We recently sat down with one of our Regional Managers to discuss 5 keys to improving your company’s value and critical considerations for maximizing business valuation. Keep reading to learn how modeling and financial analysis reveal levers you can pull to affect business results and improve your company’s value in the short and long-term. We highlight the main parts to our discussion below. If you’d like to hear the full discussion in one video, click here.
We've determined in conversations that the five keys to improving enterprise value, and thus the overall financial health of the company in long term and short term plans are:
- Assets in Place, which refers to getting the most out of the existing resources the company has.
- Expected Growth, which is a focus on top-line, either through increasing scale or scope.
- Length of High-growth Period, which is management's idea of when to accelerate, and when to hit the brakes.
- Returns, which is a focus on margin, and sometimes even talking about the retention of earnings within the company at the end of each period.
- Cost of Financing, which is where a bank comes in to give hands-on help with the problem solving. This can refer to the tenor of financing, to make sure that it finances something on terms that are appropriate for what is being financed, and that what is being financed is accretive to the company, and capable of paying itself back, capital structuring, and current versus long-term financing.
Conceptually, commercial banking relationships have largely become one-sided in the last few decades. Any lender can analyze the company's financial statements, then determine the likelihood of repayment of a loan, but that isn't necessarily conducive to the success of the company itself, it's just something done in favor of the bank.
There are three commonly asked questions that business owners and operators have. We believe that by offering another set of eyes to analyze how the company is doing, and how to best position it going forward, we can overcome that one-sided concept and serve as we should – as a valued partner and stakeholder in the success of our clients. So our answer to these three questions is, what we've developed Horizon Analytics to address.
It's probably not news to anyone that financial modeling is important to the success of a company, however, surveys show that it's not being effectively executed at middle-market companies.
We found that over half of companies only attempt forecast or modeled outcomes without detail, or based on industry norms from management's experience. The other 40% or so who engage with outside consultants, or have in-house financial planning and analysis capability, tend to absorb material expenses associated with that.
So in our previous slide only about 12 respondents felt highly confident in their use of financial modeling, and key barriers to improvement are noted here. Specifically what data to use, what to do with it, and how to interpret results.
That's where we come in. Horizon Analytics is something that we have developed as a tool to gather data from your financial statements, as well as the cache of other economic data. It generates the custom financial model and forecast of the company, and allows us to test all kinds of variables. Results are straightforward, easy to interpret, and can be highly customized. We can generate all of the standard key performance indicators, or KPIs that any company may want to watch, as well as what we consider the key KPI, which is estimated enterprise value.
We’ll be taking you through some sample results for our concept company, Skyline Engineering. Skyline is experiencing aggressive sales growth, and they have provided us two years of financial statements, and year to date. Basically that's all we need to get started, so it's not the full level of burden associated with applying for a loan, it's just some basic financial information to put some numbers together. After working up our analysis based on provided company financial statements, we'll meet and discuss the company, its place in the economy and its industry, our forecast, and a variety of KPI outcomes, including enterprise value from testing a few sample scenarios, which we'll go through.
We like to start with a peer comparison. Private companies by nature have difficulty gathering information on how their private peers are doing because this information is not public. Even with highly experienced management team seeped in their industry, changes to rules of thumb are often tough to follow. We work with a number of data sources to provide industry scorecards.. In this case, we compared Skyline to its 2019 industry average. A key takeaway here is that Skyline's gross margin is about 20% weaker than its competitors. And a contributor to that, could be the cost associated with about 50% slower collections of its invoices, compared to the competitors. Examples like this point to strengths that management can decide to emphasize, and weak points that management can decide how to improve.
We start our model by setting a conservative starting point or a Base Case. Based on the historical financial statements provided, we set assumptions that generate a full five-year set of forecasted financial statements – balance sheet income statement and cash flow statement, as well as all associated KPIs and ratios. In Skyline Engineering’s case we included management's projected 24% current year revenue increase due to new contracted business, and then we kept sales growth to industry projections for succeeding years at 4%. We kept margins and a conversion of assets aligned with historical figures, except for slight market increases to operating expenses over time to simulate inflation. We also included a planned uptick in CapEx investment for the current year, also in line with what management plans to do. So with these variables, the estimated enterprise value of the company or the key KPI came in at $20.7 million.
In the second case (Gross Margin Improvement), we simulate what the effect of gross margin improvement would do to Skyline Engineering’s overall performance and estimated value. We improve gross margin, to the researched industry norm of 37%, and leave everything else as it is in the base case. With this one change, enterprise value improves dramatically to $34.2 million with unchanged sales levels.
Skyline’s Management let us know that they forecast more aggressive revenue growth after 2020 than the 4% industry standard stated in the Base Case scenario. We want to show that we can listen to Clients and include different scenarios in this simulation. In this scenario (AR Days/Sales Growth), we test higher sales growth and faster collections. We increase sales at 10% annually to show outperformance of industry forecasts and winning of market share from competitors. We also decrease AR collection times from 70 days to 55 days, which doesn't show up on this summary tab, but in the detail of the model we share with the company we can clearly show where we've done that.
Both aggressive sales growth and collection speed, as any business operator knows require a fair amount of hustle and probably some investment. In this case that hustle would pay off and generate positive results for the company, but not near the level of impact that the Gross Margin Improvement case showed. The resulting enterprise value came in at 3.13 million or about $3 million less than keeping sales growth conservative and focusing on aligning gross margin with the industry.
This last case is no surprise, but with the Gross Margin Improvement and the sales and collection improvements from the previous two cases combined we get the strongest result, $47.4 million. This could be out of the realm of possibility, or it could prove to be very doable; there could be some slight improvements to be made to the different elements, and the sales margin and collections features that we've identified have levers to pull. But the most valuable takeaway for management, and for the bank in this case, which as a bank we are invested in the success of Skyline, is that we've identified some areas of focus, and we can discuss further what to do with these findings.
Horizon Analytics models produce a full set of forecasted financial statements, including an income statement balance sheet, and cash flow, and relevant ratios for all of the five years that we generally forecast. We can also draw the forecasts out further, if management has longer term plans, it's just there's always that law of diminishing returns associated with forecasting too far in the future, so we generally stick with five years as the happy medium of how far out to go. This is just a snapshot of the information provided, we do give you the full set of financial statements when we discuss the results of our modeling, but you can see how seeing this data tell a story over time from period to period can bring up important points of discussion and possibly alert Skyline and the bank of obstacles and opportunities to prepare for.
You don't have to take our word for it if you can see what a lot of satisfied companies were willing to share with you about their experience in using Horizon Analytics. And a lot of these are companies you could research in the news as well, for a lot of successful transactions that they've taken on recently. To hear what our Clients have to say about Horizon Analytics, visit pmbank.com/HorizonAnalytics
You've done your financial modeling and analysis - now what?
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