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Tradelines MissionComplexity Staffing Productivity Analysis IFMA Utilities Council Philadelphia, Oct

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Title: Tradelines MissionComplexity Staffing Productivity Analysis IFMA Utilities Council Philadelphia, Oct


1
Tradelines Mission-Complexity Staffing
Productivity Analysis IFMA Utilities Council --
Philadelphia, October 20, 2005 Steve Westfall,
President Tradeline, Inc. swestfall_at_TradelineInc.c
om (925) 254-1744, ext 14
  • AGENDA
  • The Mgt-Complexity-Score/Headcount concept
  • Organizational diagnostics
  • Which variables drive staffing (Sensitivity
    Analysis)
  • Scenario planning tracking over time
  • What about the outliers?
  • Span of management
  • Industry groups (Example Bio-pharmaceuticals)
  • FM/CRE action items

2
  • HEADS MATTER
  • CEO Board actions Heads Capital
  • Big cost cutting cut jobs
  • Growing divisions add jobs
  • FM/CRE groups not immune Headcount challenges

3
  • In the News Companies recently dealing in HEADS!
  • Hewlett-Packard announces
  • 2001 - 6,000 jobs
  • 2005 -14,000 jobs
  • Eastman Kodak announces
  • 2004 -15,000 jobs
  • 2005 -10,000 jobs
  • Kimberly Clark announces
  • 2005 - 6,000 jobs
  • Ford Motor Company announces
  • 2005 -10,500 jobs (white collar)
  • Sun Microsystems announces
  • 2002 - 8,500 jobs

4
Agenda
  • The Mgt-Complexity-Score/Headcount concept
  • Organizational diagnostics
  • Which variables drive staffing (Sensitivity
    Analysis)
  • Scenario planning tracking over time
  • What about the outliers?
  • Span of management
  • Industry groups (Example Bio-pharmaceuticals)
  • FM/CRE action items

5
(No Transcript)
6
Over-staffed relative to the Panel
Under-staffed relative to the Panel
7
  • On-payroll FM/CRE
  • Personnel (The Force)
  • Per 1000 pp served
  • (The Mission)
  • Mission Complexity Score (MCS)
  • (How complex is the Mission?)

8
How they stack up 76 FM/CRE groups
FM staff per 1000 people served
9
How they stack up 76 FM/CRE groups
FM staff per 1000 people served
FM staffing model range .2 FTEs/1000 to 100
FTEs/1000, a range of 500 to 1!
10
How they stack up 76 FM/CRE groups
FM staff per 1000 people served
Average 20/1000
Median 13/1000
11
How they stack up 76 FM/CRE groups
FM staff per 1000 people served
Average 20/1000
Median 13/1000
12
How they stack up 76 FM/CRE groups
FM staff per 1000 people served
Leaning-down by 3- 4/year 6 years ago
Average 23/1000 Median 17/1000
Average 20/1000
Median 13/1000
13
  • FM/CRE Headcount per 1000 people served
  • Total service heads on payroll
  • (Population served/1000)
  • Example 90 svc heads, 1,500 population served
    60 heads per 1000
  • Mission Complexity drives FM/CRE staffing per
    1,000 people served
  • Scope Space types 25
    Services outsourcing
  • Population served Vacant RE (acquisition,
    lease mgt)
  • Own/lease Warehouse Engineering
  • Types of leases Office Planning space mgt
  • Technol use Manufacturing Operations
    maintenance
  • Churn Research Mail
  • Seated, unseated Computer ctrs… 4
    others Custodial…. 20 others

14
Note Population-served drops out as a Mission
Complexity factor when the organizational metric
is FM/CRE heads per 1,000 people served
(companies normalized for size).
  • FM/CRE Headcount per 1000 people served
  • Total service heads on payroll
  • (Population served/1000)
  • Example 90 svc heads, 1,500 population served
    60 heads per 1000
  • Mission Complexity drives FM/CRE staffing per
    1,000 people served
  • Scope Space types 25
    Services outsourcing
  • Population served Vacant RE (acquisition,
    lease mgt)
  • Own/lease Warehouse Engineering
  • Types of leases Office Planning space mgt
  • Technol use Manufacturing Operations
    maintenance
  • Churn Research Mail
  • Seated, unseated Computer ctrs… 4
    others Custodial…. 20 others

