Jaksa Magdalenic’s Post

When we build financial models 📈, there are three key properties that we should try to achieve. 👇 The first two, 𝗙𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆 and 𝗔𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 are often what modellers put the most effort into: • 🤸 𝗙𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆 - allowing the user to see best and worst possible outcomes through assumptions that can be easily manipulated to create different scenarios and sensitivities • ✂️ 𝗔𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 - preparing the model in such a way that it can be updated or modified in future, to track outcomes or incorporate new revenue/cost items But these two should never come at the cost of the most important trait: 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗮𝗯𝗶𝗹𝗶𝘁𝘆 💡. In fact, by making your model 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗮𝗯𝗹𝗲, you will probably go a long way to achieving the first two properties! But what does understandability mean in the context of a model, and why is it so important? The first thing to realise is that a financial model is all about 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻. Ultimately when we build any model, we are trying to 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝗮𝗻 𝗶𝗻𝗳𝗼𝗿𝗺𝗲𝗱 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻, whether that's investigating the size of a market, assessing the return of a new initiative, or preparing a quote in a bid process. In most cases, the people ultimately making that business decision aren’t the same people building the model. So our model must communicate clearly the answer, yes, but also 𝗵𝗼𝘄 that answer was arrived at. And we’re not just communicating with the 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗲𝗿. We’re also communicating with: • Our 𝗺𝗮𝗻𝗮𝗴𝗲𝗿, if we have one, who needs to know what we’ve done, and how (and how well!) we’ve done it. • A 𝗳𝘂𝘁𝘂𝗿𝗲 𝗰𝗼𝗹𝗹𝗲𝗮𝗴𝘂𝗲 or 𝗰𝗹𝗶𝗲𝗻𝘁 of ours who needs to edit and maintain the model • 𝗢𝘂𝗿𝘀𝗲𝗹𝘃𝗲𝘀 - how often have you come back to a model that you haven’t looked at for a while and completely forgotten how part of it works?! Creating an 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗮𝗯𝗹𝗲 𝗺𝗼𝗱𝗲𝗹 makes that communication so much easier, with all parties. It’s not easy though, even for experienced modellers, so having a set of guidelines (𝘰𝘳 𝘦𝘷𝘦𝘯, 𝘦𝘳, "𝘳𝘶𝘭𝘦𝘴") to work with is super-important. I'll be posting some of mine here in future, but feel free to share yours in the comments!

FINANCIAL MODELING: DATA ANALYSIS AND MATHEMATICAL MODELS TO HELP COMPANIES PREDICT THE FUTURE AND MAKE DECISIONS. Financial modeling is the process of using mathematical models to analyze and predict a company’s financial data. It plays an important role in helping companies assess their financial health and lay the groundwork for future business decisions. In this article, we’ll cover the concept, purpose, key steps, and importance of financial modeling.

The Power of Financial Models

Development of Financial Model

I often imagine what the world would look like without numbers. Without financial forecasts, risk assessments or data-driven decisions. That is just a chaotic landscape where businesses stumble blindly. That's where the power of financial modeling and data comes into play. It's like having a crystal ball, but instead of predicting the future, it helps you understand the present and shape the future. By constructing intricate models, we can simulate various scenarios, analyze trends, and make informed choices. Think of it as building a bridge. Before you lay a single brick, you need to understand the terrain, the weight it will bear, and the potential risks. Financial modeling is the blueprint that ensures the bridge stands strong and supports your business goals. With data as our foundation, we can uncover hidden patterns, identify opportunities, and mitigate risks. It's like sifting through a pile of gold dust, finding the nuggets that will make your business shine. So, the next time you encounter a complex financial challenge, remember the power of financial modeling and data. It's not just about numbers; it's about building a stronger, more resilient future

