Unlocking Strategic Business Scenarios with Generative AI as a Project Assistant - Scenario Generation USMCA
Preface
In today's dynamic business environment, strategic planning is more crucial than ever. Companies need to anticipate market trends, prepare for various scenarios, and adapt to changing circumstances. Generative AI offers a powerful tool for creating diverse and insightful business scenarios, enhancing the strategic planning process. Here’s how businesses can harness generative AI for scenario generation in their business plans.
For more than eight years, we at iMB.Solutions have had a client from the mobility industry, which supplies the automotive industry as a Tier 1 and Tier 2 supplier. We have already carried out projects of various types for our client in Brazil, Argentina, Europe and, for the last two years, also in Mexico. These ranged from projects to increase productivity, relocation of value creation to Argentina, to projects to reorganize the supplier structure in the USMCA economic area. Here we were primarily active in the Mexican plants. Our client has a strong affinity for technology and is very open to tools such as generative AI.
See also blog
Case Study: Process Mining & GenAI - the road will be longer than expected - or not?
blog cover, June 2024, designed by iMB.Solutions Team Mexico
In the current short-term project, part of a larger project mission including Brazil as well, I was appointed to the project to actively support the scenario planning for the 2025-2027 business plan. This project phase is extremely important as it focuses exclusively on the strategic part. The attentive reader should understand that a strict distinction is made between strategy and tactics.
While strategic planning is exclusively concerned with the generation of scenarios and how to react if the various scenarios occur, tactical planning involves the allocation of resources. This is where the well-known detailed business plan with the allocation of costs, expenses, income and revenue is created. This planning is then primarily carried out in spreadsheet applications.
In contrast, very creative tools, such as design thinking, are used extensively in scenario generation, i.e. strategic planning. The basic idea and the different phases of design thinking can be adapted very well and used in the context of strategic scenario generation. Generative AI is also used as an assistant in virtually all stages of scenario planning. Particularly in view of the available sources of all kinds and the speed of new facts, it quickly becomes clear that a linear planning approach can no longer lead to the goal. Generative AI assistants are particularly well suited to somehow sorting out this non-linearity.
The current project was carried out by me in Mexico in Q3 2024. Among other things, the focus set by the client was on the question of how the environment of the USMCA economic area could change after the US elections on November 5, 2024.
As part of this project, I led the Mexican and US project team and also worked with think tanks, e.g. at the University of New Mexico (NM), USA.
The planning approach is quite innovative. After evaluating the results, this process will also be applied in Brazil later this year in 2024.
blog cover, some real world images were post-processed with a generative AI software, other generated by DALL-E ( iMBdigital.Gallery_, August 2024, São Paulo, Brazil)
What is Generative AI?
Generative AI refers to a subset of artificial intelligence that can create new content from existing data. It leverages machine learning models to generate text, images, music, and even complex strategic scenarios. By analyzing vast amounts of data, these models can identify patterns, predict outcomes, and propose innovative solutions.
Benefits of Generative AI in Business Scenario Generation
Enhanced Creativity and Innovation: Generative AI can produce a wide range of potential scenarios that human business strategists might overlook. By exploring unconventional ideas, businesses can discover unique opportunities and innovative strategies.
Data-Driven Insights: AI models can analyze historical data, market trends, and competitive landscapes to generate scenarios grounded in real-world insights. This data-driven approach ensures that scenarios are not just imaginative but also relevant and feasible.
Speed and Efficiency: Traditional scenario planning can be time-consuming and resource-intensive. Generative AI can rapidly produce multiple scenarios, allowing project managers and executives to evaluate and iterate on strategies more quickly.
Risk Management: By generating various scenarios, including worst-case and best-case outcomes, businesses can better prepare for uncertainties and develop robust contingency plans.
Practical Applications of Generative AI in Scenario Generation
Market Expansion Strategies: Generative AI can help businesses explore new markets by generating scenarios that consider different entry strategies, competitive responses, and regulatory environments. For example, an AI model could analyze global and local economic data and predict the potential success of entering a new region, similar to the past expert systems, but much quicker and minimized costs today.
Product Development and Innovation: AI-generated scenarios can aid in product planning by simulating consumer responses, technological advancements, and competitor actions. This allows businesses to prioritize product features, identify market gaps, and anticipate future trends.
Financial Planning: Generative AI can create financial scenarios that consider various economic conditions, investment strategies, and revenue models. These scenarios help businesses plan budgets, allocate resources, and manage financial risks effectively.
Supply Chain Optimization: AI-driven scenarios can optimize supply chain strategies by predicting disruptions, evaluating supplier reliability, and suggesting alternative logistics solutions. This ensures that businesses maintain resilience and efficiency in their supply chains.
