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 or overlooked task to the average owner. By pushing off this important task, a vehicle begins to deteriorate quickly until eventually the vehicle breaks down and is in the shop for two weeks. The price of this check-up is substantially different than the collective cost of regular check-ups.
Similar to a vehicle’s importance to a person, corporate financial planning’s deliverables are critical to an organization. The numbers gathered, analyzed, and presented to executives in budget and forecast reports drive crucial decisions for a company’s future. However, one wrong input or inadequate data in the budget and forecast models can lead to big decisions doomed for failure. Just like a vehicle, corporate financial planning’s deliverables need to be well maintained to prevent costly mistakes.
- Quality Data – Vehicles require fuel to run; 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 quality reports to support business decisions. Inadequate data used in models will lead to unreliable reports deemed useless by executives. Without reliable planning reports, executives must make decisions for a company’s future with little support. Many factors play into determining data quality, such as the reliability of the source system, accounting for any manual changes, and the timeliness of capturing the 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.
- Fine-Tuned Models – 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 are examples of various parts in a corporate financial planning model. Whether these models are in a million-dollar system or in Excel, regular upkeep is critical. Failure to technically maintain these 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. By taking the time to regularly maintain these models, corporate financial planning will prevent a future costly mistake as a result of an insufficient model. Regular maintenance may even require completely rebuilding current parts of the model to remove legacy assumptions or recurring errors.
- Effective Output – Accordingly, 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 does not mean it is effective to its owner. For example, a convertible car may work perfectly but would be considered ineffective to 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. In other words, no matter how efficiently a vehicle runs, the effectiveness of that vehicle plays a large role in vehicle maintenance. Vice versa, a vehicle can only run effectively for a short time without regular maintenance. So, oil change on the way home today? Or, is it time to trade-in that convertible?
To read more on data quality for planning systems, read Like Putting Gasoline in a Diesel… How Bad Data Can Ruin a Host Analytics Tenant.