June 12, 2017
I have observed often that students (and even professionals) get confused with Financial Modelling and Financial Forecasting. These two terms are often used interchangeably as well (mostly in a wrong context). These are neither exactly the same thing nor they are two disjoint sets. Let’s try to understand these concepts with the help of an example.
Imagine that you are working as a Credit Risk Officer in a bank. The Rolling Motors, a car manufacturing company, is one of the bank’s existing corporate clients. The company already has taken two loan facilities from the bank with which they have set-up two car manufacturing units, one in Pune and another one in Chennai. Now the company wants to set-up another car manufacturing unit in Thane, Mumbai and has approached the bank for a third loan facility. You, as the credit officer, will have to evaluate this proposal and take a decision if the bank wants to extend the third loan facility to the company.
Basically, there would be two parts you would have to evaluate. In the first part [part-1], you would like to understand how well the Rolling Motors Company has been performing till now and their conduct of the existing two loan accounts. In the second part [part-2], you would try to assess if the proposed third plant would make sense for the company to set-up and if it would make sense for the bank to extend the third loan facility.
For part-1, you need to take their historical financial numbers and put in a spreadsheet in a structured format. You would like to understand the company’s sales growth YoY, improvement in gross profit margin over last few years, the major cost heads such as raw material, labour cost, plant maintenance cost and if these cost items as a percentage of revenue have remain within an acceptable level for last few years, EBITDA margin, net cash flow, current ratio movement, working-capital requirement, debt servicing etc. This part is known as the Historical Financial Modelling which is used to assess a company’s current state of affairs and how it has performed over last few years.
As regard to part-2, you’ll have to understand the future benefit to the company by setting-up the third manufacturing plant. To assess the future benefit, we first need to start with forecasting car demand in the market for next few years to see if there would be consumer appetite in future to buy the type of cars that the Rolling Motors would manufacture from the third plant. Based on this demand forecast, you can estimate the sales the third plant can possibly generate for the company. There would be other things to consider here as well – such as the projected market share of Rolling Motors, the future selling price of a car, any regulatory change that can impact the car sales (eg. BS-IV emission standard) etc. When you have a realistic estimate of the revenue, you can gradually forecast the other line items such as raw material cost, labour cost etc. This would help you to prepare the estimated cash-flow that the third plant can generate in next few years and if that would be sufficient to meet the debt repayment obligation for the third loan facility. This part is known as the Financial Forecasting Modelling.
In this context, Financial Modelling primarily comprises of two parts – historical performance analysis and future performance prediction i.e. Forecasting. Therefore, Financial Modelling and Financial Forecasting are not exactly two different things, rather Financial Forecasting is a subset of the holistic Financial Modelling exercise.
Depending on situations, there could be different types of parameters that one need to forecast in the context of financial modelling, such as demand forecasting, sales forecasting, unit price forecasting, raw material price forecasting etc. We can employ qualitative or quantitative or a combination of both methods as deemed suitable for a case.
Qualitative forecasting methods employs surveys and depends heavily on viewpoints of experts in a particular field. This method is particularly useful to predict the short-and-medium trends, but has limitations of biasness over quantitative method of forecasting.
Quantitative forecasting methods uses data from the past, evaluate causal relationships among parameters to predict the future numbers.
Each of these methods requires separate discussion for detail understanding. I’ll take up each of these methods in my future articles.
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