Implementing Generative AI in Business Planning
Data Collection and Integration: Successful AI scenario generation starts with high-quality data. Businesses need to collect and integrate data from various sources, including market reports, customer feedback, and internal performance metrics.
Choosing the Right AI Tools: Several generative AI tools and platforms are available, each with unique features and capabilities. Businesses should choose tools that align with their specific needs, whether it's natural language processing, image generation, or predictive analytics.
Collaborative Approach: While AI can generate valuable scenarios, human expertise is essential for interpretation and decision-making. A collaborative approach that combines AI insights with human judgment ensures well-rounded strategic planning.
Continuous Learning and Adaptation: The business environment is constantly evolving, and so should AI models. Regularly updating AI models with new data and feedback helps maintain their relevance and accuracy.
Project Management Restrictions
In our project mission in this case, we applied generative AI in a wide variety of contexts over the course of the project. It began with the assistance of generative AI to structure the project globally. Once we had determined the aspects that we considered important as a team, we used the generative AI assistant to extract the relevant sources from the Internet and make them available to us as the project team in accordance with the global project structure. The data sources were updated frequently.
Over the course of the project, the generative AI assistants were constantly consulted during scenario generation and evaluation. We also repeatedly used the generative AI assistant to create systems for evaluating the scenarios, change weightings and compare the resulting scenarios with our initial sources.
So you could say that our project team was constantly “working” iteratively with the generative AI assistant.
In this context, it was also important for us to use generative AI tools where we as a project team could actively change the sensitivity in dealing with data and sources through the generative AI tool.
Put simply, it was about being able to consciously change the generative AI filter between “factual-objective” handling and creative handling of data and sources in stages. What we expected from the AI tool was that we could actively and consciously change and use the so-called AI hallucination.
In practice, this means, for example, that we tied the generative AI assistant closely to the factual-objective prompt in the information collection phase in order to focus on the large information base. In the scenario generation phase, however, we deliberately wanted to have generative AI assistants that, like us humans in design thinking workshops, allow greater tolerance for creativity and interpretation of the data landscape.
Adopting Design Thinking for Business Scenario Creation
The rapidly evolving business environment in the USMCA economic area called for creating a robust and adaptable scenarios - crucial for strategic planning. Traditional scenario planning often relies on linear thinking and predefined assumptions, but as the complexity of business challenges increases, there's a growing need for more innovative approaches. This is where Design Thinking comes into play—a philosophy that emphasizes empathy, creativity, and iterative problem-solving, which can be transformative when applied to business scenario creation. This approach was then combined with generative AI tools in the project to structure the necessary dynamics and data volumes and to support the team's evaluation.
With iMB.Solutions, we have many years of very profound experience in the application of Design Thinking in a wide variety of project missions and industries. If you would like to learn more about Design Thinking, I recommend the following link to a blog:
>>>Blog: Transformation & Design Thinking
Understanding the Design Thinking Philosophy
Design Thinking is a human-centered approach to innovation that draws from the designer's toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success. It's a process that consists of five stages: Empathize, Define, Ideate, Prototype, and Test.
In this paragraph, I would like to explain the work phases to the reader and briefly introduce the generative AI tools we used. The list of tools does not mean that we have used them all to the same extent. They represent a selection that can be used depending on the requirements and have corresponding advantages and disadvantages. However, I cannot guarantee an individual assessment, as the project requirements and the corresponding project team can simply be too different.
However, before we could enter into the individual phases of design thinking to create and finally evaluate the strategic scenarios, we in the project team first had to structure the mission and ensure that we had the relevant sources available close in time.
Curate Data and Source Pool
Browse AI is a no-code web scraping tool designed to simplify data extraction from websites. It allows users to define specific data points they need and automatically extracts that information without requiring any coding skills. With Browse AI, you can set up web scraping automations using an easy point-and-click interface, download data as spreadsheets, or sync it with Google Sheets. It also supports scheduling tasks, monitoring data for changes, and integrating with other software via Zapier or REST API.
Perplexity is an AI-powered search engine designed to provide accurate, trusted, and real-time answers to any question. It uses advanced algorithms and web crawlers to gather and index information from the internet, making it a powerful tool for deep web searches. Perplexity emphasizes transparency and user control, allowing users to customize their search experience and safeguard their privacy.
NWO.ai is a generative AI tool designed for sentiment forecasting and cultural trend analysis. It leverages machine learning and natural language processing to continuously scan and analyze vast amounts of unstructured data from sources like social media, news, and search engines. This allows it to identify emerging narratives and forecast consumer sentiment with high accuracy. The platform is particularly useful for businesses and government agencies to understand customer needs, track global cultural shifts, and make data-driven decisions. We used this application intensively during the course of the project, particularly in the field of data science. The real big plus of this tool was the possibility to convert unstructured data points into actionable insights focused on our project mission.
