Featured Image Source:  Cisco Telos

About the OODA Loop Exponential Innovation Series

Based on the strength of the insights garnered over the course of 2022 from the research theme Exponential Disruption (which culminated in the panels and OODA community conversations at OODAcon 2022) our new OODA Loop Series,  Exponential Innovation, will pivot and “drill down” on the technical, organizational and market-driven structures driving these disruptions.  This research is all in the context of this year’s overall theme  – Jagged Transitions  -which is meant to invoke the challenges inherent in the adoption of disruptive technologies while still entrenched in low-entropy old systems and in the face of systemic global community threats and the risks of personal displacement.

The OODA Loop Exponential Innovation Series is a boots-on-the-ground, in-the-trenches research effort with a focus on emerging technologies, deep-tech, tough-tech, and advanced technologies for three reasons:

• Exponential technologies (artificial intelligence, quantum science, biotechnology) are consistently included in all of these classifications or monikers (emerging, deep, etc. ) used to describe a portfolio of technologies poised to ignite one of, if not the, most transformative periods in human history; and
• NatSec Investments, American Competitiveness, and Exponential Innovation:  We are already seeing significant interest in the articulation of exponential innovation best practices in the “community of practice” (government agencies, military branches, VCs, startups, etc.) focused on a new wave of investment in national security and American competitiveness; and
• Exponential growth in the context of the volume and scale of global cybersecurity incidents and the future of global health security (bioterrorism, pandemic and disease surveillance).

The Exponentials Business Strategy Framework

The Exponentials Framework is a proven framework for the design of a technology ecosystem built to sustain the exponential scale and speed of the current technological and scientific era.  Exponentials are not futurist high-level concepts.  They are not intellectual bugs, but the central organizing feature of the technological road ahead.

Exponentials:  The business strategy framework known as “exponentials” is based on the exponential acceleration of the following technologies.  These exponential technologies are creating new competitive risks and opportunities for enterprises that have historically enjoyed dominant positions in their industries:

• Quantum Technologies and Quantum Networks 
• Artificial Intelligence
  • Computer vision: The ability of computers to identify objects, scenes, and activities in unconstrained (that is, naturalistic) visual environments
  • Machine learning: The ability of computer systems to improve their performance by exposure to data without the need to follow explicitly programmed instructions 
  • Deep Learning:  The deep learning algorithm is a powerful general-purpose form of machine learning.   It uses a variant of neural networks to perform high-level abstractions such as voice or image pattern recognition.  
  • Natural Language Processing:  The ability of computers to work with text the way humans do—for instance, extracting meaning from text or even generating text that is readable, stylistically natural, and grammatically correct.
  • Speech recognition: The ability to automatically and accurately transcribe human speech
  • Optimization: The ability to automate complex decisions and trade-offs about limited resources
  • Planning and scheduling: The ability to automatically devise a sequence of actions to meet goals and observe constraints
  • Rules-based systems: The ability to use databases of knowledge and rules to automate the process of making inferences about information
  • Computational Innovation:  Deep learning algorithms, as well as visual, gestural, and spatial computational needs, are emerging as focus areas for the technology industry because they all require high levels of computational resources. This opportunity to address future processing challenges has not escaped the semiconductor subsector: Besides the NVidia Tegra mobile chip, the IBM TrueNorth chip,  Intel’s Xeon E7 v3 server chip, and Qualcomm’s Snapdragon mobile processor are also designed to address the need for computational innovation for AI. 
• Robotics
• Additive Manufacturing
• Synthetic or Industrial Biology
• Further Computational Innovation (i.e. Quantum Networks)

The Characteristics of the Exponential Technologies Framework, Exponential Organizations, and Ecosystems

Exponential Technological Growth:  Salim Ismail (the founding executive director of Singularity University and former head of innovation at Yahoo) explains the doubling pattern and trajectory which further accelerate Moore’s Law (contributing to the exponential growth of an innovation) in the following way:

1. First, the doubling pattern identified by Gordon Moore in integrated circuits applies to any information technology. Ray Kurzweil calls this the Law of Accelerating Returns (LOAR) and shows that doubling patterns in computation extend all the way back to 1900, far earlier than Moore’s original pronouncement.
2. Second, the driver fueling this phenomenon is information. Once any domain, discipline, technology, or industry becomes information-enabled and powered by information flows, its price/performance begins doubling approximately annually.
3. Third, once that doubling pattern starts, it doesn’t stop. We use current computers to design faster computers, which then build faster computers, and so on.
4. Finally, several key technologies today are now information-enabled and following the same trajectory. 

Ismael also mentions Google Ventures (which is the venture capital business unit of the Alphabet holding company) as “an almost perfect exponential organization.”

Moonshots: Projects that aspire to exponential, tenfold improvements [1,000 percent increases] in performance.

Emergent Exponential Organizations (ExOs): We are on the lookout for research, companies, and technologies in the NLP and GPT-3 space (and in a broad swath of industry subsectors) for case studies, lessons learned, and insights into scalable and replicable exponential organizational and operational techniques.

