Leading tools to help prepare for and to navigate increasingly turbulent times for scale-up stage tech firms: - Scenario planning - Productivity enhancement drivers, particularly for knowledge-based work - Instrumenting and monitoring revenue generation dynamics for signs of significant market and customer changes - Individual, group, and institutional methods to increase the velocity of learning and adaptation, as well as distributed action - Increasing awareness and sensitivity to changes in customer value proposition and adoption decision mechanics

1. Dave Litwiller
March 30, 2023
MARKET VOLATILITY
CONSIDERATIONS FOR
SCALE-UP STAGE TECH COMPANIES
IN 2023
MARCH 30, 2023
DAVE LITWILLER

2. BACKGROUND
• It looks like increased economic and business volatility
will be with us for a while
• Partial causes:
• Inflation which is more than transient
• Higher interest rates
• Tightening credit
• Quantitative tightening
• Military conflict
• There is continuing potential for further shocks:
• Financial system, macroeconomic, geopolitical and supply
chain

3. BACKGROUND
• The outlook for the second half of 2023 and potentially
into 2024 is a growing likelihood of a recession, or at least
a significant slowing of growth
• As a slowdown takes hold, expect further disruptions from
the cascading reckoning in both the private and public
sectors from the excesses of the prior decade+ of
historically low interest rates combined with extraordinary
fiscal stimulus

4. OVERVIEW
• Today’s discussion: The leading tools to help prepare for and
to navigate increasingly turbulent times for scale-up stage
tech firms:
• Scenario planning
• Productivity enhancement drivers, particularly for knowledge-
based work
• Instrumenting and monitoring revenue generation dynamics
for signs of significant market and customer changes
• Individual, group, and institutional methods to increase the
velocity of learning and adaptation, as well as distributed
action
• Increasing awareness and sensitivity to changes in customer
value proposition and adoption decision mechanics

5. SCENARIO PLANNING
• What it is? A strategic planning method pioneered in the
1970’s to help prepare for future uncertainties and
disruptions
• Scenario planning is based on developing a range of
plausible, internally consistent narratives for the company
and its industry
• Each scenario is not designed to be a prediction or
forecast
• Instead, the scenarios collectively are tools to help leaders
explore a range of potential outcomes and prepare for
different contingencies

6. SCENARIO PLANNING
• Suggested approaches for scenario planning:
• Consider a quantitatively wider range of qualitatively
different scenarios as catalysts to strategic thinking vs.
what would have been used in recent years

7. SCENARIO PLANNING
• Typically heading into a likely downturn, look at financial ranges 2*
or even 2.5* of what would be considered during more benign
business conditions
• Scenarios should be different enough to create mutually exclusive
choices in prospective strategy and execution to create meaningful
contrast, choice, and discussion about frames of reference and risk
• Spend time talking about the conditions which would constitute
sufficient signal strength for the governance and leadership to
switch from one scenario to another among a range of plausible
possibilities as time and circumstances advance
• Beyond financial dimensions of each scenario, be specific about
ramifications at a minimum for technology, product, target markets,
customer development and enabling operating capabilities

8. PRODUCTIVITY
GROWTH
• One thing which may be different with this economic
slowdown and future recovery, given the pandemic-era
changes in the labour force and continuing low
unemployment: A stronger divergence between firms which
can generate higher, sustainable productivity vs. those which
cannot
• Predominantly body shop methods for growing and
expanding businesses are likely to be difficult to sustain
• The leverage of productivity growth will potentially raise the
stakes in at least two areas with widespread applications and
implications:
1. The use of generative AI in knowledge-based work
2. Robotic process automation (RPA)

9. GENERATIVE AI
• A few things which are becoming clear already from the rapid
uptake of tools like ChatGPT, Dall-E, Copilot and their peers:
• Used well, they really can enhance productivity for many
kinds of knowledge workers
• Using them to advantage depends on users having
• A lot of context for the problem domain and solution space
users are working in
• Ability to abstract their needs/problems correctly to get the
best out of the AI,
• Sufficient dexterity to quickly probe multiple possibilities,
usually through what is increasingly known as prompt
engineering, and,
• Enough domain knowledge to keep the AI tools on track
(sidestepping hallucination and nonsense answers)

10. GENERATIVE AI
• Generative AI is already showing strong impact in a wide
range of knowledge work, including
• Generating ideas, arguments and counterarguments
• Writing prose and generating images
• Conducting background research
• Coding and debugging
• Performing data analysis
• And, further domain-specific abilities

11. GENERATIVE AI
• Enhancing capabilities in these realms has profound
implications for boosting productivity in many scale-up
stage tech businesses
• The impacts are likely to be strong enough that this won’t
be a neutral event
• Firms which adopt these technologies and practices better
than their competitors will get ahead; those which do not
will fall behind

12. GENERATIVE AI
• Two main acceleration forms in creative knowledge work:
• Divergent phase, through suitable seeding, increasing the
range of plausible options in set-based design or multiple
avenue exploration for subsequent consideration, to help
avoid premature lock-in on a single or preferred solution,
as well as improve the odds of finding recombinant insights
• Convergent phase, to help with error identification,
correction and other forms of debugging, tuning and
optimization, as well as documentation

