Despite the constantly churning mechanisms of business, the traditional budgeting process has changed little since the 1920s. An organization can spend months creating a blueprint for the next year and then expend even more effort to stay on that defined path—regardless of whether the initial assumptions were correct. This inefficient process creates static numbers that quickly become obsolete. They also do little to support strategic decision-making.

And there are plenty of other major flaws of the century-old approach:

  • Even with spreadsheets and analytics, finance professionals are stuck with a laborious process of back-and-forth negotiation between varying assumptions and expectations.
  • Organizations are married for a year to negotiated targets, adding little value to planning in a rapidly changing world.
  • An overemphasis on “making the numbers” takes away focus from strategic initiatives and can be counterproductive in allocating assets.
  • In-house financial analysts are sidetracked by having to collect and validate data, rather than having the bandwidth to generate the analysis needed to plan alternative action.
  • The traditional budget becomes a negotiation game where reaching bonus targets becomes more important than optimizing outcomes.

Organizations clearly need a better model. Like a ship, an organization’s structure, capacity, ability to produce value, and even speed and location are the result of thousands of past decisions. Planning is the process of assessing the ship’s position and capabilities against where it is trying to go. Plans cannot be based on where the ship went last year; they need to be forward-looking.

No captain or crew can perfectly predict what will happen. They can, however, track the ship’s progress in pursuit of specific targets, while adjusting when off course and increasing speed when on the right track.

Alternate Approaches

There are a number of viable budgeting methods that address the traditional process’s weak spots.

Rolling Forward. Traditionally, organizations set targets to indicate where the organization wants to go. Forecasts then indicate what is likely to happen based on the organization’s current configuration and change initiatives. The two views do not always align.

Using a rolling horizon can help to continuously monitor an organization’s course for a consistent time period. Static budgeting typically forecasts to a wall (i.e., only to the fiscal year-end). Doing so focuses attention on meeting targets set before the year began. The problem? Managers quickly learn to negotiate low targets.

Rolling forecasts use a consistent horizon (five quarters out, say) to provide visibility and time to address new realities. Visibility shifts from “making this year’s budget” and bonus targets to long-term concerns, including outperforming the competition and reaching strategic goals.

Rolling forecasts also help organizations consider the full impact of spending decisions and actions. Organizations with large-volume businesses, predictable trends, and access to large customer data sets tend to benefit the most from using a rolling forecast.

Driver-Based. Some organizations choose to combine a rolling horizon with a driver-based forecast. Instead of being based on opinions and past performance, driver-based forecasts zero in on key environmental and operational factors. They employ logic diagrams to represent causal and quantifiable relationships between underlying drivers and their effects on the overall business. (For example, a logic diagram can map out the whole process that occurs from identifying the potential customer universe to total sales leads, sales calls, and eventual gross sales.) That gives management a deeper understanding of cause-and-effect relationships.

Driver-based models look for mathematical relationships, such as between sales targets and units already sold. (For example, what is the issued sales leads to sales calls ratio? The sales calls to unit sales ratio?) The value of each individual driver can be identified by past performance, benchmarks, and marketplace indicators. The more relationships tracked in a logic diagram, the more that can be predicted and the more lead time an organization has to act.

The greatest advantage of using a driver-based forecast is identifying the handful of key drivers that will make everything else flow. Organizations benefit most from driver-based forecasts when they understand systems thinking and their businesses well enough to develop predictive logic diagrams. Organizations using activity-based cost management, in particular, are excellent candidates because of their experience mapping process activities and drivers.

One Step Beyond. Organizations that have success with driver-based rolling forecasts may be ready to completely dispense with tradition. A more adaptive approach, “beyond budgeting,” revamps the entire financial and performance management process. Instead of focusing on meeting budgeting goals, an organization concentrates on tracking internal and external drivers of performance on a rolling horizon and dynamically adapting plans and allocating resources.

This approach is ideal for organizations wishing to replace a centralized budget approval process with a self-regulating and decentralized approach. The elimination of bureaucratic rituals can lead to (1) faster responses when drivers change and (2) a collective shift in focus to investing in long-term goals.

Beyond budgeting, however, requires leadership that has moved beyond a command-and-control mindset to instead empower all levels of decision makers. It also requires transparency and trust. Finally, it does not work for organizations still struggling to align operations on shared values and goals. (See the sidebar, “First Principles,” below.)

In Real Life

New York–based LT Apparel Group, a privately held supplier of clothing brands such as Adidas, Carhartt, and French Toast, redesigned its budgeting process and used technology to streamline forecasting.

LT Apparel Group redesigned its forecast process well enough to ditch the annual budget.

