Relief Operations: How to Improve Humanitarian Systems with Smart Analytics & Knowledge Management

Prof. Haluk Demirkan
haluk@uw.edu
strong business understanding with deep technical background
Professor of Service Innovation and Business Analytics
Milgard School of Business, University of Washington (UW) - Tacoma.
Co-Founder & Board of Director - International Society of Service Innovation Professionals
Track Chair: Analytics, Mobile & Service Science at the Hawaii Int. Conf. on Sys. Science
Professional student
PhD in Information Systems & Operations Mng.;
PME & ME in Industrial & Systems Eng.;
BS in Mechanical Eng;
PMP from PMI
We cannot solve our problems with the same
thinking we used when we created them.
Albert Einstein
"Relief Operations: How to Improve Humanitarian Systems with
Smart Analytics & Knowledge Management," 84th Civil Affairs
“PHOENIX” Battalion Academic Week, Joint Base Lewis-McChord
(JBLM), WA, March 2015.

Transdisciplinary Application of
Service Science + Information Systems + Supply Chain Management
for Sustainable Innovations
Selected Awards and Honors
2015 - IBM Faculty Award (being nominated) – Service Innovation Ecosystem Lab
2014 - Association for Inf. Sys. ranked 5th in Top-100 World-wide IS Researchers
2012 - Recipient of Center for Services Leadership Research Award
2011 - Journal of Service Research – Service Innovation
2010 - IEEE Computing Society – Research on Sustainable IT Services
2011 - Decision Sciences Journal of Innovative Education – Analytics
2008 - IBM Faculty Award – Research on Design Science for Self Service Systems
Academic experiences: ~ 15 years
higher education teaching, and inter- and trans-disciplinary applied research
Professional experiences
15+ years of professional work & executive education experiences on strategic
information systems & management
Selected Academic Accomplishments Since 2002
150+ publications including HBR, Informs, IEEE, ACM, and others
Research, Consulting & Professional Education with Intel, American Express, IBM,
Bank of America, Citibank, AT&T, MicroStrategy and many others
Co-Editor of a Book Collection Service Systems & Innovations in Business and Society
WHO I AM - Haluk Demirkan, PhD & PMP
2

Relief Operations: How to Improve
Humanitarian Systems with Smart
Analytics
DATA INFORMATION KNOWLEDGE
DECISIONS
WISDOM
CHANGING THE
RULES
Cognitive Analytic
Thinking
+
Systems Thinking
+
Intuitive Design
Thinking
INNOVATIONS
with
Efficient &
Effective Decision
Making
5COPYRIGHT 2015 © Haluk Demirkan

Expect the Unexpected
COPYRIGHT 2015 © Haluk Demirkan 7

Humanitarian
assistance in
numbers
http://www.globalhumanitarianassi
stance.org/wp-
content/uploads/2013/07/GHA-
Report-2013.pdf
8

Foreign Aid
In fiscal 2013, U.S. government funding for humanitarian
assistance and international development will total around $23
billion. (Back in October, I included spending on diplomacy in
the numbers that I reported. In order to directly address the
question of how much we give in aid to other countries, I'm
now leaving out diplomacy and operations of the State
Department.)
Foreign Military Assistance
In addition, the U.S. will spend around $14 billion in fiscal
2013 for foreign military assistance – that's money spent on
training foreign armies and providing them with weapons.
https://www.nationalpriorities.org/blog/2013/05/06/how-much-foreign-aid-does-us-give-away/

http://www.alnap.org/what-we-do/effectiveness/sohs
http://sites.duke.edu/dukeresearch/2012/02/15/solving-the-worlds-humanitarian-problems/
IMPROVEMENT?
• Timeliness
• Coordination
• Needs assessment
• Upward accountability
GROWTH
• Funding up in all sectors (still
persuaded as insufficient)
• Increased delivery of materials
and services
• More agencies and aid workers
Progress is incremental and generally slow
According to ALNAP Institute
Report “The State of the
Humanitarian System”

