introduction 1 mcgill university’s experience in planning: lessons that might be learned
Post on 21-Dec-2015
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Planning: lessons learned
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Planning, along with decision making, is an integral part of the job of the Vice-chancellor, the Provost, the Vice-presidents, the Deans, the Chairs, the Directors.
Planning: lessons learned
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Planning is based on:– Vision, wisdom, judgment, and
experience;– Solid and clearly understood data.The role of the data is to inform, not to
drive, the planning, be it strategic or tactical.
Planning: lessons learned
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It is a challenge to turn a vast amount of fine grained data into useful business intelligence.
• The senior administrator needs to really understand the data,
• IT project manager needs to really understand the needs of the user.
The only good answer is that they must both invest quality time and effort.
Planning: lessons learned
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Open access to information • to fine grained data• to aggregated/analyzed/filtered data• to analytic toolsDownside: some people will do incorrect analyses with the dataUpside: everybody can check that MY analyses are correct.
Planning: lessons learned
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Administrative and reporting structure is very important.
• Reporting lines• Assignment of responsibility• Flexibility• Good communication at every level
across silos
Planning: lessons learned
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Warning: never forget to take into account• Institutional politics• Personal ambitions• Defense of turfHuman nature has always been a major
factor in success as well as in failure.
About me
Core position: Professor of Physics ( now emeritus )
Past administrative positions:Chair, Department of PhysicsAssociate Dean of ScienceInterim Dean of ScienceAssociate Provost – responsibilities included• Courses and academic programs• Student affairs, Admissions, Registry, Residences, …
Interim Registrar
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About McGill University
• Founding date of McGill University: 1821 • Degrees granted in 2008-09: 7675• 35,300 students (19 % international,
22 % graduate )• 1,627 tenured/ tenure-track faculty
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About McGill University
International Rankings :• THES 2009: 18• Shanghai Jiao Tong 2009: 65Canadian Rankings: • Macleans (medical/doctoral) 1
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The Quebec context
Bachelor Masters DoctoralBishop's U. 567 6 0 Concordia U. 4546 1012 115 U. Laval 4920 1438 283 McGill U. 4090 1198 399 U. Montreal + 6804 2280 409U. Sherbrooke 2523 1020 110 U. Quebec 9272 2328 268 Total 32722 9282 1584
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The Quebec context
• Government (MELS) university budget envelope = cad$M 2490
• Distribution of operating grants: –most (~4/5)“normed” by weighted or
straight FTE– Some targeted by general priorities, – Some targeted by special priorities.
• Value of a weighted FTE = available envelope divided by the total weighted FTEs
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The Quebec context
Government data bases (input is audited)• Students: GDEU –complete (except for grades) SRS ;
• Staffing: EPE and SYSPER• Research grants/contracts: SIRU• Buildings and facilities: SILU• Finance: SIFU
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Vice-Principals (Planning) at McGill University
• 1966-1969 Carl A. Winkler, Planning & Development • 1973-1976 Dale C. Thomson,
Planning • 1976-1981 E.J. Stansbury, Planning • 1981- 1986 E.J. Stansbury, Planning &
Academic Services16
Vice-Principals (Planning) at McGill University
• 1986-1989 Paul Davenport, Planning and Resources • 1989-1997 François Tavenas,
Planning and Resources• …………
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Heads of Planning at McGill University
• ………… • 2006-2008 Helène Perrault, Associate
Provost (Planning & Budgets)• 2009- Pierre Moreau, Executive
Director, Planning and Institutional Analysis (PIA) and Senior Advisor (Policy Development)
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University Planning Office: 1990-2000
Institutional analysis – scope:• Space and facilities• Organization table• Student enrolment • staffing, especially academic staff• Research grants • Data exchanges and benchmarking:
AAUDE, G10 (later G13), etc. 19
University Planning Office: 1990-2000
Institutional Analysis: methodology• Fixed census dates• Precise and standardized data definitions • Transparency and open access –McGill Fact Book: open on the web
• Metrics• Space database and tools
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The PBA budget model
• Data and analysis: UPO / VP(Planning ).• Faculty budgets– Initial budget cut to reduce deficit and
generate free money– Substantial part of the allocation is
enrolment driven;– Smaller part is a discretionary allocation; – Changes smoothed over some years
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The PBA budget model
• Service unit budgets –Historical plus adjustment.–No formula
• Total scaled to predicted income.• Process iterated several times between
November and May.
