Private equity companies have endured a decade of market volatility, rising interest rates, and unprecedented events, testing the sector’s financial resilience and return on investments. Those who have sustained have learned to be proactive instead of reactive. By setting business strategies based on real-time data, they’ve adapted more quickly to unexpected events. However, this can be a challenge: companies need multifaceted analysis to ensure their leaders and investors have access to the right data to address the problems they’re tasked with navigating. Simultaneously, leaders need a common understanding of how market dynamics may impact business value and operations. In response, many PE-backed companies have looked to their forecasting processes to obtain quicker insights.
A faster, more repeatable forecast will be more valuable for private equity companies. By forecasting at least quarterly, and making forecasting as routine and reliable as possible, companies can understand their performance against goals, quickly course-correcting if required. This doesn’t require an exhausting process—as time is valuable—and in many cases, finance leaders can get a good snapshot of organizational performance by looking at the most important drivers. With this approach, your team can be more efficient and drive meaningful results.
In many cases, companies have adopted rolling forecasting as their approach. With a more effective forecasting process, companies can achieve:
While rolling forecasting does provide important capabilities, it’s an advanced approach, and one that most organizations will need to build up to. But no matter where you are in your journey, activating faster forecasts will help you directionally predict future performance—allowing for immediate action. With these benefits clear, how should companies approach their forecasts?
To get the most out of a forecasting process, PE firms and their backed companies (PortCos) will need to anticipate their unique needs. For PE firms themselves, this means utilizing forecast data to calculate implied valuations to support exit planning, data to set performance-based compensation for leadership, and debt compliance monitoring for their PortCos.
PortCos’ needs center on providing data both to their leadership and to their portfolio managers. A good PortCo forecasting solution will provide clear performance expectations, ensuring there are no surprises for their owners. It should also allow leaders to manage and understand cash flows, deliver data on how to plan for and prioritize investments, and provide scenario planning capabilities for revenue, margin, and operating expenses.
These unique needs are due to the unique requirements of PE firms and their PortCos—the need to support revenue generation and growth both at the individual company level and to drive PortCo valuations at the fund level. Leaders need access to the platforms and analytics to support key decisions and their strategy for the company. For any PE-backed company, this means a heavy focus on EBITDA and adjusted EBITDA. These data points are primarily driven by growth but enhanced by cost containment—keeping expenditures low while maintaining topline growth. Companies need confidence and evidence that their growth and expansion plans will work for their benefit and that of their PE partners. And because PE companies will often have dozens of companies in their portfolios, these processes and functions should be repeatable and streamlined.
PE companies looking at their forecasting processes should also think about the time horizon for their forecasts. While standard forecasts will extend towards the end of the budget period (usually the fiscal year), leading organizations that use rolling forecasting processes can achieve up to an 18-month time horizon from the current date, ensuring they can stay on track with growth expectations. These longer-term forecasts are usually reforecasts of the annual budget, updated based on the actual results within the budget period. Companies need to do this to ensure that there is an up-to-date plan for how budget targets will be met or how shortfalls will be addressed.
At a minimum, PE-backed companies should do this on a quarterly basis while working toward making this a routine monthly process. The level of detail in these forecasts will vary by organization but should be kept at a relatively high level. Finance teams should focus their valuable time on the more material parts of the business. If there are 30 revenue lines on the P&L but 90 percent of revenue comes from only five of them, focus time on forecasting those five. This approach will allow the team to run the forecast faster and still be appropriately accurate.
Leading organizations will institute a rolling forecast—a continuously updated forecast that projects 12-18 months forward, going beyond the static 12-month period of a typical budget. Companies without an effective forecast process carry significantly more business risk and can potentially miss guidance on earnings, which may negatively impact their value.
For value-add forecasting, it is critical that companies perform this within a connected enterprise tool that is integrated with their tech stack. This tool should feed outputs to a purpose-built BI and analytics tool for proper reporting and analysis.
PE companies also require a budget that details operational expectations for the business for the upcoming year to ensure that the execution plan is clear and targets are met. For PE-backed companies, key areas to budget are sales and revenue, operating expenses, margins, EBITDA and adjusted EBITDA, headcount and related expenses, and Capex. Ideally, an organization will use a combination of top-down and bottom-up budgeting, with top-down allowing for strategic modeling from an executive level and bottom-up providing the operational plan for how the top-down will be executed.
As PE companies and their PortCos establish their budgeting and forecasting processes, they’ll need to work deliberately. We recommend a multi-stage process that first delivers the basic needs from a forecast and then adds advanced capabilities.
To begin, your company will need a plan. Timelines and expectations for budget and forecast should be clear and enforced, and the budget and forecast targets should be directly tied to overall company targets and strategy. The plan will need to be documented and clearly communicated to all stakeholders to ensure alignment around how your forecasting will work.
Ideally, an organization will facilitate the budget process in a connected tool that is integrated with the broader tech stack. Bottom-up budgeting should utilize data points pulled in from source tools—for example, headcount and employee expense data from the HRIS system. This entire process should be automated, to minimize the version control problems that come with building budgets via Excel.
