The 2 double feeds black box is a modelling with 2 variables (human geography, physical geography) of the risk encountered. I have assumed for the presentation these risk were irrationalbehaviors. have presnted the with a mtrix risk portofolio and a combineee

1. GEO-HEALTH JOB
2 FEED BLACK BOX TO FORECAST HAZARD
ANALYSIS CRITICAL CONTROL POINTS
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013

2. 2 feed black box to forecast hazard analysis critical control points
A FORECAST METHOD
Curves of Disaster forecast reconciled with the organization environment to
cope with tenses and the stress (psycological, brunts i.e wellbings,...assets,
lives, properties of the hazardous event -tsunamy, earthquake,...)
Number of
affected people
How,
when,
Yes we where,
can ! who,
forecast
what,...
Can we make
Recovery x ? it ?
indicator
real
No we
cannot !
Time line
T (event) T?
ΔT : recovery leadtime
Graphs and the representation of the gap/risk
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO

3. 2 feed black box to forecast hazard analysis critical control points
BRUNTS (AFFECTION OR RECOVERIES) AND JOBS (LOSSES)
DURING A DISASTER
Before the crisis During the crisis After the crisis
Gross Domestic DISASTER
Product (GDP)
Real GDP
GDP max x
People affected or Average Gross
GDP
recovering Domestic
Or deads Product
GDP
Maximum Maximum
GDP job losses GDP
production production
Less GDP
production
GDP min JOB x Job
Affectation Job changes, less jobs, returning
and leveling humanitaire jobs to normal
JAN. FEB . MAR. APR. MAY JUN. JUI. DEC.
Calendar
(timeline)
HURRICANE SEASON IN USA
(FLORIDA-GULF COAST)
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO

4. 2 feed black box to forecast hazard analysis critical control points
INDICATORS Indicators
Survivor progress 100
0
Survivor
numbers
Method Probability
important Brunts (Physical deterministic method
100 affectation) 0
A
F
F uncertainty
E weak
C 0 ----
T Scale of the recovery
E
D ++++
Recovery (R)
100
Maxi-
Psychological illness
0
100
Recovery (R)
Risk source (losses of lives, losses of their family members, livelyhood
and properties- insurance cannot return the wellbeing of survivors (as
these are material assets- while survivors have lossed their
psychological assets)
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
© GS RADJOU, BIRD CEO February 6- 8, 2013 – CEGeoIC_2013

5. 2 feed black box to forecast hazard analysis critical control points
BRUNTS (AFFECTION OR RECOVERIES) AND JOBS (LOSSES)
DURING A DISASTER
PROCESS 1
PROCESS 1 PROCESS 2
PROCESS 2
DATA INPUTS OUTPUTS
1- VARIABLES
(A,R)
COST
2- ASSESSMENT Parameters (*) GDP
3 STATUS Parameters (*) Parameters (*)
(spatial, time) Parameters (*) RESOURCES
(spatial, time) (Survivors...)
(M,m,m) (Survivors...) ALLOCATIONS
For any variables ASSISTANCE
(parameters) ….
3- uncertainties Uncertainties
(δ) (δ)
(*) Encyclopedia of Geography: geography risk
= physical geography + human geography
Interdisciplinry CODATA Conference CEGeoIC, Boagota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO

6. 2 feed black box to forecast hazard analysis critical control points
L E V E L S O F R I S K S
(AND RISK EQUIPROBABILITY)
Lucky survivors,
No
they have been able
recovery/
Survivor
50%
recovery
Survivors
100%
to recover mentally
0% and physically, but
Affected
they have no
A Affected by People partially
People fully
recovered Survivors houses, no food,
tsunami recovered
(but, no physical 33,33% (without assets livelyhood
F (survivor with
brunts
(but, no physical
assets or
assets or
brunts)
F livelyhood)
livelyhood)
and properties
E People lives
Affected by People partially
50%
(Brunts) C
affected people
(Physical recovery
tsunami
(survivor with
recovered
(but, no physical Brunts
T
No mental recovery brunts assets or
livelyhood)
33,33%
Affected
E People never People lives Affected by Survivors
affected people
D recovered,
(life physical and (mental recovery
No physical
tsunami
(survivor with 33,33% (100% With
Psychological brunts brunts- full
recovery
damages) burnts)
Most Affected
Between survivors 33,33% 33,33% 33,33%
of the tsunami first instant
R E C O V E R Y
(Survivors)
Equipro-probability (P) for each/every scenario cases of survival (recovery) with
various brunts/affectations case ~ P = 1/9 ≈ 0.11= 11,11.%
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO

7. 2 feed black box to forecast hazard analysis critical control points
RISK MATRIX PORTOFOLIO
A REGION
A3 A3 R1 A3 R2 A3 R3
A2 A1 R2
A2 R1 A2 R3 Risk
A2 R1
class
A SITE
A1 A1 R1 A1 R2 A1 R3
R1 R2 R3
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO

8. 2 feed black box to forecast hazard analysis critical control points
AFFECTATION TABLE
(DUAL GRAVITY TABLE
50% SURVIVORS-50% NTO SURVIVORS)
People lives (A)
affected People
by physical affected likely SURVIVORS
brunts To not survive MORE THAN
Psychological 50%
illnesses (Sufferers)
-People less affected
People lives And
Survivors
NOT SURVIVING affected Recovering-
with brunts
UNDER Physically psychological
50% brunts
(Sufferers)
-People more
affected People lives
and affected
not recovering- psychological
brunts
Intangibles-mental illness, psychological distress (R)
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO

9. 2 feed black box to forecast hazard analysis critical control points
RISK PORTOFOLIO MATRIX WITH A SCENARIO
RISK CLASSES
DETERMINISTIC
PROBABLISTIC
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO

10. 2 feed black box to forecast hazard analysis critical control points
HYBRID ORGANIZATIONS
Keys -codes-
Weight of an organization 1 ½½ ¼¼¼¼ b: blue
g: grey
B: black
P+p = 1 (99.99%) ≈100%
A1 R2 A1 R1 A2 R1 A3 R1 A2 R2 A1 R3 A2 R3 A3 R3 A3 R2
b g
b b g b g g B g g B B g B
g b
b b g b g g B g B g B B g
Probability p Probability P
Trend: not survivors Trend: survivors
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO

11. 2 feed black box to forecast hazard analysis critical control points
RESOURCE PLANNING
DATA IN DATA OUT
3 = not surviving
CRISIS DISASTER 0-25%
NORMAL (ASSUMED) 2= likely to survive
STARTS STARTS
REFERENCE 25%-50% people
survived
3= 50% -100%
survivors
3 2 1
UNCERTAINTIES
+ 50%
Time
0 T1 T2 T3 T4 T5 T6
EXPERIENCE (REAL)
REFERENCE
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO

12. 2 feed black box to forecast hazard analysis critical control points
QUESTIONS / IMPROVMENT
actions Can we make it better means ? expectations
Direct road Indirect road
map/action map/action
Can we reduce..... Can we save....
Can we reduce the risk Can we save people lives
Can we increase people resilience Can we protect their
assets
Can we prevent the risk occurrence
Can we protect their
Can we adapt the environment to livelihoods
hazards
Can we protect their
Can we manage hazards properties
…... ….
Results/outputs =
Conciliation between actions and expectations need to be materialized-
if not => there will be a gap or a failure causing increasing risks
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO

13. 2 feed black box to forecast hazard analysis critical control points
THANK YOU!
GEORGES RADJOU
Business Innovation Research Development
''BIRD''
gsradjou@outlook.com
Www.facebook.com/gsradjou
Www.slideshare.net/gsradjou
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO