Influencing Power Law Generative Mechanisms to Strategic Advantage in Scale-up Stage Technology Businesses

1. Dave Litwiller
Apr. 1, 2022
ENGINEERING
POWER LAW DYNAMICS
Influencing Power Law Generative Mechanisms to Strategic
Advantage in Scale-up Stage Technology Businesses
APR. 1, 2022
DAVE LITWILLER

2. BACKGROUND
• Many strategic and financial factors in high technology
industries follow Power Law or Power Law like
distributions, often creating winner-take-most end games
• Some common attributes and forms of Power Laws which
are frequently discussed:
• Pareto distributions and 80/20 heuristics
• Income distributions
• Market power concentrations
• Stock, commodity and crypto prices over time
• Fractals, in biology, the physical world and elsewhere
• Less discussed are the generative mechanisms which
give rise to Power Laws in the first place, and the
interventions to influence them

3. INTRODUCTION
• Power Laws can be created by many mechanisms
• Preferential attachment (a.k.a. rich get richer)
• Combinations of exponentially distributed phenomena
• Multiplicative processes in combination with a minimum threshold of
viability
• Optimization, including networks of agents, and processes of and
akin to natural selection
• Phase transitions
• One very high profile case in point in tech:
• Web3 unfolding right now
• The speed and inevitability with which Power Laws emerge in many
high growth technology industries makes influencing them a matter
great import and usually of lasting significance

4. DIFFERENCE BETWEEN
POWER LAW AND
NORMAL DISTRIBUTIONS
• The independence of individual events in the underlying
process which give rise to Power Laws (a.k.a. Cauchy or
Lorentz Distributions) are different than those which
create Normal Distributions (a.k.a Bell Curve)
Power Law
Distribution
Normal
Distribution
Individual Events Interrelated Independent
Memory Some Memory Memory-less

5. DIFFERENCE BETWEEN
POWER LAW AND
NORMAL DISTRIBUTIONS
• Graphically, the difference between Power Laws (a.k.a. Cauchy or
Lorentz Distributions) and Normal Distributions (a.k.a Bell Curve)
• Takeaways: Power Laws have tighter peaks, and fatter tails;
turbulence tends to cluster and extreme events are not uncommon

6. COMPLEX SOCIO-TECHNICAL
SYSTEMS
• One of the core generative mechanisms which give rise to Power
Laws in socio-technical systems under competition for
resources is a belief probability distribution of how agents in a
market or network react to a new event or opportunity based on
recent history:
Crowd
Anti-Crowd
Number
of Agents
Believe the
Opposite will
Happen
Believe the
Same will
Happen

7. SUBTLE SHIFTS,
BIG CONSEQUENCES
• Small changes in the symmetry of the belief distribution
can unbalance dynamics
• Asymmetry of the belief distribution gives rise over time
and cumulative events to very large changes and quasi-
stable trajectories, i.e. Power Laws
• A leading case in point is preferential attachment
mechanisms

8. FURTHER PLACES TO SEEK
OUT POWER LAW POTENTIAL
• Power Law dynamics also often unfold:
• Where exponential dynamics are at play in constituent
technologies, business operations, and the industry
• Where there are multiplicative factors at work
• Where rapid change, adaptation, and institutional learning
are most important to survive and thrive
• In transitions such as crises, or where an industry moves
from an amorphous protean state to something more
ordered and settled

9. LEVERAGE POINTS
• For high growth technology businesses, Power Law
generative mechanisms drive both individual and
combined effects for almost all parts of the business,
including:
• Capital raising, liquidity and valuation
• Customer, user and partner acquisition and retention
• Talent acquisition and retention
• IP
• Data and AI models
• Access to and sway over the most constrained resources
• Regulatory influence
• Platform and interoperability standards
• Community, media and public relations

10. INFLUENCING
OUTCOMES
• There is a well-worn playbook of high-level techniques to
try to advantageously influence Power Law industry
dynamics
• These have become almost trite in many cases, and
lessened in effectiveness
• In some situations from overuse and imitation
• In others from the predominant influence of the largest and
best resourced ecosystem players
• Often now, a more adapted approach is necessary to
regain efficacy affecting Power Law dynamics and
outcomes, particularly at the scale-up stage

