A vehicle is heavily relied on for many tasks, such as getting to work, traveling on vacation, or hauling home improvement items. The maintenance of a vehicle is often an intimidating task to the average owner. But if this important task is overlooked, a vehicle can deteriorate quickly. Eventually the vehicle can break down and be in the shop for two weeks. The price of repair is substantially greater than the collective cost of regular check-ups.
The way a functional vehicle is necessary for a family, corporate financial planning’s deliverables are critical to an organization. The data presented to executives in budget and forecast reports drives crucial decisions for a company’s future. However, wrong or inadequate data in the budget and forecast models can doom big decisions to failure. Just like a vehicle, corporate financial planning’s deliverables must be well maintained to prevent costly mistakes.
Vehicles require fuel to run, and quality fuel allows a vehicle to run better. The fuel for corporate planning is data. Quality data is a crucial component that enables corporate financial planning to produce accurate reports that support business decisions. Without reliable planning reports, executives must make decisions for a company’s future with little support. Many factors play into determining data quality:
- Reliability of the source system
- Accounting for any manual changes
- Timeliness when capturing data
By conducting a thorough analysis of the data quality used in planning models, corporate financial planning can determine the necessary steps to improve their fuel.
Many parts of a vehicle require regular check-ups. The oil needs to be changed, the brake pads need to be replaced, and the tires need to be rotated. The model used by corporate financial planning for budgets and forecasts also has parts: the collection model that gathers data from different businesses, the revenue model, and the capital expenditure model. Whether these models are in a million-dollar system or in Excel, regular upkeep is critical.
Failure to technically maintain models can lead to broken links, missing pieces of data for critical formulas, or version control issues. No matter how sufficient the data brought into the model is, a poorly maintained model will not produce the necessary outputs. Regular maintenance may require completely rebuilding current parts of the model to remove legacy assumptions or recurring errors.
With quality fuel and regular maintenance, a vehicle should run properly for at least its intended useful life. However, just because a vehicle runs properly doesn’t mean it’s effective for its owner. For example, a convertible car may work perfectly but would be considered ineffective by a rancher. Similarly, quality data and technically sufficient models may not produce effective outputs. The outputs produced by the data and models must conceptually align with the business decision needs. Each report and metric produced by corporate financial planning’s model must be rationalized with the executive team. If considered ineffective, it’s either time to replace a part or trade in for a new vehicle.
By following all components of this maintenance checklist, corporate financial planning can efficiently and effectively meet the needs required to make critical business decisions.