Contents
"...some words of wisdom Mike Arrington once shared with me. He said “numbers always ruin a good story.”
What Mike meant by this is you can raise a seed (or Series A) on a story. But at some point, you will have numbers; users, user growth, revenues, and revenue growth. You will also have a burn rate. And those numbers will become the thing you are judged on and your nice story will be “ruined” by the numbers." -- http://avc.com/2015/03/numbers-can-ruin-a-good-story/
Key Metrics
(and typical values)
What you want to do is get 'results' and increase the probability/amount of 'success', but you can't quantify or measure 'results' and 'success' directly.
Good characteristics of a KPI (key performance indicator) metric:
- precisely, objectively defined. E.g. the word 'customers love us' is, by itself, imprecise, but the 'net promoter score' is precise.
- can be measured using tools at your disposal. If you're product is a website, "makes customers smile" is precise but it's hard for you to see if they are smiling when they are looking at your website. Similarly, "how often customers mention us to their friends" is hard for you to measure, but "how likely customers say they are to mention us to their friends on a survey" can be measured, as can "how many new signups claim they were referred by a friend".
- if you could cause the metric to increase without changing anything else, that would cause you to become more successful. E.g. when 'revenue' goes up, that has a direct effect of increasing profit; if you could increase revenue without increasing costs or decreasing quality etc, that would have a direct effect of making you more successful.
- effort to make the metric better will generally have more positive than negative indirect effects. E.g. although some ways to increase revenue would hurt you (such as selling items below cost, or selling shoddy goods or services), much of the time things that increase revenue help.
- effort to make the metric better may have good side effects (e.g. if make yourself more well-known in an effort to increase revenue, that might also draw investors and business partnership opportunities).
- is not something that is good in small amounts but bad in large amounts. For an example where this is not the case, imagine that an internal study found that taking some time to solve customers' problems actually caused them to think they you were giving them better service; even if that were true, you wouldn't want to make '(increasing) customer wait time' a metric because surely there is a point beyond which increasing customer wait time would make customers less happy rather than more.
- the metric is 'almost a definition of success', that is, it is merely one way to precisely state something that you think is part of being successful anyways. E.g. if someone told you that they were using 'profit over the past year' as a metric, you'd probably say, that sounds reasonable, when people say a business is successful, part of what they mean is that it makes a lot of money.
In addition, a metric should be something that you'd like to adopt as a goal. Like any goal, it should:
- be something that you think is worth focusing on, to the exclusion of other things, because you think you can change it a lot. For example, if you are a distributor/reseller of a customized product that takes weeks for the OEM to produce, don't make 'time from customer order to delivery' your metric because you can't do much about it (maybe you could deliver it the same day it arrives at your location instead of the next day, but this is a small fraction of the total).
- not be misaligned with your company mission/vision/values/goals/business model/strategy. For example, if your strategy is to ship low-volumes of only the highest-quality products to discerning customers, then metrics regarding margins and quality fit better with your strategy than metrics regarding reduction of cost and increasing sales volume.
People recommend focusing on 3-5 metrics.
There are some financial metrics (such as revenue and profit) which are important across industries. Beyond these, different industries and business models have different metrics which are most important. It's worth trying to find out what metrics other companies in your industry, or who have your business model, use.
Basic financial metrics
SAAS metrics (software-business-specific)
- Monthly Recurring Revenue (MRR)
- Churn
- Cost to Acquire a Customer (CAC)
- Average Revenue Per Customer (ARPU)
- Customer Lifetime Value (LTV)
- average customer rate of return (J ratio)
- Average Cost to Serve (ACS)
- renewal rates
Links:
Consulting metrics
I hear that consulting often uses revenue, rather than profit, as a metric for partners. I'm not positive why this is revenue and not profit, but presumably it's because, as consulting is not a scalable business model, the partner can't do much about costs; the consulting firm is billing by the hour, and the primary cost to the firm is people's time, and a given person assigned to a project will have a set rate that they are paid.