In most cases, we then compared the corresponding results and generated data with the ChatGPT 4o version of OpenAI in order to carry out interpretations, data cleaning, analyses and, in some cases, visualizations.
Empathy in Scenario Creation
US truck, Arizona, U.S.A., 2024
The first stage of Design Thinking is empathy—understanding the needs, desires, and challenges of the people, stakeholder and shareholder involved. In business scenario creation, this means deeply understanding the stakeholders, including customers, employees, partners, and even competitors. Instead of just relying on data and trends, engage with these stakeholders through interviews, surveys, and immersive experiences. This approach ensures that the scenarios are grounded in real-world concerns and aspirations, not just abstract concepts.
For example, if you're creating scenarios for the future of industrial logistics and supply chain for automotive systems, spend time with customers in their logistic hubs close to the Mexican boarder and in Arizona, New Mexico, Texas and California, understand their frustrations and delights, and consider how these insights might shape future value chain landscapes. During the project mission, we spend most of the time in the boarder areas of Arizona and New Mexico, less in Texas and no intervention in California. Of course, an incredibly high density of information and data was also generated and collected in this “microcosm”. The mere registration and organization of the diversity of data and information using only a pad and pencil undoubtedly entails a high degree of unavoidable superficiality and/or an extremely long project period without generating meaningful information for necessary management decisions.
Outset AI is an innovative platform designed for adaptive AI-driven interviewing. It leverages artificial intelligence to conduct and moderate interviews, providing a seamless and efficient way to gather deep qualitative insights. Here are some key features we identified as extremely useful:
AI-Moderated Conversations: The AI interviewer engages participants in meaningful discussions, dynamically probing deeper based on their responses.
Automatic Synthesis: The platform automatically transcribes and analyzes interviews, identifying common themes and highlighting key quotes.
Multilingual Support: Outset AI can conduct interviews in multiple languages, making it accessible to a diverse range of participants. We used Spanish and American English.
Flexible Modes: It offers various modes such as audio, video, and text, allowing for rich data collection. During our project mission, we engaged with all three formats.
This approach combines the depth of qualitative interviews with the speed and scale of surveys, making it a powerful tool for research and strategic decision-making. Another major advantage is that the sources can be accessed digitally at any time and can be used to support arguments with management. The decision-making process becomes more informed and ensures that a large number of voices are heard in a short space of time.
Otter.ai is an AI-powered transcription service that provides real-time transcription of spoken language into written text. It is widely used for meetings, lectures, and interviews. Otter.ai can automatically generate meeting notes, summaries, and action items, making it a valuable tool for productivity and collaboration. It integrates with popular platforms like Zoom, Google Meet, and Microsoft Teams, and offers features like live captions, audio recording, and slide capture.
Rev AI is a suite of advanced speech recognition and natural language processing APIs developed by Rev.com. It provides highly accurate automatic speech recognition (ASR) capabilities for transcribing audio and video files into text. Rev AI offers both asynchronous and real-time transcription, along with additional features like language identification, sentiment analysis, topic extraction, summarization, and translation.
Trained on millions of hours of human-transcribed audio, Rev AI sets the industry standard for transcription accuracy across diverse voices and accents. It’s known for its best-in-class accuracy, low word error rates, and support for over 36 languages. The service can be deployed both in the cloud or on-premises, making it suitable for various applications and industries.
This tool was our workhorse - both internally and in the field.
Dovetail AI is a powerful tool designed for transcription and analysis. It automatically transcribes video and audio recordings into text, supporting over 40 languages. The platform uses AI to highlight key moments and sentiments in transcripts, making it easier to uncover insights from interviews, customer feedback, and other data sources. This helped our team quickly analyze and share valuable information without spending hours on manual work.
Xelper AI is a tool designed to streamline and enhance the user interview process through AI moderation. It allows you to upload your interview guide, generate a chatbot, and invite your target audience to participate. Within 24 hours, you receive a detailed analysis via a personalized dashboard. This process helps generate insights from real user interviews quickly and with minimal effort, making it easier to build the right products faster. No fundamental experience accumulated during the project mission.
Conversia AI is an advanced tool designed for adaptive AI-driven interviewing. It leverages artificial intelligence to conduct interviews, analyze candidate responses, and provide real-time feedback. The system adapts its questions based on the candidate’s answers, ensuring a more personalized and dynamic interview experience. This technology helps streamline the recruitment process by offering standardized evaluations, saving time, and improving the overall quality of candidate assessments. No fundamental experience accumulated during the project mission.
Defining the Problem Space
Once we've gathered insights through empathy, the next step is to define the core challenges and opportunities. This involves synthesizing the information collected to identify key themes and patterns. In scenario creation, this stage helps to clarify the strategic questions that the scenarios need to address.