I am 100% certain my financial model will be wrong (but it can still be useful with this 👇) It needs to be 𝙙𝙚𝙛𝙚𝙣𝙨𝙞𝙗𝙡𝙚. Let's be real -- no one knows the future. At all. In fact, it's laughable to even entertain such a notion. But -- we can make reasonable and thoughtful guesses about what 𝘮𝘪𝘨𝘩𝘵 happen. (Let's call them "assumptions" to make ourselves feel better, but at the end of the day it's just "educated guesses") Whether or not these assumptions are reasonable all boils down to 𝙙𝙚𝙛𝙚𝙣𝙨𝙞𝙗𝙞𝙡𝙞𝙩𝙮. ~~~ 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 𝟭: CEO: "We've grown 5% the last couple years, but this year we expect to grow 40% because our marketing team is going to churn out a bunch of viral content." Me: ".....k" ~~~ 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 𝟮: CEO: "We've grown 5% the last couple years and are confident our existing customers will renew along with a strong pipeline of new contracts we expect to close. I think we'll grow 8% this year based on the data we've compiled and after talking with the team." Me: "Sounds reasonable." ~~~ 𝗪𝗵𝗮𝘁 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗛𝗮𝗽𝗽𝗲𝗻𝗲𝗱: It ended up being a slower year and we didn't capture the pipeline we thought we would. As an investor or member of the C-Suite, am I disappointed? Sure. But am I 𝘧𝘳𝘶𝘴𝘵𝘳𝘢𝘵𝘦𝘥 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦 𝘵𝘦𝘢𝘮 because their model was "wrong" ? No. (at least in Example 2) -- because the assumption was 𝙧𝙚𝙖𝙨𝙤𝙣𝙖𝙗𝙡𝙚 and 𝙙𝙚𝙛𝙚𝙣𝙨𝙞𝙗𝙡𝙚. Example 1 would be a different story. The entire premise was absurd. ~~~ 𝗪𝗿𝗶𝘁𝗲 𝗜𝘁 𝗗𝗼𝘄𝗻 The best way to make your model defensible? Write. It. Down. Say "why" you've made the assumptions you have, and provide some context for each. That is 𝙙𝙚𝙛𝙚𝙣𝙨𝙞𝙗𝙡𝙚 and 𝙧𝙚𝙖𝙨𝙤𝙣𝙖𝙗𝙡𝙚. It doesn't need to be anything fancy. Usually just another tab in your model. (if you want to be fancy you can make some of it formula-driven, but that's not the point here) Write it down. Check it. Print it. Explain it to your team. That's a good model. That's 𝙙𝙚𝙛𝙚𝙣𝙨𝙞𝙗𝙡𝙚. ~~~ 👋 Hey, I'm Chris Reilly, and I post about Financial Modeling in the middle-market. 𝘱.𝘴. making this assumption page is one of the final lessons in my Financial Modeling Education program. Check it out here 👉 https://lnkd.in/eG_uVhsE

