Building a Financial Modelling Strategy for a Business

Introduction to the co-author

Mark Vigors’ 34-plus-year career has spanned financial services and technology across a variety of major organisations such as Westpac, Telstra and Equifax.

As a General Manager and Program Director he gained deep experience running large teams delivering transformational outcomes. He now serves as the Chief Operating Officer of POTENZA, bringing a clear view of process, system and solution delivery best practices.

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

Throughout his career, Mark has focused on driving transformational technology change across a range of different clients primarily within Australia but also across other international locations including North America and Asia Pacific.

A substantial portion of these projects lean towards accounting and finance teams and their decision engineering solution that combines forecasting, budgeting and planning amongst other analytics and modelling enhancements.

Many of these enhancements are tackled following a technology diagnostic which is grounded in the client's strategy and how enabling financial modelling capabilities, linked to their strategy, is a key ingredient to the success of these projects and ensures value for clients.

It's based on this strong linkage between financial modelling and decision engineering that has seen Lance and Mark work closely together to enable clients to develop and execute their financial modelling strategies, for improved decision-making that is insightful and robust.

This is also the reason why he is passionate about this topic and helping clients with their financial modelling strategies.

Topic and context in no more than 3 sentences

To build a financial modelling strategy you have to consider these 3 key concepts:

1. Planning is essential whereas plans are useless.

If you don’t have a plan on how to develop financial modelling you will never get there. At the same time, your plan needs to be adequately flexible to deal with what is discovered on the journey and those that it impacts. Plans to develop financial modelling skills will impact the way people work and this is a key obstacle you must overcome early.

It’s likely to be a battle in the same way Eisenhower's famous quote, “In preparing for battle I have always found that plans are useless but planning is indispensable.”

2. Nothing will work unless you cover the People, Process and Technology, in that order.

Too often this order is reversed favouring a technology solution first approach for planning, forecasting, and modelling, taking priority over both the people and the process.

Unless there is clarity on what the strategy will mean and how it will impact people, the behaviours and culture won’t change. Irrespective of the solution quality, it will fail, if through no other consequence of abandonment by people. Considering what a solution will mean in terms of the people’s day-to-day, as well as their long-term career prospects and promotions, is key to their engagement.

Unless there is clarity on the process, how can a solution be designed to meet business needs? The process and the people need to be an integral part of the selection and design of the solution and not just an executive or IT lead project. Understanding the process, and its functional requirements, is a fundamental input to the selection and design of a technology solution.

Too often a top-down selection of solutions, that are simply not aligned with the bottom-up tasks on the battleground, is a perfect recipe for failure.

3. Alignment to business strategy is critical. Misalignment = missed opportunity.

The entire purpose of building a financial modelling strategy is to enable better decision-making that aligns with achieving objectives in the future when there is a lot of complexity and unknowns.

Ideally, the business plans and strategy are clearly defined because developing a financial modelling strategy that doesn’t align with the business strategy is a missed opportunity that adds greatly to the risk of failure.

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

When you went to school hopefully you played or at least attempted sport. You watched others compete in it on sports day at least. The linkages between sport and business are undeniable and if one were to explain this topic to school goers it’s a great place to start is to talk about how a team becomes successful and wins in sports. It comes down to the coaching having some core strategy.

A sporting strategy would be say choosing your mates and a few others that you knew could play the game and then putting them into positions that leverage their strengths and goals in what they want to achieve. This way you can get the best out of them for themselves and the team as well.

Financial modelling strategies are much the same and making sure that you build a cohesive team around the financial model. This is not a one-person game. The road to building a successful financial modelling capability lies in all players in the data and tech ecosystem. Let's put it simply in a table:

Let’s get more into the business game, shall we?

A business strategy is a plan for how a company will achieve its goals and objectives. It outlines the steps and actions a company will take to reach its desired outcomes. Simply put, it's a plan for success; like your plans to win the next soccer, golf, cricket, rugby or netball game.

With no strategy, your chances of success are greatly reduced.

Design a strategy and get alignment with teammates (colleagues) and the coach (management) and your chances increase.

A business strategy typically includes the following elements:

● Vision and mission

● Market and industry analysis

● Competitive analysis

● Customer segmentation

● Products or services offered

● Marketing and sales approach

● Financial projections

● Organizational structure

● Implementation plan

By having a clear business strategy in place, a company can focus its efforts and resources towards reaching its desired outcome.

Companies become focused on developing a financial modelling strategy as they recognise the benefits of making better decisions with the data they have. This data is often scattered amongst a sea of unstructured and manually managed spreadsheets. The companies recognize that structuring the data, coupled with financial modelling skills, is the secret to success in this domain.

What practical steps can people take to learn more?

Combining strategy and financial modelling design concepts is not simple.

A financial modelling strategy is becoming an increasingly important business capability as the world of data and decision-making becomes more complex and competitive.

Those who can harness the value and insights in their data through skills like financial modelling and data analytics will continue to outperform their competitors who don’t.

It’s best to break this down into objectives, considerations, and key results (call it OCKR).

