By Garett Robertson
In preparing for battle, I have always found that plans are useless, but planning is indispensable.
– Dwight D. Eisenhower
Most business owners would agree that there is value in strong budgeting and forecasting process, yet few feel confident in their ability to create these kinds of tools in any way that could deliver the value they need. As a result, the budgeting and forecasting process is seen as a deeply time consuming and distracting endeavor even by members of the finance and accounting teams.
Knowledge is power, and a well-managed forecasting process can mean the difference between sinking and swimming in today’s rapidly evolving business world. So how do entrepreneurs and executives bring value to the process and make it worth everyone’s time? From our experience working with clients, the following five areas are critical to an effective forecasting process.
1. ALIGN STRATEGY TO FORECASTING ACTIVITIES
Although it sounds straightforward, from our experience this is one areas that is most often neglected. Instead of relying on historical trends as a basis for future activities, it is important to build into models the impact of strategic initiatives. New equipment could alter assumptions about productivity while new marketing channels may not only carry new sources of revenue, but also contain unique cost structures. Additionally, new markets may contain regulations or other nuances that can and should be quantified in a good model.
Entrance into new markets, acquisitions or other forms of expansion/contraction should be quantified in the forecast to not only evaluate the profitability of the project but also to assess proper timing so that the company can properly resource the initiative without overleveraging. Ultimately any changes to the business model will affect business performance. It is incorrect to rely on traditional assumptions when new business models are being built and implemented.
2. INVOLVE THE APPROPRIATE STAKEHOLDERS
Oftentimes critical insights are missed in forecasting when the appropriate stakeholders are left out of the process. For a manager trying to project costs of a production facility, it would be wise to involve the production manager in the process. Not only would he gain valuable insights, but he would also gain the trust and support of the production manager. The same could be said about any other division in the company.
Many companies will arbitrarily assign a target to a team by pushing for arbitrary increases to sales or reductions in cost with limited context, analysis or justification. This can undermine trust in teams and build silos within an organization if the teams do not have the capabilities, or insight to accomplish the change. Conversely, other companies allow their managers to simply produce a budget for the executive team to incorporate into the overall plan. This could lead to misalignment between operational divisions or overly generous and potentially wasteful expenditures.
The interplay between the executive, finance and various departmental managers is critical to ensure that targets are meaningful, strategically aligned and doable. This back and forth is a critical piece to building reliability and accuracy into the process.
3. FORECAST FROM LEADING INDICATORS
It is important to note that there is a difference between leading and lagging variables. Processes are driven by inputs and throughputs while they are evaluated by outputs. Lagging indicators are output variables and can be misleading if used to forecast future events since they are not causal in nature. One reason why models lack power in the evaluation of strategic initiatives is the failure of aligning leading KPI’s to the model instead relying on lagging KPI’s.
Gross margin %, number of units sold, DSO, or accounting figures are lagging indicators that are really only useful in assessing business results. In a forecast, these sorts of indicators do little to actually help. Measures more useful in forecasting would be pipeline statistics such as but not limited to conversion ratios or productivity measures. Additionally, worker counts, efficiency ratios, defect rates, or other cost drivers would be more accurate predictors of future costs than simply historical norms or other lagging variables.
4. BE FLEXIBLE
Although driving accountability is key, adhering rigidly to outdated or otherwise inaccurate forecasts seldom accomplishes more than disrupting teams and wasting time. Despite everyone’s best efforts to get it right and even with proper support from all stakeholders, the actual results could still deviate from the forecast for a variety of reasons. Using them too rigidly only incentivizes stakeholders to be overly conservative in future estimates, hide critical information, manipulate or even falsify reports in an attempt to circumvent painful confrontations that add little value to their work.
Forecasts should be used as a compass to evaluate the direction of the company. If a forecast number is missed, a discussion with the relevant parties should occur to determine why it was missed. Was it due to a mistake or poor performance on the stakeholder’s part, or was it due to something else such as a poorly made assumption or key shift in conditions that would invalidate model parameters?
Instead of building rigid structures, based on long fixed periods, use rolling forecasts that focus on shorter term objectives and don’t be afraid to make adjustments as you go. As an example, if the current forecast is annual, then consider making it an annual forecast with rolling months or quarters instead of just relying on annual updates. During periodic performance reviews, validate assumptions or pivot.
5. SET REASONABLE COMPLETION TIMELINES
Too many times executives build a process that takes many months to complete. It is not uncommon to see the process take six months or more. By the time it is complete, much of the data and assumptions could have passed their shelf life. When combined with a rigid process, the forecast becomes little more than a paperweight.
Consider shortening forecasting lifecycles by using software and other tools to automate parts of data collection and analysis. While a complex ERP may be out of reach for many small businesses, there are plenty of tools that can work even for small businesses with capital limitations.
Also, instead of focusing on detailed multiyear projections, consider a waterfall approach where near term objectives are more detailed and long term less. In reality businesses pivot frequently anyway invalidating assumptions and models with long time horizons so build reasonable long-term models and focus accuracy on nearer term.
