GPS and Strategic Planning

The GPS Framework:
A Comprehensive Approach to
Strategic Risk Management
Damon Levine, CFA, CRCMP
Vice President, Enterprise Risk Management
Assurant Inc.
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Legal Disclaimer
The views expressed herein are my own and not
necessarily those of my employer, Assurant Inc.
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About the Speaker
• Damon Levine is Vice President, Enterprise Risk
Management at Assurant Inc.
• 20 years experience in actuarial consulting,
portfolio strategy, and risk management with past
presentations to the ERM Symposium, ISO's ERM
Forum, and the Actuarial Society of NY.
• Published in The Actuary, SOA's Risk
Management journal, and the Society of
Actuaries exam syllabus.
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Today’s Key Takeaways
• A clear understanding of the approach, tools,
methods, and scalability of GPS
• The ability to measure all types of threats to
strategic execution with the same set of metrics
• The capability to manage strategic risks with a
powerful and practical method which:
•Creates buy-in and improves both strategic planning and
execution
•Enables informed management reaction to strategic risks
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Agenda
ERM, Strategic Risk Management, and GPS
Risk Quantification in GPS
Important GPS Concepts and Tools
An Execution Management Cycle
Quantitative Applications
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A Convenient Fallacy
• Strategy versus strategic objectives
• Risks to strategic objectives
• Does strong Enterprise Risk Management
(ERM) imply effective Strategic Risk
Management (SRM)?
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GPS: Goals-Progress-Strategy
• Goals: Ensure a well defined business goal,
i.e. strategic objective; it identifies key risks to
achievement of the objective and its
foundational “critical-to-success” goals and
lower level checkpoints
• Progress: GPS includes key progress metrics
and an Execution Management Cycle (EMC)
• Strategy: the EMC assesses risk evolution and
informs risk-intelligent “course correction”
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Risk Quantification in GPS
• Scenario analysis



Goals
Process: the risk interview
Benefits
• Probability
• Macro events and conditional probability
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Example: Scenario Approach
Scenario Summary for Foreign Exchange Rate Risk (Dollar vs. Euro)
Scenario Description
Probability
1. Exchange rate stays within 10% of
March 1 levels for next 12 months
Impacts to Business Drivers
Year 1 Earnings Impact
Company Value Impact
2. Dollar appreciates vs. Euro by 10-20%
Assume baseline forecast interval Assume baseline forecast Assume baseline forecast
35% estimate applies
interval estimate applies
interval estimate applies
$US Sales Down 20% (vs.
25% baseline, post currency translation) -$20M
-$54M
3. Dollar appreciates vs. Euro by >20%
20% $US Sales Down 35%
-$35M
-$95M
4. Dollar depreciates vs. Euro by 10-20%
5. Dollar depreciates vs. Euro >20%
15% $US Sales Up 15%
5% $US Sales Down 30%
$15M
$30M
$41M
$81M
Statistical Expectation
-8M
-22M
Downside Conditional Expectation
-27M
-72M
Challenges
[list perceived difficulties in risk prevention or impact reduction]
Mitigations
[identify existing risk controls that reduce likelihood and/or expected business effects]
Potential for Action
[assess the expected benefit to the company’s risk-reward profile from additional focus or effort on risk mitigation]
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Financial Quantification of Risk
• Frame each scenario’s impacts in terms of key
performance drivers including sales/other cash
flows, expenses, etc.
• Translate scenario impacts into effects on income
statement and balance sheets
• Spreadsheet logic and accounting rules make the
key metrics simply “fall out” of model (e.g.
earnings, ROE, IRR etc.)
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Additional Tools: Old and New
• Well known techniques from ERM play key
roles in GPS


Scenario approach to risk ID and quantification
Mitigation/control assessment
• Potential for Action (PFA)
• Required Recovery Ratio (RRR)
• The Logical Framework Approach (LFA)
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Potential for Action (PFA) and
Risk Velocity
• PFA is a qualitative assessment of the
expected improvement in a company’s riskreward profile due to increasing or expanding
risk controls/mitigation
• Expected “bang for the buck” of additional
effort/resources for a specific risk exposure
• Risk Velocity: measure of expected time from
risk manifestation to financial impact
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Required Recovery Ratio (RRR)
• Assume a strategic objective based on a sales metric and 3year forecast horizon: year 1: 100M, year 2: 200M, year 3:
250M (a 3-year total of 550M)
• Assume actual year 1 sales are 50M and define RRR by the
“get back on plan” relation:
50 + RRR(200+250) = 550
• RRR=111%  we must outperform forecast by 11% in years
2-3
• Higher RRRs  smaller likelihood (estimated at beginning of
year or before project launch!)
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RRR & Probability of Success
• RRR is a function of actual performance to date and
plan projections for the remaining time horizon
• Various ranges of RRR are considered before a
strategic project launch and corresponding
probabilities are estimated
• RRR, in conjunction with other indicators, provides a
dynamic estimate of the probability of goal
achievement
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The Logical Framework Approach (LFA)
• A powerful management tool driving successful
strategic planning and execution
• Developed in 1969 for the United States Agency for
International Development (USAID)
• Originally used for international development
projects and used in over 35 countries
• Very effective in corporate settings to ensure
attainment of strategic objectives
• Temporal Logic Model and If-Then Thinking
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Effective Strategic Planning and LFA
• A “time-reversed” causal chain


