Special K-Factor

With that out of the way, let’s examine some other variables that can make or break your delivery forecasting:

The Reason for the Seasons – If you think customers’ K-Factors don’t fluctuate throughout the year, you would be wrong. A car has a range of MPG for city and highway driving. Also, if you like to spend your summers doing burnout contests you can bet your MPG will be even lower. Similarly, sometimes homeowner’s usage patterns are different in different seasons. A system that allows seasonal K-Factors, and also allows you to adjust the season dates based on your geography, can be a great benefit. After all, spring in Bangor, Maine is not the same as spring in Annapolis, Maryland…except for last winter.

Hot Water – You can also get yourself in some hot water if you don’t have a good way to account for hot water usage. Since hot water usage is year round, some systems use a second degree day clock and fictitious “summer degree days” to account for it. I find the idea of summer degree days confusing because it muddies the idea of actual degree days being a measurement of how cold it is below 65 degrees. I prefer the baseload or gallons per day calculation. A seasonal K-Factor plus a seasonal baseload is a great way to account for year-round usage in a more logical manner and keep you out of hot water.

Pull! – That’s a skeet shooting reference and also a reference to doing delivery pulls, because in both skeet shooting and delivery pulls, you want to be as accurate as possible. Your system should allow you to fine tune your pulls by showing “what if” scenarios for pulling ahead and showing you more specific customer information to help you better prioritize when you are running behind. Better delivery pull functionality means more accuracy and better total delivery optimization.

Adjusting to the Real World – Many systems will also automatically adjust the K-Factor and baseload by comparing the projected delivery to the actual. This is usually done within limits so that a single anomaly doesn’t throw someone way off, but it’s a great way to keep the forecasting in tune. Everyone needs a little reality check now and then.

The Exception to the Rule – As many people have pointed out, K-Factor systems are not perfect. That’s why it’s critical to have a good exception-based reporting mechanism to allow you to review customers who, for one reason or another, are way off from what the system predicted. But remember, using your exception report is like brushing your teeth. For best results, do it regularly.

Big Brother – Lastly, there are those customers who despite your best efforts are just unpredictable, like the guy who likes to have random propane bonfire parties. You may never be able to predict his usage, and that’s where tank monitoring can be your friend. Tank monitoring is an investment, but if you target it for just the small percentage of your customers who have the most erratic usage, it can be a smart investment. Big brother is watching…in a good way.

Hopefully this helps. And remember, with some minor adjustments to your forecasting practices, you’ll soon be eating a hearty breakfast of optimal drops with a side of great bottom line improvements. Yummy.