11. RECOMMENDATION
• Consider for starters the generative
agent probability distribution
mechanism which leads to
preferential attachment
• Then, for each aspect of the
business model and industry
dynamics, revisit how the
distribution could be shifted in a
more favourable way

12. ANALYTICAL METHOD
• Useful insights can usually be gained analyzing to root cause and
with sufficient statistical depth the choices agents made in recent
decisions about engaging or otherwise working for or with the
company:
• Why those who normally follow or match the crowd did so again?
• Why those who usually follow the crowd made a rare exception?
• Why those who are usually contrarian made an exception?
• Why those who are regularly contra the herd continued to be so?
• As an example, an existing process in many well run scale-ups
which is similar to this:
• Periodic deep dive win-loss analyses in sales, often as part of
monthly or quarterly business reviews

13. ADVICE
• Don’t solely look at the extremes of the belief distribution, as
many analytical methods often encourage
• Narrowly looking at agents most strongly and consistently for
and against only tells part of the story, even if those are the
most vivid and anecdotally powerful accounts
• Especially for very competitive personalities, and those given
to see extreme positions as the only ones that can be
intellectually rigorous, it can require effort to see internal
dynamics and the external ecosystem in less dichotomous
terms
• Instead, a look across the spectrum of agent perspectives,
information sources and motivations
• Doing so provides a larger picture of current dynamics and
potential influence points from which to affect more positive
outcomes

14. ANALYSIS OF OTHER
GENERATIVE MECHANISMS
• Take an inventory and list the other generative
mechanisms which give rise to Power Laws that are
credibly at play, or likely will soon be
• Map the larger likely flows of amplifying and attenuating
feedback among them, to determine the predominant
directions of causality and rates of impact
• This is more art than science
• It is usually better to be quick and approximate rather than
slow and ultra-detailed in this kind of causality analysis
• At the same time, consider the role of historical factors
which likely used to have Power Law generative influence
which may now be weakening with time and changing
circumstances

15. MOVING FROM
ANALYSIS TO ACTION
• Based on the foregoing causal analysis, list the credible
possibilities for improvement
• Rank them, and group related interventions
• Ranking factors to consider:
• Magnitude of attainable impact
• Growth and likely reliability of impact over time
• Resources required, as well as support structure, cost and
ongoing maintenance
• The key to success:
• Actuating on signal vs. noise; to be able to consistently
pursue the most impactful efforts, while at the same time
avoid being consumed by the constant thrum of less
significant issues

16. ADVICE
• Internal:
• The foment of ideas and pace of execution to come out on
top in Power Law emergence or reform requires a lot of
trust among people
• Trust has to be based on mutual respect and quality of
individual contribution as circumstances evolve, in balance
with the ability to have a vigorous debate about competing
ideas and approaches
• Conflict is necessary, but about ideas, not about people
• People need to trust that their colleagues are moving
forward in their ideas and capacity to stay at the forefront
of the industry, and can execute quickly once plans are set

17. ADVICE
• External:
• Periodically reassess the question, “What would a
predominant player in our industry do to gain leverage
from the present situation?”
• Then, consider anew what can be done at the scale-up
stage to create or synthesize similar influence

18. SUMMARY
• Many forces in technology industries promote and reinforce Power
Laws, among them
• The financial model of venture capital
• Network effects and lock-in effects
• Industry evolution, maturation and power concentration
• Increasing returns to scale and scope
• Self-similarity in that predominance in one domain or scale often delivers
significant advantage in others
• Endogenous and exogenous shocks and crises
• Significant competitive advantage flows to companies with the ability to
both identify and activate multifarious interventions which can shift
Power Law dynamics during their emergence and evolution
• Thorough analysis of Power Law generative mechanisms contributes to
creating a wider range of options to maximize impact and efficiency for
gaining industry influence and superior business economics

19. FURTHER
DISCUSSION
For additional dialog analyzing and influencing industry
Power Law dynamics:
dave.litwiller@communitech.ca