For instance, if the challenge is the disruption of traditional supply chain in the USMCA business environment due to the outcome of U.S. presidential election on Nov. 05, 2024 or by enlarged e-commerce for spare parts, the problem definition might revolve around how physical B2B commercial spaces can remain relevant in a digital-first world.
UserEvaluation AI is a powerful tool designed to streamline the process of extracting valuable insights from various data types, including audio, video, text, and CSV files. It leverages advanced AI models, such as GPT-4, to perform tasks like transcription, sentiment analysis, and clustering of data. Key features include:
AI-Powered Transcription: Converts audio and video content into text in over 57 languages.
Insight Generation: Quickly extracts actionable insights from your data, providing sources for each insight.
Multimodal AI Chat: Allows you to extract and visualize key information across multiple files.
AI-Generated Reports and Presentations: Automatically creates detailed reports and presentations enriched with data visualizations.
Sentiment Analysis: Identifies mood trends in customer interactions to refine strategies.
Data Organization: Uses a Kanban board to keep insights organized and shareable.
This tool is designed to help businesses understand their customers better and make data-driven decisions efficiently.
Userview AI is a tool designed to streamline the analysis and synthesis of user interviews. By uploading audio or video recordings, it quickly generates detailed interview reports, providing valuable insights and clustering similar feedback for better understanding and decision-making1. This makes it easier for teams to identify patterns and key themes from user data, ultimately enhancing product development and user experience.
Kraftful AI is a powerful tool designed to enhance product management through AI-supported insight analysis and clustering. It leverages advanced AI models, like GPT-X-turbo, to provide deep insights into user feedback and product performance. Kraftful’s capabilities include:
Qualitative Data Analysis: It helps product managers interpret user feedback at scale, identifying key themes and sentiments.
Clustering: By grouping similar data points, Kraftful aids in uncovering patterns and trends that might not be immediately obvious.
Actionable Insights: The tool generates tailored recommendations to optimize features, improve user experience, and identify market opportunities.
Overall, Kraftful AI empowers project teams to make data-driven decisions and create products, services and processes that delight users.
GetCurious AI is a platform designed to enhance user research through AI-supported insight analysis and clustering. It offers tools for conducting AI-moderated interviews, creating AI-powered studies, and generating comprehensive reports. The platform helps project teams quickly recruit participants, conduct studies, and derive deep insights from qualitative data. By leveraging AI, GetCurious AI enables faster and more efficient analysis, making it easier for project teams to understand user needs and improve their offerings.
Miro AI is a powerful tool designed to enhance collaboration and productivity on the Miro platform. It offers AI-supported features for insight analysis and clustering, which help project teams organize and make sense of large amounts of data quickly. Here are some key functionalities we identified:
Clustering by Keywords: Automatically groups sticky notes based on similar keywords, helping to identify patterns and themes in brainstorming sessions or user research projects.
Clustering by Sentiment: Organizes sticky notes into positive, neutral, and negative categories, allowing teams to quickly gauge the overall sentiment of feedback or ideas.
AI Sidekicks: Provides instant AI-powered assistance on the canvas, such as generating summaries, creating diagrams, and offering strategic guidance.
These features streamlined the process of analyzing and organizing information, enabling our project team to focus on refining key insights and making informed decisions. This tool was our workhorse - both internally and in the field.
Ideation: Expanding Possibilities
In the ideation phase, the goal is to generate a wide range of ideas, in our case strategic scenarios, without judgment. This is where creativity and lateral thinking come into play. For business scenario creation, ideation involves imagining various future states of the relevant business world that could impact your business. Encourage brainstorming sessions with diverse teams, including members from different departments, industries, or even external experts. The more diverse the perspectives, the richer the scenarios.
For example, when imagining future supply chain scenarios in the USMCA business environment between the US and Mexico, consider not just technological advancements but also potential shifts in consumer behavior, economic conditions, and regulatory environments.
Ideanote is an AI-powered idea generator designed to help companies quickly brainstorm and develop new ideas. It allows users to input their business or project details and select a topic for idea generation. The AI then produces a list of innovative ideas tailored to the specified parameters. This tool is useful for generating cost-saving strategies, enhancing customer satisfaction, and creating new products and services. Additionally, Ideanote offers features for collecting, evaluating, and managing these ideas, making it a comprehensive solution for fostering creativity and innovation within organizations. It is an iMB.Solutions workhorse.
Stratup.ai is an AI-powered platform designed to generate innovative startup ideas tailored to specific topics or industries. By leveraging advanced AI models, it analyzes current market trends and opportunities to provide unique and creative business ideas. Entrepreneurs can explore over 100,000 AI-generated ideas, helping them unlock their full potential and fuel their entrepreneurial journey. Not applied during the project mission.