We frequently hear that organizations spend too much time gathering data and planning. While getting the right data into your forecast is important, it shouldn’t leave you no time for analysis. A better planning tool can help you keep your focus where it needs to be. As teams look at moving from Excel or offline tools to packaged, enterprise applications, the following evaluation criteria should be carefully considered as a starting point:
Note that pricing and commercials are considerations, but buyers should consider this separately from the primary evaluation criteria. Also, ensure that the right people are involved in the evaluation process. This likely means a cross-functional team across the business, IT, and purchasing.
Teams must have the right process in place to perform real analysis, with scenario analysis being particularly important. There are several ways teams can ensure the budget and forecast better facilitates scenario analysis, including:
The number one way teams block themselves from effective scenario analysis is by including too much detail in the plan. This bogs down the process and results in teams spending too much time compiling and tidying up the details and not nearly enough time on scenarios. It also makes it more time-consuming and difficult to build the scenario out.
Because scenario planning is key to your new solution’s function, this should be top of mind early in the process and not something to be figured out later. Assess what types of scenarios you’ll want to run and build them into your plan.
What areas do executives and finance leaders consistently scrutinize and ask questions about? Those may be the right areas to prepare placeholder scenarios. Simulating scenario analysis will also ensure the team is ready to run these when asked.
While modeling a scenario, do not change too many assumptions at once. Doing this makes it hard to track what’s actually driving the variance versus the base case. Think of it like a science experiment—when multiple variables are changing, it becomes much more challenging to understand what is really happening.
Most PE-backed companies know the “80-20 rule” for demand and revenue forecasting: Focus on the 20% driving 80% of the revenue. For scenario planning, apply the same principle – ensure that the scenario drivers are focused on the most material parts of the business. For instance, select cost drivers that have the most material margin impacts, and flex those assumptions to see what different scenarios yield. You can also use ‘relative forecasting methods’ for major OPEX expense items—for instance, forecasting expenses as a percent of revenue instead of as detailed build-ups. Using simple drivers and blended costs can also help cut down on the time needed for scenario creation and analysis—for instance, forecast employee cost by overall headcount and pay grade by level instead of by individual employee. This will allow for better flexibility in modeling an employee cost scenario. Lastly, keep in mind that the most appropriate scenario drivers or assumptions will vary significantly by industry.
The best scenario planning tool won’t help your business if nobody uses it. In advance of rolling out your scenario planning tool, identify who will review the results and what they’ll do with the information. Consider macro scenarios vs. micro scenarios (i.e. high price/low volume vs. specific product line-item scenarios). Work with senior management to understand the scenario analysis they’re discussing vs. detailed cost center management discussions, and to decide how to present the results. Bringing in helpful data visualizations and anticipating questions that will be asked during the presentation will allow you to use your leaders’ time more effectively. Finally, ensure there’s reporting in place to show clearly how a scenario compares to the base case.
Although AI and machine learning are still evolving technologies, and it’s sometimes difficult to separate the hype from the actual benefits, there’s clear potential for AI to reshape the PE business. Organizations that don’t prepare for these new technologies will likely fall behind, as many organizations that can lean on AI/ML will outperform their competitors. Forecasting has several areas where AI/ML capabilities can contribute to your bottom line.
To get started, PE companies should ensure they have the right foundation for data to be used by AI and ML tools. If data is disorganized or unavailable, these tools will have nothing of value to consume, and if the data is inaccurate or incomplete, the results of AI-powered analysis will be unreliable too. Consider the following questions:
Having a clear plan for your AI and ML implementation is also important. Identify objectives and use cases to make sure you’re implementing the right tools for the right reasons—not just using AI to use AI. For finance teams specifically, AI and ML may allow the forecast process to be partially or fully automated. If your team is conducting the same repeatable activities every month, think about how to automate those steps. From there, you can expand—for instance, developing a strategy to train an ML tool to take a first stab at the full forecast.
While there’s no shortage of startups that will try to sell you new AI-powered tools, it’s always simpler to start with something you already have. Many SaaS providers are building out new AI components within their tools, and you might either have access to these components already or be able to access them as a simple add-on to your current software. Do your research to understand what is available and how to use it.
For companies that have already adopted AI and begun to see some value, meanwhile, it will be essential to begin assessing costs and benefits. The hype cycle has led companies to invest in a broad range of tools, and like any other investments, some will perform and some won’t. Take advantage of what works and don’t be afraid to cut what doesn’t.
Finally, don’t forget human judgement. AI and ML can unlock tremendous value, but they’re not perfect. Ultimately, anything generated by AI will need to be checked by people to make the right decisions for the organization. Even AI power users understand the limits of their tools, ensuring better outcomes.
As interest rates continue to fall and the election results are in, the M&A market is heating up. PE companies and their PortCos should take steps to enhance their forecast capabilities to ensure they can understand potential for growth, future cash flows, and possible value-add scenarios. In addition to establishing a streamlined and standardized forecast process, enterprise technology will assist companies in unlocking additional value in these areas.
Achieving this state may take investments in data capabilities, new AI/ML tools, or enhanced planning capabilities. Whatever path you take, don’t let perfection get in the way of progress. The best approach is the one that provides you with useful data the quickest. By being able to answer ‘what if’ questions, you’ll make your organization more agile, more intelligent, and ultimately more profitable. As you navigate this process, also remember you don’t need to do it alone. Numerous private equity companies and their PortCos have relied on Spaulding Ridge to help them achieve their goals. Contact us if you’d like to learn more about how better forecasting can lead to better profitability.
