Industry 4.0

• direct digital manufacturing (DDM) or 3D printing
• artificial intelligence
• unmanned aerial systems (UAS) or drones
• blockchain
• RFID
• VR/AR/XR
• etc.

Emergence and spread of an innovation

• DDM is limited to tasks such as prototyping, “soft tooling,” and the on-demand production of customized and spare parts due to high costs

• Drones are used in experimentations and in production : oil platforms inspection (Shell), medical product delivery (Zipline), continual inventory control in its warehouses (IKEA)

Advanced manufacturing technology (AMT)

• Control, track, or monitor manufacturing activities, either directly or indirectly (Boyer et al., 1997, p. 332)

• The challenge is not assessing the benefits of an AMT

• It is about “the appropriateness of associated decisions and processes—primarily in terms of the technologies’ fit or match with a range of internal and external contingencies.”

Three types of fits in the classic AMT literature.

These are the fit between the technology and

1. economic and strategic factors,
2. operational and supply chain factors, and
3. organizational and behavioral factors.

Technological fit with economic and strategic factors

• Managers calculate or estimate economic potential of a business case using project finance techniques

• “AMT researchers have long stressed the limitations of any overreliance on narrow capital budgeting-centered approaches.”

• Especially for infrastructure technologies that have many direct and indirect outcomes (both positive or negative)

Off diagonal positions

Hayes, Robert H., et Steven C. Wheelwright. « The Dynamics of Process-Product Life Cycles ». Harvard Business Review, 1 mars 1979. https://hbr.org/1979/03/the-dynamics-of-process-product-life-cycles.

• “Investments in new technology often resemble the ante in a poker game. One does not expect any direct return from the ante itself. It simply allows one to play the next set of cards.” Hayes and Jaikumar (1991, p. 173)

• Das and Narasimhan (2001, p. 539) reported that “the use of AMT … does not appear to encourage firms to assume ‘off diagonal’ positions in the Hayes and Wheelwright (1979) framework.”

Technological fit with operational and supply chain factors

• How the technology integrates with the firms’ operating model

• This can be particularly challenging if the process affects routines, responsibilities, and reporting channels

• AMT literature (e.g., computer-aided manufacturing, flexible manufacturing systems, etc.) were mainly developed for specific manufacturing applications.

  • The role of supply systems has been under-investigated.
  • Some suppliers perceived most of their buyers (i.e., the manufacturing firms) as unsophisticated customers
  • This buyer–supplier knowledge gap would only exacerbate the challenge of operational fit.

Technological fit with organizational and behavioral factors

• If any new technology is to be fully implemented, it will require acceptance by users : training is key

• But there is more than training, more recent literature examines the managerial behavioral aspects of technology adoption (e.g. design)

Drones are not a traditional AMT

• not intended for manufacturing applications (leisure and military)
• flying is unprecedented in factories : open new possibilities but with constraints (flight time, payload, wind turbulence, noise, safety, privacy)
• flexibility of the on-board equipment (cameras, sensors, and robotic arms)
• users are familiar with the technology

#1 Fit with economic and strategic factors

The business case for drones remains unclear compared with traditional investment options such as forklifts, mounted cameras, and material handling systems.

First law of technology

• “Overestimate[ing] the short-term impact of a truly transformational discovery, while underestimating its longer-term effects.” Collins (2010)

• See also : Brynjolfsson, Erik, Daniel Rock, et Chad Syverson. « The Productivity J-Curve: How Intangibles Complement General Purpose Technologies ». American Economic Journal: Macroeconomics 13, nᵒ 1 (janvier 2021): 333‑72. https://doi.org/10.1257/mac.20180386.

Exploration vs. Exploitation

Techniques de l’Ingénieur. « Comprendre les différences entre exploration et exploitation ». Consulté le 9 août 2023. https://www.techniques-ingenieur.fr/fiche-pratique/innovation-th10/l-intrapreneuriat-au-service-de-l-innovation-dt137/comprendre-les-differences-entre-exploration-et-exploitation-1744/.

Disruption

#2 Fit with operational and supply chain factors

Market pull versus technology push (Mowery & Rosenberg, 1979; Nemet, 2009)

• drones were developed for non-OM applications and are being pushed onto OM problems
• it is often unclear whether a problem needs a technological solution or a technology seeks a problem to resolve

Drone technology ecosystems

• One way to address a low perceived fit between emerging technologies and internal operational factors might be to outsource development and deployment to specialized suppliers.

• The vivid drone startup industry is actively looking for development partners, implementation pilot projects, and potential customers.

#3 Fit with organizational and behavioral factors

• New technology
  • no organizational structures
  • require extensive training
• Automation raise the employment question
• Creates risks (see earlier discussion)
• Negative opinion about the tech

Case studies

“We find that—when faced with fast-emerging technologies in thriving ecosystems—companies do not follow a linear technology adoption pattern, where adoption commonly starts with a business case. Instead, companies trial technologies by focusing on a “use case,” which allows a potential business case to evolve, or not, over time.”

Technology push from a thriving ecosystem

Hype and timing

You don’t want to be too late or too soon

Mature technology : autonomous flying was available for IKEA

Procurement readiness to develop and to support experimentation

Hype Cycle Model

The use case

It differs from the business case, and it comes from Information Systems literature

In many ways, the use case is a manifestation of what Orlikowski (2000) called the idea of “technology in practice,” which is a perspective that starts with human action and examines how structures emerge through recurrent interactions with available technology. She notes that some technologies-in-practice (not all) can become institutionalized over time, but this is rarely permanent. Moreover, the familiar “black box” notion of technology only exists as a result of stable patterns of use (Latour, 1987). In observing this nascent technology, we were inside the black box and were forced to explore different possible technological–organizational connections.

Future research

It is likely that such characteristics will be similar for other Industry 4.0 technologies, such as AI, blockchain, and wearables—where the original application space was far from the factory.

Would our findings be different for technologies that were originally developed to solve operational problems, such as manufacturing execution systems, cyber-physical production systems, cobots, or industrial robots?