Ideamap AI is an innovative tool designed to create instant mind maps using artificial intelligence. It allows users to input their ideas or topics, which the AI then organizes into a visual mind map within seconds. This tool is particularly useful for brainstorming, learning, and summarizing information. Users can refine the AI-generated mind maps, collaborate with team members in real-time, and export the final maps as images or share them via a URL. This is one of our workhorses if it comes to brainstorming and mind mapping assisted by generative AI.
Prototyping Scenarios
Prototyping in Design Thinking is about creating tangible representations of ideas. In scenario creation, this can be translated into building detailed, narrative-rich scenarios that describe different possible futures. Instead of just listing bullet points, craft stories that bring the scenarios to life, making them relatable and easier to grasp.
These prototypes can take the form of written narratives, visual maps, or even role-playing exercises. The goal is to make the scenarios vivid and engaging so that stakeholders can easily understand and relate to them.
This phase was not used as part of this project mission.
Testing and Iteration
The final stage of Design Thinking is testing, which involves putting your prototypes in front of users and stakeholders to gather feedback. In scenario creation, this means presenting your scenarios to key decision-makers and other stakeholders to see how they resonate, and to test their relevance and impact.
Feedback should be used to refine the scenarios, making them more robust and actionable. This iterative process ensures that the scenarios are not just theoretical but are practical tools that can guide strategic decision-making.
Testing and iteration were not part of this project mission. The various scenarios were presented to management and the associated restrictions, assumptions and possible implications were presented in a weighted form. The next steps now depend on the internal management assessment and the actual developments in the coming months.
Integrating Design Thinking into Your Organization
To successfully adopt Design Thinking for scenario creation, it’s essential to embed this philosophy into the culture of your organization. Encourage cross-functional collaboration, foster a mindset of continuous learning and experimentation, and prioritize empathy in all strategic initiatives. By doing so, your business can stay ahead of the curve, adapting to changes in a way that is both innovative and grounded in the real-world needs of your stakeholders.
Design thinking is a purely human-centered approach to problem solving. The numerous applications of generative AI in particular provide massive support for human-centered problem solving and allow us humans to once again become what we are: creative.
Adopting and combining Design Thinking and generative AI for business scenario creation transforms the process from a static, linear exercise into a dynamic, human-centered exploration. By emphasizing empathy, creativity, and iterative testing, organizations can develop scenarios that are not only more relevant and resilient but also more aligned with the needs and aspirations of their stakeholders. In an increasingly unpredictable world, this approach can provide the strategic foresight needed to navigate uncertainty with confidence.
The Project: The Scenario Simulations and Outcomes - Navigating US-Mexico Trade Under Trump: 5 Keys to Competitive Advantage
Introduction
Initially, we explored three broad scenarios for US-Mexico trade if Trump wins the upcoming election. While a close, cordial relationship between the two administrations would be ideal, early indications suggest that this best-case scenario is unlikely. Instead, we need to prepare for a scenario where trade is compartmentalized amidst deteriorating relations on other fronts.
In this overall context, it is important to note that the USMCA Agreement must be renewed by all three participating nations (USA, Mexico, Canada) by July 01, 2026. If one of the three partners no longer agrees to the current agreement, either it will have to be completely renegotiated or the agreement will become completely obsolete and will not be continued.
image captured in the US sunbelt States, roadtrip Austin (TX) to Albuquerque (NM)
The Reality of US-Mexico Trade
Regardless of the fate of the USMCA, US-Mexico trade will continue until July 2026. However, border security will become the top priority, leading to a shift back to a Just In Case logistics mindset. Nearshorers will need to bullet-proof their supply chains to ensure compliance with US rules, especially those prohibiting Chinese materials. Keep in mind that regulations like the UFLPA are US rules and do not apply to Mexican producers. Additionally, if the US militarizes the border, your shipments may not be prioritized by inspectors.
Under a Trump administration, border security and efforts to stem the supply of illicit drugs will dominate US-Mexican relations. Trade will still be important, but it will take a back seat to security issues. The good news for nearshorers is that Mexican production is likely to become even more competitive if Chinese output is hit with punitive tariffs. Even if Mexican production faces new 10% tariffs, a North American strategy remains advantageous.
To maximize the benefits of the Mexican nearshoring plan of our client, we forecast to take several proactive steps now to avoid problems later, if this scenario will be turned into reality from January 2025.
image captured in the State of New Mexico (NM), U.S.A.
Key Assumptions
A Trump administration will be more overtly anti-China than the current administration.
The border will be militarized to some degree as border security becomes a priority.
US-Mexican relations will likely suffer as the US focuses on closing the border to migrants and arguing for aggressive pursuing drug traffickers on both sides of the border.
