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The art and science of Strategic Financial Modeling have never been more crucial. As companies strive for growth, the role of financial models in forecasting, valuation, and scenario analysis cannot be overstated.

Ian Bennett, with over two decades of experience in Strategic Financial Modeling, sheds light on the intricacies and challenges within this critical domain.

With a background that spans across continents and industries, He offers invaluable insights into what makes a financial model effective and how modelers can adapt to the evolving demands of businesses.

In this article we will dive into the essence of what makes a good financial modeler, exploring the blend of technical prowess, curiosity, and problem-solving skills necessary to navigate the intricacies of Strategic Financial Modeling effectively.

You will gain insights into balancing planning and execution, the pivotal role of Excel and emerging technologies like AI, and the fundamental practices that ensure model accuracy and reliability.

Who is Ian Bennett

With 24 years of experience in Financial Modeling, Ian Bennett began his career as a financial auditor before discovering his passion for Excel and Strategic Financial Modeling.

Moving from Manchester to London, he transitioned into Strategic Financial Modeling, today he leads a team in Australia and contributes to the field globally.

His achievements include earning the Master Financial Modeler designation from the Financial Modeling Institute (FMI), a testament to his expertise and contributions to the industry.

While Ian has extensive experience across various industries, he finds particular joy in modeling for renewables and hotels.

He appreciates the complexity of project finance in renewables and the driver-based, elegant structure of hotel models, demonstrating his versatile expertise and passion for contributing to significant sectors like energy transition.

The Challenges of Strategic Financial Modeling

Strategic Financial Modeling is a crucial task in business, often involving complex calculations and projections. Ian shared an eye-opening experience with a particularly problematic financial model he encountered about a decade ago.

Used by a large organization for valuation, this model was notorious for its complexity and size, presenting a multitude of challenges:

Size and Performance: The model was extremely large, about 40 to 50 megabytes, and took approximately 10 minutes to open on a standard laptop.

Analysis Time: Running tools for analysis took over a day, indicating the model's complexity and inefficiency.
Ownership and Modifications: Numerous individuals have modified the model over time, each leaving their mark. This led to a "Frankenstein" model that lacked coherence and was difficult to understand or trust.
Cost of Audit vs. Rebuilding: The cost of conducting a full integrity audit was estimated to be double the cost of rebuilding the model from scratch. Despite this, the organization opted to continue using the existing model, highlighting the challenges of dealing with legacy systems.
Eventual Rebuild: After eight years, the model was finally rebuilt, simplifying it and tailoring it to the organization's current needs.

The Critical Aspects of Strategic Financial Modeling

Ian's experience underscores 2 critical aspects of Strategic Financial Modeling:

Purpose-Driven Design: Financial models should be built with a clear, primary purpose in mind. Over time, as the model's purpose evolves or expands, its structure should adapt accordingly to maintain simplicity and relevance.
Relevance to Current Needs: When rebuilding a model, it's essential to approach it with fresh eyes, focusing on the organization's current needs and thinking patterns. This ensures the model remains effective and easy to use.

This case study not only sheds light on the complexities of Strategic Financial Modeling but also offers insights into best practices for creating effective and reliable models.

It underscores the importance of maintaining simplicity, focusing on a model's primary purpose, and aligning with current organizational needs.

What Makes a Good Financial Modeler

The qualities of an effective financial modeler go beyond mere technical skills. They encompass a blend of curiosity, problem-solving abilities, and the capability to understand and apply Strategic Financial Modeling techniques.

This combination enables modelers to adapt to new challenges and devise innovative solutions for complex problems.

Key Qualities

Technical Skills: Mastery of Strategic Financial Modeling techniques, the 3 financial statements, and Microsoft Excel is fundamental. It forms the backbone of a modeler's ability to construct accurate and reliable models.
Curiosity: A genuine interest in exploring new tools and methodologies. This drives continuous learning and adaptation to evolving Strategic Financial Modeling landscapes.
Problem Solving: The essence of Strategic Financial Modeling lies in solving problems. Modelers must think critically about the best approaches to tackle the challenges at hand.