todo:
"In SaaS?, you’d try to get a 3X ratio for CAC:LTV" -- [1]
" Key Financial Indicators
All three indicators are important, but emphasis shifts depending on stage:
Cash (Early Stage: Pre- Product/Market Fit)
Run Rate (Growth Stage: Post- Product/Market Fit)
Annual Revenue (getting ready to IPO)"cash (and runway):
- good for 'early stage'/ pre-product/market fit
- often cash accounting is good for this stage
- crucial metric is runway; "the timer has started"
- each month, look at:
- how much money is in the bank
- how much the money in the bank decreased from the previous month ('net monthly burn rate') (note: if you have income from the business then the total amount of money you spent may be greater than the net monthly burn rate, because the net monthly burn rate is income minus spending)
- 3 month running avg of that number ('3 month running avg monthly burn rate')
- how many months of runway you have left (extrapolated from monthly burn rate) (money in bank divided by monthly burn rate)
- how many months of runway you have left (extrapolated from 3 mo running avg burn rate) (money in bank divided by 3 mo running avg monthly burn rate)
- note: should begin seeking more financing if you have <= 6 mo runway
run rate:
- good for post-product/market fit but pre-IPO, eg when the company is rapidly growing and reliant upon financing
- often accrual accounting is good for this stage
- Annualized Run Rate: take the revenue earned in the most recent quarter and multiply it by 4
- note: an acronym for this, ARR, is ambiguous because ARR can also mean Annually Recurring Revenue
- Annually Recurring Revenue (SAAS-specific): take the annual contract value of all existing subscriptions as of the end of the most recent quarter
- if accrual accounting is being used, and the company is growing, then Annually Recurring Revenue includes subscriptions that can't yet be recognized as revenue. This is because even if it is paid upfront, in accrual accounting, a subscription is not recognized as revenue until it is 'earned'. For example, if a customer pays $120 upfront for a 12-month subscription, the SAAS company doesn't earn anything immediately, but then earns $12 of this each month (by providing the service that the customer paid for). The $120 is called 'deferred revenue' (which is not counted in revenue, at least not immediately) in accrual accounting. But the whole $120 is immediately counted in the Annually Recurring Revenue formula.
- deferred revenue is good, not bad, because it allows the company to finance growth out of the deferred revenue rather than seeking more investment. It's like an interest-free loan.
- note: a non-GAAP measure. In a growing SAAS company, this number is typically larger than Annualized Run Rate. Make sure investors, journalists, etc don't mistake your Annually Recurring Revenue numbers for revenue numbers!
- note: an acronym for this, ARR, is ambiguous because ARR can also mean Annualized Run Rate
- to make the Annualized Run Rate/Annualized Recurring Revenue distinction even more confusing, even though these are already projections in a sense, you will often want to have forecasts of all three of revenue, Annualized Run Rate, Annually Recurring Revenue at some timepoint in the future (eg six months from now). This gives you six quantities in total: current revenue, current Annualized Run Rate, current Annually Recurring Revenue, projected revenue, projected Annualized Run Rate, projected Annually Recurring Revenue
- Annually Recurring Revenue may be a good metric to use as a base for multiples when computing SAAS valuations
Links:
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" Some of the most common SLAs I have seen used are:
Availability: the percentage of the time the service is operational. While it is tempting to want to have a system that has 100% availability, achieving this can be really difficult, as well as expensive. Even large and critical systems like the VISA card network, Gmail or internet providers don't have 100% availability - over years, they will be down for seconds, minutes or hours. For many systems, the four nines availability (99.99%, or about 50 minutes downtime per year) is considered high availability. Just getting to this level is quite the work usually, to get to.
Accuracy: is it ok for some of the data in the system to be inaccurate or lost? If so, what percentage is acceptable? For the payments sytems that I worked on, accuracy needed to be 100%, meaning no data was allowed to be lost.
Capacity: what expected load should the system be able to support? This is usually expressed in requests per second.
Latency: in what time should the system respond? What is the time that 95% of the requests and 99% of the requests should be served? Systems usually have a lot of noisy requests, hence the p95 and p99 latencies are more practical usage in the real world." -- [2]
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https://docs.newrelic.com/docs/apm/new-relic-apm/apdex/apdex-measure-user-satisfaction#
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"There is a rule of thumb in SaaS? that you should eventually reach annual revenue equal to the amount of capital invested. " [3]
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