Speed and scale do not just happen: they are design elements.  An Exponential Organization (ExO)  is an organization whose impact (or output) is disproportionally large, at least 10 times larger, compared to its peers because of the use of new organizational techniques.  Based on ExO research conducted in 2016, Google was No. 5 on the Top 100 ExOs list, along with companies such as Airbnb, Uber, Tumblr, Medium, and Twitch. At No. 1 was the collaborative code and software development site GitHub.  The most vital example of an ExO:  the restructuring of Google into its parent company Alphabet was an exponential organizational restructure designed to prioritize 10x growth as a business priority supported from inception by the new company’s enterprise architecture.

Alphabet is, by design, an exponential organization (ExO).  It was unsurprising that the re-organization of Google into the Wall Street-friendly Alphabet happened right in the middle of the AI M&A wars in the 2015/2016 timeframe.  The same design elements of Alphabet that allow for Google, Google X, YouTube, and the cybersecurity acquisition Mandiant to be in the same portfolio of Alphabet companies also allowed for AI acquisitions and will allow for quantum computing bets also to join the Alphabet portfolio.

Business Ecosystems:  A complex, dynamic, and adaptive community of diverse players who create new value through increasingly productive and sophisticated models of both collaboration and competition.

Business Model Transformation: New business units are created to increase volume and grow revenue through exponential computing-enabled innovation.  The most striking finding is that technology companies create new business units to increase volume and generate revenue by using the rapidly commercializing technology innovation not only for product innovation but also for structural, operations, process, and business model innovation as well.  Change at this speed and scale creates opportunities—and risk—which will challenge strongly held beliefs at the core of a company’s business model.  These new units are also designed to transform the architecture of the parent company over time. Such restructuring underlines exponential technologies’ potential to completely revolutionize the technology sector—and take many vertical industries and markets along.

Multisided Platforms (MSPs):  Technologies, products, or services that create value primarily by enabling direct interactions between two or more customer or participant groups. See Andrei Hagiu, “Strategic Decisions for Multisided Platforms,” (MIT Sloan Management Review, December 19, 2013).

Development Platforms:  Platforms— which are increasingly supported by global digital technology infrastructures that help to scale participation and collaboration— help make resources and participants more accessible to each other. Properly designed, they can become powerful catalysts for rich ecosystems of resources and participants, defining the protocols and standards that enable a loosely coupled, modular approach to business process design.  Exponential developer platforms are emerging that allow organizations to collaborate with a community of passionate developers, which accelerates the speed and scalability of product development and product release efforts.

Platform-as-a-Service Offerings (PaaS): Modular, extensible products are redesigned for the computing-intensive demands of exponential computing, allowing both current and new customers to easily transition to PaaS offerings  – as well as companies to rapidly position their PaaS offerings in new markets.  Again, an example from recent AI market history:  In the case of Amazon, machine learning as service dates back to the company’s early offerings of infrastructure as a service (IaaS) and software as a service (SaaS) through Amazon Web Services (AWS). Amazon’s launch of a machine learning-based PaaS offering can be seen as a direct result of its significant, long-term strategic research and development investments, notwithstanding the criticism these investments attracted from investors and Wall Street.

PaaS Extensions: PaaS vendors provide a virtual IT environment that allows businesses to develop and run their own customized applications without having to manage the details of a physical or cloud-based data center.  Many companies will enhance current PaaS offerings through modular, extensible products designed for exponential technologies’ computing-intensive demands. This approach allows a company’s current and new customers to easily transition to the PaaS offering and enables the company to rapidly position its exponential computing PaaS offerings in new markets. The AI business ecosystem, the IBM Watson Group, is illustrative: Watson Services on Bluemix is an open-standard, cloud-based PaaS for building, managing, and running applications of all types, such as mobile, big data, and new smart devices, providing a fully integrated service for cognitive technology innovation.  In the case of early AI PaaS extensions, typically these platforms and PaaS offerings target high-value, immediately addressable markets such as analytics, cloud computing, social, mobile, and security.  It will be interesting to see if exponential computing targets these same markets, or if new high-value immediately addressable markets eclipse these current markets and/or are more value-driven in an exponential innovation context.

What Next?  Quantifying Exponential Innovation

Our research is primarily concerned with insights into designing, quantifying, and measuring exponential outcomes and impacts – as seen through the lenses of exponential innovation and:

• Risk, Threats, and Opportunities
• Business Model Generation
• Value Proposition Design
• Top-Down vs. Bottom-Up Innovation
• Innovative Groth Metrics
• Exponential Growth as a negative indicator and/or early warning system  (pandemics, cyberattacks)
• Private Sector vs. Public Sector Enabling of Technology
• Dual-Use and Commercial Technology Development
• Network Effects and Nodes of Exponential Value Creation (with Quantitative Analysis and Visualizations)
• Product Roadmaps
• Objectives and Key Results (OKRs)
• Exponential CapEx vs. OpEx
• Exponential Key Performance Indicators (KPIs)
• Customer Acquisition Cost (CAC)
• Average Revenue Per User (ARPU)
• Customer Lifetime Value (LTV)
• Monthly Active Users (MAU)
• Customer Churn Rate (CCR)
• Monthly Recurring Revenue (MRR)
• Revenue growth rate
• Revenue Churn Rate (RCR)
• Use of Funds Maps relative to KPIs; and
• Exponential Outcomes (with Quantitative Analysis and Visualizations)

https://oodaloop.com/archive/2023/02/06/ooda-loop-on-exponential-disruption/

https://oodaloop.com/archive/2023/01/20/ooda-almanac-2023-jagged-transitions/