15
Note 1 Population-served drops out as a Mission
Complexity factor when the organizational metric
is FM/CRE heads per 1,000 people served
(companies normalized for size).
  • FM/CRE Headcount per 1000 people served
  • Total service heads on payroll
  • (Population served/1000)
  • Example 90 svc heads, 1,500 population served
    60 heads per 1000
  • Mission Complexity drives FM/CRE staffing per
    1,000 people served
  • Scope Space types 25
    Services outsourcing
  • Population served Vacant RE (acquisition,
    lease mgt)
  • Own/lease Warehouse Engineering
  • Types of leases Office Planning space mgt
  • Technol use Manufacturing Operations
    maintenance
  • Churn Research Mail
  • Seated, unseated Computer ctrs… 4
    others Custodial…. 20 others

Note 2 No two companies, even companies in the
same industry, have the same mix of these
factors, and for any one company the mix changes
from year to year.
16
  • Calculate a Mission Complexity Score (MCS)
  • Scope X Space X Services

17
  • Calculate a Mission Complexity Score (MCS)
  • Scope X Space X Services
  • Space score SoYo SrYr SmYm…
  • Where S Weight for type of space (office,
    research)
  • Y of space (office, research)

18
Note Point-scoring for predictive analysis is
not a new idea. The Credit Industry has been
doing this for years in credit scoring to predict
the probability of debt repayment. It is based
on what is called Structured-equation,
Multi-variant Analysis.
  • Calculate a Mission Complexity Score (MCS)
  • Scope X Space X Services
  • Space score SoYo SrYr SmYm…
  • Where S Weight for type of space (office,
    research)
  • Y of space (office, research)

19
How they stack up 76 FM/CRE groups
FM staff per 1000 people served
20
How They Stack Up
21
How They Stack Up
22
How They Stack Up
HIGH MCS Armstrong World Indus, Chiron, Corixa,
Corning Inc, DuPont, Eastman Chemical, Ford,
Intel 2, Intel 3, Lawrence Livermore Natl Lab,
Pfizer, Pioneer - a DuPont Co., Roche Palo Alto,
Sandia Natl Lab

MID MCS BASF-RTP, Boehringer Ingelheim, Dow
Corning, FedReserve Bank Chicago, Fred Hutch
Cancer Ctr, FreddieMac, GlaxoSmithKline
Stevenage, IBM-Sterling Forest, Intel 1, Int'l
Truck Engine, Lexmark International, Lincoln
Fin Group, Navy Fed Credit Union, Northrop
Grumman, RAND, SAFECO, Thrivent Financial,
Univera, USAA, Vision Services Plan
LOW MCS AIM Investments, Alaska Court System,
Alliant Energy, BlueCrossShieldMA, Cargill, GE
Corp-U.S., General Motors, GlaxoSmithKline-Greenfo
rd, GlaxoSmithKline-Harlow, Harley-Davidson,
Honeywell, IBM-Northcentral, IBM-Raleigh, IndyMac
Bank, Luxottica Retail, Microsoft Puget Sound,
Millennium Pharm, Nortel Networks, Onyx Software,
Sears, Sempra Energy Util's, Siemens ICN, State
of WA Dept of Ecology, Time Warner Cable, Walter
Reed AIR, World Bank
23
How They Stack Up
HIGH MCS Armstrong World Indus, Chiron, Corixa,
Corning Inc, DuPont, Eastman Chemical, Ford,
Intel 2, Intel 3, Lawrence Livermore Natl Lab,
Pfizer, Pioneer - a DuPont Co., Roche Palo Alto,
Sandia Natl Lab

Same industry, totally different staffing models
How to compare?
MID MCS BASF-RTP, Boehringer Ingelheim, Dow
Corning, FedReserve Bank Chicago, Fred Hutch
Cancer Ctr, FreddieMac, GlaxoSmithKline
Stevenage, IBM-Sterling Forest, Intel 1, Int'l
Truck Engine, Lexmark International, Lincoln
Fin Group, Navy Fed Credit Union, Northrop
Grumman, RAND, SAFECO, Thrivent Financial,
Univera, USAA, Vision Services Plan
LOW MCS AIM Investments, Alaska Court System,
Alliant Energy, BlueCrossShieldMA, Cargill, GE
Corp-U.S., General Motors, GlaxoSmithKline-Greenfo
rd, GlaxoSmithKline-Harlow, Harley-Davidson,
Honeywell, IBM-Northcentral, IBM-Raleigh, IndyMac
Bank, Luxottica Retail, Microsoft Puget Sound,
Millennium Pharm, Nortel Networks, Onyx Software,
Sears, Sempra Energy Util's, Siemens ICN, State
of WA Dept of Ecology, Time Warner Cable, Walter
Reed AIR, World Bank
24
How They Stack Up
HIGH MCS Armstrong World Indus, Chiron, Corixa,
Corning Inc, DuPont, Eastman Chemical, Ford,
Intel 2, Intel 3, Lawrence Livermore Natl Lab,
Pfizer, Pioneer - a DuPont Co., Roche Palo Alto,
Sandia Natl Lab

