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Knowledge Strategy & McKinsey
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Value Propositions and Accenture
Common KM Value Propositions• Effectiveness/Responsiveness.• Efficiency.• Innovation.
Accenture• KXchange – representative approach and mindset of many!
• Technology: D-Base, Discussion Forums, Collaborative Tools and Expertise Locators.
• Massive investment in technology and organization infrastructure.• Works well with repeatable work (when you can drive re-use) and
where information is really what needs to be transferred.
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Information Versus Knowledge in Retail Banking
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DocumentsDocumentsDatabasesDatabases
ReportsReports
• FactsFacts• IdeasIdeas• TheoriesTheories
• IntuitionIntuition• BeliefsBeliefs• ValuesValues
• RoutinesRoutines• ProceduresProcedures• InstructionsInstructions
• ExpertiseExpertise• InstinctsInstincts• Informal Informal
PracticesPractices
EXPLICIT TACIT
KnowWhat
KnowHow
ManualsManualsEngineering Engineering
MethodsMethods
DialogueDialogueConversationConversation
MentoringMentoring
ExperienceExperienceApprenticeshipsApprenticeships
CoachingCoaching
Types of Knowledge
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1. Knowledge & Strategy.
2. KM at McKinsey.
3. Remembering 9/11.
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Cluster in groups of 2-3… My left side of the room focus on codification. Be prepared to
discuss:• Randall Love’s search• The overall strategy and economics• Primary investments in technology and infrastructure to support it.• Incentive schemes (and focus)
My right side of the room focus on personalization. Be prepared to discuss:• Marcia Blenko’s search• The overall strategy and economics• Primary investments in technology and infrastructure to support it.• Incentive schemes (and focus)
Where Would You Characterize Accenture? McKinsey?
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Choose between Two Strategies
Codification• Link is person-to-document
• Extract, store and share through computers
• Reuse codified knowledge across similar tasks
Personalization• Link is person-to-person
• Share and apply through people networks
• Channel expert advice to unique problems
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Codification: Access Health
Call-in medical center with 500 nurses Nurses assess and direct patients Use 500 pre-developed software algorithms
“We’re not inventing new ways to cure decease. We’re taking available knowledge and inventing processes to put it to better use.”
CEO Joe Tallman
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AH relies on “Reuse Economics”
Costs:1 algorithm=$40,000variable costs=$20.
Usage:For first 300 algorithms; reused 8,000 times on average last year
Reuse of knowledge assets drives profits, not economiesof scale based on volume
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no. times reuse of software algorithm
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Personalization: Memorial Sloan Kettering Cancer Center
No. 1 rated cancer center in the U.S. Most innovative and customized cancer treatment in
the country Heavily based on personal communication between
doctors, scientists, etc. Co-located in 17 disease teams; meetings Investing heavily in re-use misses the point here
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Different strategies, different drivers
Codification Fast, efficient delivery of
products “reuse economics” People: “implementers”
Personalization unique solutions to unique
problems “expert economics” People: “inventors”
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Incentives and IT systems differ
IT for Codified: heavy investments “library” + search engines
Incentives for codified:
- to write up documents,
- to use documents
IT for Personalized: minor investments “people-finders” + search for
people
Incentives for personalized:
- to help others directly
- to ask for help
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1. Knowledge & Strategy.
2. KM at McKinsey.
3. Remembering 9/11.
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McKINSEY3 minutes to come up with THE answer
• What strategically differentiates McKinsey? How does KM (repositories, collaborative technologies and employee development) play into this?
• What were the key elements of the knowledge management project launched in 1987?
• Be prepared to discuss the Jeff Peters vignette. Specifically, how did he solve his problem?
• What challenges does McKinsey face as evidenced in the case and vignettes?
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General Case Questions: McKINSEY• What strategically differentiates McKinsey? How does KM in terms of
repositories, collaborative technologies and employee development play into this?
• Solve tough, high-end and big-dollar problems that require a high degree of expertise and creativity.
• People are inventors, not implementers.
• Most problems are unique and solutions customized.
• KM investments for them are heavily oriented to connecting people.
• Technically (expertise locators and even repositories)
• Organizationally (staffing and culture).
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General Case Questions: McKINSEY
• What were the key elements of the knowledge management project launched in 1987?
• A common database of client work (e.g., sales presentations, deliverables, analytic techniques, etc.).
• Client Sectors and Competence Centers hired a full time practice coordinator to monitor quality and direct consultants to content.
• Established both I shaped and T shaped career paths.
• Knowledge Resource Directory (paper-based) of firm experts and documents.
How important was it that the 2,000 documents that Matasonni and Manville collected be high quality?
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Jeff Peters in Sydney• Be prepared to discuss the Jeff Peters vignette. Specifically, how did he
solve his problem?
• Issue: Bid for growth strategy of respected financial services organization. But local industry expertise “conflicted out.”
