M2M valuation

Connected device applications are not all equal. Consumer-oriented devices may have a revenue generating life of 2-3 years while cars and industrial machinery a life of 5-8 years. In extreme cases, utility-like devices related to smart grid or smart city transport may be operational for even longer periods of time.

As a result of these variations, business developers and CFOs need suitable tools to manage both the risks and the rewards associated with different application opportunities. This is where valuation techniques become useful. They not only help to quantify new opportunities but they can also drive business model innovation.

Consider a simplified example of a batch of connected devices with a 7-year operating window. The service provider supporting the connected device application incurs three sets of cost from each of the following:

• selling the solution,

• providing the device hardware,

• and, operational costs to support the connected device once it has been deployed.

These costs are offset by revenues from set-up activities (e.g. professional services and sale of the device to the end user) and from in-service data traffic. The cash flow illustration below shows the contribution of each cost and revenue item, including a ramp up effect as the total population of 100,000 connected devices is deployed over an initial 3-year period. The cumulative cash profile for this example indicates a break-even point by Year-4.

The service provider’s incentive is to tune the business model (service proposition, operational delivery etc.) to become cumulative cash positive as early as possible. This also has to be achieved without introducing operational problems that may require costly, corrective intervention.

This may be achieved in one of several different ways:

• Sales costs – these can be lowered by offering standardized solutions and working with partners to originate sales more cost effectively. In some instances a high total cost of sales can be justified for a high volume deployment because the average cost of sale per device is acceptably low.

• Device costs – cost levels can be influenced by the choice of standardized components and decisions about functionality and quality of engineering. Providers should not overlook the possibility of avoiding device costs if the customer treats their acquisition as an outright purchase.

• Set-up revenues – there is anecdotal evidence that companies adopting connectivity solutions understand the value of design support activities and are prepared to pay for this as a professional service.

• Usage revenues - these can be charged in a variety of ways including data usage, by numbers of data sessions etc. The timing of revenues can also be managed either through up-front payments or strictly on a ‘when-used’ basis. Companies can also build predictability into their revenue projections by agreeing long-term deals. This variety of approaches can all help to improve the revenue profile which feeds into the cash position.

• Operating costs – the aim here is to keep costs to a minimum while ensuring that connected devices function properly. Platform technologies are the usual approach to handle the operational support and scale issues specific to M2M. Clearly, these costs will be influenced by the choice and cost implications of in-house vs. third-party provider platforms.

The different ways of optimizing the overall cash profile can be a useful prompt for business model innovation. For example, can device costs be tackled though a subsidy or lease-financing strategy in exchange for a longer contractual commitment? Perhaps operating costs can be lowered by offloading device management to customers via a toolkit of device probes and a device-management portal.

Applying quantitative data to each of the cost and revenue items allows a valuation to be placed on each connected device. This involves calculating the net present value of future cash flows. For example, consider the case of a 100,000 unit deployment where the cost of sales is $500,000. Assume that the service provider does not pass on the full cost of a device and incurs a cost of $20 for each one i.e. a partial subsidy. Furthermore, the service provider earns a set-up fee of $1,000,000, revenues of $2 per month per deployed device and operational costs of $1 per month per device. Applying a discount rate of 10% yields a net present value of almost $6.4m for the project or an average of $64 per device. This serves as a base to evaluate and compare alternative business model strategies.

With additional analysis, the prospects for extending services (account management, follow-on sales costs, possible replacement of devices etc.) for this deployment after its planned 7-year life can also be factored into this valuation.

The valuation framework can also be used to assess probabilistic events. For example, what are the commercial implications if a 10% device failure rate forces hardware to be replaced? Or, consider the example of a 5-year service life device that is designed using a 2G module. How is the life-time value of these devices affected if there is a 25% chance that 2G modules will need to be upgraded to 3/4G modules?

This illustration is for a relatively simple M2M deployment. It does not account for additional sources of revenue which can easily be factored into the analysis. I will return to this topic in a later post and to provide examples of specific revenue and cost benchmarks from different markets.

NOTE: Some of these ideas have previously been outlined in a study I conducted for the GSMA entitled - Connected Life: The Need for New Business Models (2012)