One of the biggest variables to optimising a mobile device population is deciding how many devices to keep in a spare pool to issue workers when their primary device needs maintenance. It is important to get the decision right, because the spare pool is an important component of the total cost of your mobile environment. The spare pool decision can be based on data and informed projections of device failure rates and life cycles, however, most organisations don’t have this data, and base their decision on their appetite for risk (or on a hunch).

If you don’t keep enough mobile devices on hand you risk disrupting operations and losing productivity because workers won’t have the tools they need to do their jobs. That disruption can be easily avoided by keeping a lot of spares, but that creates another problem: inefficient use of capital. An oversize spare pool locks a lot of your money into underutilised devices, and prevents the capital from being used in ways that can provide a stronger, more immediate benefit to the business.

The decision is too important – and potentially too costly – to be left to a hunch. Mobile device analytics lets you make an informed decision by giving you accurate data about the size and status of your current mobile device population, and ongoing, real-time information about device health so you know when to expect to service or replace them.

One of the reasons it has been hard for organisations to predict their future needs is because they base their projections on incorrect assumptions about their current mobile device populations. Almost every customer we’ve worked with has learned that the number of devices it has available for work is far different from the number it thought it had. In one extreme example, a customer learned that 60 percent of the mobile devices it had purchased were not being used.

Many organisations buy new devices to replace those that they consider lost, when actually the “lost” devices are still within the enterprise. They may appear lost because their batteries are dead or their wireless connections failed, so they can’t be detected.

Mobile device analytics can prevent these problems. It provides performance monitoring that can prevent battery and wireless failures from occurring, and also supports device location tracking. Those and other features help keep more devices available more of the time, so customers need less in their spare pools.

Let’s Look At The Numbers

It is typical for 30 percent of an organisations’ mobile devices to be unused on any given day. That’s a pretty significant number!

This percentage was calculated based on our work with a variety of customers with device estates ranging in size from hundreds to tens of thousands and data from anonymous visitors that use our online ROI Calculator to establish the savings that could be made by using mobile device analytics. If we consider a company with 1,600 tablets and an average hourly labour rate of £30/$39.00 per hour, reducing the underutilisation rate from 30 percent to 20 percent would save this organisation £39,600/$51,780 annually.

Mobile device analytics allows organisations to safely reduce their spare pools/unused device levels to 10 percent of the population. In this same case, that would produce £79,200 /$103,560 in annual savings. Before you decide how many devices to stock in your organisation, decide to use mobile device analytics to get an accurate baseline of what you have, and to get the insight needed to keep them running more reliably. When planning the size of your mobile device population you are essentially deciding whether to have more devices or to have more cash.