The document discusses using scenario planning to address the risk of routing bribery payments through third-party vendors. A workshop is proposed to generate scenarios on this issue over the next 5 years. Participants identify trends, strengths/weaknesses, and unknown factors. Scenarios are created on the impact of bribery cases, including a scenario where a large fine is imposed. Strategies are formulated to monitor for "early signals" of scenarios and centralize compliance functions. The process outlines interviews, workshops, and follow up needed to conduct the scenario planning exercise.

1. Hernan Huwyler
4th meeting
Governance, Risk and
Compliance Management
Scenario Planning

2. Mathematics to pseudoscience

3. Words of estimative probability
We know it is misleading since 1964! Sherman Kent study

4. More problems with adjectives
risk
management
Enterprise
Operational
Strategic
Project
IT
Portfolio
Legal
Reputational
Business continuity
Financial
Fraud

5. The real RM problems
Large actual vs. budget differences
– missing targets, growth in particular
– uninsured losses
– complex renegotiations
– the “journalist” approach
Biased decisions
– “recalibrations” on past experiences
– bonus schemes
– poor articulation of strategies impacted on risk identification
None of them addressed by colourful heat maps
RM not changing any decision and not detecting unknown issues

6. The intern test
Discover how managing…
insulated RM policy
library of risks
ad-hoc workshops
KRIs reporting
emerging risks
…. takes 2 months to master

7. Decision-making in budgeting
– current operations in long-term planning
– development and bidding plans
Quantify risk
– analytical tools to model risks
– tips to better predictions (calibration techniques) for mid-managers
Investment analysis
– approving investments
Holistic ISO 31000
– still need to report risks
Goals to achieve?

8. Sales volumen
Sales price
Labor / fuel costs
Inflation
FX rates
Interest rate
Fines / claims
Construction time
Approach
Cash flow
EBITA
Capital budget
Tender price
Tariff pass-through
request
Budgets for
current business
units
Development
plans
Investment
requests
Financing
alternatives
Bidding
Predictive models for one scenario to simulations
Assumptions Model Decisions

9. Model risks in the current planning activities
– excellent for investment decisions
Assumptions in demand, costs and time
– internal and external risk factors (e.g. competitors)
– alternatives when decisions are made (what if)
Payoff tables with net present values NPVs
– maximum expected cash flow
– most likely cash flow
– PERT estimate: (best case + worse case + av. case * 4 ) / 6
– alternative: 10% and 90% most likely cases
Decision trees

10. Decision trees
Decision Event - Probability 10 yr contract
NPV
Expected
Individual
subsidiary
No price renegotiation - 90%
Good negotiation - 10%
1,000
2,000
900
200
1,100
As part of a
consortium
No price renegotiation - 80%
Good negotiation - 20%
500
3,000
400
600
1,000
NPV of revenues and costs
Each event affects many budget assumptions
Combine analytical risk identification
Transfer this model to mgmt accounting

11. Scenario analysis
Scope: physical assets, data, people, reputation
Assess current controls on assets → vulnerabilities
Early indicators of occurring scenarios
Identify key assumptions
Identify impacts from external sources →
“out of trends”
Craft plausible futures → “stories” or “Alternative worlds”
Time horizon → tip: 3/5 ys
Alternative outcomes → primary and secondary losses
Simulation
Based on internal and external data
Threats
Assets
Losses

12. Calculate alternative possible outcomes of a risk
– understand how risk affects the budget assumptions
• What if there is a new regulation? Bad weather?
– project consequences for all assumptions
– tip: limit to assumptions with the higher impact
• Several possible scenarios
– macro economics, demand, cost prices
– optimistic, baseline and adverse → stress testing
– assign probabilities to each scenario
– tip: involve mgmt, finance, hr, mkt and ops experts
Objectives
– identify top risks
– ensure consistency in assumptions
• bias: estimate a good economy for sales and bad for costing
– exercise flexibility
• develop contingency and prevention plans
• identify early warnings if an scenario occurs
Scenario analysis

13. Scenario analysis
Assumptions Best Base Worst
Growth in demand 7% 5% 2%
Tariff increase – inflation (in real terms) 2% 0% -7%
Days of outstanding sales 50 days 70 days 180 days
Impact on cash flow
Growth in demand 2% 0% -5%
Tariff increase – inflation (in real terms) 8% 0% -15%
Days of outstanding sales 5% 0% -10%
Scenario analysis Cashflow % Occurrence
Best €50M 20%
€30MBase €40M 50%
Worst €0M 30%
Cash flow w/o scenario analysis Cash flow w/ scenario analysis