MID MCS BASF-RTP, Boehringer Ingelheim, Dow
Corning, FedReserve Bank Chicago, Fred Hutch
Cancer Ctr, FreddieMac, GlaxoSmithKline
Stevenage, IBM-Sterling Forest, Intel 1, Int'l
Truck Engine, Lexmark International, Lincoln
Fin Group, Navy Fed Credit Union, Northrop
Grumman, RAND, SAFECO, Thrivent Financial,
Univera, USAA, Vision Services Plan
Pharmaceuticals at all levels How to compare?
LOW MCS AIM Investments, Alaska Court System,
Alliant Energy, BlueCrossShieldMA, Cargill, GE
Corp-U.S., General Motors, GlaxoSmithKline-Greenfo
rd, GlaxoSmithKline-Harlow, Harley-Davidson,
Honeywell, IBM-Northcentral, IBM-Raleigh, IndyMac
Bank, Luxottica Retail, Microsoft Puget Sound,
Millennium Pharm, Nortel Networks, Onyx Software,
Sears, Sempra Energy Util's, Siemens ICN, State
of WA Dept of Ecology, Time Warner Cable, Walter
Reed AIR, World Bank
25
How They Stack Up
HIGH MCS Armstrong World Indus, Chiron, Corixa,
Corning Inc, DuPont, Eastman Chemical, Ford,
Intel 2, Intel 3, Lawrence Livermore Natl Lab,
Pfizer, Pioneer - a DuPont Co., Roche Palo Alto,
Sandia Natl Lab

MID MCS BASF-RTP, Boehringer Ingelheim, Dow
Corning, FedReserve Bank Chicago, Fred Hutch
Cancer Ctr, FreddieMac, GlaxoSmithKline
Stevenage, IBM-Sterling Forest, Intel 1, Int'l
Truck Engine, Lexmark International, Lincoln
Fin Group, Navy Fed Credit Union, Northrop
Grumman, RAND, SAFECO, Thrivent Financial,
Univera, USAA, Vision Services Plan
Evidence suggests Utilities are at all levels as
well How to compare?
LOW MCS AIM Investments, Alaska Court System,
Alliant Energy, BlueCrossShieldMA, Cargill, GE
Corp-U.S., General Motors, GlaxoSmithKline-Greenfo
rd, GlaxoSmithKline-Harlow, Harley-Davidson,
Honeywell, IBM-Northcentral, IBM-Raleigh, IndyMac
Bank, Luxottica Retail, Microsoft Puget Sound,
Millennium Pharm, Nortel Networks, Onyx Software,
Sears, Sempra Energy Util's, Siemens ICN, State
of WA Dept of Ecology, Time Warner Cable, Walter
Reed AIR, World Bank
26
Agenda
  • The Mgt-Complexity-Score/Headcount concept
  • Organizational diagnostics
  • Which variables drive staffing (Sensitivity
    Analysis)
  • Scenario planning tracking over time
  • What about the outliers?
  • Span of management
  • Industry groups (Example Bio-pharmaceuticals)
  • FM/CRE action items

27
2. Organizational diagnostics
High MCS upper right
Low MCS lower left
28
Agenda
  • The Mgt-Complexity-Score/Headcount concept
  • Organizational diagnostics
  • Which variables drive staffing (Sensitivity
    Analysis)
  • Scenario planning tracking over time
  • What about the outliers?
  • Span of management
  • Industry groups (Example Bio-pharmaceuticals)
  • FM/CRE action items

29
Sensitivity Analysis
Company A
Company B
30
Mission changes Sensitivity Analysis
31
Mission changes Sensitivity Analysis
32
Sensitivity Analysis Automation packages
(61.6 heads/1000 - 55 heads/1000) X
10.2(thousands) 67.7 heads
The staffing sensitivity of Company A (which has
no automation systems in place) to automation
initiatives - 68/632 heads, or 10.7 headcount
savings
Company A (10,200 served)

