Albert Einstein once noted, “Not everything that counts can be counted, and not everything that can be counted counts.”
His meaning points to the pursuit of hypotheses over the establishment of absolutes. Let’s translate that into the world of budgeting and forecasting, where the process aims to provide insight into things that are difficult to grasp as a business constantly changes. But that doesn’t mean the effort isn’t worthwhile! As PwC noted in its classic report:
Managing business performance in today’s complex and rapidly changing business climate is crucial for any organization’s short-term and long-term success. In order to maintain investor confidence and provide insight to top management, there is an increased demand for finance organizations to provide prospective insights on business trends and drivers of performance.
Over the past decade, this “rising demand” has transformed the role of the CFO, expanding it beyond finance per se to one that encompasses business strategy and operational leadership. “As they accept a more strategic rule inside their organizations, they also push for a higher level of data integrity and a ‘single source of truth’ for all data that drives their insights,” notes James Kosur in a Business Insider column.
So we’d better be sure of what we’re counting and what we consider to be facts. We’re living in an age where data grows at astonishing rates – new data sources are continually being introduced – and the quality of existing data may erode over time. Understanding “what’s what,” that single source of truth we can rely on, is a difficult task indeed, particularly with data that is more dispersed, distributed, and voluminous than ever before.
The Problems of Historical Data
Annual budgets and forecasts are based on a snapshot in time from historical data. Most budgets focus on top-line elements such as profit and loss or balance sheet elements. These numbers stem from the various teams and business units building individual budgets using different systems and nomenclature. In some companies, teams still need to request reports from IT to build individual budgets, which add days and weeks to the process. Self-service has not reached all knowledge workers, which slows down decisionmaking and execution.
Some business units struggle under the weight of all the information they have to digest, how to clean the data they have, the lack of integration between different units and regions, and clashes over access rights. All these problems make consolidation very difficult and erode operational agility. When discrepancies arise, many find them excruciating to audit and reconcile. PwC’s research addresses this point: “Historical weaknesses in the budgeting and forecasting process persist, limiting the perceived value of the financial planning process within the organization. The process continues to be time consuming, iterative, and inaccurate.”
In their book Beyond Performance Management, Jeremy Hope and Steve Player cite a particularly horrific example of this issue:
At one global company, there were 75 levels of review and consolidation, and it took a huge amount of time and effort to produce a forecast. Such was the detail involved that one business unit alone spent 585 people days over eight weeks to produce a forecast that was immediately out of date. Not only do forecasts take too long, but also their quality leaves a lot to be desired.
The authors conclude that using the rearview mirror of budgets and variances to manage performance when the market is changing so rapidly is a “recipe for disaster.”
Spreadsheets at the Epicenter of Inefficiency
Spreadsheets have been in the market for decades. They are very good tools for what they were designed for: providing an easier way for accountants to add rows and columns of data quickly. The 36-year-old concept hasn’t changed much over time; yet spreadsheets remain the de facto tool employed in the budgeting and forecasting process. Ninety percent of all organizations still use spreadsheets for planning, even though it reduces efficiency, increases the risk of human error, reduces data transparency, and creates multiple versions of the truth.
Spreadsheets weren’t designed to be an enterprise data analysis or forecasting tool, nor were they created to be data storage systems. Using them for these additional purposes causes problems for managers and typically results in wasted time and effort. For example, creating a budget using Excel means collecting a lot of data from disparate places, rekeying the data, and creating workbooks that can span dozens of pages, each one with endless columns and rows. As these workbooks are passed around for editing and updating, more versions are created, resulting in not only a data storage problem, but also a navigation and auditing nightmare due to “alternative” facts.
Corporate Performance Management: The Right Tool
In a column on the B-Eye-Network, Chris Colvin discusses the performance management framework as an approach to overcome the traditional failings of the historical, spreadsheet-based approach to planning and forecasting:
A performance management framework enables organizations to set goals they hope to achieve, metrics by which to measure the success of the business units’ achievements, monitor the results, and adjust the plan to ensure goals are attained. Whether an organization is looking to create a performance management framework or if one already exists, the following changes improve the efficiency of the performance management team and enable the organization to react more quickly as their business climate changes.
The changes he points to:
- Using short-term goals to support long-term objectives
- Identifying internal and external drivers
- Evolving all the time
- Integrating information systems and business processes
Bottom line: a modern planning solution must support data transparency and accuracy across the enterprise. It has to be open for change, easily adjustable, and needs to support teams that span across continents and divisions. This is not possible when using Excel alone.
Some CPM vendors reject Excel and see it as a problem to eradicate. Others recognize that Excel remains popular with business users for good reason and have instead focused on managing the data issues through providing Excel add-ins and keeping the ease of use and familiarity. Some solutions are cloud-only; others are on-premises only. Still others provide highly flexible hybrid options. Some solutions specialize in one area, such as visualization, data discovery, dashboards, planning, or big data, while others are unified, providing rich functionality that supports business process and controlling (i.e., financial) functions.
Whatever an organization’s preferences are, all solutions should enable users to work in the environment they prefer— and refer to a single source of truth, which won’t negate Einstein’s point. However, it will make the decisions that are the outcome of planning and forecasting less error-prone, based on more accurate historic data, enriched with industry trend data, and more compelling as drivers of business value.