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The PBA budget model
• Undergraduate FTE is based on courses:FTE = (number of student credit hours
taught by a unit)/30• Graduate FTE (non-thesis) is as above.• Graduate FTE (thesis) is based on
enrolment–Time limits: masters = 1.5 years, PhD =
3 or 4 years. 24
The PBA budget model
Weighted student units:WSU = (weight of the degree level)*FTECurrent weights are:• Bachelor = 1• Masters = 2• PhD = 3.3
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The PBA budget model
• Budget allocated to a faculty = (faculty weight)*(total WSU of the faculty)• Faculty weight is a measure of the
cost of the disciplines in the faculty
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The PBA budget model
• Departmental budgets are determined by the Dean, not central administration• The PBA model is not believed to be
sensible for units smaller than faculties.
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The PBA budget model
• Strength:–Predictability–“fairness”–Connection with the government
funding model
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The PBA budget model
• Weakness:–Needs driven rather than vision driven–Quantity driven rather than quality
driven–Open to manipulation–Transparency
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Budget 2003
The PBA budget model was found to be increasingly unsatisfactory for McGill’s purposes, and was abandoned around 2003.
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Senior Administration
1997. • The position of Vice-Principal (planning)
is left unfilled.• University Planning Office reports to both
VP Academic and VPAdmin & Finance).• The budget is back in the hands of
VP(Admin & Finance)
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Senior Administration
The “Provostial” model of university administration is introduced. • <2001 : “Vice-Principal(Academic)”• 2001: “Vice-Principal(Academic) and
Provost”• 2003: “Provost”
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Senior Administration
The “Provostial” model of university administration is completed. • 2007: Provost is responsible for the
budget• 2009: new Office of the Budget -
reporting to the Provost
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Current budget model
Current budget model. Its pillars are:• a strategic plan (vision),• faculty compacts, including–academic renewal–enrolment targets
• multi-year budget (incl. deficit reduction targets)
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Current budget model
• Compared to PBA model:–The form: very different–The substance: much the same–The difference is the starting point for
the budget iterations–Budget was and is “Research driven” • ( please explain)
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Current budget model
• Faculty compacts– Iterative discussions between Provost
and Deans– Informed by data analysis ( and
projections ??? ), performance indicators, benchmarks, ….–Constrained by operating budget from
the government 36
3 Science Departments
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Dept. Professors UG FTE GR FTEComputer Science
28 123 45
Earth & Planetary
11 107 10
Psychology 33 500 33
Central offices -- planning
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• Office of Planning and Institutional Analysis Executive DirectorProvost
• Office of the Budget DirectorProvost
• Campus and Space Planning Office AVP(Univ. Services) Vice-Principal(Admin&Finance)
Central offices -- planning
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• Enrolment Services RegistrarDeputy ProvostProvost
• Information Technology Services CIOVice-Principal(Admin&Finance)
Observations
“In the old days”.–the best information was based on
direct contact with reality–the information, understanding
and analytic power were all in the head of the decision maker.
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Observations
At the present time.– Enterprise data systems with a vast amount
of fine grained data– It would be irresponsible not to use this
information–Business Intelligence tools to reduce and
package this information are not (yet?) really satisfactory
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Observations
Is the quantitative information generated by the BI tools:
• a solid and accurate representation of parts of reality?–I think yes, if we work hard at it;
• a reliable representation of full reality?–I think not, at least not for a long while.
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