Enterprises can respond to change faster and more effectively by developing agile forecasts for all lines of business. When business is unpredictable, connected planning and scenario modeling are imperative.
Many businesses are still stuck in legacy planning systems…or stuck with legacy planning mentality. Here are the seven signs we’ve seen at our clients when they are stuck in a legacy planning system or mentality, and how to move on.
1. Heavy Reliance on Excel
If your budgets and forecasts are consolidated and/or entirely created in Excel, and you are planning mostly outside your planning system, you have a problem. Excel is error-prone, there is no version control or ability to collaborate, and it’s tedious to consolidate multiple disparate files when it’s time to consolidate.
It's time to escape the Excel grind with a modern, connected planning system so that you can collaborate with colleagues for improved short- and long-term planning.
2. Planning with only GL Data
When the data collected from planners—either in Excel or within planning software—is primarily GL account data, it’s very difficult to analyze the root cause of the variance. A modern, connected planning system should include statistics and assumptions that drive real numbers.
Planning with only GL data is especially problematic when operators are expected to complete the plan. Instead of collecting results, statistics and assumptions should be collected in a driver-based model— allowing planners to speak in their own language and understand and act based on variances.
3. Legacy Planning Mentality with a Shadow Excel System
Enterprises may have a planning software in place, but there is a legacy planning mentality where planners still maintain a shadow Excel system to model and calculate the numbers that are ultimately uploaded to the system. This limits visibility into underlying assumptions and is inefficient, as planners with similar roles often maintain duplicate models across the enterprise.
Models should be refined and incorporated into the planning system, replacing the shadow Excel models.
4. Planners Need to Run Reports or Query Raw Data from Operational Systems
If planners are extracting data from operational systems and manipulating it in Excel to inform their budgeting and forecasting processes, it’s a sure sign of a legacy system or mentality. The time spent collecting data reduces the time planners are available for value-added analysis.
Instead, data that is needed to support planning decisions should be available and leveraged within the planning tool, allowing planners to apply assumptions regarding forward-looking trends to drive their forecasts.
5. Level of Detail is Too Much or Too Little
Oftentimes, less is more, but it's not always that simple. The level of detail included needs to support accountability within the enterprise, especially if compensation is tied to the data. But too much detail often leads to confusion and wasted time. For instance, too much detail on something innocuous like office supplies which may only account for 1% of the overall budget, is overkill. But if you’re not detailed enough on labor which may be your most expensive line item—and is tied to accountability in HR and Payroll—you may be in trouble.
Instead, consider the level of detail as it relates to volatility and materiality:
- Highly material and volatile elements should receive more attention—planning for these needs to be supported by models that enable scenario and sensitivity analysis. For instance, fuel expense for a cruise line. This is a highly material item which is also volatile based on oil prices.
- Planning for elements that are material, but not volatile can often be supported by straightforward driver or trend-based models. For instance, compensation (i.e., labor rates) and benefit expenses are almost always material, but not volatile like a commodity such as oil.
- Elements that are not material or volatile require the least attention, and planning for these elements should typically be completed at a consolidated level and/or with simple trend-based methodologies. For instance, the office supply example above.
6. Monolithic Model
One-size-fits-all models, especially in a heterogeneous enterprise with several lines of business, require a lot of compromise which simply may not work for each line of business. In fact, when these monolithic models are built to satisfy “least common denominator” requirements, they typically offer very little value to any lines of business. While these models can make it easier for Corporate Finance to roll up the disparate plans, the lines of business themselves are often left maintaining their true business models in Excel (again), and then going through machinations to twist their true plans into the format required to submit to the monolithic compromise model.
Keeping the dimensions of materiality, volatility, and accountability in mind, the planning system should be evolved with bespoke models that support unique planning needs within the enterprise.
7. Planning has a Lack of Connection
When there is a lack of connection, dependencies within the enterprise are not supported within the planning tool. For example, functions that depend on volume assumptions need to wait for the revenue function to generate a volume forecast, the forecast is forwarded (typically in an Excel file via email) to the functions that require it, and then they begin their planning process.
For example, a cable company makes assumptions about the number of calls to the call center and customer care expenses based on existing subscribers, but when more subscribers are added in the volume forecast, the plan is out of sync. There’s a deadline to complete the plan, so a higher revenue number is entered, but there’s no time to adjust the numbers downstream. Volume is up by 5%, but there’s no way to explain the expense variance because the plan is unbalanced and disconnected. When the volume forecast needs to be revised the entire cycle begins again. This is inefficient and with it comes many version control issues.
Instead, the planning system should be connected and aligned, so it is dynamic and flexible enough to efficiently model the impact of changes in underlying assumptions and drivers. We recommend that our clients drive more accountability to metrics rather than plan numbers. For instance, accountability should be to cost per call instead of a high-level customer care expense number that’s generated with nothing to back it up.
You can see common themes in the seven examples above—heavy reliance on Excel and disconnected, inefficient processes. If these are red flags in your enterprise, we can help with a connected Oracle Enterprise Performance Management (EPM) cloud system with connected planning. Cloud-based EPM transcends the finance department to include every area of your business.
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