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Why Your Strategy Needs a Fresh Perspective — And How AI Fits In (Part 2)

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Why Your Strategy Needs a Fresh Perspective — And How AI Fits In (Part 2)

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Why Your Strategy Needs a Fresh Perspective — And How AI Fits In (Part 2)

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Why Your Strategy Needs a Fresh Perspective — And How AI Fits In (Part 2)

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Why Your Strategy Needs a Fresh Perspective — And How AI Fits In (Part 2)

Insight

Why Your Strategy Needs a Fresh Perspective — And How AI Fits In (Part 2)

Strategy is only real when it adapts — and drives action.

Published

May 8, 2025

Kristian Luoma
Kristian Luoma

Kristian Luoma

, Co-founder

kristian@in-parallel.com

Linkedin ↗

Contents

9 min read (1728 words)

Introduction

How GPS Works

Why GPS Matters (and Why It’s Machine-Readable)

GPS in Action: The Tesla Example

How We Recommend Implementing GPS

GPS vs. Other Frameworks

The Bottom Line: Adaptive, Actionable Strategy

Conclusion: Turning Strategy into Action

Contents

9 min read (1728 words)

Introduction

How GPS Works

Why GPS Matters (and Why It’s Machine-Readable)

GPS in Action: The Tesla Example

How We Recommend Implementing GPS

GPS vs. Other Frameworks

The Bottom Line: Adaptive, Actionable Strategy

Conclusion: Turning Strategy into Action

Contents

9 min read (1728 words)

Introduction

How GPS Works

Why GPS Matters (and Why It’s Machine-Readable)

GPS in Action: The Tesla Example

How We Recommend Implementing GPS

GPS vs. Other Frameworks

The Bottom Line: Adaptive, Actionable Strategy

Conclusion: Turning Strategy into Action

In Part 1, we explored why static strategy models lead to misalignment, wasted effort, and a widening gap between strategic intent and real-world execution. We introduced the GPS framework (Goals–Problems–Solutions) as a structured way to bridge this gap — helping organizations continuously adapt and ensure their strategy remains relevant.

Now, in Part 2, we’ll break down how GPS works in practice. By systematically identifying obstacles and continuously refining solutions, organizations can stay aligned with their goals—even as conditions change. This approach is not only intuitive for human decision-making but also machine-readable, making it possible to integrate AI into strategic execution effectively.

In Part 1, we explored why static strategy models lead to misalignment, wasted effort, and a widening gap between strategic intent and real-world execution. We introduced the GPS framework (Goals–Problems–Solutions) as a structured way to bridge this gap — helping organizations continuously adapt and ensure their strategy remains relevant.

Now, in Part 2, we’ll break down how GPS works in practice. By systematically identifying obstacles and continuously refining solutions, organizations can stay aligned with their goals—even as conditions change. This approach is not only intuitive for human decision-making but also machine-readable, making it possible to integrate AI into strategic execution effectively.

In Part 1, we explored why static strategy models lead to misalignment, wasted effort, and a widening gap between strategic intent and real-world execution. We introduced the GPS framework (Goals–Problems–Solutions) as a structured way to bridge this gap — helping organizations continuously adapt and ensure their strategy remains relevant.

Now, in Part 2, we’ll break down how GPS works in practice. By systematically identifying obstacles and continuously refining solutions, organizations can stay aligned with their goals—even as conditions change. This approach is not only intuitive for human decision-making but also machine-readable, making it possible to integrate AI into strategic execution effectively.

In Part 1, we explored why static strategy models lead to misalignment, wasted effort, and a widening gap between strategic intent and real-world execution. We introduced the GPS framework (Goals–Problems–Solutions) as a structured way to bridge this gap — helping organizations continuously adapt and ensure their strategy remains relevant.

Now, in Part 2, we’ll break down how GPS works in practice. By systematically identifying obstacles and continuously refining solutions, organizations can stay aligned with their goals—even as conditions change. This approach is not only intuitive for human decision-making but also machine-readable, making it possible to integrate AI into strategic execution effectively.

How GPS Works

GPS follows a structured decision-making process, closely mirroring the OODA loop (Observe, Orient, Decide, Act) — a proven model for agile, real-time adaptation. Let’s dive into how it works.

  1. Set Your Goals
    These can be high-level strategic pillars like “Deliver the most enjoyable shopping experience,” or “Automate supply chain processes,” or “Grow market share by 15%.”

