth.
6. A new, more agile governance structure. Fast and forward-looking governance (common in technology firms) need to be transplanted into collaborations. This will require a shift to more flexible, two-speed approaches to procurement, finance, HR, and IT across multiple organizations that complement—but do not replace—existing governance processes. This approach will also need a preemptive and proactive focus on issue resolution, different from traditional project management office processes, which are typically backward-looking to review progress. A common control tower concept, which is frequently applied in digital transformations, can provide direction and help clear hurdles. This new approach will unleash the speed of transformation.
7. Extensive and safe platforms for sharing lessons learned and technologies.Platforms need to be put in place to create structured exchanges of information, management approaches, effectiveness of technologies or solutions, and the capabilities of providers, especially to foster stronger 4IR adoption by SMEs. This will require clear rules for the open, protected, and risk-free exchange of data and potentially sensitive information such as the return on investment of use cases or cybersecurity issues. Knowledge sharing increases the speed of transformation through the broad awareness and adoption of best practices.
8. Extending the collaborations and platforms for third-party innovation. Data is the engine that is propelling 4IR adoption and innovation. Giving third parties access to data will help stimulate experimentation with customer data and crowdsourcing of innovation. This will require new data stewardship concepts that not only provide rules for the exchange, use, and protection of data, but also stimulate more extensive use by third parties. Third-party innovation allows for the co-creation of locally relevant offerings and increases the speed of development of these offerings.

These new collaboration model elements are not independent of one another. Rather, governments and private companies can deploy a combination of elements. For example, Germany’s Fraunhofer Society is government-led, but it also provides a platform for sharing information and best practices. Moreover, Fraunhofer’s collaboration with Singapore’s national universities and research foundation extends beyond its original ecosystem to enable third-party innovation. Together, these elements can drive broader, more agile, and forward-looking collaboration between multiple countries and public and private stakeholders.

To test the relevance and importance of these hypotheses, we have mapped them against the six collaboration opportunities (see figure).

Finally, these collaborations will need to have the successful elements of any traditional collaboration to build and maintain trust and safeguard the individual partners’ economic interests while also moving toward a greater overall outcome for all:

• Develop a clear vision of the objective, targeting an outcome of the collaboration that aligns and galvanizes all partners.
• Put together the right team. Having upfront clarity on each partner’s core capabilities and how they will contribute unique assets, people, or resources is essential to achieving the target outcome.
• Establish clear internal governance processes that are aligned across all partners, and ensure sufficient flexibility and autonomy to make a range of decisions within the context of the partnership.
• Have open and transparent communication channels for all partners to work together, with willingness to adapt as necessary.
• Have a defined conflict resolution and mediation process along with specified exit triggers and a process for irresolvable disputes.
• Develop a platform for ongoing performance tracking and learning, enabling continuous improvement within the partnership.