13. ROBOTIC PROCESS
AUTOMATION
• It is increasingly possible to handle the ~80% of routine
business processes mainly through automation, limiting
ongoing human involvement to supervision, quality control,
exception handling, and guiding ongoing improvements
• The remaining ~20% of less common cases is often more
trouble than its worth to try to automate
• In total, there are significant efficiency gains to be had from
RPA in many businesses, especially those that were born
digital as is the case for many scale-up stage tech
businesses today
• The usual starting place is the processes which have the
highest volumes of relatively routine transactions

14. CHANGES IN REVENUE
GENERATION DYNAMICS
• At times of significant change in economic and business
conditions, the generative mechanisms for the sales
pipeline can undergo significant change
• Blunt aggregate monitoring and reporting of the sales
pipeline can conceal difficulties, and precious response
time can be irretrievably lost

15. CHANGES IN REVENUE
GENERATION DYNAMICS
• Things to do in times of growing economic strains:
• Revisit which sales pipeline analytics are most meaningful
and predictive in light of current circumstances
• Watch for stage-to-stage velocity changes in the sales
funnel, especially at MOFU and later
• Cohort analysis is powerful to show high frequency
changes over time
• Pipeline coverage ratios typically have to go up a lot during
more difficult times, often as high as 2.5* to 3* LTM
incremental sales

16. RAPID ENTERPRISE
ADAPTATION PROCESS
• The faster the rate of internal and external change, the
more important it is to build and enhance an enterprise-
wide learning and adaptation system
• Continuous Improvement, Root Cause Analysis,
Corrective and Preventative Action and Correction of Error
methodologies applied business-wide are among the
leading tried and tested methods most scale-up stage
companies employ to systematize enterprise adaptation

17. RAPID ENTERPRISE
ADAPTATION PROCESS
• The added benefit of these systems for leadership and
management:
• They create a driver for communicating, evaluating, updating,
teaching and distributing learning about the appropriate frame
of reference to use when solving problems and making
decisions
• The further dividend of these system in trying times:
• When there is a good real-time mechanism for keeping more
people on a similar wavelength about how to solve problems
and make decisions, it helps keep up the ability to delegate
and distribute problem resolution in larger enterprises,
countering the natural tendency for recentralization of
authority in more turbulent business conditions

18. CHANGES IN CUSTOMER
PURCHASE BEHAVIOUR
• In B2B in more challenging times:
• Customers tend to favour smaller, less risky deals
• Required payback times come way down, often to as short as
three to six months
• Expect greater use of zero-based budgeting among buyers,
and less entitlement spending from year to year
• Generally as a response to more challenging business
conditions, the way to go is to be ready to parse product and
service delivery into smaller increments, with rapid
deployment, and short time to realized value for customers
• Measure these parameters, monitor performance, and apply
corrective actions as needed

19. CHANGES IN CUSTOMER
PURCHASE BEHAVIOUR
• In B2C:
• There can be significant changes in the value prop that
customers want in more challenging, stressful financial times
• The foundations of previously established product-market fit
can even come into question
• The best course of action is often to start by being very
humble about assuming how peoples’ wants and needs may
have changed as economic conditions downshift
• Then, do a wholesale reevaluation of whether the product
delivers the same utility and peace of mind it used to, as
evidenced by rate of real-time uptake to strong recurring
usage, referrals and virality
• After that, do a gap analysis of current state vs. target, survey
users about the root causes of divergences, and move to
close the gaps

20. TAKEAWAYS
• Competitive forces may accelerate in many ways during the
coming economic slowdown for scale-up stage tech firms
• The time may well be at hand for transformative mainstream
impact across much knowledge work for generative AI and
RPA, and their ability to provide a lasting and significant
productivity lift
• This is very different from the productivity impact of ICT
overall for the past twenty years, which has been tepid
• We may be in the midst of a very big moment
• In the recent past, frothy markets and abundant capital gave
hope to a lot of different business approaches that won’t be
sustainable now
• Looking ahead, more prudent spending and investment will
magnify the differences between firms which get stronger
through their adaptability, methods, workflows and
technologies, relative to those which do not

21. SUGGESTIONS
• If you haven’t done so already, consider having a
company wide hackathon and demo event capstone about
how to improve methods and workflows using generative
AI and/or RPA
• Be mindful of confidentiality and data privacy obligations,
which may require preparation of sufficiently anonymized
data for development, test and demonstration

22. INDICATIVE
REFERENCES
• Impact of ChatGPT on a range of knowledge work:
• Experimental Evidence on the Productivity Effects of
Generative Artificial Intelligence, Shakked Noy and
Whitney Zhang, March 2, 2023 Working Paper
• https://economics.mit.edu/sites/default/files/inline-
files/Noy_Zhang_1.pdf
• Impact of Copilot on entry level programming:
• The Impact of AI on Developer Productivity: Evidence from
GitHub Copilot, Sida Peng et al, Feb. 13, 2023
• https://arxiv.org/pdf/2302.06590.pdf

23. FURTHER
DISCUSSION
For additional dialog about adapting to the slowing
macroeconomic picture and response options in start-ups
and scale-ups:
dave.litwiller@communitech.ca