KPI assessment and measurement is purely speculative without reconciliation and verification of the core data. Proper grouping of related metrics and monitoring relative movement is also key to understanding change. For example; in the recreational vehicle industry where discretionary spending is driving sales, large ticket sales historically had a lag time behind inverted prime.
Forecasted seasonally adjusted COGS allows calculations of target seasonal inventory levels based on desired annual turnover. In today's business climate, understanding the complexity and relativity of KPI is crucial to long term success. Intuit and QuickBooks are trademarks and service marks of Intuit Inc., registered in the United States and other countries. Without trend forecasting of the metrics used to assess KPI, there is no indication of whether a business or market is on the mend, on the way out, or what may be the cause of a problem.
Viewing mounds of printed numbers without visualizing the trends and relative timing of key metrics becomes overwhelming for the most intelligent analyst. When seasonal trends are removed from sales data, a rolling quarter moving average compared to the linear sales trend visualizes market change directions. By today's standards, inventory based KPI, such as gross sales, gross profit and current inventory will get you about as far as the Wright brothers' first flight. The Red trend line represents the Quarterly moving average of actual sales after removing seasonal trends.
Keep in mind that trends can change due to outside conditions which are out of control of the business such as the recession of 2008-2009.

Manufacturer's representatives respect solid market information and are at most times more willing to help resolve real inventory problems rather than apply unsubstantiated pressure to increase inventory levels. Seasonal trend analysis and the ability to "normalize" metrics are the only true way to benchmark with other outside sources or company history.
When metrics are compared to other metrics, there are patterns that emerge, which cannot be seen by traditional assessment.
Understanding predictive analytics requires knowledge of relative timing and reaction between key metrics. When collectively monitored with inverted prime, you can add judgment to the equation, and adjust inventories in advance. Frankly, without two plus years of solid monthly data, my advice is to asses risk at your own risk.
However, understanding that the change in one metric will relatively have an effect on other metrics, which provides unfair insights resulting in advanced business decisions. With the understanding of inverted prime, fuel prices, new home construction starts, an RV company could adjust large ticket inventories and adjust for the market change with a couple months advanced lead time. The understanding of monitoring metrics holistically allows the birds-eye-view into the future. Furthermore, since nearly every business is seasonal, traditional KPI formulas used by most, are useless without applying seasonally adjusted annual rates (SAAR), trend analysis, and seasonality forecasting. Can you accurately predict target inventory levels without knowing your desired turnover, and forecasted COGS based on seasonal trends?
But once the results are properly grouped and displayed visually, analysis becomes much easier to understand.

Some reconcile floor plan accounts only because the lender sends a representative periodically for flooring checks. Try combining the analogy of "hitting the ground at full speed" with "its water under the bridge".
But for the most part, most businesses do not reconcile or verify the data enough to rely upon it.
With the aid of a few tools combined with solid judgment, book keepers and managers can become analysts and consultants.
One Live Wire from UPS) would be inactive because power supply is not available from UPS and batteries (Because it is Automatic UPS System). Live Wire from Main board to UPS) would be inactive because power supply is not available from power house.
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