I am 100% certain my financial model will be wrong (but it can still be useful with this 👇) It needs to be 𝙙𝙚𝙛𝙚𝙣𝙨𝙞𝙗𝙡𝙚. Let's be real -- no one knows the future. At all. In fact, it's laughable to even entertain such a notion. But -- we can make reasonable and thoughtful guesses about what 𝘮𝘪𝘨𝘩𝘵 happen. (Let's call them "assumptions" to make ourselves feel better, but at the end of the day it's just "educated guesses") Whether or not these assumptions are reasonable all boils down to 𝙙𝙚𝙛𝙚𝙣𝙨𝙞𝙗𝙞𝙡𝙞𝙩𝙮. ~~~ 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 𝟭: CEO: "We've grown 5% the last couple years, but this year we expect to grow 40% because our marketing team is going to churn out a bunch of viral content." Me: ".....k" ~~~ 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 𝟮: CEO: "We've grown 5% the last couple years and are confident our existing customers will renew along with a strong pipeline of new contracts we expect to close. I think we'll grow 8% this year based on the data we've compiled and after talking with the team." Me: "Sounds reasonable." ~~~ 𝗪𝗵𝗮𝘁 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗛𝗮𝗽𝗽𝗲𝗻𝗲𝗱: It ended up being a slower year and we didn't capture the pipeline we thought we would. As an investor or member of the C-Suite, am I disappointed? Sure. But am I 𝘧𝘳𝘶𝘴𝘵𝘳𝘢𝘵𝘦𝘥 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦 𝘵𝘦𝘢𝘮 because their model was "wrong" ? No. (at least in Example 2) -- because the assumption was 𝙧𝙚𝙖𝙨𝙤𝙣𝙖𝙗𝙡𝙚 and 𝙙𝙚𝙛𝙚𝙣𝙨𝙞𝙗𝙡𝙚. Example 1 would be a different story. The entire premise was absurd. ~~~ 𝗪𝗿𝗶𝘁𝗲 𝗜𝘁 𝗗𝗼𝘄𝗻 The best way to make your model defensible? Write. It. Down. Say "why" you've made the assumptions you have, and provide some context for each. That is 𝙙𝙚𝙛𝙚𝙣𝙨𝙞𝙗𝙡𝙚 and 𝙧𝙚𝙖𝙨𝙤𝙣𝙖𝙗𝙡𝙚. It doesn't need to be anything fancy. Usually just another tab in your model. (if you want to be fancy you can make some of it formula-driven, but that's not the point here) Write it down. Check it. Print it. Explain it to your team. That's a good model. That's 𝙙𝙚𝙛𝙚𝙣𝙨𝙞𝙗𝙡𝙚. ~~~ 👋 Hey, I'm Chris Reilly, and I post about Financial Modeling in the middle-market. 𝘱.𝘴. making this assumption page is one of the final lessons in my Financial Modeling Education program. Check it out here 👉 https://lnkd.in/eZC9jjpa

𝐂𝐨𝐦𝐦𝐨𝐧 𝐅𝐢𝐧𝐚𝐧𝐜𝐢𝐚𝐥 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠 𝐌𝐢𝐬𝐭𝐚𝐤𝐞𝐬 & 𝐇𝐨𝐰 𝐭𝐨 𝐀𝐯𝐨𝐢𝐝 𝐓𝐡𝐞𝐦: Avoiding mistakes in financial modeling is essential to maintaining the integrity and precision of your models. 𝐇𝐞𝐫𝐞’𝐬 𝐡𝐨𝐰 𝐭𝐨 𝐚𝐝𝐝𝐫𝐞𝐬𝐬 𝐭𝐡𝐞 𝐦𝐨𝐬𝐭 𝐜𝐨𝐦𝐦𝐨𝐧 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬: ➤ 𝐇𝐚𝐫𝐝𝐜𝐨𝐝𝐢𝐧𝐠 𝐕𝐚𝐥𝐮𝐞𝐬 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯: Use cell references for numbers in formulas to make models more dynamic and easier to update. ➤ 𝐍𝐨𝐭 𝐒𝐭𝐫𝐞𝐬𝐬-𝐓𝐞𝐬𝐭𝐢𝐧𝐠 𝐌𝐨𝐝𝐞𝐥𝐬 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯:  Run sensitivity analyses with different scenarios to test your model’s resilience. ➤ 𝐔𝐧𝐫𝐞𝐚𝐥𝐢𝐬𝐭𝐢𝐜 𝐀𝐬𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧𝐬 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯:  Base assumptions on historical data or industry benchmarks to keep them realistic. ➤ 𝐂𝐢𝐫𝐜𝐮𝐥𝐚𝐫 𝐑𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞𝐬 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯: Avoid or carefully manage circular references to prevent model crashes. ➤ 𝐈𝐧𝐜𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐭 𝐅𝐨𝐫𝐦𝐚𝐭𝐭𝐢𝐧𝐠 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯: Maintain consistent units (e.g., percentages vs. dollars) and use clear formatting. ➤ 𝐈𝐠𝐧𝐨𝐫𝐢𝐧𝐠 𝐓𝐢𝐦𝐞 𝐋𝐚𝐠𝐬 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯: Account for cash flow timing differences to improve forecasting accuracy. ➤ 𝐎𝐯𝐞𝐫𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐈𝐧𝐭𝐞𝐫𝐞𝐬𝐭 𝐚𝐧𝐝 𝐈𝐧𝐟𝐥𝐚𝐭𝐢𝐨𝐧 𝐑𝐚𝐭𝐞𝐬 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯: Include discount rates and inflation to make long-term projections more accurate. 𝐌𝐢𝐬𝐮𝐬𝐢𝐧𝐠 𝐅𝐢𝐧𝐚𝐧𝐜𝐢𝐚𝐥 𝐑𝐚𝐭𝐢𝐨𝐬 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯: Correctly calculate ratios and interpret them in the context of industry standards. ➤ 𝐎𝐯𝐞𝐫-𝐂𝐨𝐦𝐩𝐥𝐞𝐱 𝐌𝐨𝐝𝐞𝐥𝐬 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯: Keep models simple where possible, focusing on accuracy over complexity. ➤ 𝐅𝐚𝐢𝐥𝐢𝐧𝐠 𝐭𝐨 𝐔𝐩𝐝𝐚𝐭𝐞 𝐌𝐨𝐝𝐞𝐥𝐬 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯: Regularly update models with new data and assumptions to maintain relevance. 𝐏𝐫𝐨 𝐓𝐢𝐩: Regular model audits can help catch errors before they cause problems. 𝐏𝐒:  What’s your process for stress-testing a financial model, and how do you ensure your assumptions are sound?

