Finance teams are facing unprecedented challenges in producing accurate forecasts, as external factors continue to impact company performance. Each passing year seems to bring its own set of obstacles – from pandemic disruptions and supply chain bottlenecks to labor shortages, inflationary pressures, and fluctuating interest rates. These exogenous factors have repeatedly forced finance teams to “throw out” their forecasts, leaving stakeholders, particularly investors, fatigued and frustrated.
Yet, amidst this uncertainty, a common thread emerges across the finance landscape: constraints. Regardless of industry or company size, businesses consistently grapple with critical limitations, with labor issues often taking center stage. However, our discussions with numerous CFOs reveal a concerning trend – finance leaders struggle to effectively incorporate these constraints into their forecasting processes. When asked to rate their teams’ capabilities in attribution analysis, CFOs consistently score them below average, typically less than 5 out of 10.
To address these challenges, we’ve engaged in extensive dialogue with CFOs. Through these conversations, we’ve not only gained valuable insights into the specific constraints they face but, more importantly, we’ve identified practical solutions to help overcome these hurdles and improve forecasting accuracy during times of uncertainty.
Community Insights: Constraints Wreak Havoc on Forecasting
CFOs across diverse sectors, from energy to retail, pinpoint revenue visibility as their primary constraint. Both industries are engaging with customers to understand their long-term needs, whether it’s major equipment requirements (considering lead times) or significant customization (factoring in specialized labor). While longer-term planning and forward commitments are positive developments, they introduce more variability around customer financial performance. A customer’s financial distress or a poor quarterly earnings report can completely derail forecasting efforts.
A CFO of an Alaska native-owned conglomerate shared his planning challenges operating in an environment where shareholders receive significant distributions which are not fully defined at the time of forecasting. The distribution requirement naturally limits capital available for growth investments, significantly impacting the forecast. This is similar to what we call the free cash flow generation constraint, also known as “The Big Circular” given that forecasted free cash flow (in this case, after distributions) influences the forecast itself, becoming both an output and an input. Any major change or unforeseen distributions can disrupt forecasting efforts, even rendering the forecast obsolete.
A CFO of a cannabis licensor and manufacturer revealed to us her experience and insights living with constraints across all facets of the business. From regulatory changes and lack of traditional bank financing to unknown state licensing timelines, raw material sourcing challenges in new markets, tight liquidity runways, and capital raising timelines – the multitude of these constraints poses significant hurdles to constructing an accurate forecast.
Any of the constraints mentioned above can wreak havoc on forecasting – to the point of rendering the forecast useless shortly after its finalization! We have spoken to countless CFOs who lament that their forecasting processes are either 1) inaccurate, 2) immediately obsolete due to changes, and/or 3) result in functional finger pointing come variance analysis time.
So, how can CFOs and finance leaders counter this challenging environment?
The solution is straightforward: Incorporate constraint-based forecasting into your process.
FWF Applications: Implementing Constraint-Based Forecasting
Constraint based forecasting enables finance teams to isolate the constraints impact throughout the forecasting process. One way to implement this is through ‘modules’ within forecasting builds, utilizing yes/no toggles and timing flex for events (binary events like capital raises, or grant awards).
For example, we led the construction of rolling forecasting processes for a cancer treatment research and development company. Largely funded by grants, whose timing and amount were uncertain (the constraint), we developed and incorporated grant modules into forecasting tools that not only enabled department-level assumptions associated with an individual grant, but also enabled grant as standalone data dimensions so that the company could assess actual vs. forecast variances apart from individual grant awards.
Another approach is a forecasting build such as the “layer cake”, a bottoms-up or ZBB-like approach which associates all P&L items with a respective business ‘layer’ such as 1) keeping the lights on, 2) rolling-off existing customers, 3) maintaining and retaining customers, 4) upsells and new logo acquisition, and 5) product/market R&D and expansion. Modules and tagging allow for additional data capture in your forecasting process which can be leveraged for better performance insight and context throughout the following year.
These approaches all have the same core requirements – assumptions and components of the forecasting build are ‘tagged’ and/or ‘dimensional-ized’ to associate inputs and outputs with corresponding pieces.
Determining these tagging and dimension requirements is a critical element of forecasting process design. It sets the tone from the outset on how departments and functions approach their inputs and builds. Don’t underestimate the value of this element – it helps clearly communicate the themes (and constraints!) of the forecasting initiative throughout the organization, which is vital for effective forecasting.
Finance leaders have noted better results by prioritizing whole-company transparency over a numbers-first approach, aligning with the overarching goals of the forecasting initiative for the year. This is particularly true when dealing with constraints, as the limits of one department may be the primary determinant (or lowest common denominator) in setting the forecast for others.
Takeaways
By incorporating constraint-based forecasting into the design, development, and dialogue related to the forecasting process, finance teams deliver more buy-in within their organizations, back recommendations with quantifiable justification, and effectively bridge the gap on expectations vs. realities with stakeholders. It also generally compresses the forecasting cycle as demonstrated by our cancer treatment R&D client. The successful deployment and implementation of the rolling forecast process incorporating binary constraints (the grants), saved the finance team significant time in variance analysis and grant compliance reporting. All outcomes worth striving for!
Interested in learning more about budgeting and forecasting best practices?
View our Budgeting and Forecasting Readiness Playbook here.
Explore our blog on Constraint-Based Budgeting here.
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First Water Finance (FWF) is a finance solutions platform supporting finance leaders, business owners, and capital partners through FP&A, Corporate Finance, and Community. FWF has supported over 100 management teams and sponsors, concentrated in emerging and mid-market enterprises, professionalizing and accelerating the finance function in pursuit of growth, acquisition, and/or sale objectives.