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Exponential Metrics for Digital Transformation

Chapter 3 | Networked leadership Guidebook

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:

  • Network Size: how many people, devices, data points, or other nodes are in a network.
  • Network Quality: how practical, functional, and attractive a network is to its members
  • Network Growth Rate: how much the network is growing or shrinking over time

Network Size

How many people, devices, data points or other nodes there are in a network


Third-Party Apps

The number of third-party apps or other digital offerings on a Multi-Sided Platform or marketplace

Private APIs

Number of APIs available to strategic partners and clients

Customer Validation (Users Willing to Pay for X)

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)

Algorithms (Beta)

Number of successful algorithm sets (or models) developed by a data science team

Data Points

Number of data points (total) across data sets

Network Size

Category of metrics for the number of members in a network (such as people, devices, organizations, or data points)

Internal APIs

Number of APIs for internal stakeholders (measures the quality and utility of network of systems)

Patents

Number of successful patents filed, which can increase network size or network uniqueness

Data Models (Alpha)

Number of preliminary algorithms or data models; can be affected by quality and quantity of data sets

Gross Merchandise Volume (GMV)

Total amount of money spent on a platform (an indirect measure of network size and quality)

Social Objects

How many social objects get shared (may be divided per user)

Unique Visitors

Number of unique individuals who visit a digital property (couple with network quality metrics to avoid vanity measures)

Minimum Viable Products (MVPs)

Number of MVPs released to market (pre-testing offerings for user alignment both improves quality and helps create an early network of potential users)

Customer Creation

Number of paying customers

API Calls

Times a given API has been accessed (may be divided by the number of unique users making the calls)

Network Quality

How useful, functional and attractive a network is to its members


Weak Signals

The number of points of information in a forecasting or trendcasting network

Third-Party Apps

The number of third-party apps or other digital offerings on a Multi-Sided Platform or marketplace

Network Quality and Engagement

Category of metrics for the utility and attractiveness of a network

Algorithms (Beta)

Number of successful algorithm sets (or models) developed by a data science team

Time on Site

Measure of network quality on content sites

Time On Page

A measure of network quality on content sites

Public APIs

Number of APIs available to the public (a specific measure is needed)

Core Action User Retention

Improvement of retention for new cohorts (users taking a core action in/for the product)

Internal APIs

Number of APIs for internal stakeholders (measures the quality and utility of network of systems)

Patents

Number of successful patents filed, which can increase network size or network uniqueness

Data Models (Alpha)

Number of preliminary algorithms or data models; can be affected by quality and quantity of data sets

Gross Merchandise Volume (GMV)

Total amount of money spent on a platform (an indirect measure of network size and quality)

Social Objects

How many social objects get shared (may be divided per user)

Social Object Shares

Number of social objects (like a video or status update) shared from or in a network

Frequency of Engagement

Amount of engagement per user over a period of time (usually 7 or 30 consecutive days); can indicate 'power users'

Social Object Engagement

Amount of engagement a given social object, or average social object, receives

Dollar Retention and Paid User Retention

Percent of users paying and average amount paid, indicating if users are getting strong value from a network

Daily Active Users

Number of users interacting with a service, app or offering per day

Utilization Rate

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)

Repeat Visits

Number of returning visits

Switching or Multi-Homing Costs

Measurable value to users from switching to a new network (measures network attractiveness)

Success Rate

Frequency of successful user matches (with another user or inventory) in a network

Network Internal Traffic Source

Amount of traffic generated inside a network vs. coming from outside it

Exit Rate

Percent of users who leave a service on a given screen, stage or functio. Indicates barriers or unattractive experiences

Active Users

Number of users actively using your platform (define 'active' specifically; use the same definition throughout).

Sell-Through Rate

Number of units sold in a period divided by the number of items at the beginning of the period

Prevalence of Multi-Tenanting

Number or percentage of users who are on more than one competing platform (Amazon and Alibaba, or Lyft and Uber)

Organic New User Percentage or Organic Share

For one-sided networks, organic new user share measures the number of users invited by their friends to improve experience; multi-sided networks, it can also measure desire for increased supply or demand.

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)

Energy Needed for Product to Become Effective for User

Amount of effort needed to reach the minimum threshold for a product to be useful (eg, Facebook's 'magic number' of 10 friends)

Customer Tickets

Number of customer tickets opened in a given time period (expresses either dissatisfaction or occasionally positive engagement)

Time From Feature Request to Deployment

Time between a feature being requested and it being deployed

Time From Bug Report to Bug Fix

Measures responsiveness of a software team to users, supports a high-quality experience and builds trust

API Calls

Times a given API has been accessed (may be divided by the number of unique users making the calls)

Network Growth

How much a network is growing or shrinking over time


Network Growth Rate

Category of metrics for the rate of growth (or attrition) for a network

Social Object Shares

Number of social objects (like a video or status update) shared from or in a network

Frequency of Engagement

Amount of engagement per user over a period of time (usually 7 or 30 consecutive days); can indicate 'power users'

Social Object Engagement

Amount of engagement a given social object, or average social object, receives

Dollar Retention and Paid User Retention

Percent of users paying and average amount paid, indicating if users are getting strong value from a network

Daily Active Users

Number of users interacting with a service, app or offering per day

Sell-Through Rate

Number of units sold in a period divided by the number of items at the beginning of the period

Prevalence of Multi-Tenanting

Number or percentage of users who are on more than one competing platform (Amazon and Alibaba, or Lyft and Uber)

Organic New User Percentage or Organic Share

For one-sided networks, organic new user share measures the number of users invited by their friends to improve experience; multi-sided networks, it can also measure desire for increased supply or demand.

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)

Energy Needed for Product to Become Effective for User

Amount of effort needed to reach the minimum threshold for a product to be useful (eg, Facebook's 'magic number' of 10 friends)

Retention by Location or Geography

For businesses with local network effects like ride-sharing services, how user retention in established markets compares to users in new markets

Power Users

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

Match Rate

Ease with which two sides of a marketplace or community can find each other

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