Objectives

● Clearly defined purpose and goal of what success looks like and how you know you are closer or further away. For example, we want to be able to stress test key business drivers and test the results of those scenarios as soon as possible post their implementation. SMART (Specific, Measurable, Achievable, Relevant, Time-bound) objectives and goals are best to ensure ambiguity is reduced.

● Alignment amongst all key executives and staff. Without alignment, there is a risk that efforts will be made in the wrong areas or in conflict with the defined purpose. To gain alignment a roadmap of change will be helpful to provide insight as to how the business will benefit from this capability over time.

● Narrow context, then expanding is vital to ensure the ocean isn’t boiled too early. Financial modelling, and modelling in general, is such a broad capability that can cover almost all areas of the business. There is a risk that if the scope and context aren’t initially focused small wins will evaporate and be overruled by wanting to do too much. A great place to start is the regular annual budget process and then enable better scenario-based decision-making before expanding to project, investment or business modelling.

Considerations

● Skills that are required to be developed, or acquired, to achieve the objectives. This may range from project management skills, technical skills and of course people and change skills.

● Tech stack that is required and has been linked to the objectives listed above. The tech stack should be as flexible as possible whilst also fit for purpose and controllable to ensure offline, and unstructured, modelling doesn’t remain in wide use. There will be a natural tension between flexibility and control and it’s finding that happy medium that meets business needs is critical. The danger here is being sold the golden solution by a vendor only to realise too far down the rabbit hole that it’s never going to meet the requirements, or worse, is rejected by the user community. This is a common pitfall of many tech projects.

● Investment that may be required to achieve the objectives what returns would be expected from that investment and over what time. This is often one of the most controversial considerations, whilst also being the most important. If you can’t get a return for your efforts, why do it? If possible, test with a small investment and expand for a larger step change.

● Commitment of people who believe in the benefits and are passionate about driving these throughout the organisation. Ideally, this should include cross business/functional personnel with a core group of people focused on the success of enabling this capability.

● Clarity in the process for those both executing, as well as those engaged with operationalising and embedding, the strategic plan. This will require ongoing monitoring and adjustment both in the initial and subsequent embedding phases, to ensure the implementation remains aligned with the business demands and keeps pace with changes in conditions.

Key Results

Whilst the specific key results will differ significantly between organisations, the following are some examples of useful results to achieve in terms of capability and how you might benchmark your organisation against achieving these results.

● Highly automated and intelligent performance tracking:

○ Completing month-end close with detailed analysis of current month and year-to-date performance against the approved budget, long-term plan and prior periods.

○ Based lined scenarios and sensitivities run to predict the performance for the remainder of the year with root cause analysis of why the organisation is behind or ahead. This is aligned to core business drivers, so people can make informed decisions and take corrective action.

● Measurement of key projects with visibility on progress and Red, Amber, and Green status with projections of delivering on agreed outcomes. Internal Rate of Return/Net Present Value, or other financial and operational benefits, are measured.

● Rolling and integrated finance, business, and operational insights that price visibility to all key management and they have full visibility of their key metrics and goals. At any given month staff should have no misunderstanding as to how they are performing relative to their scorecards and operational goals (this will vary based on role, but reporting is personalized to them)

● Automated commentary and democratization of insights and self-serve business intelligence and reporting. Getting data visually into the right hands at the right time.

● Unit economics modelling that visually displays the value driver tree that gives non-financial leaders clarity on value creation and distraction on an absolute and percentage basis.

● Cash flow, equity and debt modelling that explores how the organizations most scarce resource (cash) is managed and maximized for the benefit of shareholders, employees, and other key stakeholders eg banks or funding providers.

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

There is not a lot of information available on this specific topic, which is one of the reasons why Mark and Lance decided to write a blog on the topic.

There are of course lots of sources on SMART, OKRs etc but this is specifically focused on financial modelling.

There are certainly a lot of links on the technical skills and technology on financial modelling and data-driven decision making but very little in terms of how you build a capability, team and culture focused on this core skill throughout the organisation to maximise its value.

If you want to find out more about how this is achieved or are interested in how you could develop your financial modelling strategy, stay tuned to these articles and other insights.

Alternatively, you can join the upcoming Financial Modelling in Excel meetup to explore this further.

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

It’s becoming increasingly important to understand more than just the technical skills of building models but what it means to develop teams and the capability to harness it for any business.

Being the lone modeller can be a challenge when business decisions are made across many companies with limited or no structure in considering scenarios and options relative to that decision.

To elevate the value as a financial modeller outside the model can be empowering and rewarding as you enhance and develop a broader awareness of this vital business capability.

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

The exciting developments of large language models, bots, automation and other AI technologies will change the way we think about decision-making and modelling but in general, this won’t solve the higher-order strategic priorities beyond just a short-term task.

AI will help in ways previously not thought possible for idea generation, creativity-accelerated training rapid prototyping and technical solutions.

AI won’t understand your people, their fears and concerns and the culture needed to evolve as new tools and skills change the way they work.

AI will help with some, but not all obstacles, especially when it comes to the biggest obstacle being teams’ willingness to adopt change.

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