Synchronising Success: The Art of Perfecting and Aligning Financial & Data Models
DALL-E 3 sourced via Co-pilot (Humans are safe for now excuse AI spelling)

Synchronising Success: The Art of Perfecting and Aligning Financial & Data Models

Introduction to the co-author

Dhanusha is a founder of POTENZA and is responsible for driving POTENZA’s Global expansion. He has 25+ years of digital transformation and management expertise behind him. Dhanusha was the former Chief Enterprise Architect – BFSI at the London Stock Exchange Group, and an Enterprise Technology Specialist at Microsoft.

He also played senior roles in several listed corporates including Hemas Holdings PLC and John Keells Holdings PLC in Sri Lanka. Dhanusha is a member of the Forbes Technology Council and an executive alumnus of the University of Oxford, where he studied Strategic Innovation.

He is currently serving on multiple corporate boards in Sri Lanka, Singapore, and Australia as a Director.

Why did Dhanusha select the topic and why is he passionate about it?

As a Tech executive who has been involved in many different projects across Data Engineering, SAP Enterprise Resource Planning implementations and Automation delivery, the job is never entirely done post “go-live”. Having worked as the Chief Enterprise Architect in the Banking and Financial Services Sector for the London Stock Exchange Group this was abundantly clear.

There is a role to play to ensure ongoing alignment of technology and capabilities to meet the strategic goals of the organisations, which is continuous. As and when new tech is deployed, it’s critical to ensure its alignment with the technology stack, tools and business objectives.

Once a solution has been built, the technology doesn’t change or evolve without some focused effort and investment, however, the dynamism of the external business environment which is out of our control, automatically influences key strategic decisions.

This calls for agility in everything we do as a business and the need for continuous alignment is the way to sustain and thrive in making the right decisions repeatedly. Many businesses fail in this phase of technology adoption, in both aspects of focus and investment.

The ebb and flow of new competitors, products, laws, customer behaviours and demands directly affect those trading conditions. Sometimes those changes are not obvious, and the ultimate financial impacts may not be felt until it’s too late. This is why there is a need to constantly evolve the decision-making processes and the technology that supports that constant change.

The annual budgeting process drives important decision-making and arguably the most critical cycle of decisions and investment each year.

  • What are we doing about our cost base?
  • Is it necessary to research new products, channels, or ways of working?
  • Do we need to grow or shrink certain parts of the business?
  • What investment do we need to protect and run the business vs change the business?

This leads naturally to tech projects involving the accounting and finance teams in this annual planning process, which is often heavily reliant on manual static spreadsheets (vs scalable, integrated, and dynamic ones).

The finance team is having to evolve their decision-making process and the speed they respond to these queries as data becomes more accessible, and tools become more powerful whilst the rest of the business is also keen to leverage those insights to drive performance.

This ultimately leads to developing a capability within businesses to ensure ongoing alignment of financial models to ensure they are both accurate but also efficient in keeping pace with changes in business drivers and expected financial outcomes.?

Topic and context in no more than 3 sentences or concepts

Post the development process of a decision-making tool, which is often in the form of a model, there is a need to maintain ongoing alignment of both the inputs (assumptions) and the outputs produced. This can be summarised in 3 key concepts namely:

1. Accuracy and Adaptability

Financial models must be accurate representations of real-world financial scenarios and therefore need to be adaptable to reflect changes in underlying trading conditions that will impact assumptions as a result of market conditions. The accuracy will eventually degrade over time as the real-world results diverge from the model outputs due to changes in the internal and external environments.

For example, a new cheaper product enters the market and improves on the solutions offered by the current products. The demand as forecast by a model that ignores this new product will be overstated as customers looking for a solution will most likely select the cheaper and potentially better product. The real world has now taken a different direction from the demand forecasted and hence the model, product and business need to adapt to this divergence. There are of course multiple paths to take to solve this:

  • Reduce price (never a good idea as it erodes margin and is potentially the beginning of the end)
  • Innovate and develop better features or add-ons to remain competitive
  • Develop an entirely new product and abandon the existing one
  • Do nothing (still an option) but adjust demand downwards and quantify the impact
  • Offer competitors to buy your product (if you are really desperate).