1. Efficiency and effectiveness
2. Political dilemmas
3. Criticism of humanitarian
organizations
4. Preparedness and risk reduction
5. Partnership and working together
6. Coordination – lack of incentives to
coordinate
7. When things go wrong????
8. Leadership
9. Networking and relational skills
10. Accountability to recipients
11. Values and sectorial experience
Innovation
Working in complexity with limited information
SOME OF THE KEY CHALLLENGES ARE

12. Unpredictability: Not knowing the type of disaster or location in
advance poses a significant obstacle to predict what information
will be needed, and where and how such information may be
obtained.
13. Multiple interests: With people reacting, and even panicking,
immediately after disasters, as a result, information spreads in
various forms, including rumours and myths, complicating
information gathering.
14. Organizational setup of humanitarian organizations: The typical
humanitarian response is a short-term life-saving engagement,
creating a mental barrier against establishing KM systems.
15. Lack of adequate funding: Donors are not necessarily willing to
fund long-term KM processes in an emergency setup due to the
temporary nature of responses.
16. Cost of systems: KM systems require long-term planning,
appropriate structures, and systems, which many NGOs cannot
afford.
17. Human resources capacity: NGOs tend to invest in training and
capacity building of professionals who will be directly involved in
service delivery to victims, relegating the need for future learning.
MORE CHALLENGES ARE

18. Staff turnover: Experienced humanitarian workers are among the
most mobile employees, affecting institutional memory and
learning.
19. Technological infrastructure: The challenges are not necessarily
the same all over the world – some areas/ continents have better
technological infrastructure than others.
20. Limited coordination and collaboration: The lack of coordination
and collaboration between international NGOs is reinforced, though
not openly, by inter-NGO competition to access common funding
sources.
21. Exclusivity: International NGOs tend to trust certain sources of
information over others, such as government data of the host
country.
22. Organizational secrecy: Organizational learning is not freely
shared among humanitarian actors, for fear of being seen as
measures of organizational performance.
23. Confusion: Especially at the peak of a humanitarian crisis, too
much information may be gathered, which at times can lead to
confusing and contradictory information, which needs experienced
personnel to navigate.
MORE CHALLENGES ARE

Working in complexity with limited information
HOW TO
create consistent and cost-effective solutions
US dispatches aid to Philippines
after Typhoon Haiyan kills at least
10,000

RESEARCH INDICATES THAT THERE ARE 5 TRENDS THAT
MAY HELP ORGANIZATIONS TO TACKLE HUMANITARIAL
CHALLENGES
1. Democratization of Science: It took researchers 13 years and 2.7
billion dollars to sequence a single human genome for the first time.
Now a company can sequence 100 genomes a day for less than $100
each. Lower costs allow humanitarian groups to deploy innovative
technologies (such as vaccines) on a large scale.
2. Increase in Computing Power: “The power of computing is increasing
exponentially, while the cost is decreasing exponentially. This provides
us with exceptional ability to use computer power to help understand
and solve problems,” Dehgan said.
4. Decentralization of Manufacturing: Certain 3D printers, for example,
now have the ability to produce 70 percent of the parts needed for
another 3D printer. Online course materials such as iTunesU and MIT
OpenCourseWare help support individuals that are trying to solve their
own problems.

RESEARCH INDICATES THAT THERE ARE 5 TRENDS THAT
MAY HELP ORGANIZATIONS TO TACKLE HUMANITARIAL
CHALLENGES
4. Connectivity: Cellphones act as gateways to human knowledge,
providing people with access to information they didn’t have before.
5. Data, Data, Data: “A kid in Africa has more power and knowledge in his
hand with a smart phone than President Clinton had 15 years ago,”
Dehgan said. Technologies such as remote sensing, crowd sourcing and
bioinformatics will add new types of data to our pool of knowledge.
DATA INFORMATION KNOWLEDGE
DECISIONS
WISDOM
CHANGING THE
RULES

Quick Review - What is Information ?

