Your Guide to Manufacturing Financial Modeling

5 Min Read

Now more than ever, manufacturers need to understand the ins and outs of their finances. 


Sudden shifts in customer behavior could affect product demand. Supply chain disruptions could lead to spikes in costs for raw materials. These situations and more can impact your bottom line. Yet understanding the extent of these impacts is what separates financially sound manufacturers from the rest.


Enter financial modeling—a tool used to visualize future financial performance. In this guide, we’ll cover the fundamentals of manufacturing financial modeling so your team can implement this essential process at your company. 


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Understanding financial modeling

For manufacturers, modeling can be used to forecast inventory production, expected cost of goods sold, revenue based on pricing, and more.

For example, let’s say a manufacturer of men’s jeans wants to forecast their profits for their Q4, which coincides with the holiday season. The financial model will consist of three components:


  1. Historical Data

  2. Formulas

  3. Assumptions (variables)


The first two components are pretty straightforward. Our manufacturer could use sales history from the previous five Q4s to forecast the sales and revenue for this upcoming Q4.


But what about assumptions? Assumptions are the variables that models use to predict different outcomes. Variables can be industry benchmarks, adjusted historical data, or other information that might influence future performance.


Going back to our jeans manufacturer, leadership might want to understand how Q4 could play out assuming a twenty percent drop in sales. Going one step further, they could also see how a price increase might help make up for the sales drop.


This brings us to another important point: one financial model should never be enough. Manufacturers need to test varying assumptions in order to gain a more complete view of their financial situations. Without these different assumptions, all we would see is an average of past performance (which isn’t helpful, since business environments are always in flux).


Simply put, assumptions are the foundation of any financial model. They need to be as accurate as possible for models to be useful. In a normal business environment, let alone our COVID-19 world, this is hard to do.


Yet with the right tools and some savvy thinking, it’s possible. This starts with debunking a common conception with financial modeling.

Financial modeling is for planning, not predicting

Financial models are made to be actionable. They help leadership understand possible future scenarios and plan accordingly. For manufacturers, planning objectives can fall into three categories:


  1. Planning Push Processes, including inbound logistics, manufacturing, material planning, and procurement. Financial modeling can help plan out inventory levels and optimize warehouse space.

  2. Planning Pull Processes, including order management, outbound logistics, and packaging. Financial modeling can help optimize distribution to end customers.

  3. Strategic Planning, such as capital planning and plant improvements. Financial modeling can help understand cash flows, future margins, expenses, and other factors needed for decision making.

Let’s say our jeans manufacturer is considering building another factory to keep up with growing demand. Some scenarios leadership would want to review include:


  • Baseline: A scenario that will be used as a comparison to more unlikely or extreme scenarios. Baseline projections typically use previous sales history and include predictable assumptions (e.g., continuous trends). For our company, let’s say sales are expected to increase at a steady 3 percent year-over-year.
  • Optimistic Scenarios: What if sales do much better than expected? Our manufacturer may want to look at how additional revenue may change the financial structure of their investment.
  • Pessimistic Scenarios: What if sales hold flat or decline? Our manufacturer would want to know the extent of the financial burden of a new factory.

Financial models are holistic

While financial models are made with numbers, they’re used by people to make decisions. They help leadership visualize the outcomes of different pricing options. They help explain how a large capital investment could provide long-term benefits.


In other words, financial models should be used to help tell a story. Decisions aren't made in isolation, and a narrative can help leadership understand the broader impacts of their financial decisions. It's through this combination of context and numbers that the best decisions are made.

Tools for financial modeling

For too long, the go-to tool for financial modeling has been the spreadsheet. Veteran financial professionals are probably all too eager to speak about their drawbacks, from building financial statements from scratch to quality checking for formula errors.


These problems are only compounded when it comes to financial modeling. Analysts have to create copy after copy of spreadsheets for different assumptions. This can quickly lead to confusion between the spreadsheets—a worst-case scenario when relying on them to make top-level financial decisions. 