Each mentioned option requires that the model is adaptable to these scenarios for the output to be relevant.

2. Consistency and Standardisation

Ensuring consistency in the structure and standardisation across models facilitates easier updates, reviews, and comparisons.

This can be particularly helpful when different people are using the model and when it comes time to change the model often months later. By using a consistent and standardised model design, those changes are a lot easier to make and specifically identify the logic and content that needs to be adjusted.

Standardised models can also be driven by adopting or embracing most of the key elements in a financial modelling standard mentioned below.

3. Continuous Monitoring and Updating

As mentioned in the first point, accuracy can only be managed and controlled with regular monitoring of real-life outcomes. These are most likely to be financial results but could also be operational results and customer satisfaction and performance.

The continuous monitoring should typically be embedded into the month-end management reporting by deploying a rolling process where actual performance is compared to forecasted results to check accuracy. This is a critical step to keep the model alive and relevant.

The size and correlation between the drivers and resultant variance between these two results (forecast vs actual) will dictate where the model needs to be adapted.? The process of updating financial models is crucial to maintain their relevance and alignment with the business's current and forecasted financial performance.

The more automated and streamlined the updating process is the better.

If you had to teach this topic in a class to school kids what key tips would you give them to focus on

DALL-E 3 sourced via Co-pilot

Teaching the concept of financial model alignment to school kids requires simplification and engagement. Here are some key tips you could focus on:

1. Use Simple Analogies

Compare financial models to something familiar, like a recipe for a meal or dessert. Just as you need the right ingredients and steps to make a delicious meal, eye-watering dessert or a fancy dish, you need accurate data to go into a clearly structured process of building the calculations and logic for a financial model.

Skip or substitute some ingredients, adjust the steps or take shortcuts and or meal is likely to come out vastly different, potentially even worse than you think. A minor alteration could have devastating effects on the taste, texture, look and possibly the smell of the food.

Alter the data and the process of building the model and equally devastating decisions could be made.?

2. Emphasize the Importance of Checking Your Work

Whether you are writing an exam or completing your homework and assuming you have the time it’s always a good thing to check your workings.

It increases your chances of getting a better result. When we are under pressure humans make mistakes and checking your workings is a good habit to get into. It will also help later in life when you have to check other people’s work.

One day if you are successful enough to lead other people, you will need to learn the skill of checking other people’s work so again checking skills is important.

The need for accuracy in models is similar to checking homework before submission. Mistakes can lead to wrong answers, just as errors in a model can lead to incorrect financial decisions.

Catch them early and it can save the day, leave them, and risk your work being downgraded, marked down or ignored.

3. Encourage Curiosity and Continuous Learning

Things move so fast today in all spheres of our lives, especially technology. Stress the importance of staying updated, much like keeping up with the latest games or gaming technology.

If you had never played “Fortnite”, “Roblox” or an EA Sports game on an X-box, PS4/5 or Nintendo Switch you would probably feel out of touch with other school kids. The importance of staying up to date ensures you feel connected and can enjoy times with your friends.

Financial models also need to be updated with the latest information, and technology adoptions to stay useful and advanced amongst other competing solutions and to meet the increasing demands of customers wanting advanced modelling solutions that can handle today’s data challenges.?

By focusing on these tips, kids can grasp the foundational concepts of financial modelling in a fun and relatable way.

What practical steps can people take now to learn more

To learn more about financial modelling, here are some practical steps that you can take.:

1. Start with the Basics

Gain a solid foundation in accounting and finance principles, including financial statements and how they connect to cash flow (cash is still king!) with key financial ratios and key performance indicators and margins.

Understanding the business terminology and how business performance is measured is essential in understanding and building financial models.

2. Excel Proficiency

Develop strong Excel skills, as it's the primary tool used for financial modelling. Learn to create formulas and use functions effectively, especially some of the latest Modern Excel formulas and functions.