What Is an Information System (IS)?
IS: A group of components that interact to
produce information
So, what is information?
– Information is created when data are put
into meaningful and useful context
A Socio-economic system with four
components
–IT (Enabler)
–Process (Beneficiary)
–People (User)
–Organization (Facilitator)COPYRIGHT 2015 © Haluk Demirkan 19

- Technology is becoming a commodity
- Decreased cost of information flow
- Increased speed of information flow
- Increased ease of organizing
and accessing data
- Dispersion of the sources of knowledge
- Dispersion of the sources of innovation
- The role of ICT
- Open markets
- Time & distance
service based offerings
services are delivered
through Internet
services scale on demand to
add or remove resources as
needed
services can share a
generalized pool of resources
to build economies of scale
Web
2.0, 3.0
Autonomic,
Dynamic, Self-
healing systems
SLAs
Virtualization,
Scalability
Utility, Grid
Computing
Internet-of-
things/
everything
Dynamic
workflows,
BPs
Virtual Computing
(Cloud/Fog)
On-demand self
service
Rapid elasticity
Pay per use
Ubiquitous network
access
Location
independent
resource pooling
..
Smart Services
Service-Oriented-X
BP-, architecture,
infrastructure, data-, -
information &
analytics-as-a-service
with usability, speed &
relevance
- reusable
- composable
- stateless
- loosely coupled
- discoverable
- interface-contract
- inter- & intra-
organizational
Enterprise
2.0, 3.0
Mobile
solutions
SQL
noSQL
w. ETL
w/o
ETL
reporting
predictive
scorecards
alerts & proactive
notification
dashboarding
searching
Semantics,
ontology
OLAP
prescriptive
sharing
co-creation
analytics
interaction
Big Data
volume, velocity, variety, veracity, variability, value
Enterprise
Data
Public
Data
Social
Media
Sensor
Data
Transactions
Camera,
Audio Data
RFID
tags
capture
Active
DW
Analytics
visual discovery
in-memory
analysis
ad hoc query
MS Office
integration
visualization
scorecardingWorkflow
integration
stream data
Stream
data
SOCIAL
SYSTEMS
COGNITIVE
SYSTEMS
SERVICE
SYSTEMS
DIGITIZATION
smart automation
INTERNET-OF-X
MOBILE
SYSTEMS
ANALYTICS

Fact Based Decision Making is possible
with IS
DATA INFORMATION
FUNCTIONALITY
& SERVICES
ORGANIZATIONAL NEEDS
Analytics is the use of
•data,
•statistical and quantitative analysis,
•exploratory and predictive models,
and
•fact based management
to drive decisions and actions.
KNOWLEDGE DECISION

Driving Value from the Data

“There is no question that we are living in an era of data and information
explosion.”
[Demirkan, H. and Delen, D. “Leveraging the Capabilities of Service-Oriented Decision Support Systems: Putting
Analytics and Big Data in Cloud,” Decision Support Systems and Electronic Commerce, 2014.]
COPYRIGHT 2015 © Haluk Demirkan
23

Cheaper storage and evolution of digital data and information collection devices,
such as cell phones, laptops, sensors.
Organizations are shifting from transactional processing to “interaction
processing” where people, their interactions with products, services and each
other, are generating large volumes of new data.
Cloud computing is changing the economics of computing; it is creating a
fragmentation of data and it enables more economical storage and analysis of
data.
Computing is shifting to mobile delivery; computationally intensive applications are
no longer confined to desktops.
There have been significant improvements in a wide range of quantitative
modeling software tools.
For example, Facebook, a social-networking website, is home to 40 billion photos,
and Wal-Mart handles more than 1 million customer transactions every hour,
feeding databases estimated at more than 2.5 petabytes. There are 4.6 billion
mobile-phone subscriptions worldwide and 1-2 billion people use the internet.
[The Economist, Data,data everwhere, A special report on managing information, Feb 27, 2010.]
WHY IS THIS ALL HAPPENING?