14. Tool http://goo.gl/UiKJnH

15. Estimated performance
Year
Estimatedcashflow
1 2 3 4 5 6 7
Project net cash flows
Best case (5%)
Worse case (95%)
Risk of being short
of cash after
overoptimistic
assumptions

16. Simulate outputs for more +1k scenarios (runs)
– Output: 1 cash flow – 2 project NPV
– Not only the most likely scenario
Lower and upper limits in assumptions
– from previous experience or subjectively
– tip: previous sensibility analysis to identify key
assumptions, focus on high to moderate risks
– random distribution to simulate an aggregated result
Discuss aggregated scenarios with stakeholders
– Do we have capabilities (EUR, FTEs, know-how) to deal with
extreme scenarios?
Monte carlo

17. Monte carlo in SAP

18. Trade-off
Choose between
capital investments
Allocate available
capital
Identify competitive
advantages
Risk and return
Risk exposure
Net present value at risk as % investment
Internalrateofreturn
Low risk and return
High risk and return
A
B

19. Recommendation
Hubbard, D. (2009), The
failure of risk
management (here)
Key Improvement to Risk
Management
“Use calibrated probabilities
to express your uncertainties
and use those uncertainties in
Monte Carlo models of your
organization as a system.”

20. Thomas, P. (2013) The Risk of Using Risk Matrices
(here)
Cox, L.A. (2008) What's wrong with risk matrices
Flage , R. (2012) A reflection on some practices in
the use of risk matrices
Elmontsri, M. (2014) Review of the strengths and
weaknesses of risk matrices (here)
References

21. Hernan Huwyler
4th meeting
Governance, Risk and
Compliance Management
Workshop Scenario Planning

22. Discussion case: bribery by 3Ps

23. Scenario planning?
Scenarios are stories about the future
Participative learning exercise
Scenario analysis applied to strategic planning
–1st step: scenario generation
future plausible and rigorously constructed events
affecting performance objectives
critical questions faced by decision-makers
–2nd step: scenario planning
reactions for scenarios with great uncertainty

24. “What if” in scenario planning

25. What are the issues to be explored?
– macro scenarios, market or investment decisions or learning
– Tip: link them to core problems and growth plan assumptions
How long should the time horizon be?
– I.e.: 5 years long term planning / 20 years for concessions
Which business units should be included?
Workshop
How we can mitigate the risk of routing bribery
transactions through third-party vendors in the next 5
years?
1 Frame the issue

26. Which are the managers dealing with the issue to
explore?
Who has the experience to produce better inputs?
Are other people representing interests outside the
organization?
Workshop
Risk owner: compliance
SMEs: internal audit, legal, contracting, finance
External dialog: investor relations, CEO?
2 Identify participants

27. To the participants: Which are the trends and key control
vulnerabilities in our organization and sector? Which data
supports them?
– Tip: look for blind spots / weak signals
Workshop (possible answers)
More 3rd party advisors to obtain licenses
Increasing number of invoices submitted for services never
performed detected by audits
Misrepresentation issues in booking services by the shared
service center
Background checks disqualified many vendors
Increasing impact on the reputation after corruption cases
3 Identify the known

28. Strengths
Ethical leadership
Coordination
Intellectual capital
Healthy bonus incentives
Strong due diligence / background
check
Weaknesses
Strong need to use external advisors
to get licenses
Controls by shared services center
Decentralized compliance program
Weak financial controls
Opportunities
Leverage skills across compliance,
finance and audit
Implement a fraud/corruption
detection solution
Collaborative efforts on GRC
Threats
Impact on the reputation
Political changes
Increased scrutiny by stakeholders
Criminal liability
Emerging competition
3 SWOT analysis (illustrative)

29. 3 impact/predictability grid
Impact
Predictability
Low High
HighLow
FCPA
UK ABL
AML
Enforcement in
developing countries
Increased
reputational loss
Populist
movements

30. To the participants: What are the external unknown
factors?
Workshop (possible answers)
Extraterritorial anti-bribery laws enforced in current
markets
Tougher licenses to obtain by authorities
Improper payments detected by AML
ERP solutions to prevent corruptions
Criminal liability for corporations going global
4 Identify the unknown

31. If you could speak with an oracle, what things would you like to
know about the corruption cases in this organization in 2022?
If the organization were to collapse after a corruption scandal by
2022, what might have caused the collapse and why?
4 Brainstorming questions

32. To the participants: What are the best and worst
case scenarios for the identified trends on the
performance of the scoped BUs?
Workshop (possible answers)
Fines
Penalties
Reputation
5 Create possible scenarios

