psm workshop -- october 14, 2011

© 2011 IBM CorporationPSM workshop -- October 14, 2011

Technology, Data, Analytics New possibilities in our lives --

The important role of tomorrow’s mathematics professionals

Lilian Wu,

Worldwide University Programs Executive, IBM

© 2011 IBM Corporation2

Everything is becoming

INSTRUMENTED

We now have the ability to measure, sense and see the exact condition of practically everything.

INTERCONNECTED

People, systems and objects can communicate

and interact with each other in entirely new

ways.

INTELLIGENT

We can respond to changes quickly and accurately, and get better results

by predicting and optimizing

for future events.

WORKFORCE

MANUFACTURING

SUPPLY CHAIN

CUSTOMERS

TRANSPORTATION FACILITIES

IT

Analytics & Optimization


Volume of Digital DataEvery day, 15 petabytes of new information are being generated. This is 8x more than the information in all U.S. libraries.

By 2010, the codified information base of the world is expected to double every 11 hours.

Massive amounts of data being captured on natural and man-made engineered structures, processes and systems

Importance of Decision Making70% of executives believe that poor decision making has had a degrading impact on their companies’ performance

Only 9% of CFOs believe they excel at interpreting data for senior management

Analytics, modeling, and visualization of these data can help to run our systems more effectively


Types of Analytics

Based on: Competing on Analytics, Davenport and Harris, 2007

Deg

ree

of C

ompl

exity

Standard Reporting

Ad hoc reporting

Query/drill down

Alerts

Forecasting

Simulation

Predictive modeling

Optimization

What exactly is the problem?

What will happen next if ?

What could happen … ?

What if these trends continue?

What actions are needed?

How many, how often, where?

What happened?

Stochastic Optimization

Descriptive

Prescriptive

Predictive

How can we achieve the best outcome?

How can we achieve the best outcome including the effects of variability?

5 © 2011 IBM CorporationGlobal University Programs

Analytics Skills Areas that IBM and Clients Need

Understanding the types of analytics Database design Data collection & mining (finding, cleansing, normalizing) Database systems (design, implementation, on-line analytics of data) Rules-based data integration and reduction Stream computing and computing for multiple, parallel processing Statistical analysis Predictive analytics (modeling, simulation, forecasting) Prescriptive analytics (optimization) Descriptive analytics (score cards, dashboards, alerts) Analytics in -- marketing, text, web, risk, transportation, energy, etc. Risks, privacy, security, legal Implications Project management Inference and decision making Applying analytics to real world problems


Vassar Brothers Medical Center

Technology changes how systems and processes work – need mathematical models to better understand the changes and their consequences

– 365 bed Regional Hospital in Poughkeepsie, NY– Four Centers of Clinical Excellence

• The Heart Institute• Women’s & Children’ Services• The Dyson Center for Cancer Care• Center for Advanced Surgery

– Nurses• 700

– Physicians• 520 privileges

– Campus• 515,000 Sq. Ft.

Multiple StructuresRanges - 10 to 100 years

– Freestanding Ambulatory Center• 130,000 Sq. Ft• 15 miles south


Hospitals are Complex Systems

Hospitals

“Modern medicine is one of those incredible works of reason: an elaborate system of specialized knowledge, technical procedures, and rules of behavior.”

– Paul Starr, author of The Social Transformation of American Medicine

Patients

Doctors

Nurses

Staff

Administrators

Family members

Employers

Insurers

Governments


OR techniques -- model and analyze new processes

RFID tags to track IV pumps – IV pumps – nurses typically spent over an hour each day looking for equipment –

resulted in pumps being hoarded• No being properly cleaned • Not certified to be pumping the correct amounts

– Changed to tagging each pump with an RFID to track location. – Twice daily equipment census and pick up unused pumps collected from central

locations

Improve Asset Utilization– Reduce over-buying, lost assets

Workflow Optimization– Match equipment/people to need

Results– Reduce time staff spends looking for missing devices– Pumps cleaned and certified to be pumping the correct amounts– Planned purchase of $0.5M of new pumps – not necessary


OR -- city planning and management using geographical data

DC Water & Sewer Authority -- Automated scheduling in a user selected zone of the city

Goal: •Number of Crews = 2•Shifts: 1 day shift per crew•Objective: Assign as many WO’s as possible to each crew, while maximizing the sum of the priority of the WO’s while meeting constraints of shift duration, lunch break & travel time.

Goal: •Number of Crews = 2•Shifts: 1 day shift per crew•Objective: Assign as many WO’s as possible to each crew, while maximizing the sum of the priority of the WO’s while meeting constraints of shift duration, lunch break & travel time.

User selected region for scheduling

User selected region for scheduling


Statistical Models -- city operations using historical data

Buildings: Reduce energy use and reduce greenhouse gas emissions

1,400 K-12 Public School Buildings in New York City 150 million sq ft – Joint project w. CUNY

– Static Data (5 years energy consumption, building characteristics, weather)– Statistical analysis, monitoring, simulation, optimization of energy use, GHG

emissions and retrofit planning with budget constraints

• Technical Challenges– Processing large volumes of historical data from various sources– Developing physics-based models and statistical models for energy

consumption– Simulation of energy demand, energy supply, and building operations to

reduce energy consumption, cost and GHG emissions

Results for March 2011– Martin Luther King Junior High School reduced its electricity consumption by

35.1% and 216,061 pounds of CO2 – The top 10 winning schools collectively saved 327,003 pounds of CO2 and

average reduction of 16% in electricity consumption


Water -- In the last 100 years global water usage has increased at twice the rate of population growth

Produces table grape, pepper, stone fruit and citrus varieties on 12,000 acres in California

•Analyzed different irrigation systems (incl. newer drip systems) impact on crop yields -- decreased water usage by 8.5% since 2006

•Better matching of farming equipment to specific harvesting tasks -- decreased fuel consumption by 20% since 2006


Monitoring and data collection

Natural Water System Management for Galway Bay (Ireland)

Marine research infrastructure of sensors and computational technology interconnected across Galway Bay collecting and distributing information on:

– coastal conditions– pollution levels– marine life

Streaming real-time information to allow better decision-support related to:

– Weather threats– Pollution alerts– Algal bloom prediction– Rogue waves, etc

The monitoring services, delivered via the web and other devices – used for tourism, fishing, aquaculture and environment

Adapted from Smart Bay reference documentation

See video at http://www.youtube.com/watch?v=n2XakurQCgU


Dynamic Real-time Model for Galway Bay

Nat’l U of Ireland Galway and IBM collaboration

Develop model of the water quality of a bay based on the hydro-dynamics of chemical diffusion. Sensors measuring the speed at the water surface will gather data and special streaming software will be used to continuously collect and add new data to recalibrate the model and its predictions.

Two goals: 1. proof of concept for building -- a real-time continuous assimilation system (computer system + software) to model situations where real-time data + a model (e.g., traffic, smoke, fire, ...) are important; and 2. the science will inform analysis of the ecological impact of the release of waste water from the County of Donagal waste water treatment plant into its estuary.


Unstructured data / Natural language

Much of our smart world is built using highly structured dataBut a large portion of information is unstructured

Much is based on natural language -- highly contextual and full of

ambiguity.

The sheer mass of these unstructured data Difficult for unassisted humans to assimilate

Beginning to explore what computers can do to assist


Watson

Human Language

• Ambiguous, contextual, imprecise, and implicit• Contains slang, riddles, idioms, abbreviations, acronyms, …• Seemingly infinite number of ways to express the same meaning

psm workshop -- october 14, 2011

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