Business Intelligence, is neither a product nor a system. It is, rather, a
constantly evolving strategy, vision and architecture that continuously seek to
align an organization’s operations and direction with its strategic business
goals.
BI refers to technologies, applications, processes and practices for the
collection, integration, analysis, and presentation of data to generate
information and knowledge for complex decision making processes
BI’s purpose is to support data-driven (evidence based with analytics)
business decision making
Business analytics represents the combination of skills, technologies,
applications and processes used by organizations to gain actionable insights
for their business based on data, statistics, quantitative modeling and
simulation, optimization and natural language processing.
That’s why having efficient and effective decision making processes with
right data that is transformed to be meaningful information with data-driven
discoveries (e.g. analytics) are becoming mainstream processes for
companies to run smarter, more agile and efficient operations.

Principles of Information
Delivery
Permission-based
Personalized
Proactive Alerts & Notification
Medium of Choice
Interactive
Information Delivery
The Five W’s
WHO?
WHAT?
WHEN?
WHERE?
WHY?
Subscribers
Content
Schedule
Devices
Alert Criteria

Make Better
Decisions
Increase
Value
Build Better
Services
Foster Citizen
Relationships
Right information – knowledge – power - empowerment
Free flow of information
Delivery of data – information – knowledge - decision
Intelligent decision making (fast and good)
Analytical logistics
Supply chain networks
Enterprise resource planning
Business performance management
Some of the goals are
Reduce
Cost
Innovative decision making
Increase
Outcome

Trends

BI systems provide valuable information for decision
making
1. Reporting systems
–Integrate data from multiple systems
–Sorting, grouping, summing, averaging, comparing data
2. Data-mining systems
–Use sophisticated statistical techniques, regression
analysis, and decision tree analysis
–Used to discover hidden patterns and relationships
How Do Business Intelligence (BI) Systems
Provide Advantages?

3. Knowledge management systems (KMs)
–Create value by collecting and sharing human
knowledge about products, products uses, best
practices, other critical knowledge
–Used by employees, managers, customers, suppliers,
others who need access to company knowledge
4. Expert systems (ES)
–Encapsulates knowledge in form of “If/Then” rules
–ES can improve diagnostic and decision quality of non
experts

Three Generations of BI/BA
First Generation: DSS – Separate decision support databases – late
70’s, 80’s, and early 90’s
Second Generation: Traditional data warehousing with data marts
(dashboards, reporting), Enterprise-wide applications (scorecards,
master data management, OLAP – from 90’s to present
Third Generation: 2000’s and near future
–Strategic BI
–Real-time BI
–Analytics
–Business Performance Management
–Knowledge Management
–Data Mining
–Self Service BI
–Mobile BI
–Social Networks and BI
–Big Data

Many different users of BI
Leaders/Executives – Focused on the overall
organization
Business Decision Makers – Focused on single
areas of the business (finance, HR, manufacturing, and
so forth)
Information Workers – Typically managers or staff
supporting the infrastructure, application
development/deployment
Line Workers – Employees who might use BI without
even knowing it
Analysts – Employees who build models to perform
the extensive data analysis needed

TYPES OF BI SOLUTIONS

• In today’s very complex world, organizations must find innovative ways to
become more collaborative, virtual, accurate, synchronous, adaptive and
agile.
• They need to be able to rapidly respond to needs and changes.
• Many organizations noticed that the data they own and how they use it can
make them different than others.
Data, information & analytics are becoming primary assets for many
organizations.
Gartner says that “Between 70% to 80% of business
intelligence projects fail. (Jan 2011)
According to Computerworld “More than half of all Business Intelligence &
Analytics projects are either never completed or fail to deliver the features
and benefits that are optimistically agreed on at their outset. While there are
many reasons for this high failure rate, the biggest is that companies treat BI
projects as just another IT project.”
SO WHAT? …the role of data, information & analytics…

The present: Pitfalls for enterprise
applications/unexpected findings
Slow implementation
Incompatible systems
Organizational barriers
Demanding users
Inflexible systems
Information overload and quality
New laws & regulations
BI governance
Need for user-centered design strategies
Complications from a decentralized organizational structure
Weak information management
Need for cross-organizational program development
Lack of funding for ICT strategic planning and implementation
Resistance to technology
Complications in developing ICT infrastructure due to short-term
focus
Lack of trained personnel

