The impending Digital Dust Bowl: Mitigation, survival and interdependence

Acts of nature helped create the Dust Bowl; AI-enabled acts of man will stir up the Digital Dust Bowl

Myriad developments such as inexperience with newly automated methods of farming, topsoil shifts, and periods of drought and high winds triggered the Dust Bowl of the 1930s, which exacerbated the ongoing decline of the U.S. economy. Today, the high affordability and rapidly spreading use of analytics and machine learning software reduce the amount of labor necessary to perform complex tasks. In short, we are farming our labor pool in different ways and destabilizing our labor markets in a manner similar to the way automated machinery destabilized our topsoil and helped trigger the Dust Bowl, a calamity with far-reaching economic consequences that compounded the troubles of a country suffering through the Great Depression, cemented in history in the John Steinbeck classic “The Grapes of Wrath.”

We are, in essence, creating a Digital Dust Bowl of displaced manufacturing, clerical and middle-management workers whose jobs will be replaced by automated machines and different methods of establishing trust in a wide range of economic transactions. Technology executives and strategists comprehend this better than most other business and political leaders as we have lived in this world for decades. Ways to mitigate the disruptive economic and social impacts to these accelerations have yet to gain broad-based consensus within the policy making institutions as evidenced by the current political climate at the national level. It is this lack of consensus that hinders our ability to mitigate the impending economic impacts of the accelerating rate of technological innovation.

Major economic shifts pressure the interdependencies between citizens, businesses and governments

Figure 1 outlines the main intersecting domains of people (laborers and consumers), businesses, and government and trust institutions tasked with regulating and certifying the activity between individuals and businesses as well as with “protecting the commons.”

Winning the business of digital transformation services requires a process-led approach

Discerning between a catch-all phrase and a discrete market opportunity

TBR hears a broad range of positions on the digital transformation (DT) market in its interactions with advisory and IT services vendors, with vendors applying the term with extremely broad strokes, often geared more toward marketing than defining a concrete capability. While some seek to bucket DT as an all-encompassing umbrella under which a huge range of disruptive technologies exist, others use the term more judiciously to discuss leveraging technology to functionally change a business. While digital transformations cannot exist without disruptive technologies, the concurrent yet also independent themes can complicate conversations about the topic.

Upon the launch of TBR’s DT research program, the first task was to seek commonality among vendors to best cross-compare industry adoption rates and vendor penetration — ultimately examining how to best identify where pockets of spending are coming from, what technologies are being adopted by end users, which areas vendors are investing in and, most importantly, where vendors are generating business from. To achieve this, we’ve decided to look at DT from a process standpoint, understanding that client initiatives are generally not about reinvention of the full enterprise, but rather modernization of a discrete business function, such as supply chain or customer engagement, to take better advantage of the technological capabilities that exist in today’s market.

We believe a process-focused examination of DT will enable us to answer the following questions:

A list of TBR's digital transformation research questions

 

Oracle guides its customers into IoT

Oracle’s expanded IoT cloud

Oracle IoT Cloud focuses on offering easy integration with Oracle’s Business Intelligence Mobile Cloud and can be offered as both a SaaS application and a PaaS offering. Interestingly, Oracle did not highlight Amazon Web Services, Microsoft (Nasdaq: MSFT) or Google as partners, indicating the company prefers to keep data inside its own cloud. Oracle also announced, through the combination of Oracle IoT Cloud and its enterprise applications, the creation of new industry-focused solutions, such as digital field service, smart connected factories and digital fleet management. Oracle’s examples of areas where the company is currently seeing the most demand through its customer base include:

  • Digital Field Service: Showcases intelligent remote monitoring, failure prediction, over-the-air repair and dynamic technician dispatch. The solution features IoT Asset Monitoring Cloud, CX Service Cloud, CX Engagement Cloud and CX Field Service Cloud, plus the use of AR for guided equipment repair.
  • Smart Connected Factory: Demonstrates how incident detection, root cause analysis and smart resolution are performed within minutes in a connected factory. The solution features IoT Production Monitoring Cloud, SCM Cloud and ERP Cloud, and the use of VR to navigate the manufacturing floor. It can also be used for remote worker training.
  • Digital Fleet Management: Showcases real-time shipment tracking, risk management and logistics synchronization. The solution features IoT Fleet Management Cloud and Oracle Logistics Cloud.

Powering the company’s cloud offerings, and the enterprise applications, is the new Oracle IoT Cloud Applications. The first round of these applications includes asset monitoring, connected workforce, fleet monitoring and production monitoring. Again, Oracle is focused on where it observes the most IoT activity when developing these applications. Oracle also introduced a number of capabilities to Oracle IoT Cloud:

  • Digital Twin for Supply Chain Management: For creating a digital representation of a physical asset to deliver enhanced analytics
  • Digital Thread for Supply Chain Management: A way to connect business process frameworks and create a “system of systems” to join traditionally siloed elements in real time through a digital supply chain
  • Artificial Intelligence and Machine Learning: These technologies are holistically integrated across Oracle’s IoT solution portfolio to assist digital twin and digital thread and produce overall insight from data.

These features show that Oracle has the capability to shepherd its customers though the more common vertical use cases at this time. TBR would not be surprised if Oracle were to release new industry-focused solutions and applications at a regular half-year cadence as it monitors the market and listens to its customers’ requests.