Strategic objective  Critical-to-Success Goals  Sub-goals
and Tasks
Plan left to right and (ideally) execute right to left
• If-Then thinking and progress metrics in an SRM
setting
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An Execution Management Cycle
• ID Critical-to-Success (CtS) Goals
• Goals  Progress  Strategy
Goal definition and project planning
 Risk ID and progress assessment with metrics and early
warning indicators (EWI)
 Adaptive Management: strategic course correction and
tactical actions

• Informed and dynamic execution of an
objective from start to finish
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GPS in Action: Managing Strategic Execution
Define SMART Strategic Objective,
Critical to Success (CtS) Goals & pre-requisite tasks
Yes
Yes
Select metrics/indicators, upfront RRR analysis, and
risk ID & quantification through scenario approach
Do we need
to re-define
metrics/EWI or
revise
risk scenarios?
Calculate and track metric/EWI values, risk velocity
& exposures, mitigation effectiveness (PFA), and RRRs
No
No
Does overall strategy
need to be altered?
Research performance drivers, metrics and EWI.
Employ Logical Framework techniques to analyze
CtS goals, sub-goals, and if-then assumptions
Report and interpret data and findings,
PFAs, and overall risk-reward outlook/assessment
Apply adaptive management: revise risk mitigation
Business tactics/strategy and inform ‘go/no-go’ calls
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GPS and Strategic Planning
• Strategic objective  Critical-to-Success (CtS)Goals
 Sub-goals and Tasks
• Identify challenges and risks to attaining CtS goals
and the smaller sub-goals or tasks (include LFA’s ifthen thinking)
• Quantify potential impacts in light of existing
mitigations or controls
• Provide a ranking of key risks and their PFAs to
prioritize management action
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Progress Assessment
for Strategic Objectives
• At regular time steps GPS will:



Identity and quantify risks to key tasks, projects, and CtS
goals and assess corresponding risk controls/mitigations
Determine progress metrics, RRR & outlook for success
Provide an estimate of the expected benefit of increased
mitigation effort (PFA)
• Crucial performance indicators are tracked
and reported for those areas driving success
(e.g. training, marketing , sales, profit, etc.)
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Enabling Adaptive Management
• The EMC allows for:
Timely assessment of progress toward goals expressed in
objective measures and metrics
 A dynamic view of risks to achievement of the key
foundational tasks and the overarching strategy
 A risk-intelligent basis for course correction: high level
and tactical revisions to business plans