Five Steps our Client as Nearshorer Needs to Prepare for a Trump Presidency
1. Double Down on Compliance
Customs has always been a significant issue for Mexican exporters, but border security and customs inspections are about to intensify. We expect our client’s shipments to face more scrutiny and budget time and resources for enhanced inspections of trucks and shipping materials. New compliance measures will aim to keep Chinese production out of the US market and target illegal drugs and migrants.
Speed to market has been a major advantage for nearshorers, but now it's a double-edged sword. Expectations for speedy delivery remain high, but a high-security border will be slow and cumbersome to manage.
There are three bodies of law to consider: Mexican rules governing IMMEX and normal operations, US rules which will likely become more stringent, and potential US sanctions on Chinese producers. Compliance with trade rules has not traditionally been an issue at the US-Mexico border, but a Trump administration may use paperwork and inspections for national security purposes.
2. Bulletproof Supply Chain
Whether sourcing from Mexico or maintaining legacy suppliers in Asia, our client has to ensure to know every detail of the production inputs. UFLPA is usually associated with cotton and textiles but can also affect solar panels, tech, electronics, mined materials, and auto parts. You are responsible for all upstream inputs in components bought from Mexico, Vietnam, Thailand, etc. Non-compliant materials, even if relabeled, are your problem.
Remember that UFLPA is a US rule and does not apply to Mexican businesses. The auditing, certification, and documentation are your responsibility.
3. Have Logistics Options
A Trump administration might militarize the border, leading to potential delays and shutdowns without explanation. Our client has to ensure to have alternative options for surface freight, other routes, rail, and shipping.
American managers often prefer to build close to a Port of Entry and rely on that crossing for all shipments. However, in the event of closures or delays, your business could be severely impacted.
We had to explore our options in terms of alternative land routes, rail options, and sea options.
4. Build Goodwill
Maintaining good relations in Mexico has not traditionally been an issue due to the strong presence of bi-cultural Mexican managers. However, if the feasible next US administration is perceived as undermining Mexico's sovereignty and dignity, the negative impact could affect the team of our client.
Under the Biden nearshoring boom, maintaining good relations was straightforward. Under Trump, you'll need to work harder to maintain good relations with your management team, workers, and the community. Providing good jobs made you a hero under Biden, but if Trump starts aggressive actions against everything south of the Rio Grande, your popularity could drop quickly.
5. Adopt a Just In Case Mindset
The US-Mexico border has been a significant advantage for nearshorers like our client, but under Trump, it could become a double-edged sword. Most cross-border shipping will be hassle-free, but when snags occur, they could be serious and long-lasting. Warehousing in Texas and Arizona is relatively cheap. While keeping inventory around is not ideal, it may become unavoidable under a feasible Trump administration.
What a Harris Presidency Means for Nearshoring: A Balanced Continuation
The potential election of Kamala Harris as President of the United States carries significant implications for nearshoring—a trend that has been gaining momentum as companies seek to relocate parts of their supply chain closer to the US. With Harris at the helm, nearshorers from the US, Mexico, and even China may find themselves navigating both familiar and new challenges. Here’s a closer look we identified in our scenario creations at what a Harris presidency could mean for this crucial sector.
Kamala Harris, candidate for U.S. presidential election November 2024, image cut from Vogue Cover
The evaluations by our generative AI assistant also showed us astonishing sources that are apparently not published so intensively. This data has a global view of the possible scenarios, but is extremely important with regard to USMCA economic relations, also against the background of drawing up a strategic business plan for our client.
The reputation of the Republican Party, hereinafter referred to as the GOP (Grand Old Party), is that it is historically superior to the Democratic Party, hereinafter referred to as the DC, on economic issues. However, the evaluation of the data provided by the generative AI assistant revealed a different picture.
Since the end of the Second World War, the GOP's economic record has been noticeably worse than during DC administrations. Sources from Harvard University were particularly evident here. This data showed an average annual growth of 4.23% in the case of DC governments as opposed to 2.36% in favor of GOP administrations. That's a staggering annual difference of 1.87% in favor of DC governments. It gets even more astonishing when you analyze the dynamics. Nine out of 10 recessions in the US since the end of World War II were triggered during GOP administrations. In the same context, it can be seen that in the last ten changes of administration from a DC president to a GOP president, PIB growth collapsed significantly. In the opposite cases, the exact opposite happened. Since the end of the Second World War, both the GOP and the DC have had seven presidents. In the case of DC presidencies, an average of 88 million jobs were created, in contrast to just 32 million in the case of GOP administrations. In this overall context, it is also interesting to analyze that in the case of GOP governments, fiscal expansion was always significantly higher than in the case of DC governments.