Before 2014, LT Apparel’s forecasting process occurred semiannually, largely due to the amount of time it took to produce a budget with spreadsheet models shared from multiple locations. The process sometimes took five months to complete, including dealing with consolidation issues and system crashes. As a result, sometimes actuals arrived before forecasts were finalized.

LT Apparel found it a challenge to overcome the ineffectiveness and inaccuracies laden in its semiannual approach. The apparel industry operates on long lead times. Using overseas manufacturers means it sometimes takes 18 months for products to go from concept to the consumer. The organization needed a more reliable, long-term forecast to better plan for fluctuations in commodity pricing and labor rates, and ultimately to invest its available cash flow.

LT Apparel redesigned its forecast process with the following features:

  • Rolling horizon — The new process involves monthly forecasts to facilitate asset allocation. The forecasting team sets the forecast for 30 months out and then keeps that horizon rolling. Most months require only small changes to the forecast. Material updates are aligned with the individual brand’s production and selling calendars. As the forecast is updated, the model leverages 24 months of historical data.
  • Driver-based — The forecast is automatically fed with variable cost structures, new-hire assumptions, and fixed expenses based on historical data. The forecasting team focuses on a small number of key drivers, such as sales projections and distribution costs, with many tied to seasonal rolling averages.
  • Decentralized accountability — Process owners are responsible for providing critical information on key drivers. For example, a wholesale planning department provides the variables related to sales, margin, and inventory. The logistics team then develops the distribution volume metrics and related costs. These inputs feed the forecast model.
  • System analytics capabilities — A cloud-based enterprise performance management (EPM) system provides a single source of truth and a modeling component to build and report on the rolling forecast.

The new EPM software was fully implemented by December 2015, and all planning templates were integrated by June 2016. By the end of 2016, LT Apparel had eliminated the annual budget. The retailer has seen improvements in process accountability and financial projection accuracy, and the new forecast provides the information necessary to plan cash reserves and capital investments.

All In

Minnesota-based Park Nicollet Health Services replaced its traditional budgeting process with a beyond budgeting approach. The provider of primary care clinics, urgent care centers, and pharmacies was formed out of a 1990s merger. Through the early 2000s, it had trouble yielding a positive operating result. The process for developing its budget required the finance and accounting function to combine 240 budgets and then produce a number estimating the scale of the loss.

Park Nicollet Health Services operates without an annual budgeting cycle; instead, it makes planning a continuous process.

Management would then return those budgets to operational managers to “try again,” because the estimated loss was too big. Requiring two such passes, the budgeting process would take up to seven months to complete. Board approval would come very late in the new year.

Because the existing process didn’t work, the organization shifted to a focus on targets, unbiased forecasts, and action plans to address forecast and target gaps. The goal was to be forward-thinking rather than always justifying performance based on a budget made months ago.

As a first step, finance examined its processes and mapped its value streams. Looking at the scale of dysfunction in its traditional budgeting approach, it completely eliminated it. Instead, the organization decided to:

  • Base goals on maximizing performance potential;
  • Base evaluation and rewards on relative improvement with hindsight;
  • Make planning a continuous process with forecasts set on a rolling horizon of six quarters;
  • Provide resources in response to need and market opportunities;
  • Coordinate company activities according to prevailing customer demand; and
  • Set base controls on effective governance and performance indicators.

Instead of focusing on setting budget needs and justifying variances, employees now have the bandwidth to focus on Lean management. And instead of judging employees on their capacity to meet the budget, evaluations focus on improvement in process performance. Annual bonuses are based on relative financial performance instead of the budget, and the organization now bases goals on profit potential.

Finance and accounting measures performance based on costs for year-end service and units per full-time employee. Instead of comparing actual performance to a budget, the function compares actual performance with the previous quarter and — since Minnesota health care has a lot of seasonality — the same quarter last year.

Park Nicollet’s effort has eliminated waste, empowered employees to make thoughtful decisions, and focused the finance and accounting function and the larger organization on work that matters. Although mergers have occurred since its budgeting transformation, Park Nicollet continues to operate without an annual budgeting cycle.

Moving beyond a traditional budgeting approach requires persistence to ensure a truly adaptive process doesn’t devolve into an exercise in budgeting revisions. The ultimate goal in planning should be to dynamically adjust resource allocations as needed to reach strategic goals. The point is not to make numbers hit a magic target but instead to allocate resources and act wisely.

Steve Player is a senior research fellow working with APQC’s financial management research team. He is the co-author of “Future Ready: How to Master Business Forecasting.” Paige Leavitt is a writer and editor focused on process and performance improvement in business and education. As principal research lead, Rachele Collins, Ph.D., is responsible for APQC’s best practices research in financial management. 

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