• Management has a realistic view of the
priority for shoring up risk mitigation and
increased focus on strategic elements
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Stochastic Approaches
• Scenario impacts need not be point estimates
• Uniform, triangle, normal or other
distributions may be assumed for impact
estimates of key business drivers or income
statement items
• Refining scenario analysis with conditional
probabilities
• Macro factors and correlation
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Stochastic Simulation in Excel
• Assume a risk source modeled with three scenarios:
S1 = no/mild impact, S2 = moderate impact, and S3 =
severe impact & probabilities 60%, 30%, 10% resp.
• Generate random digit in (0,1): r
• Use r to determine which scenario has occurred:
0<r<.6 S1, .6<r<.9 S2, and r>.9 S3
• Next slide illustrates this concept in Excel; note that
subintervals corresponding to scenarios have widths
equal to the scenario probabilities
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Stochastic Simulation in Excel (cont’d)
•Assume P(S1)=.6, P(S2)=.3 and P(S3)=.1
•Use “=rand()” in Excel to generate random digit, r, from (0,1)
•The rule below associates r with a particular scenario (i.e.
the random value of r indicates the scenario which occurs)
0
0.1
if r falls in (0,.6) then S1 Occurs
0.2
0.3
0.4
0.5
r in (.6,.9) then S2 Occurs
0.6
0.7
0.8
r>.9-->S3
0.9
1
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Simulation of a Strategic Objective
with Two Risk Sources
•A random digit from (0,1), r1 determines the simulated scenario for risk source 1
•Another independent random digit r2 determines the simulated scenario for risk source 2
Use r1 and r2 to indicate simulated state of each risk source
r1=.6531
scen 3
prob=.30
scen 2
prob=.50
scen 1
prob=.20
1
0.7
0.2
0
risk source 1: scenario 2 is simulated
r2=.3215
0
0.4
scen 1
prob=.40
0.9
scen 2
prob=.50
1
scen 3
prob=.10
risk source 2: scenario 1 is simulated
determine performance for strategic objective X:
aggregate impacts from above simulated scenarios
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The Macro Factory Overlay
• Model macro factors that significantly affect
likelihood of outcomes for risk sources of
strategic objective X
• Simulate macro factor states: M1,M2,… (e.g.
recession, inflation, pandemic)
• For each macro state i, estimate strategic
objective probabilities: pr(scen 1 | Mi),
pr(scen 2 | Mi), …
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Simulating Strategic Objective Performance
Generate several random digits from (0,1) to simulate the state of each of the
macro factors; i.e. model the “state of the world”
For each risk source (R1, R2,…) affecting the performance of strategic objective
X, we note the “activated set” of scenario probabilities
For each of R1, R2, …generate a random digit from (0,1) to simulate which
scenario occurs for each of these risk sources
Simulate performance of Strategic Objective X: Based on the simulated
impacts for the scenarios, aggregate the effects on key metrics such as
earnings, IRR, ROE, etc
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Macro Factor Based Simulation of a
Strategic Objective
r1=.3531
0
0.2
1
scen 1
prob=.20
scen 2
prob=.80
Economic scenario 2 is simulated
r2=.8108
scen 1
prob=.20
1
0.7
0.2
0
scen 2
prob=.50
scen 3
prob=.30
Regulatory scenario 3 is simulated
The above macro scenarios activate conditional probabilities for each risk source of the objective…
Strategic Objective Risk Source X
Macro “state of the world” activates conditional probabilities for simulation of risk x:
(15%,60%,25%), (20%,50%,30%), (10%,55%,35%)
Simulate each state of each Risk Source X, Y, Z,…thus simulating the strategic objective
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Simulated Infusions
• Best estimate/baseline forecast for 3 years of
objective X: B1, B2, & B3 (e.g. $earnings in years 1-3)
Risk-adjusted Capital
• Denote years 1, 2, and 3 earnings levels in simulation
ofk, aandStrategic
Objective
k by E1k, E2
E3k
• Notional supplemental flows to meet baseline: B1E1k , B2- E2k , and B3- E3k for years 1-3 respectively
• Kth infusion = PV(supplement) = (B1- E1k)/(1+i) +
(B2- E2k)/(1+i)2 + (B3- E3k)/(1+i)3
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Strategic Objective Risk Capital
• In large number of simulations observe 95th%ile of
simulated infusions
for strategic
objective X
Risk-adjusted
Capital
of a Strategic Objective
th
• RACX = risk-adjusted capital = 95 %ile of infusions
• In one run risk capital may be determined for all
objectives simultaneously: RAC1, RAC2, …
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Return on Risk-Adjusted Capital
• Calculate in large run: RAC1, RAC2, …
of a Strategic Objective
• Observe average “reward” for each objective (e.g.
average PV(distributable earnings) or IRR): y1, y2,…
• Define return on RAC for the “strategic objective i”
as RORACi = yi/RACi
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The Portfolio View
• Simulation allows for portfolio infusion notion and
RACPORT and yPORT, the average reward for the
portfolio of strategic objectives
• We may define RORACPORT = yPORT/ RACPORT
• Estimating a strategic objective’s contribution to
portfolio RAC and RORAC
• “Risk classes” and exposure to macro factors
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Risk Appetite
• A previously vague or “pie in the sky” risk
construct
• Now we may define:
Desired risk class allocation of the portfolio of
strategic objectives
 Support only those objectives increasing RORACPORT
 Portfolio exposure limits to specific macro factors

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Risk-Intelligent Capital Deployment
• Based on upfront risk analysis how does one
decide on the “green light” for an objective or
choose among competing objectives?
• Illustrative policy:



Priority based on objective or portfolio RORAC
Priority as a function of resulting portfolio exposure to macro
factor(s) or maximum risk class allocation
Consider performance distribution of the objective
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In the Research Paper
• More detail, slower buildup to ideas
• A risk-adjusted compensation framework and
100 Day Implementation Plan
• Definitions & examples of risk velocity, RRR, &
PFA
• Illustrative application to a new product launch
• Available online at:
http://www.ermsymposium.org/2013/pdf/erm-2013-paper-levine.pdf
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Closing Thoughts
• These techniques generally apply to ERM and
to a large extent, GPS is an application of
robust ERM to strategic risks
• GPS will still “work” if only partially
implemented and does not commit a
company to a single SRM/ERM path
• Contact: [email protected]
• Questions?
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