Stability in Nearshoring: A Double-Edged Sword
For nearshorers based in Mexico, continuity is key, and a Harris administration would likely be more of the same, a continuation of the Biden administration’s policies. This is generally good news for businesses that thrive on predictability. However, it also means that companies will have to grapple with the same issues, particularly when it comes to navigating US-China relations and environmental regulations.
The enduring challenge lies with China. A Harris administration wouldn’t have the authority to force Mexico to alter its Foreign Direct Investment (FDI) or government registration laws, especially concerning Chinese companies. This leaves the door open for Chinese state-supported enterprises to legally operate in Mexico, complying with United States-Mexico-Canada Agreement (USMCA) and IMMEX rules just like everyone else. This means “Hecho en Mexico” products could still be sold in the US through platforms like Amazon and Costco, but the competitive landscape might shift.
The Political Landscape: Harris and Nearshoring
The political dynamics of nearshoring under a Harris administration would be a blend of familiar and new elements. The transition from Biden to Harris would likely maintain the focus on Mexico as a key nearshoring destination, but with added emphasis on environmental and security compliance. Here are five key points we identified nearshorers should keep in mind:
No. #01 - USMCA is Here to Stay (For Now)
The USMCA is likely to survive its 2026 review with minimal changes. However, businesses should brace for potential increases in Regional Content Requirements and the introduction of more stringent environmental standards. Proving the sustainability of supply chains and ensuring compliance with US rules like the Uyghur Forced Labor Prevention Act (UFLPA) and CHIPS Act will be crucial.
No. #02 - China’s Persistent Influence
China will remain a significant factor in nearshoring decisions. Despite previous attempts to reduce Chinese influence in Mexico through tariffs and entity lists, Chinese companies are expected to continue expanding their operations in Mexico. Both the Harris and Sheinbaum administrations may be caught off guard by the scale of Chinese manufacturing investments in Mexico.
No. #03 - US-Centric Compliance
New regulations targeting China will likely be enforced on the US side of the border. While Mexican companies aren’t subject to US-specific laws like UFLPA or CHIPS, US-based businesses will need to ensure their supply chains are free of sanctioned goods and services. This could mean increased scrutiny and inspections once products cross into the US.
No. #04 - Rising Costs and Bureaucracy
Compliance with new regulations and the continuation of existing policies will likely lead to higher operational costs. These additional expenses could be tied to environmental projects, social programs, and other governmental initiatives. Businesses will need to be prepared for more paperwork, inspections, and potential delays at US entry points.
No. #04 - An Ideal Nearshoring Environment
Despite the challenges, a Harris administration could still represent the best possible scenario for nearshorers in Mexico-USA. The continuity of policies provides a stable environment for businesses to plan and operate, with no major disruptions expected until at least 2026.
A Closer Look at the Harris Administration’s Priorities
To understand the potential impact of a Harris presidency on US-Mexico trade, it’s important to examine her approach to key issues such as border control, cartels, drugs, and China:
Border Control: The Harris administration would likely continue the Biden administration’s relatively light touch on border issues, focusing on incremental, bureaucratic solutions rather than drastic measures. This approach could mean higher costs for commercial traffic but fewer disruptions.
Cartels: Given her history as California’s Attorney General, Harris is likely to make the fight against cartels a top priority. The current strategies for managing cartel-related issues are expected to continue with minimal changes. However, it is highly likely that a more efficient integration with the new Mexican President Claudia Sheinbaum will be sought in order to tackle the problem in a more integrated manner.
See also blog
Claudia Sheinbaum: Mexico’s First Female President-Elect - A Historic Victory
Blog cover, iMB.Solutions, 2024
Drugs: Harris is likely to maintain existing policies on drug enforcement, particularly concerning fentanyl, which has been a focal point of the Biden administration. No major new initiatives are expected in this area.
China: The biggest challenge remains China. Mexican supply chains could face increased competition from Chinese companies, which are likely to ramp up their operations in Mexico. The US will continue to enforce its trade policies on the US side of the border, leaving Mexican companies to navigate the complex landscape of international trade.
Key Learnings - Enhancing Scenario Planning with Generative AI: A Game-Changer for the Future
In the rapidly evolving landscape of business and technology, scenario planning has become a critical tool for organizations aiming to anticipate and navigate uncertainty. Traditional methods, however, often struggle with the sheer complexity and number of variables involved. This is where generative AI comes into play, offering powerful solutions to address the limitations of conventional processes.
Generative AI allows organizations to explore a far broader range of scenarios than would be possible through human effort alone. By leveraging advanced algorithms and models, companies can generate, analyze, and refine a multitude of options, leading to more informed decision-making.
I have personally gained experience with the following tools as part of further training measures and customer projects.