“ It’s not enough to have the
perfect data model or best of
breed technology alone - you
need to coordinate the many
facets of a data warehouse
project, much like a conductor
must unify the many
instruments in an
orchestra…[the right] pieces
must be brought together in the
right order and at the right time
[to deliver a symphony].”
From The Data Warehouse Lifecycle Toolkit, 1998

We need to rethink about how to co-develop and sustain
a successful data/information/knowledge management
“to compete strategically with digital innovations
(business intelligence & smart services)”
rethink about how to co-develop (not develop)
INNOVATIONS
with
Efficient &
Effective Decision
Making
Cognitive Analytic
Thinking
+
Systems Thinking
+
Intuitive Design
Thinking

…integrate knowledge assets with semantics
TODAY most knowledge is dispersed
To be made useful, it must be
– Located
– Integrated
Knowledge integration takes place
– Across disciplines
– Across organizations
– Across cultures
I-shaped: Deep knowledge in a single discipline
A-shaped (or Π-shaped): Deep knowledge in two disciplines
T-shaped: Deep knowledge in one discipline with a basic understanding
of a number of others
– Understands systemic impact of disciplinary knowledge
– Understands customer needs
– Interdisciplinary collaboration

have major skill gaps
in mobile, business
analytics and security
* Includes business analytics, mobile computing, social business, and cloud computing.
Sources: IBM Tech Trends report 2012, Enterprise Strategy Group, CompTIA
report a skills shortage in the
ability to manage information
Among organizations worldwide today…
has all the skills it needs to be
successful applying advanced
technology* for benefit
An acute shortage of skills threatens organizations’
ability to address emerging opportunities and risks
EDUCATION NEEDS

The Business Analyst
Applies business intelligence, predictive
analytics, and other techniques to turn
information into business insight
Source: IBM Tech Trends report 2012
Data & Information Management
Combines the skills needed to collect,
store, manage, and understand patterns
and trends in data
The Cyber Security Professional
Requires a broad portfolio of security
skills and systems thinking applied to
business priorities
The Next Generation Software Engineer
Employs the skills and methodologies
needed to keep pace with the rapidly
evolving software engineering discipline
Business Intelligence & Analytics
60% of enterprises face a shortage
of business analytics skills today
40% of enterprises report a skills
shortage in ability to manage information
39% of organizations adding IT staff plan
to hire information security professionals
65% of enterprises face a shortage
of mobile development skills today
Information Security Software Engineering & Mobile Dev
FOUR KEY SKILLS THEY SEEK TO HIRE

CHALLENGES: The Problem With Data
Data is not information!
Data is often:
–spread across several systems
–stored in different formats
–may even be localized at different units
The first challenge is to consolidate the
data so that it is consistent and
accessible
The next challenge is to use it for
tactical/strategic advantage

Recommendations
Thinking and acting globally
Start from strategy (problems/issues)
–Don’t ask what people want – find out what people need
Clearly defined objectives
Tightly-coupled processes with BI
Perform the requirements, data modeling and views
Define the performance goals
An agile and self-driven work-force – skilled people
Rapid development
–3 month phases – evolutionary nature of development

Strategic, Tactical, Analytical, Operational BI

INFORMATION IS POWER with
Rapid assessment reports
Appeals, proposals, and project/program monitoring
and evaluation documents
Organizational architecture used in previous
responses
Humanitarian research documents
Coordination meetings and proceedings
Virtual collaboration networks
Publications of universities and research institutions
News articles and online resources
It is common to hear people say that “information is
power.”

Detecting Opportunities and Threats
You are the eyes and ears
Assess and relay significant new knowledge to the
team

The Urgency Addiction
What we regard as “first things” are mainly urgent things.
The Four Fundamental Needs
Physical
–Things such as food, clothing, shelter, economic well-being, health
Social/Emotional
–The need to love, relate to other people, to belong, to be loved
Mental
–The need to learn, develop, and grow
Spiritual
–The need to have a sense of meaning, purpose, and contribution
“To Live, to Love, to Learn, to Leave a legacy”
56

System tends to
operate within the
same mental and
practical models: real
improvements require
changes in mindset
and organizational
culture with education