  2. Identify the Problems (Obstacles)
    Ask: What might prevent us from achieving these goals? These could be anything from resource shortages and regulatory changes to market disruptions and competitor launches. The important part is to constantly scan for new Problems and update them as circumstances shift.

  3. Develop Solutions
    For every Problem, define one or more Solutions — concrete initiatives that will neutralize or otherwise overcome the obstacle. If your Problem is “Inefficient last-mile logistics,” your Solutions might be “Expand courier partnerships” or “Implement store automation for faster pick-ups.” Each Solution is then assigned a priority based on how critical it is to remove that Problem.

  4. Reassess and Adapt
    GPS is not a one-and-done exercise. You continuously reprioritize Problems and Solutions as new data emerges, ensuring you never lose sight of the biggest threats to your Goals.

While it’s easy to assess the most important goals and prioritize them, we often struggle with prioritizing activities related to Solutions. This is really where Problems help — solving the biggest Problem should most often be the priority.

Why GPS Matters (and Why It’s Machine-Readable)

  1. Adaptive Strategy Execution
    Strategies often fail when teams ignore the obstacles. GPS puts Problems at the forefront. By methodically scanning and prioritizing them, you stay alert and responsive. If a new competitor comes to market, it’s immediately added to the “Problem” list — no waiting until next quarter’s review.

  2. AI-Collaboration
    AI can’t help you effectively if it only sees operational metrics. It needs to understand your goals, the obstacles to those goals, and the potential solutions. Because GPS is structured and can be interlinked across different levels of decision-making and operations, it’s inherently machine-readable. With this data, AI can:

    1. Suggest creative Solutions.

    2. Predict the impact of each Solution on your Goals.

    3. Analyze the quality of the Solutions proposed in the current operating environment. 

    4. Find the most important priorities on the fly. 

    5. Automate repetitive parts of the strategy assessment process.


  3. Institutional Learning
    By continuously capturing both successes and near misses, your organization builds a repository of knowledge. This is where AI shines, as AI algorithms can learn from these patterns, leading to more accurate forecasting and better decision-making over time.

  4. Clarity & Transparency
    GPS spells out exactly what you’re trying to achieve – what’s in the way, and the plan to fix it. No fluff, no buzzwords. This clarity helps teams avoid confusion and keep efforts aligned with the strategic north star.

GPS in Action: The Tesla Example

Let’s take a simplified look at Tesla — a company with the bold vision to “accelerate the world’s transition to sustainable energy.” I use this example because most of us are familiar with this clear, concise expression of their strategy.

Interestingly, it naturally aligns with the GPS (Goals–Problems–Solutions) framework we’re proposing.

In a machine-readable format, their strategy might look something like this:

  1. Goals

    1. “Expand market share of electric vehicles (EV).”

    2. “Achieve mass adoption of sustainable energy solutions.”

    3. “Continue to innovate on battery technology for lower costs and higher range.”

  2. Problems (Obstacles)

    1. Funding (e.g., they needed a lot of money to challenge the incumbents).

    2. Supply chain challenges (e.g., sourcing lithium for batteries, global semiconductor shortages).

    3. Production bottlenecks (e.g., scaling new Gigafactories).

    4. Regulatory uncertainties (e.g., changing emissions standards, incentives, or tariffs).

    5. Growing EV competition (from both legacy automakers and emerging startups).

    6. Consumer cost barriers (EVs often have higher upfront costs than traditional vehicles).

  3. Solutions

    1. “Build and ramp up additional Gigafactories.”

    2. “Secure long-term lithium and raw material contracts.”

    3. “Invest in advanced battery R&D to reduce costs.”

    4. “Expand direct-to-consumer sales channels in new markets.”

Each Solution is prioritized based on its impact, feasibility, and how urgently it needs to be implemented. If building a new Gigafactory is the most impactful way to address production bottlenecks, it goes to the top of the list.

As the market evolves — competitors launch new EV models, battery tech breakthroughs emerge, or governments introduce new incentives — Tesla updates its Problem set. That continuous loop means Tesla isn’t blindsided by a sudden shortage of critical materials or a shift in global interest rates that might affect factory construction.

This continuous cycle enables Tesla to identify and tackle the biggest threats to its ambitious goals. No matter how often external conditions change, the GPS framework keeps everyone aligned — ensuring a shared understanding of core objectives, key challenges, and the highest-priority solutions.

