Futurists use a research-driven approach called strategic foresight to explore possible futures and inform decision-making. Is strategic foresight and its scenario-making approach worth it for architects to better explore the future, or Is it a domain just for futurists like Gerd Leonhard, or it can be “democratized” for enterprises and architects? Should we seek support from foresight in thinking about our future sustainable enterprise in the fog of societal, economical and geopolitical challenges and multiple future signals that are already impacting our current reality? Is it worth investigating, can exploration be accelerated by GenAI ?
There are individual level challenges that we are often facing, especially in short term scenarios. However, I will focus this article mostly on team – and – organization levels.
1.Useful cheat sheet for individual level shorter term decision challenges that can help you before you “push the button” to get into action (published by Kristin Demafeliz on LinkedIn). But for longer term perspectives, I do not recommend a “gut feeling approach” recommended by GE’s former CEO, Jack Welch but a book that I love, by Daniel Kahneman, Nobel Prize winner, “Thinking Fast and Slow”. So even at the individual level, let’sfocus on analytical thinking instead of thinking fast and relying on your gut feeling. Below is a table showing how, even at an individual level, a GPT app can help you to explore alternatives and consequences.
2. Team level challenges where it can be useful to explore the use of foresight techniques and strategic scenarios.
When we look at statistics published by CIO magazine on the rate of failure of cloud migration projects or the staggering rate of failure of digital transformation initiatives as published by McKinsey, it is obvious that foresight and scenario making should be in the toolkits for enterprise or business architects. For example, a number of such techniques can be used to facilitate design thinking workshops, exploring alternatives with various trade offs in the design of a complex system, new solution, or a new project plan. Nonetheless, an environment constrained by a rigid approach dictated by management, by our corporate culture or even national culture or political party could promote building a “consensus” imposed from the top. In such a context, rather than pushing the boundaries of innovation, a political party will likely seek to mold existing AI technologies to fit its own socio-political objectives expressed by top management. Iin this case we would have to instruct a GPT-like system to respond only in “acceptable” thoughts and terms to our prompts. However, I am convinced that it will be quite easy to break out of this “jail” and seek alternative answers from a GPT platform accessible from abroad or an open-source foundation model installed locally like LLAMa.
Below you’ll find the case study that can be generated with the support from ChatGPT that can be instructed by an experienced enterprise or business architect with good prompt engineering skills and with access to research and insights explored by his/her VP Strategy office.
Digital Transformation in a Mid-Sized Manufacturing Company
Introduction
This case study explores how a mid-sized manufacturing company leveraged foresight and strategic scenario techniques to drive digital transformation. By fostering team collaboration and creating consensus, the company was able to explore alternatives, challenge assumptions, and build a future-ready organization.
Company Background
- Industry: Manufacturing
- Size: 500 employees
- Location: United States
- Current State: Traditional manufacturing processes with minimal digital integration
Objectives
- Primary Goal: Achieve digital transformation to enhance operational efficiency, innovation, and competitiveness.
- Secondary Goals:
- Foster a culture of innovation and adaptability.
- Develop a clear roadmap for implementing digital technologies.
- Build consensus among stakeholders on the vision and path forward.
Process Overview
- Imagine Possibilities That Don’t Yet Exist
- Futures Workshops: Organized workshops with cross-functional teams to brainstorm and visualize the future of manufacturing. Techniques included speculative design and science fiction prototyping.
- Outcome: Generated creative ideas such as smart factories, AI-driven quality control, and IoT-enabled supply chains.
- Challenge Mental Models and Assumptions
- Assumption Surfacing and Testing: Facilitated sessions to identify and question existing beliefs about manufacturing processes and technology adoption.
- Devil’s Advocate and Red Teaming: Engaged teams to critically evaluate proposed ideas and challenge the status quo.
- Outcome: Identified several outdated assumptions, such as the belief that digital transformation is too costly and complex for mid-sized companies.
- Examine Unintended Consequences
- Futures Wheel: Used this technique to map out potential first-order, second-order, and third-order effects of adopting various digital technologies.
- Impact Analysis: Assessed the broader impacts of digital transformation on employees, supply chain partners, and customers.
- Outcome: Highlighted potential risks such as workforce displacement and data security issues, which were then addressed in the planning phase.
- Gather and Analyze Data for Foresight
- Environmental Scanning: Conducted thorough research on industry trends, emerging technologies, and competitor activities.
- Big Data Analytics: Leveraged data analytics to understand current operational inefficiencies and customer preferences.
- Outcome: Gathered valuable insights that informed the strategic planning process.
- Anticipate New Opportunities and Offerings
- Opportunity Mapping: Visualized potential opportunities in areas such as predictive maintenance, customized manufacturing, and digital twin technologies.
- Innovation Labs: Established an internal lab for experimenting with new digital technologies and solutions.
- Outcome: Identified high-potential opportunities that aligned with the company’s strategic goals.
- Create Plans and Roadmaps
- Backcasting: Defined a desired future state (fully digitalized operations) and worked backwards to identify necessary steps and milestones.
- Strategic Roadmapping: Developed detailed roadmaps outlining key actions, timelines, and responsible teams.
- Outcome: Created a clear, actionable roadmap for digital transformation, including short-term wins and long-term initiatives.
- Build Future-Readiness and a Shared Perspective
- Visioning Exercises: Engaged stakeholders in creating a shared vision of the future, ensuring alignment and buy-in.
- Scenario Planning: Developed multiple scenarios to anticipate different future contexts and build strategic resilience.
- Leadership Development: Conducted training sessions for leaders to enhance their foresight capabilities and future-oriented thinking.
- Outcome: Fostered a culture of innovation and adaptability, with a shared understanding of the company’s digital transformation journey.
Results and Impact
- Operational Efficiency: Improved by 20% within the first year due to the implementation of digital technologies.
- Employee Engagement: Increased as employees felt more involved in the transformation process and were trained for new roles.
- Innovation: Accelerated with the establishment of the innovation lab and the adoption of new technologies.
- Market Competitiveness: Enhanced by offering new, customized products and services enabled by digital technologies.
Conclusion
By leveraging foresight and strategic scenario techniques, the company successfully navigated its digital transformation. The collaborative approach not only built consensus among stakeholders but also prepared the organization for a dynamic and uncertain future. This case study demonstrates the power of strategic foresight in driving meaningful and sustainable change.
See a very good example for foresight:
https://www.dhl.com/de-en/home/insights-and-innovation/thought-leadership/case-studies/logistics-2050.html & https://www.youtube.com/watch?v=DcRdvj28EWU
Authored by Alex Wyka, EA Principals Senior Consultant and Principal