You should be familiar with Power Query, Dynamic Arrays, and eventually more advanced tools like LAMBDAs.

3. Learn Financial Modelling Techniques, Data Analytics and standards / best practice

It’s important to at least gain some form of familiarity with both techniques in financial modelling as well as data analytics. The world of data analytics is coming ever so closer to the world of financial modelling, and we have to keep an open mind in these areas.

Across both domains, we should develop a robust approach, and best practice or follow some of the standards/approaches to building robust decision models (financial and data).

You don’t have to specifically follow one standard to become great at financial modelling but at least understand the core concepts they all are aligned on.

Some examples of these include.

  • Structured separation of assumptions, logic, and outputs
  • NO hardcoding inside formulas
  • Clearly define the start and end of the model
  • Create an easy-to-navigate and consistent time series and formula design i.e. never mingle time series on the same row i.e. monthly, quarterly, and annually as calculations.
  • Avoid having too many rabbit holes in your models like external links, and complex macros nobody can understand, use or fix when they break.
  • Adopt a star schema for data modelling with ideally one-to-many relationships across your financial dates calendar
  • Upstream fixing of data issues, not in DAX or MScript
  • Familiarise yourself with techniques like scenario management, sensitivity analysis, Monte Carlo simulation, regressions, discounted cash flow and numerous valuation techniques like EBITDA, revenue multiples and price to book etc.

?4. Choose the Right Training Course

Select a financial modelling course or program that aligns with your learning style and goals.

This might start with just an intermediate or advanced introduction to Excel before you do a full-blown course on building financial models from scratch. You might even want to then specialise in project finance modelling, business modelling or SAAS modelling to name a few specific ones.

5. Get qualified or certified to gain confidence and knowledge

Explore a possible qualification or certification in financial modelling like the Financial Modelling Institute. Perhaps read this previous article on financial modelling qualifications as a starting point.

6. Practice with Real-World Data

Apply what you've learned by practising with real-world examples and building your own financial models. You might even build a personal financial model on your own personal balance sheet, salary and living expenses for any scenario of your choice. Practice makes you perfect!

7. Continuous Learning

Stay updated with the latest financial modelling methods and industry changes. Commit to lifelong learning and development. Things are moving so fast, especially with the augmentation of Artificial Intelligence (AI) inside Excel and everywhere you turn. AI can help speed up the process of designing and building your financial model, hence whenever you can, make use of it.

8. Network and Connect with others

Connect with finance professionals and learn from their experiences. Sharing knowledge can provide new insights and opportunities. Consider attending the many meetups that exist around the world.

Currently, Australia hosts two of the top 5 Financial Modelling in Excel meetups across Sydney and Melbourne. The meetups are free and a great way to meet and learn from others in the industry. Get connected!

9. Get Tech Savvy, the gift that keeps giving

Get familiar with some of the latest technology and solutions both inside Excel as well as outside of it with tools like Power BI and the Power platform. Having an idea of how data is organised and how it flows into your model will always come in handy when building models. This will give you the advantage of better describing your needs to a Data Engineer if the data flows are complex.

The opportunities to automate the end-to-end process are endless. In most cases, the only limitations are our minds.

10. Get started

What are you waiting for? Start tomorrow!

By following these steps, you can build a strong foundation in financial modelling and enhance your skills over time.

Where are good places (links) to find out more on the topic?

If you are looking for places to learn more about financial modelling here is a list of useful resources

How important is this skill in the context of learning Financial Modelling?

Being an expert financial modeller means you recognise that models are not perfect and have flaws that over time need to be ironed out. In addition, a rolling operational model isn’t ever complete as the world and reality keeps evolving.

Managing ongoing alignment is therefore a critical skill in financial modelling for several reasons:

1. Ensures Model Accuracy

Regular alignment ensures that financial models reflect the current market conditions and business realities, which is essential for accurate forecasting and decision-making.