Generative Adversarial Networks (GANs)
Generative Adversarial Networks (GANs) are a groundbreaking technology widely used to generate realistic synthetic data. GANs operate through the interaction of two neural networks—a generator and a discriminator. The generator creates data, while the discriminator evaluates its authenticity. Over time, this adversarial process leads to the creation of high-quality data that can be used to simulate diverse scenarios. For scenario planning, GANs can help organizations visualize and explore a wide array of potential futures, enhancing their ability to prepare for different eventualities.
Variational Autoencoders (VAEs)
Another powerful tool in the generative AI arsenal is the Variational Autoencoder (VAE). VAEs are designed to learn and represent complex data structures, making them invaluable for understanding the underlying patterns and uncertainties in a dataset. By altering these latent variables, VAEs can generate alternative scenarios that reflect different dimensions of uncertainty. This capability is particularly useful when organizations need to explore multiple “what-if” situations, offering a richer understanding of possible outcomes.
Monte Carlo Simulation
While not strictly a generative AI model, Monte Carlo simulations remain a cornerstone of scenario analysis, especially in fields like financial risk management. This technique uses random sampling to model and simulate a variety of potential scenarios, providing a probabilistic view of different outcomes. When integrated with generative AI models, Monte Carlo simulations can be enhanced to explore even more complex and nuanced scenarios, offering a robust framework for decision-making under uncertainty.
Deep Reinforcement Learning (DRL)
Deep Reinforcement Learning (DRL) represents the cutting edge of AI in scenario planning. DRL algorithms, such as deep Q-networks (DQNs), learn by interacting with their environment, continually improving their strategies based on feedback. This makes DRL particularly well-suited for scenario analysis in dynamic and complex environments. By simulating different strategies and their potential outcomes, DRL can help organizations identify optimal approaches to future challenges.
Tailoring the Approach to Your Needs
It’s important to note that the effectiveness of these tools depends heavily on the specific context and requirements of your scenario planning process. Factors such as the availability of data, computational resources, and the desired level of detail all play a role in determining which approach is most suitable. By carefully selecting and combining these tools, organizations can enhance their ability to anticipate and adapt to future challenges.
Generative AI is not just a buzzword; it’s a transformative technology that can significantly elevate the quality and depth of scenario planning. If you’re interested in exploring how these tools can be applied to your specific use case, don’t hesitate to reach out. The future is uncertain, but with the right tools, it doesn’t have to be unpredictable.
graphic representation of scenario restrictions, 2024
Résumé
Generative AI holds immense potential for transforming strategic business scenario generation. By leveraging AI's creative, data-driven, and efficient capabilities, businesses can enhance their strategic planning, stay ahead of market trends, and better manage uncertainties. As generative AI continues to advance, its role in shaping the future of business strategy will only grow, offering new possibilities and driving innovation.
Scenario creation is a powerful tool in the arsenal of any business that wants to navigate the uncertainties of the future with confidence. However, the value of these scenarios depends heavily on the expertise of the futurist crafting them. By carefully distinguishing between charlatan futurists and professional futurists, businesses can ensure they receive reliable, actionable insights that drive informed decision-making. In an uncertain world, investing in the right futurist is not just wise—it’s essential for staying ahead of the curve.
While basing factories in Mexico might become slightly more cumbersome under a Trump administration, reliance on China will be nearly impossible. Vietnam, Thailand, and India face similar challenges as Mexico, so your competitive position remains strong. However, you must be prepared to manage more challenging HR, logistics, and customs environments as relations with Mexico could become rocky.
In conclusion, a Harris presidency would likely be a continuation of current US-Mexico trade policies, with a few added complexities related to China and environmental regulations. Nearshorers should be prepared for more compliance requirements, higher costs, and increased scrutiny, but they can also take comfort in the stability and predictability that a Harris administration would bring to the table. The nearshoring landscape will continue to evolve, but for now, it seems poised to thrive under this “best of all possible worlds” scenario.
Disclaimer
The content of this blog has been agreed with the client. The early publication as a blog is unusual, but the client has agreed to it, as the facts and contexts examined and evaluated may be confirmed or changed in the coming weeks. A later publication would be of less interest in view of the topicality of the facts. The blog describes the environment of the project mission in the USMCA economic area as it is relevant to the client. References, explicit statements or action plans from the derived scenarios are not included in the blog, as they are considered company secrets. The market scenarios assessed as relevant with potential action plans are also not part of this blog. Political aspects that are not normally part of our project missions are covered here. The project mission aimed at scenario generation of economic conditions in the USMCA economic area, with special attention to the US presidential election and its strategic implications for US-Mexico relations. In order to make this case study understandable to the reader by using generative AI models to create strategic scenarios, these statements and assessments had to be integrated into the blog without reinforcing political biases.