What is the key role of the financial model in beginning a business, especially industrial sector? Does the deep financial analysis have a positive effect or a negative one?  Financial Modeling is time-consuming. Since modeling depends on the analysis of data, the accuracy of data impacts the results. Incomplete or even minor flaws in the data can result in major impacts on the outcomes. Especially in the industry sector. Industrial businesses don't have stable data in the beginning. After starting the production line it is possible to see the full picture.

Model calculations look "frozen"? Here's how to fix it 👇 ~~~ 📌𝗙𝗿𝗲𝗲 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲: Circularity is often part of LBO Modeling. Here's a starter guide 👉 https://lnkd.in/eYE3vgR4 ~~~ 𝗪𝗵𝗮𝘁'𝘀 𝗚𝗼𝗶𝗻𝗴 𝗢𝗻? First off, this is most likely an unintended circular reference. This can happen when you have Iterative Calculations turned on (and perhaps forgot you did so...). (Excel won't notify you about new circular references because Iterative Calculations are designed to handle them) 𝗧𝗵𝗲 𝗙𝗶𝘅 1. Turn 𝙤𝙛𝙛 Iterative Calculations (File > Options > Formulas > check box in upper-right corner) 2. Find the circular reference and "delete" it (just punch in a zero on the circular cells until you can find the broken formula) This may solve everything. Or... 3. Add a circularity breaker (only do this if the circularity is intended, like for Interest Expense) You can use a formula like this: = if ( Circ_Break="ON", 0 , [regular formula]) "Circ_Break" is a named range in your model, usually built with data validation to be an ON/OFF list. The circularity gets "broken" when the formula is temporarily set to 0. Then, you can toggle the breaker back OFF again, and the formula should resume as usual. 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 I generally advise against circularity unless it's in a debt-heavy FP&A/LBO Model. In this scenario, you're trying to quickly pay down debt and need a precise interest calculation. Otherwise, try to avoid circularity if you can. Hope this helps 🙂. ~~~ 👋 Hey, I'm Chris Reilly. 🛑 Stop burning out nights and weekends at the office—I help middle-market finance professionals master real-world financial modeling in one week. 🌐 Click "Visit my website" for more information.