Incremental projects have a slew of metrics associated with them, ranging from end results (like revenue or profitability) to precursor KPIs (Key Performance Indicators).
The value (or distraction) of metrics has been covered in nearly every business publication in the last twenty years, but most of that coverage focuses on incremental metrics. These focus on the linear processes of organizations and are often premised on the belief that the entire business or process is fully knowable, predictable, and measurable.
However, leading innovations in the digital era are often based on network effects—the ever-increasing value of a network as more people, devices, or data points are added to it. Classic examples include telephone and train networks; more modern examples include social media networks and cryptocurrencies.
For projects based on network effects, progress towards metrics appears slow at first, so it's hard to know how it's going or show accountability for doing so inside large, skeptical organizations.
You can learn more about network effects in our guide to Thinking for a Digital Era, especially under "From 10% to 10X" and "The Exponential Journey."
Exponential metrics measure aspects of network effects:
How many people, devices, data points or other nodes there are in a network
The number of third-party apps or other digital offerings on a Multi-Sided Platform or marketplace
Number of APIs available to strategic partners and clients
Number of users explicitly willing to pay for something, even if they have not paid for it yet (can be measured by interest forms, deposits, etc)
Number of successful algorithm sets (or models) developed by a data science team
Number of data points (total) across data sets
Category of metrics for the number of members in a network (such as people, devices, organizations, or data points)
Number of APIs for internal stakeholders (measures the quality and utility of network of systems)
Number of successful patents filed, which can increase network size or network uniqueness
Number of preliminary algorithms or data models; can be affected by quality and quantity of data sets
Total amount of money spent on a platform (an indirect measure of network size and quality)
How many social objects get shared (may be divided per user)
Number of unique individuals who visit a digital property (couple with network quality metrics to avoid vanity measures)
Number of MVPs released to market (pre-testing offerings for user alignment both improves quality and helps create an early network of potential users)
Number of paying customers
Times a given API has been accessed (may be divided by the number of unique users making the calls)
How useful, functional and attractive a network is to its members
The number of points of information in a forecasting or trendcasting network
The number of third-party apps or other digital offerings on a Multi-Sided Platform or marketplace
Category of metrics for the utility and attractiveness of a network
Number of successful algorithm sets (or models) developed by a data science team
Measure of network quality on content sites
A measure of network quality on content sites
Number of APIs available to the public (a specific measure is needed)
Improvement of retention for new cohorts (users taking a core action in/for the product)
Number of APIs for internal stakeholders (measures the quality and utility of network of systems)
Number of successful patents filed, which can increase network size or network uniqueness
Number of preliminary algorithms or data models; can be affected by quality and quantity of data sets
Total amount of money spent on a platform (an indirect measure of network size and quality)
How many social objects get shared (may be divided per user)
Number of social objects (like a video or status update) shared from or in a network
Amount of engagement per user over a period of time (usually 7 or 30 consecutive days); can indicate 'power users'
Amount of engagement a given social object, or average social object, receives
Percent of users paying and average amount paid, indicating if users are getting strong value from a network
Number of users interacting with a service, app or offering per day
Percentage of time that time-sellers on the platform or marketplace are without satisfactory results (eg, drivers who have empty cars vs. those providing a ride)
Number of returning visits
Measurable value to users from switching to a new network (measures network attractiveness)
Frequency of successful user matches (with another user or inventory) in a network
Amount of traffic generated inside a network vs. coming from outside it
Percent of users who leave a service on a given screen, stage or functio. Indicates barriers or unattractive experiences
Number of users actively using your platform (define 'active' specifically; use the same definition throughout).
Number of units sold in a period divided by the number of items at the beginning of the period
Number or percentage of users who are on more than one competing platform (Amazon and Alibaba, or Lyft and Uber)
The percentage of new users who are referrals from other satisfied users (on one-sided networks like social media) or users wanting additional inventory (like 'guests' seeking new 'hosts' on multi-sided networks airbnb)
Amount of effort needed to reach the minimum threshold for a product to be useful (eg, Facebook's 'magic number' of 10 friends)
Number of customer tickets opened in a given time period (expresses either dissatisfaction or occasionally positive engagement)
Time between a feature being requested and it being deployed
Measures responsiveness of a software team to users, supports a high-quality experience and builds trust
Times a given API has been accessed (may be divided by the number of unique users making the calls)
How much a network is growing or shrinking over time
Category of metrics for the rate of growth (or attrition) for a network
Number of social objects (like a video or status update) shared from or in a network
Amount of engagement per user over a period of time (usually 7 or 30 consecutive days); can indicate 'power users'
Amount of engagement a given social object, or average social object, receives
Percent of users paying and average amount paid, indicating if users are getting strong value from a network
Number of users interacting with a service, app or offering per day
Number of units sold in a period divided by the number of items at the beginning of the period
Number or percentage of users who are on more than one competing platform (Amazon and Alibaba, or Lyft and Uber)
The percentage of new users who are referrals from other satisfied users (on one-sided networks like social media) or users wanting additional inventory (like 'guests' seeking new 'hosts' on multi-sided networks airbnb)
Amount of effort needed to reach the minimum threshold for a product to be useful (eg, Facebook's 'magic number' of 10 friends)
For businesses with local network effects like ride-sharing services, how user retention in established markets compares to users in new markets
Amount of activity by users who have logged in for a number of consecutive days (7 or 30 days, usually), often represented in a histogram
Ease with which two sides of a marketplace or community can find each other