FEW EXAMPLES FROM FUTURE

Disaster Planning & Preparation
Pervasive computing's influence on disaster response begins with
emergency planning and preparation.
Tabletop exercises help responders visualize how emergencies might unfold,
see their own actions as part of a whole, rehearse their responses to
scenarios in the company of other first responders, and learn to improvise on
the basis of formal plans.
Whereas scenario participants often make use of sensors and
communications technology both to become familiar with these tools and to
identify incompatibilities between systems used by different responders,
researchers are now developing tools to support learning within scenarios.
Simulation games that use data & information that mix wearable devices
and sensors, large-scale displays, collaboration tools, mobile-apps and cloud-
services.
Teams can collaborate on emergency-planning processes and integrate
lessons from scenario exercises.
http://www.strategicbusinessinsights.com/about/featured/2014/2014-02-humanitarian-tech.shtml#.VRnGQVVViko

Disaster Mapping
Since 2004, GIS professionals have been developing participatory mapping
systems for use in emergencies.
Uses community efforts to create maps of villages, new towns, and other
areas that official bodies have ignored.
The OpenStreetMap project (www.openstreetmap.org) aims to create open-
source maps as an alternative to both government maps and corporate GIS
projects like Google Maps. For rapidly growing cities in the developing world,
these maps may be the most reliable and up-to-date maps available. The
Humanitarian OpenStreetMap (http://hot.openstreetmap.org) overlays these base
maps with photos and information from text messages, tweets, and other sources
to give first responders a clearer picture of conditions in disaster areas.
During the 2010 Haitian earthquake, Humanitarian OpenStreetMap produced the
most reliable and fastest-updated maps of affected areas; not only were they used
by relief workers, they were even used by the US military.
Further, the maps themselves serve as a useful filter and interface for aid workers.
They give workers a familiar, visual way to access photographs, social media, and
other data, while excluding information that is not immediately relevant.

Humanitarian-Needs Prediction
The 2010 Haitian earthquake was also the first in which researchers
tried to use social-media data to forecast how people would react to
the disaster. The earthquake severely damaged Haiti's most populous
city, Port-au-Prince; it killed or injured half a million people, and destroyed
or damaged 300 000 homes.
The aftermath of the earthquake forced 1.5 million people into temporary
housing and camps. A team of researchers based at Karolinska Institutet
in Stockholm, Sweden, worked with Haitian cellular service Digicel to
analyze anonymized records of 2 million mobile users to predict where
they would relocate.
"When disaster strikes we tend to seek comfort in our nearest and
dearest," according to Karolinska Institutet researcher Xin Lu in a June
2013 public announcement. The data showed that "where people were
over Christmas and New Year, which was just before the earthquake,
tended to be the place where they returned."

Augmented Humanitarian Technology
As the number of relief organizations operating in disaster areas has
increased, and as aid workers and victims both acquire the means to
collect and broadcast information during disasters, humanitarian groups
face a new problem: verification and management of large quantities
of data, while also coordinating relief and supply efforts. Disasters
now play out in real time in blogs and social media.
Drones and other unmanned aerial vehicles
Cognitive systems that use large amount of data to predict solutions.

The Future of Humanitarian Technology
New technologies enable them to act as "customers,
clients, co-creators, or...constituents"— as active
participants who drive the aid and reconstruction
process. If designed well, tools that allow affected
people to plan and direct their own relief, to work
with aid agencies, and to track the delivery of
supplies would empower the people who save the
most lives, better serve long-term development
goals, and allow international agencies to serve
larger numbers of people more effectively.

Humanitarian Assistance and Disaster Relief Tools, Maps and Models
http://www.onr.navy.mil/en/Media-
Center/Fact-Sheets/Humanitarian-
Disaster.aspx

For any inquiries: haluk.demirkan@gmail.com
http://www.linkedin.com/in/halukdemirkan
https://twitter.com/profhaluk
Thank you!
Know where to find the
information and how to use it -
That's the secret of success.
Albert Einstein
65

Relief Operations: How to Improve Humanitarian Systems with Smart Analytics & Knowledge Management

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