Client's Perspective on a Good Financial Modeler

From a client's viewpoint, the value of a financial modeler extends beyond technical expertise. Clients seek reassurance that their specific needs and concerns are understood and addressed.

They prioritize:

Reliability: Clients need confidence that the modeler will not let them down or oversimplify complex issues.
Listening Skills: The ability to listen and adapt to the client's unique requirements is crucial. This involves understanding the client's goals and apprehensions.
Methodology: Clients appreciate a clear, structured approach to modeling that aligns with their objectives and provides a sense of security regarding the project's success.

Importance of Listening

Effective listening is central to successful Strategic Financial Modeling.

It involves:

Active Engagement: Paying close attention to the client's needs without preconceived notions.
Patience: Allowing space for the client to express their primary concerns, which may extend beyond the immediate scope of the model.
Understanding: Gaining insights into the broader context of the project, including business and operational objectives.

Listening attentively can uncover essential details that significantly impact the model's design and functionality, leading to more successful outcomes.

Spending Time Outside Excel

A significant portion of a financial modeler's work occurs outside Excel. Proper planning and client engagement are vital phases that occupy substantial time before diving into spreadsheet work. The process typically involves:

Initial Phases: Allocating 40% of the project's timeline to scope, specify, and design stages ensure that the model meets the client's needs and minimizes later adjustments.
Use of Prototypes: Creating prototypes and templates during the early phases helps in clarifying complex aspects and securing client agreement on the model's specifications.

This approach reduces the likelihood of errors and ensures that the model aligns with the client's expectations and business objectives.

Balancing Design and Building in Strategic Financial Modeling

Finding the right balance between planning and building is crucial for financial modelers. The temptation to dive straight into Excel and start constructing the model is common. However, ensuring sufficient time is spent on the design and specification phases is essential for creating effective and efficient models.

Strategies for Maintaining Balance

Experience: Understanding the importance of planning phases comes with experience. Through trial and error, modelers learn the value of thorough preparation.
Methodology: Adhering to a structured methodology, which includes scope, specify, design, build, test, and handover phases, helps ensure balance.
Reminders: Simple tactics like placing Post-it notes as reminders not to start building immediately can help resist the urge to jump into Excel too soon.

The end goal is to achieve an unambiguous understanding of the model's purpose, its users, the outputs it will produce, and the questions it will answer. This clarity ensures the model is ready for construction.

Tools for Modern Financial Modelers Beyond Excel

Modern financial modelers have a variety of tools at their disposal, extending far beyond Excel. These include:

Cloud-Based Modeling Tools: While they have not replaced Excel, these tools offer alternatives for specific use cases, especially in cloud-based and multidimensional modeling.
Third-Party Add-Ins: A wealth of add-ins developed by the community can solve common problems and enhance Excel's functionality.
Microsoft Power Stack: Understanding the full potential of Microsoft's suite, including Power Query, Power Pivot, Power BI, Power Automate, and Power Apps, is crucial. This suite represents the future of integrated and automated Strategic Financial Modeling.

Exciting Developments in Excel

Recent enhancements in Excel signal a significant shift in its evolution, making it an exciting time for financial modelers.

Innovations like dynamic arrays, LAMBDA functions, Python integration, and upcoming features such as Copilot and Fabric, enhance Excel's capabilities far beyond traditional spreadsheet functions.

Favorite Excel Shortcuts and Technical Tips

Despite new tools and features, classic Excel shortcuts like Alt-E-S-V (Paste Special Values) remain indispensable for many modelers. Adapting to newer shortcuts (e.g., Control-Shift-V) can be challenging but offers efficiency gains.

A critical technical tip for building robust models is the integration of error checks throughout the modeling process.

Implementing checks using absolute functions and conditional formatting ensures accuracy and provides immediate feedback on potential issues. This practice enhances model reliability and builds confidence among users and stakeholders.