It all started with the Roadster, which generated enough funding to develop the Model S, on which its success then enabled Tesla to launch its first mass-market vehicle, the Model 3.

The GPS framework applies at every level — whether shaping a multi-year strategy or guiding tactical decisions on a quarterly, monthly, or even weekly basis. And that’s the whole point.

Let’s take a simplified look at Tesla — a company with the bold vision to “accelerate the world’s transition to sustainable energy.” I use this example because most of us are familiar with this clear, concise expression of their strategy.

Interestingly, it naturally aligns with the GPS (Goals–Problems–Solutions) framework we’re proposing.

In a machine-readable format, their strategy might look something like this:

  1. Goals

    1. “Expand market share of electric vehicles (EV).”

    2. “Achieve mass adoption of sustainable energy solutions.”

    3. “Continue to innovate on battery technology for lower costs and higher range.”

  2. Problems (Obstacles)

    1. Funding (e.g., they needed a lot of money to challenge the incumbents).

    2. Supply chain challenges (e.g., sourcing lithium for batteries, global semiconductor shortages).

    3. Production bottlenecks (e.g., scaling new Gigafactories).

    4. Regulatory uncertainties (e.g., changing emissions standards, incentives, or tariffs).

    5. Growing EV competition (from both legacy automakers and emerging startups).

    6. Consumer cost barriers (EVs often have higher upfront costs than traditional vehicles).

  3. Solutions

    1. “Build and ramp up additional Gigafactories.”

    2. “Secure long-term lithium and raw material contracts.”

    3. “Invest in advanced battery R&D to reduce costs.”

    4. “Expand direct-to-consumer sales channels in new markets.”

Each Solution is prioritized based on its impact, feasibility, and how urgently it needs to be implemented. If building a new Gigafactory is the most impactful way to address production bottlenecks, it goes to the top of the list.

As the market evolves — competitors launch new EV models, battery tech breakthroughs emerge, or governments introduce new incentives — Tesla updates its Problem set. That continuous loop means Tesla isn’t blindsided by a sudden shortage of critical materials or a shift in global interest rates that might affect factory construction.

This continuous cycle enables Tesla to identify and tackle the biggest threats to its ambitious goals. No matter how often external conditions change, the GPS framework keeps everyone aligned — ensuring a shared understanding of core objectives, key challenges, and the highest-priority solutions.

It all started with the Roadster, which generated enough funding to develop the Model S, on which its success then enabled Tesla to launch its first mass-market vehicle, the Model 3.

The GPS framework applies at every level — whether shaping a multi-year strategy or guiding tactical decisions on a quarterly, monthly, or even weekly basis. And that’s the whole point.

How We Recommend Implementing GPS

  1. Make “Problems” a Standing Agenda Item
    In your monthly or quarterly reviews, don’t just measure progress on goals. Ask: What new problems have cropped up, and which ones matter most right now?

  2. Set KPIs That Reflect Problem-Solving
    Yes, measure progress on overall Goals (e.g., X% revenue growth), but also track metrics that show whether specific Problems are being resolved (e.g., production delay rates, supply chain risk metrics).

  3. Centralize Your GPS Data
    Keep your GPS overview — Goals, Problems, Solutions — in a shared dashboard or collaboration platform. Transparency ensures all teams move in the same direction. At In Parallel, we offer an Intelligent Operating Model, designed to constantly feed the OODA loop.

  4. Continuously Reprioritize
    The order of Problems identified at the start of the year might not hold true by Q2. Business conditions change, so your top-tier Problems (and Solutions) might change, too.

  5. Keep Solutions Actionable
    Avoid vague and qualitative statements like “improve synergy.” Make your Solutions as concrete as possible, with clear owners and timelines.

  6. Cascade Solutions into New Goals
    A top-level Solution like “Invest in advanced battery R&D” might become a subordinate Goal for a specialized engineering team. The team then identifies its own Problems and Solutions. This cascading approach keeps every level aligned and fosters agency.

  7. Quantify Impact
    When selecting which Solutions to fund first, gauge the financial, operational, or reputational impact. Focus your resources where the payoff is greatest — and reevaluate often.

With In Parallel, all of this is optimized natively  in the Intelligent Operating Model.

  1. Make “Problems” a Standing Agenda Item
    In your monthly or quarterly reviews, don’t just measure progress on goals. Ask: What new problems have cropped up, and which ones matter most right now?

