PREDICTIVE ALGORITHMS FOR DEPRECIABLE PRODUCTS & RE-OCCURRING SERVICES

Why might you need to predict the depreciation date of a product? Safety, for one. Accounting purposes, maybe. To sell replacement products, for sure.

In industrial and commercial settings, worn out equipment can cost more than just money and loss of efficiency; it can cost you your employee and customer’s safety. Predicting when parts and equipment will wear out is a proactive way to avoid injuries due to faulty equipment.

Amortizing depreciating equipment, furnishings and fixtures accurately can make a significant difference to your bottom line and its not always possible or practical to inspect all of your assets for one reason or another. A predictive algorithmic software could surely come in handy in these instances.

Last, but surely not least, are the retail applications on depreciable goods. In retail and service industries, customer retention is a key factor in the maintenance and growth of a business. When your customer needs a refill, re-stock, upgrade or replacement, you want to be sure they come back to you. But, every customer is different. So, how can you predict when it is time to pitch the next sale?

What if there was a software that was programmed to your specifications and precisely predicted when your customer’s product has depreciated and thus is in need of replacement?

This is exactly what we will be discussing.

The example we will be looking at is the new patented Tire Tracker Notifier™ software which, with minimal input, predicts when a particular vehicle’s tires are due for a change.

The purpose of a software solution is to automate the process as much as possible. So, firstly, the software is pre-programmed with average depreciation duration data for the product, tires in this example.

Next, every case is unique, so by entering as little as 1 data point these averages can be adjusted to a particular customer’s usage patterns.

So, here’s how it works. Each customer or product is paired with an identifier, in this example a Tire Tracker™ sticker, and entered as a line in the software. Then, the condition of the product and the date are marked on the sticker and in the program at regular or irregular intervals. That’s it. The software will then use a predictive algorithm to calculate the depreciation date for the product and notify the user to contact the customer.

A highly simplified example of the required logic is as follows:

CUSTOMER 1:
New product with average depreciation duration of 2.2 years.
This customer is not available for a product check, so only baseline data is used and the customer can be contacted after a period of 2.2 years.

Now, here is where it gets interesting.

CUSTOMER 2:
Used product with average depreciation duration of 2.2 years.
This can be notated as a 6 on a scale of 10-NEW – 1-FULLY DEPRECIATED
After 6 months, the product is noted to be at an 3 on the same scale.
So, if p = Points and t = Time,
Δp / Δt = 3 POINTS per 6 MONTHS= 1 POINT PER 2 MONTHS
Then, given that the product should be replaced at the time of full depreciation, this customer should be contacted in no more than 6 months from the date of the last reading.

CUSTOMER 3:
New product with average depreciation duration of 2.2 years.
This can be notated as a 10 on a scale of 10-NEW – 1-FULLY DEPRECIATED
After 1 year, the product is noted to be at an 8 on the same scale.
So, if p = Points and t = Time,
Δp / Δt = 2 POINTS per YEAR = 1 POINT PER 6 MONTHS
Then, given that the product should be replaced at the time of full depreciation, this customer should be contacted in no less than 4 years from the date of the last reading.

This is helpful in a number of ways. Firstly, contacting customers too late means the retailer runs the risk of losing the sale to a competitor. Contacting the customer too early is bothersome, unprofessional and inefficient. Lastly, not contacting the customer at all would result in reduced customer retention and, ultimately, lost sales.

The above example is a highly simplified version, however this technique can be used to incorporate multiple data points for higher accuracy and multiple variables for diverse circumstances.

This type of software can be designed to be easy to use as well. Simply enter a data point or two and the software displays “PRODUCT OK” or “CONTACT CUSTOMER.”

This can greatly increase the customer retention and sales for any business selling a depreciable product or re-occurring service. It can be used for large-scale accounting purposes or equipment maintenance applications, as well.

If you are in the automotive service field, check out TireTracker.co to see how this technique can be used to increase your tire sales.

Interested in benefiting from predictive algorithmic software in your business? Contact Drew for a custom designed software package. It could make you thousands, save you thousands and it costs a lot less that you might think.

See more at TireTracker.co