Today, there are manufacturing financial modeling tools like Synario that remove much of the manual work out of financial modeling. Data imports are used to populate pre-built templates (e.g., financial statements) and allow for easy manipulation to test different scenarios. Synario is also cloud-based, allowing anyone on your team to access models anywhere.

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Financial modeling best practices

Don’t forget about the present

Manufacturers should always start with understanding the present. Financial models can be used to understand:


  • Whether their business is on a current trajectory to financial success (are margins large enough to sustain their business?)
  • What challenges their business is facing (is inventory turnover lower than expected?)
  • What opportunities are currently available (do current sales justify investing in more production space?)
  • Their “baseline” scenario, which can be used for comparison

Consider the timeline

Before building financial models, it’s important to consider the timeline you’re planning for.


As a rule of thumb, the longer the time period, the less reliable the forecast due to the likelihood of unforeseen variables. However, it’s possible to account for some changes with some reliability. These include:


  • Seasonality: Manufacturers likely have predictable fluctuations in production year after year.
  • Cyclical Changes: These are fluctuations that happen over two years or more. Economic and political shifts are typical causes (e.g., small recessions).
  • Continuous Trends: Some industries may see a steady increase or decrease in sales that can be used to forecast future years. For example, the video game industry has seen a 9 percent year-over-year increase in revenue, a trend that’s expected to hold for the next several years.

Implement rolling financial modeling

Annual financial modeling forecasts are no longer enough for manufacturers. Rolling financial modeling means revisiting and revising models several times a year to account for new variables that impact operations.


Today, this flexibility can’t be underestimated. What if our jeans manufacturer needs to implement new regulations to ensure employee safety? What if a supplier is suddenly unable to provide raw materials for a month?


These fluctuations are just as important for long-term decision making. Quarterly shifts in revenue may impact the viability and practicality of new warehouses or product lines.

Focus on the metrics that matter

Financial modeling should always come back to the metrics that matter for decision-making. For easy reference, we’ve outlined the financial metrics that matter the most for manufacturers.

Inventory

Manufacturers are always holding onto raw materials, good in-process, and finished products. Forecasting expected inventory levels of each is necessary for understanding current warehouse space and potential purchases of future space.


Related metrics

  • Inventory Turnover
  • Total Manufacturing Costs Per Unit

Sales and purchases

Since manufacturers tend to sell to distributors and wholesalers, most payments are made through credit rather than cash. Similarly, manufacturers rely on credit when purchasing raw materials from suppliers. Forecasting accounts receivable is vital to understanding cash flow and scheduling out payments.


Related metrics

  • Accounts receivable days
  • Accounts payable days
  • Other liability days

Capital investment

Factories, machinery, warehouses, and more place a high burden of capital expenses on manufacturers. This often leads to a reliance on debt and equity financing. Accurate models can help manufacturers understand changes in their financial structure and determine their ability for future financing.


Related metrics

  • Maintenance Costs to Total Expenses
  • Return on Net Assets

Cost structure

High fixed costs also mean that manufacturers are seeing razor-thin margins. This makes manufacturers especially sensitive to even modest increases in raw material costs or dips in sales. Without accurate forecasting, manufacturers may be overestimating revenue and underestimating their break-even points.


Related metrics

  • Break-even Point
  • Unit Contribution Margin Ratio

Gross margin

Even slight changes in sales or costs can result in significant changes to a manufacturer’s gross margin. Accurate forecasting models can give a range of potential gross margin outcomes and better prepare leadership for what could come.

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Making the most of manufacturing financial modeling

Leadership relies on financial models for everything from deciding future capital investment to understanding seasonal fluctuations in sales. Yet assumptions can change in an instant. Financial modeling can no longer be an annual exercise. Manufacturers need to incorporate this into their regular financial activities.


That’s why flexible financial modeling tools are so important. Finance teams can’t waste time creating iterations of spreadsheets. They need tools that quickly create scenarios based on new information. They need tools that clearly display information for decision-makers.


But regardless of how manufacturers go about financial modeling, just getting started is enough. We’re in an unpredictable environment, even a glimpse into that unpredictability will have lasting impacts for your business.