33. 5 Scenario matrix
UncertaintyA
LowHigh
Uncertainty B
Low High
Scenario
1
Scenario
2
Scenario
3
Scenario
4

34. 5 Influence diagram
Trend:
Increasing
reputational
damage
Time

35. 5 Fact sheet
Scenario: Considerable fine after a BU used a vendor to channel bribery payments
undetected by accounting
Top manager of BU avoids a due diligence on new vendor
Top manager uses the new vendor to route bribery payments to public officers
Public officers facilitate issuing permits for new operations
Large fine is set after a whistleblower exposed the scheme to the authorities
Description
Scenario data
Weak supervisory
controls
Decentralized operation
of a compliance program
Scheme out of the scope
of internal audit
Impact – Other costs
Legal costs: 1M EUR
Forensics advisors: .5M
EUR
Internal reorganization:
2M EUR
Impact - Fine
Best: 1M EUR
Worst: 20M EUR
Improper payments
Best: .1M EUR
Worst: 1M EUR

36. Do the envisioned follow logically from what is
known? Are the futures plausible from what we
know?
Workshop (possible answers)
Increased AML regulations are linked to anti-
bribery
6 Test of plausibility

37. To the participants to create “stories”: How the
organization and external stakeholders would
react to each scenario?
Workshop (possible answers)
Competitors would target affected clients
Public banks would deny financing
7 Anticipate interactive
dynamics

38. Corruption
impact/predictability matrix
Impact
Predictability
Low High
HighLow
Review
Contingency
plans
Monitor Develop
scenarios

39. To the participants: What strategic initiatives
should implement now to address plausible
scenarios? What are the “early signals” for each
scenario?
Workshop (possible answers)
Crisis protocol for ethics and compliance
Centralize the compliance functions for due
diligence
Monitor “early signals”
8 Formulate strategies

40. Initiation On
boarding
Generation Planning
Initial
meeting for
objective
and scope
setting
Interviews
with senior
executives
and cross
sections
3 workshops
for scenario
generation
Scenario
presentation
3
workshops
for
scenario
planning
Follow up
the
scenario-
based
strategies
External and
internal
analysis
Data
collection
and
research
Data
collection
and
research
6 hours 1 hour per
interview
(10)
4 hrs per
workshop
(3)
4 hours 4 hrs per
workshop
(3)
1 hour per
interview
(10)
Process and schedule

41. Supply chain quality of inputs, supply relative to industry demand, price of raw
materials
Product consumer tastes, market demand, availability of
substitutes and complements
Competition pricing and other forms of rivalry, new entrants,
product and process innovations, rivals’ price
Uncertainties list
Industry
Operations labor relations, availability of inputs, production
variability and downtime
Liability product liability, emission of pollutants
Credit delays with collectibles
Ethics fraud, corruption, opportunistic behaviors by managers or employees
R&D R&D activities, regulatory approval of new products
Company level at corporate or business levels

42. Social social unrest, diversity, cultural, shift in social concerns, skills,
expectations from stakeholders
Technologic disruptive innovations, digital transformation, cyber threats, business
intelligence, automatization, mobile technologies, renewable fuel
sources
Economic exchange rates, interest rates, inflation, terms of trade, China and
India, disposable income
Environmental climate change, natural disasters, available raw materials,
environmental consciousness of consumers
Political Brexit, nationalizations, far-right politics, terrorism, war, changes in
government, geopolitical stability, liberalization
government policies fiscal and monetary policies, trade restrictions,
regulations affecting the business sector, tax policy, environmental
regulations, changes in collective bargaining law
Uncertainties list
General (STEEP forces approach)

43. Budget accuracy improved
– by validating assumptions
– RM as a decision making process
– budgets disclosed risks (rather than hide them)
– Some scenarios became real
RM became visible, relevant and ongoing
– interest in profitability moved to RM
– risk culture linked to strategic plans
Better understanding of the relationships between
risk events
– by quantitative modelling and scenario planning
Final thoughts

44. Recommendation
Chermack, T. (2011),
Scenario planning in
organizations
“Scenario planning is a
revolutionary alternative
to traditional strategic
planning because it
recognizes the
unpredictable nature of
the future”

45. Miller, K. (2003) Scenarios, real options and
integrated risk management
Schwenker, B. (2013) Scenario-based strategic
planning - Developing strategies in an uncertain
world
Kahane, A. (2012) Transformative scenario
planning
Martelli, A (2014) Models of scenario building and
planning
References

46. Closing

47. Hernan Huwyler
mydailyexecutive.blogspot.com
h @gmail.com
www.linkedin.com/in/hernanwyler
hewyler
 + 45 91