System supports the amount of years of historical actuals that our organization requires

Description

Historical actuals represent past data, be it annual, quarterly, monthly, weekly or daily financial data, which can be used to analyze trends over time, assess performance, and form future strategies. This broad requirement expects that the CPM system will not limit the amount of historical data to a number of periods that devalues the system and creates a need for offline files for the user.

Example Use Case

Scenario: An automobile manufacturing company maintains 15 years of their sales, revenue, and expenses over the past decade. Due to their planning process being in Excel, they are forced to split their historical data up into several disparate files.

Solution: The CPM software can store decades of historical actuals, making the data easily accessible and sortable for the team. This allows the company to easily apply predictive methods to this robust historical data, making their forecast more accurate. These now take seconds vs the days it used to take parsing Excel files.

Considerations

Many products on the market will limit the amount of historical data to less than 5 years, or a total amount of years including planned data. For example, you may only be allowed to include 5 years of data. If you have a 3 year plan, only 2 years may be historical. This makes using predictive methods or seasonal drivers much less reliable. It also encourages users to keep historical data offline for reference which only serves to devalue the CPM system.

Take a look at your existing Excel files and determine how much historical data is there that is normalized and can be loaded into a CPM tool. Confirm with the vendor that they can take all of it, not just the last year of actuals.

Questions to Ask a Vendor

• Historical Data Capacity: Can your system handle 'x' years of historical actuals we require for our organization? What is the maximum storage capacity your software can handle?
• Scalability: How does your system scale as our organization grows and accumulates more data over time? Can it handle our data storage requirements for the next 5 years?
• Other Limitations: What is the downside to keeping X years of historical data? Should we expect slowdowns?