By embracing a balanced approach to planning and building, utilizing a broad range of tools, and incorporating advanced features and best practices, financial modelers can significantly improve the quality and impact of their work.

Rapid-Fire Responses on Strategic Financial Modeling Preferences

In the rapid-fire section, Ian shared his preferences on various aspects of model building. Here's a summary of his views:

Model Building Practices

Circular References: Strongly advised against. Ian's stance is clear: avoid them.
VBA Use: Supports using VBA for now, indicating a practical approach to automation and scripting within Excel.
Orientation: Prefers horizontal layout for model organization.
Dynamic Arrays: Recommends embracing dynamic arrays, highlighting their value in enhancing model functionality.
External Workbook Links: Advises against using external workbook links, suggesting a focus on internal model integrity.
Named Ranges: Favors named ranges, pointing to their utility in making models more readable and manageable.
Following Standards: Utilizes PwC's global Strategic Financial Modeling guidelines, underscoring the importance of adhering to established best practices.

The Future of Excel and AI in Modeling

Excel's Longevity: Ian has a strong conviction that Excel will continue to be essential, dismissing the notion of its obsolescence.
AI's Role in Model Building: Predicts AI will eventually take on a significant role in building models, emphasizing its potential to assist throughout the model development process.

Model Security and Decision-Making

Sheet Cell Protection: Recommends using protection features to secure models, provided it aligns with user needs.
Financial Models as Decision Tools: Affirms the pivotal role of Excel and financial models in corporate decision-making.

Preference for Lookup Functions

Lookup Function of Choice: Prefers XLOOKUP for its flexibility, despite noting that it hasn't gained as much popularity as anticipated.

The Intersection of AI and Strategic Financial Modeling

The integration of AI into Strategic Financial Modeling represents a pivotal shift. It acts as both a collaborator and an advisor, aiding at every stage of model development—from scope definition to handover.

Currently, AI's capabilities within Excel are limited, but its potential is undeniable. In the future, AI is expected to impact model review processes, understanding, and construction significantly.

PwC's internal tool, ChatPwC, exemplifies how AI supports Strategic Financial Modeling. It is instrumental for tasks like coding in DAX or VBA, showcasing AI's current utility.

However, as Strategic Financial Modeling moves towards cloud-based solutions, Ian believes languages like Office JavaScript will replace VBA. This transition highlights the need for a language compatible with cloud computing, further underscoring AI's evolving role in Strategic Financial Modeling.

Conclusion:

In summary, Strategic Financial Modeling is essential for informed business decisions. Key takeaways include the need for clear purpose and adaptability in models to remain relevant and useful. Effective modelers blend technical skills with curiosity and problem-solving abilities.

Clients value reliability, the ability to listen, and structured methodology in modelers. Balancing design and building, understanding tools' full potential beyond Excel, and incorporating AI and new technologies are important l for modern Strategic Financial Modeling.

Ensuring models are secure and using practices like error checks enhances reliability. Financial models, supported by Excel and evolving tools, remain at the heart of corporate decision-making.

As technology evolves, so do the tools and methodologies at a modeler's disposal. Staying curious, embracing new technologies, and following best practices are key to crafting models that drive informed decisions.

FAQs

Why is Strategic Financial Modeling important?

It's crucial for making informed business decisions, forecasting future financial performance, and assessing strategic options.

What skills are necessary for Strategic Financial Modeling?

Key skills include proficiency in Excel, understanding financial concepts, attention to detail, analytical thinking, and problem-solving abilities.

How does Strategic Financial Modeling assist in business valuation?

It helps estimate the value of a business by forecasting cash flows and discounting them to present value, providing a basis for investment decisions.

Can Strategic Financial Modeling help predict the success of a new product?

Yes, by estimating costs, pricing, sales volume, and market penetration, Strategic Financial Modeling can forecast the profitability of a new product.

What role does AI play in Strategic Financial Modeling?

AI can automate data analysis, improve accuracy, and offer predictive insights, making financial models more efficient and insightful.

Shaping Business Strategy: Ian Bennett's Insights on What makes for a great financial modeler