KPI measurement as a snap shot in time is a risk in itself. 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. Seasonal trend analysis and the ability to "normalize" metrics are the only true way to benchmark with other outside sources or company history.
KPI assessment and measurement is purely speculative without reconciliation and verification of the core data. So when someone asks if you can really measure risk, the answer is yes. Do most practice reconciliation? Most businesses reconcile their bank balance. Few reconcile inventories more than taking annual inventory. Some reconcile floor plan accounts only because the lender sends a representative periodically for flooring checks. But for the most part, most businesses do not reconcile or verify the data enough to rely upon it. The adage, "garbage in-garbage out," is especially true with KPI measurement.
Steps to identify the direction of any metric, company or market:
- Calculating seasonal trends of the metric
- Remove trends from data (Normalize or Seasonally adjust)
- Apply linear trend to the normalized metric and chart on a graph comparing quarterly moving average of the same normalized metric
- Monitor actual metric with forecasted metric on an additional graph
Proper grouping of related metrics and monitoring relative movement is also key to understanding change. Viewing mounds of printed numbers without visualizing the trends and relative timing of key metrics becomes overwhelming for the most intelligent analyst.
Assessing KPI strategies without the history & the tools of budgeting and forecasting software is asking for failure. Frankly, without two plus years of solid monthly data, my advice is to asses risk at your own risk. It has come time that the lender, CEO, department manager, and even the employee should require monthly metrics to monitor performance and bring awareness of changing trends. This practice nurtures responsibility and "taking ownership".
KPI monitoring and based totally on mathematical analysis is ridiculous. With the aid of a few tools combined with solid judgment, book keepers and managers can become analysts and consultants.
Predictive analytics is on the forefront of analysis. It also encompasses "Relative timing" of other metrics. When metrics are compared to other metrics, there are patterns that emerge, which cannot be seen by traditional assessment. 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.
For example; in the recreational vehicle industry where discretionary spending is driving sales, large ticket sales historically had a lag time behind inverted prime. Fuel prices and a few other economic metrics impact sales as well. Understanding predictive analytics requires knowledge of relative timing and reaction between key metrics. 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.
Forecasted seasonally adjusted COGS allows calculations of target seasonal inventory levels based on desired annual turnover. When seasonal trends are removed from sales data, a rolling quarter moving average compared to the linear sales trend visualizes market change directions. When collectively monitored with inverted prime, you can add judgment to the equation, and adjust inventories in advance. The understanding of monitoring metrics holistically allows the birds-eye-view into the future.