• Resolution: Immediately began using his personal network. Via this found Jeff Peters in Boston (though unavailable for 6 weeks).
• His help: 1) John Peacocke (New Zealand – 2 years in McKinsey – mostly oil and gas); 2) Patty Akopiantz (1 Year Associate with prior I-Bank experience) and 3) Jonathon Liew (first McKinsey assignment).
• Forged group of experts from all over the world.
• Found 179 relevant PD documents and followed up with 60 more people.
• Won the project and client bought in.
• Jeff not happy though (no breakthrough too much reliance inside firm).
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Video Points of Importance• For you aspiring consultants, note the opening comment about the pressure to come
up with a unique solution (with little experience).
• First stop is PD Net. They do re-use documents. But note that they also use these documents to determine who to turn to for help.
• Key is finding the 3-4 teams somewhere around the globe that can coach you through the process.
• Culture in McKinsey where you both add to the knowledge base and when you respond when asked.
• In part a product of the “One Firm” culture and hiring.
• Performance evals. from day one also emphasize both knowledge contribution (PD output) and help to others.
• Personal development and feedback built in at all stages.
• Learning during an engagement via feedback sessions.
• Development key to assignments during engagement.
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General Case Questions: McKINSEY
• What challenges does McKinsey face as evidenced in the case and vignettes?
• Managing growth: Difficult to scale the way Accenture does.
• Leveraging external expertise:
• Reaching outside the firm.
• Integrating experienced hires.
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A Web of “Effective” Information Flow…
= Associate
= Associate Principal= Manager
Hierarchy
= Principal & Director
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A low proportion of people regularly reach outside McKinsey for knowledge
55
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811
55
32
48
Under 1 year
Over 1 year
McKinsey Boston
McKinsey other
Client Other
Experienced hires are the
main exception
* Percentage of top 7 information contacts from each source type
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We are three times less likely to go outside our pod for regular information
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9Information sharing*
Within same pod
Neighboring pod
2 pods away
More than 2 pods away (or different floor)
Distance
* Weekly information sharing out of a possible 100% of interactions
vs.
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1. Knowledge & Strategy.
2. KM at McKinsey.
3. Remembering 9/11.
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What does this have to do with knowledge management??
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Give Me Five Minutes of Thought
How can KM be applied to national security?• Within Agencies?• Between Agencies?• Targeting Initiatives.• Educating.
• Us• Them
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KM and National Security Within Agencies Bureaucracy Can Stifle “Knowing What We Know.”
• CIA developing an ability to surge.
• NSA is creating new leadership networks and data mining algorithms.
Turf Wars Between Agencies (CIA and FBI) Preclude Action.• Homeland Security Office (22 agencies, 200,000 employees and $37.5B)• Bio-Terrorism Response Capability.
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9/11: A Data (Dis)Integration Case Study
January 2000: Mohamed Atta obtains U.S. visa
Who knew? State Department
June 2000: Atta meets with Iraqi intelligence in Prague
Who knew? Central Intelligence Agency
June 2000: Atta enters the U.S.
Who knew? Immigration and Naturalization Service
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9/11: Case Study, Continued
July 2000: $100K wired to Mawan al-Shehhi, pilot of one of two planes that struck WTC
Who knew? Treasury Department
December 2000: Atta and al-Shehhi leave stalled airplane on Miami runway
Who knew? Federal Aviation Administration
July 2001: Agent warns of potential terrorists in training at U.S. flight schools
Who knew? Federal Bureau of Investigation
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KM and National Security Within Agencies Bureaucracy Can Stifle “Knowing What We Know.”
• CIA developing an ability to surge.
• NSA is creating new leadership networks and data mining algorithms.
Turf Wars Between Agencies (CIA and FBI) Preclude Action.• Homeland Security Office (22 agencies, 200,000 employees and $37.5B)• Bio-Terrorism Response Capability.
Targeting Interventions.• Combat almost exclusively about information.• A key target is finding and disrupting networks.
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Small World Metrics• CC = 0.41• CPL = 4.75• Shortcuts = 0.19
Prior Contacts
http://www.orgnet.com/MappingTerroristNetworks.pdf
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KM and National Security Within Agencies Bureaucracy Can Stifle “Knowing What We Know.”
• CIA developing an ability to surge.
• NSA is creating new leadership networks and data mining algorithms.
Turf Wars Between Agencies (CIA and FBI) Preclude Action.• Homeland Security Office (22 agencies, 200,000 employees and $37.5B)• Bio-Terrorism Response Capability.
Targeting Interventions.• Combat almost exclusively about information.• A key target is finding and disrupting networks.
Educating Different Parties.• How do you help create understanding amongst disparate groups?• Religious and socio-economic differences.
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Discussion Questions For Class On Knowledge Generation
Be prepared to tell me about the knowledge brokering steps (and provide examples at each point).
