Predictive Analytics

Technology Helps Year-End Budget Processes

Many annual budgeting and forecasting practices remain plagued by the same-old deficiencies.
Vincent RyanDecember 16, 2019

‘Tis the season of merriment. ’Tis the season to take inventory and make resolutions. ’Tis the season to G.I.V.E. (more on that later) and receive – particularly for CFOs. Allow us to explain.

To most folks, December marks the arrival of the holiday season. To CFOs, it marks the final chapter of the budgeting season: an annual (exhausting) exercise that creates the foundational elements for the critical (and more ongoing) forecasting and planning activities to occur in the coming fiscal year and next quarter’s end.

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Like Santa’s cookies or Tevye’s song, the annual budgeting/planning/forecasting process is “tradition.”

It’s tradition for companies to create a forward-looking budget, which sets detailed targets for the year ahead. It’s tradition (or at least best practice) for companies to then create quarterly re-forecasts based on actual results. These re-forecasts not only capture material deviations from the budgeting exercise; they arm management (and, in a private equity context, sponsors) with timely information to evaluate root causes and course-correct accordingly.

The budgeting and forecasting exercises are not just traditions – they are critical tools. The more accurate and efficient they are, the better they drive strategic decision-making across the organization; the better they inform ongoing performance management; and the better they serve as force multipliers for enhanced organizational operations. (These tools are critical in every corporate environment, but are particularly so in PE-backed ones, where CFOs live and die by the accuracy of information and reporting).

The problem is, in many companies, these traditions are just too darn traditional, eschewing the technological enhancements that can feed better budgeting information and deliver better forecasting insights. If data talks, finance hasn’t been listening. That has resulted in budgets and forecasts that remain plagued by the same-old deficiencies.

But, they needn’t be: ’tis the season of gifting, after all. CFOs might not know it (in fact, we’d argue they most certainly don’t — at least not widely) but atop their annual wish list should be one thing: business intelligence (BI) solutions. By understanding and acknowledging that technology can enhance tradition, CFOs can leverage BI tools in their forecasting and planning exercises to address the “G.I.V.E.-ing” deficiencies of more manual or Excel-centric processes: granularity, inaccuracy, variances, and efficiencies.

Granularity. The wrong level of forecasting granularity creates opacity. If, for example, you only forecast at a regional level, how can you dig into per-store or product-level performance? Here, Excel is the problem and BI is the solution.

BI tools can create forecasting formulas that consider a wider universe of business drivers, such as working days, weather, and product promotions. These logic-driven formulas enable CFOs to identify the cause (customers, products, locations) of unanticipated variances or changes within the business. And, unlike Excel, BI tools can ingest a vast amount of transactional data and quickly deliver granular forecasts that can be rolled-up to overviews that better inform real-time course correction.

Inaccuracies. Traditional processes often create poor forecasting accuracy. Full stop.

There’s no silver bullet for inaccuracy, particularly when the reasons for variances change over time (evolving consumer tastes or technological changes, for example). But, driver-based forecasting and back-testing can create an ongoing process to improve forecasting.

BI (alone) enables this virtuous cycle. BI allows CFOs to back-test forecasting logic against actual data and further allows them to modify deviation bands to refine that logic over time. Finance can also vary back-testing logic against different time horizons and different drivers to understand what causes the most meaningful impact on company performance. Indeed, BI allows finance to leverage traditional driver-based forecasts or complex machine learning algorithms, or both. In either case, BI provides CFOs with the dynamic tools to continuously challenge and constantly improve forecasting accuracy.

A lack of confidence in forecasted numbers and broader opacity into business realities hampers business planning and investment decisions.

Variances. Forecasting accuracy (or inaccuracy, as it were) has several downstream implications: a lack of confidence in forecasted numbers and broader opacity into business realities hampers business planning and investment decisions. And while finance can work to improve forecasting accuracy via a virtuous cycle of back-testing, it can never comprehensively address inaccuracy unless it can identify the root cause of variances.

Surprise, surprise — BI can help here as well.

CFOs can use BI to build an archival tool that tracks multiple forecasts and compares them to actual results as numbers come in. This archival tool helps pinpoint the areas repeatedly driving variances versus forecasts. But, it’s not just a data tool; it can also drive behavioral change by tangibly demonstrating to accountable managers how their decisions (and potential forecasting biases) are impacting the firm from a variance perspective. What’s more, these BI tools are easily disseminated across the organization (with appropriate system/data access controls), empowering those closest to business operations to discover their own insights.

Efficiency. Traditional budgeting and forecasting processes can be laboriously inefficient, involving a significant amount of CTRL-C/V tasks. There’s the copy/paste work of compiling budget G&A, headcount, and revenue templates from various departments. At many companies, these can run into the dozens and hundreds (and the subsequent work of monitoring and flagging the inevitable changes managers make over the course of the budgeting process). Then there’s the inefficiency around actualizing forecasts: as the year progresses, forecasts are replaced with actuals via manual cut-and-paste exercises, with forecast formulas then manually adjusted accordingly.

With BI, these inefficient processes can be automated, enabling financial planning and analysis to move away from the busy work of compiling data and crunching numbers and move toward true business partnering, with a focus on delivering big-picture insights that inform strategy.

Can you also perform some of the above in conjunction with your enterprise resource planning/continuous performance management tool?  Probably. But, unlike layering on a BI tool, the time and cost to implement these capabilities with entrenched systems can be daunting and can easily spiral into yet another transformational initiative that requires significant IT involvement.

So … ’tis the season.’Tis the season for CFOs in the budgeting weeds to think about layering in a BI element to improve forecasting in the coming year. ’Tis the season to G.I.V.E.: Using BI to address the granularity, inaccuracy, variance, and efficiency issues that have long plagued traditional forecasting.

‘Tis the season to receive: Leveraging new BI-enhanced forecasts to retrieve data that can be turned into information, which can then be turned into actionable insights. ‘Tis the season for CFOs to understand that BI-enhanced budgeting and forecasting is the gift that keeps on giving.

Srin Subra is a managing director and Nate Saperia a vice president at Accordion, the private equity-focused financial consulting and technology firm.