  2. Set KPIs That Reflect Problem-Solving
    Yes, measure progress on overall Goals (e.g., X% revenue growth), but also track metrics that show whether specific Problems are being resolved (e.g., production delay rates, supply chain risk metrics).

  3. Centralize Your GPS Data
    Keep your GPS overview — Goals, Problems, Solutions — in a shared dashboard or collaboration platform. Transparency ensures all teams move in the same direction. At In Parallel, we offer an Intelligent Operating Model, designed to constantly feed the OODA loop.

  4. Continuously Reprioritize
    The order of Problems identified at the start of the year might not hold true by Q2. Business conditions change, so your top-tier Problems (and Solutions) might change, too.

  5. Keep Solutions Actionable
    Avoid vague and qualitative statements like “improve synergy.” Make your Solutions as concrete as possible, with clear owners and timelines.

  6. Cascade Solutions into New Goals
    A top-level Solution like “Invest in advanced battery R&D” might become a subordinate Goal for a specialized engineering team. The team then identifies its own Problems and Solutions. This cascading approach keeps every level aligned and fosters agency.

  7. Quantify Impact
    When selecting which Solutions to fund first, gauge the financial, operational, or reputational impact. Focus your resources where the payoff is greatest — and reevaluate often.

With In Parallel, all of this is optimized natively  in the Intelligent Operating Model.

GPS vs. Other Frameworks

  1. GPS vs. OKRs (Objectives and Key Results): While OKRs offer clarity on what success looks like, GPS clarifies what can derail it. Another key difference is thatOKRs typically run in set cycles (like quarterly), whereas GPS prioritizes continuous updating so you don’t miss urgent threats in between review cycles.

    1. OKRs: Focus on high-level Objectives and measure progress through Key Results.

    2. GPS: Goes further by incorporating a built-in mechanism to identify and prioritize problems that could derail those objectives.


  1. GPS vs. Balanced Scorecard: Balanced Scorecard can be great for high-level alignment but can become static if not revisited often. In contrast, GPS is inherently agile, spotlighting immediate blockers and guiding rapid resource allocation to fix them.

    1. Balanced Scorecard: Divides goals into perspectives (Financial, Customer, Internal Processes, Learning & Growth).

    2. GPS: More directly tackles problem-solving and forces you to frequently re-prioritize solutions as obstacles arise.


  1. Tying It to the OODA Loop: Originally formulated for military decision-making, the OODA Loop (Observe, Orient, Decide, Act) emphasizes rapid reactions in dynamic environments.

    1. Observe & Orient: GPS identifies and prioritizes Problems.

    2. Decide & Act: GPS sets the Solutions.

After implementing Solutions, you return to observing new Problems. This cyclical approach ensures that strategy evolves in real time — not just annually or quarterly.

The Bottom Line: Adaptive, Actionable Strategy

At the heart of GPS is a simple insight: Your strategy can only succeed when you proactively address the obstacles en route to the goals. By embedding Problems into the heart of your planning — rather than treating them as afterthoughts — GPS helps you pivot in real time, keep your teams aligned, and ensure that no critical threat go unnoticed. Here's why it matters:

  • Strategies fail when obstacles are ignored. GPS makes sure Problems are front and center.

  • Execution needs clarity. With GPS, what needs doing and why becomes obvious to everyone.

  • AI needs a seat at the table. A codified (machine-readable) format enables AI to support knowledge work, from spotting new threats to suggesting innovative Solutions.

  • You stay agile. When the world changes — tomorrow, next week, or six months from now — you can update your Problem set and Solutions without trashing your overall Goals.

The ultimate payoff? Organizations that continuously do the right things right — elevating performance, engagement, and results in a way that’s future-proofed against disruption.

Conclusion: Turning Strategy into Action

Success in today’s business environment isn’t about having the perfect strategy — it’s about continuously adapting to change while staying aligned with long-term goals. The GPS framework (Goals–Problems–Solutions) provides a structured, dynamic approach to strategy execution, ensuring organizations remain agile, focused, and responsive.

By systematically identifying obstacles, prioritizing the right solutions, and integrating AI-driven insights, companies can bridge the Strategy-Market Gap and execute with precision. This shift moves strategy from a static exercise to a living, evolving system — one that keeps teams aligned and decisions grounded in real-time realities.

Organizations that embrace this model will not only navigate uncertainty more effectively but also unlock a new level of strategic agility and competitive advantage. The future of strategy isn’t about rigid plans—it’s about the ability to continuously do the right things, right.

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