2. Supports Strategic Decision-Making

Proper alignment helps in making informed strategic decisions by ensuring that the financial models are in sync with the company's goals and strategies as well as being the blueprint print on how to execute that strategy.

The financial model is the mathematical representation of the strategy in motion and the expected outcomes from delivering that strategic vision.

3. Mitigates Risk

“Forewarned is forearmed” is a famous quote by Miguel de Cervantes' that applies when models are in play.

The model can help in identifying and mitigating risks by continuously monitoring model performance and making necessary adjustments in response to internal and external changes driven by reality.

“All models are wrong, some of useful” is a famous quote by George E Box

In essence, the skill of managing ongoing alignment is not just about maintaining models; it's about maintaining the relevance, reliability and usefulness of the financial insights they provide, which is fundamental to learning and applying financial modelling effectively. While there are finance and technical stakeholders involved in making a financial model a success, the role of the financial modeller in keeping the enthusiasm of the business is key in the journey of adopting financial modelling by a business. Hence sticking to the process and avoiding mistakes will help you establish quality outputs and outcomes while building your reputation as a dependable resource.

How does all this disruption, AI and Automation talk impact this topic?

The rise of Artificial Intelligence (AI) and Automation is significantly impacting the field of financial modelling in several ways:

1. Enhanced Predictive Capabilities

AI algorithms can analyse vast datasets to identify trends and patterns that may not be evident to human analysts. This can lead to more accurate and sophisticated predictive models.

These narrowly deep-focused models can then be incorporated to the overall business strategic model to understand the bigger picture more accurately.

2. Increased Efficiency

Automation can handle repetitive tasks within financial modelling, such as data entry and formula application, freeing up human modellers to focus on more complex and strategic aspects of model design, and interpretation and communicating those outputs to drive outcomes. With the automation of Data Pipelines, enabling seamless data flows into the financial models can drastically increase the efficiency of the models as well as increase business usage frequency, reducing the time-to-insight!?

3. Innovation in Financial Products and services

AI-driven insights can lead to the creation of new financial products and services, as well as the customisation of existing ones to better meet customer needs.

With the ease at which Large Language Models (LLMs) are now available to everyone, these innovations are at our fingertips and can be configured and implemented the way you want. Leverage!

4. Risk Management

AI can improve risk assessment by quickly processing new information and adjusting risk profiles accordingly, which is crucial for ongoing alignment in financial models and the decision-making capabilities of a business.

Overall, AI and Automation are reshaping the landscape of financial modelling, making it more dynamic, efficient, and capable of handling the complexities of today's financial environment.

What does ChatGPT think?

“What do you suggest should be the main focus after a financial model is built?”

ChatGPT

"Once a financial model has been built, the main focus should be on reviewing and testing the model to ensure its accuracy and reliability. This involves performing sensitivity analyses and stress testing to assess the impact of various scenarios and assumptions on the model outputs.

Additionally, it's important to compare the results of the model to actual historical data and industry benchmarks to validate its assumptions and ensure its usefulness. Any discrepancies should be investigated and addressed.

Once the model has been thoroughly reviewed and tested, it can be used for decision-making purposes. This may include using the model to evaluate investment opportunities, assess the financial feasibility of a project, or develop strategic plans. Ongoing monitoring and updating of the model may also be necessary to ensure its continued accuracy and relevance."

If you want to find more information on financial modelling and content visit the?Model Citizn website.

?

Dhanusha Muthukumarana

Technopreneur, Award-winning Innovator, Global CEO at POTENZA, Board Member of LAUGFS Holdings, Board Member of Kasper Global, Member of Forbes Technology Council, Ex-Microsoft, Ex-LSEG.

4 个月

Thank you Lance Rubin for the opportunity to co-author this article with you, on a timely topic. Cheers!

Carolina Lago

FP&A & Financial Modeling Specialist, Gartner Peer Ambassador

4 个月

Lance Rubin, you should work on that book right away. We all need some guidance to the galaxy! Besides a towel, of course!??

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