Revenue Is A Trailing Metric

Revenue Is A Trailing Metric

An interesting discussion I heard recently was “how can we enhance an organisation’s ability to hit its targets”?  The natural response is to ask “how do you hit a target” and the answer of course is that you can’t. You can’t go out and hit a target because the target (sales, in this case) is a trailing metric. To hit a sales target, you need to make sales. To make sales, you need to perform some kind of sales activity, i.e. get in touch with customers. So it follows that hitting target is not an activity, but an outcome, and performing sales activities is one predictor for whether you reach this outcome or not.

An easy way to reverse engineer this logic is to ask:

What are the lead metrics for [ desired outcome ]?

A lead metric is a metric that predicts the subsequent performance of another metric in some relatively reliable manner – that is to say there is at least a somewhat mechanical relationship between them.

If your goal is to hit a sales target, the lead metric for a sales target might be the number of sales calls you make. But of course sales calls itself is only an intermediary lead metric. What is a lead metric for sales calls? There are multiple factors involved in hitting sales targets (staff quality, motivation, incentives, etc), but a decent lead metric for the number of successful sales calls might be the number of high quality leads generated.

You may or may not have any control over lead generation and there are various types of lead generation. For example web traffic is, in an increasingly large number of cases, a lead metric for lead generation. What is the lead metric for web traffic, or what if you have no web traffic? Your lead metric might be advertising dollars, activity in your distribution channel (what/how many campaigns did you run?), content marketing quality/volume (advertising by another name), or something else entirely, such as participation at trade shows or the ability to get featured in the media or important journals.

Lead metrics are also tricky – for example, the amount of steel ordered by a manufacturer is a lead metric for the number of cars manufactured, which is an important lead metric in the number of cars sold, which clearly leads revenue and profit. Yet it is hard to see steel purchased as a reliable predictor of earnings because car sales as a metric is entirely dependent on the ability to sell a car. I doubt if it’s possible to quantitatively screen car manufacturers for their intrinsic ability to sell a car, but that I suspect that is the truly crucial metric. (A decent lead metric for a change in car sales might be changes in the availability of financing).   Likewise, hours/dollars spent on software development is a vital lead metric for the production of good software, which is vital for revenues and customer retention. But then, a lot of start-ups fail and pure hours spent on a task don’t guarantee any sort of quality or outcome. Similarly, many “mediocre” products succeed because they nail distribution and the sales process.

Likewise, it is not always easy to define the correct lead metric to focus on. You might think the whole purpose of a gold miner is to mine gold. But is its true purpose to mine gold (volume) or to maximise the price it receives for the gold it mines (value creation)?  If you think about a business for a while, you can often come to some interesting conclusions.

It’s not easy to find “truth” in lead metrics, but through the process of asking questions, you can pretty easily reverse engineer a customer funnel. It is widest at its top (web traffic), gets narrower down the middle (number of people that sign up for your free trial), and pretty skinny down the bottom (people in your credit card funnel entering their payment details in). This approach ignores conversion – if you can sell a product better, you don’t have to grow your lead metrics – but that’s a story for another time.

The point to my story is that revenue exists at the very end of this process. Revenue is a trailing metric for all of the activity that has gone before.

A common investing trap is to look at the cart before the horse. Setting aside bad accounting for now, revenue is – on average and across the business universe – an OK lead metric for gross profits and EBITDA and net profit and cash flow. If you have a software company with 80% gross margin and strong retention, revenue of course is an excellent predictor of the intrinsic value of the business. Yet revenue itself is a trailing metric for a substantial amount of process that is not superficially visible.  The implications of this are strong and not new – they go at least as far back as Phillip Fisher’s “scuttlebutt” method in Common Stocks and Uncommon Profits.

Still, if true, this statement implies that by the time you are buying a company with strong revenue growth (trailing metric), this has already potentially been priced in by more sophisticated investors (we have seen stark examples of both under- and over- priced stocks with growing revenue in Australia in recent years). The other side of the coin is that if you pay more attention to lead metrics, you may be able to be quicker on the uptake, arrive earlier on the scene, and achieve generally better performance than the wider market.

There are various approaches for evaluating lead metrics and I am no sage when it comes to benefiting from them. However, there several methods that I am aware of and use myself. In no particular order – first is a metric that I call “Marketing ROI”. It is somewhat company-specific, but I define it as average new customer revenue added in the current year divided by average marketing spend in the current/prior year (depends on revenue recognition policy and is particularly useful for a subscription product). It is not great because it is a bit slow and there is not always a direct relationship (some % of marketing spend is always about brand recognition, not customer acquisition), but if you can understand the quantitative elements that will drive sales, you can use this metric to validate whether the qualitative process is working (Xero performed excellently on this metric).

Second, R&D spend as a percentage of sales is a decent predictor of future growth in many cases, albeit very well known. Third, web traffic is another obvious one and many professional investors watch Alexa rankings and similar. Fourth, the number of features added and the length of the development cycle may be a reasonable measure for software companies (in concert with some kind of quantitative R&D spend metric and/or a qualitative customer response metric). Fifth, many professionals track metrics like number of developers or number of sales staff added, number of new leases acquired, traffic in car parks/truck volumes, et cetera. Sixth, in primary and secondary industries it’s usually very possible to get good lead metrics on pricing, capacity expansion and similar – but hard if you’re not in the industry. Seventh, many investors track customer reviews and I have heard theories that some barrier such as > 4.5 star rating may be decent for discriminating between between growing and flat same store sales. Eighth; scuttlebutt.

Lastly, from a more theoretical perspective, it ought to be possible to adjust “growth stock” earnings to arrive at some kind of measure of “reinvestment value added”. For example if you have two identical businesses and one of them reinvests 95% of its profits in R&D and hiring new staff (and the latter reinvests nothing), the former should theoretically trade at a substantially higher P/E multiple (because its profits are far lower due to this reinvestment, plus its future growth prospects should be stronger). However this is more or less the “holy grail” of detecting attractive investment prospects via accounting, and there are a large number of  VC and private equity firms trying to directly and indirectly capture this possibility via a variety of strategies. Nevertheless I think it is an important concept to keep in mind.

I expect there will be many other methods that I’m not aware of – not least because the most powerful ones are potentially quite profitable. And then you could approach lead metrics from the opposite end and ask: Are people even willing to spend money on this product?  Lead metrics are imperfect, but the point is well worth considering:

Revenue is a trailing metric and investors will benefit from increasing their focus on the metrics that lead revenue.

Food for thought.

I have no position in any stocks mentioned. This is a disclosure and not a recommendation.

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