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Neil Olonoff

Building Resilience into Business as Usual with Knowledge

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Page 1: Building Resilience into Business as Usual with Knowledge

Neil Olonoff

Page 2: Building Resilience into Business as Usual with Knowledge

Examples of catastrophic knowledge collapse What (really) is COOP? Disaster versus “business as usual” Building resilience into “business as usual”

Combine Risk Management and KM

Knowledge Enabling of Processes

Page 3: Building Resilience into Business as Usual with Knowledge
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1. All were avoidable. 2. All are examples of

catastrophic knowledge collapse.

Want proof?

Page 8: Building Resilience into Business as Usual with Knowledge

Actual telegram containing the observed

position of the iceberg that sank the Titanic.

Page 9: Building Resilience into Business as Usual with Knowledge

Documented example of O-ring

blowback on Space Shuttle

Booster Rocket

Page 10: Building Resilience into Business as Usual with Knowledge

Cover page of the President’s Daily

Brief, dated August 6,2001, entitled

Bin Ladin Determined to Strike in

US.

Page 11: Building Resilience into Business as Usual with Knowledge

Documents Show Early Worries About

Safety of Rig

Page 12: Building Resilience into Business as Usual with Knowledge

In each case, a knowledge gap resulted in a catastrophic cascade; a “knowledge collapse” How?

Page 13: Building Resilience into Business as Usual with Knowledge

Small gaps cascade to produce big impacts. These can be performance or knowledge gaps

For want of a nail the shoe was lost.For want of a shoe the horse was lost.For want of a horse the rider was lost.For want of a rider the battle was lost.For want of a battle the kingdom was lost.And all for the want of a horseshoe.

Page 14: Building Resilience into Business as Usual with Knowledge

“Process breakdown due to knowledge resource failure.”

Today, organizations “run on” knowledge

Knowledge is as essential as gas and oil in a car; food and water to an organism

In other words, the flow of knowledge is essential to operation; stopping the flow causes problems; if enough problems occur, processes break down.

Page 15: Building Resilience into Business as Usual with Knowledge

Complacency breeds neglect, and ..

Failure to ”detect weak signals”

Acceptance of faulty assumptions

Failure to implement risk management Disconnects between COOP and Business as

Usual

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Traditionally “disaster oriented.”

Views its role only in situations of catastrophe

Usually provides alternative sites and support Usually ignores “business as usual.”

Page 17: Building Resilience into Business as Usual with Knowledge

The difference between “business as usual” and a disaster is often a matter of degree in terms of the “number of processes impacted.”

© Neil Olonoff

Page 18: Building Resilience into Business as Usual with Knowledge

Decision and performance support systems that are integrated with knowledge and information sources

Combine KM & Risk Management Learn from Failure Comprehensive Who Knows What Where

resource Active, dynamic social networking systems

Page 19: Building Resilience into Business as Usual with Knowledge

Disasters teach more than successes. “Never let a good crisis go to waste.” Allow learning by exposing failure to the light

of day. Knowledge management can help by ..

Identifying “weak signals”

Institutionalizing adaptive habits

Building knowledge into critical processes

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Broad, William J. Taking Lessons From What Went Wrong. New York Times, July 19, 2010.

Carl, Joseph W. Lt Col USAF (Ret) and Freeman, George, Col, USAFR (Ret), Nonstationary Root Causes of Cobb’s Paradox, Defense Acquisition Review Journal, Vol 17. No. 55, Jul 2010, pp 337-

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1. User Involvement2. Executive Management Support3. Clear Statement of Requirements4. Proper Planning5. Realistic Expectations6. Smaller Project Milestones7. Competent Staff8. Ownership9. Clear Vision & Objectives10. Hardworking, Focused Staff

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In 1995, Martin Cobb worked for the Secretariat of the Treasury Board of Canada. He attended The Standish Group’s CHAOS University, where the year’s 10 most complex information technology (IT) projects are analyzed and discussed. The 10 most complex IT projects studied by The Standish Group in 1994 were all in trouble: eight were over schedule, on average by a factor of 1.6 and over budget by a factor of 1.9; the other two were cancelled and never delivered anything. That led Cobb to state his now famousparadox (Cobb, 1995): “We know why [programs] fail; we know how to prevent their failure—so why do they still fail?”