60
50
40
Service heads per 1,000 served
33
Agenda
  • The Mgt-Complexity-Score/Headcount concept
  • Organizational diagnostics
  • Which variables drive staffing (Sensitivity
    Analysis)
  • Scenario planning tracking over time
  • What about the outliers?
  • Span of management
  • Industry groups (Example Bio-pharmaceuticals)
  • FM/CRE action items

34
Automation implementation impact Scenario
tracking COMPANY X Forcing the benefits
3 years
35
Automation implementation impact Scenario
tracking COMPANY X Forcing the benefits
3 years
90 Days
36
Automation implementation impact Scenario
tracking COMPANY X Forcing the benefits
150 Heads, 9 Million/yr
3 years
90 Days
This plotted 4-yr history of a 20,000-employee
firm shows that automation initiatives pay off,
but they take considerable time to implement, and
in the end the economic payoff must be forced (a
staffing realignment action shown here as a
90-day reorganization)
37
Business-mission change - shrinkage Scenario
tracking COMPANY Z Forcing the adjustment
Company Z position 2005 Fewer workers served,
less lab square feet
Company Z position 2001
38
Business-mission change - shrinkage Scenario
tracking COMPANY Z Forcing the adjustment
Company Z position 2005 Fewer workers served,
less lab square feet
68 heads (4.8 million/year) FM staffing failed
to adjust downward
Company Z position 2001
39
Business-mission change - shrinkage Scenario
tracking COMPANY Z Forcing the adjustment
COMPANY Z Scenarios by the numbers in their
confidential report
40
Business-mission change - shrinkage Scenario
tracking COMPANY Z Forcing the adjustment
Note With the shedding of lab facilities
(yielding a lower Space Score and overall lower
MCS) cost/sq-ft and costs-per-1000-people-served
should go down. However, a constant cost/s-f
report (which might be construed as a favorable
outcome) could hide the fact that there was an
excess of personnel under the new scenario. Only
with the MCS-based headcount analysis is the
excess personnel cost revealed
COMPANY Z Scenarios by the numbers in their
confidential report
41
Agenda
  • The Mgt-Complexity-Score/Headcount concept
  • Organizational diagnostics
  • Which variables drive staffing (Sensitivity
    Analysis)
  • Scenario planning tracking over time
  • What about the outliers?
  • Span of management
  • Industry groups (Example Bio-pharmaceuticals)
  • FM/CRE action items

42
What about the Outliers?
43
What about the Outliers? 1 Confounding of FM and
Production Support
79 heads (5 million/yr) Production support
people counted as facilities people
44
What about the Outliers? 2 Divisional
comparisons Forcing the OUTSOURCE benefits
57 heads (4 million/year) 95 outsourced, but
left-over internal staff over-managing
outsourcers doing some work for other divisions

45
What about the Outliers? 2 Divisional
comparisons Forcing the OUTSOURCE benefits
57 heads (4 million/year) 95 outsourced, but
left-over internal staff over-managing
outsourcers doing some work for other divisions

Three other comparable divisions of the same
company
46
What about the Outliers? 3 The Foreign Factor
203 heads (14 million/year) Foreign U.S.
Divisions together Many locations, offices,
mainly full-serve leases.
47
What about the Outliers? 3 The Foreign Factor
203 heads (14 million/year) Foreign U.S.
Divisions together Many locations, offices,
mainly full-serve leases.
U.S. Division by itself of the same company
48
Agenda
  • The Mgt-Complexity-Score/Headcount concept
  • Organizational diagnostics
  • Which variables drive staffing (Sensitivity
    Analysis)
  • Scenario planning tracking over time
  • What about the outliers?
  • Span of management
  • Industry groups (Example Bio-pharmaceuticals)
  • FM/CRE action items

49
Span of Management Definition We use a Span Index
B/A (Here, 2.0) (Actual Span of Management
here would be 2.6)
A. People who manage people
B. People who dont manage people
50
How they stack up
High Outliers have a lower span of mgt (control)
at the professional staff level than the
Reference Panel
The Reference Panel has a higher span of mgt
(control) at the professional level than the High
Outliers
51
A higher Professional-level Span of Management
tends to favor better overall organizational
performance
52
How they stack up
30 Panel Members above the line have a lower
span of mgt than those below the line
30 Panel Members below the line have a higher
span of mgt than those above the line
53
A higher Professional-level Span of Management
tends to favor better overall organizational
performance
54
A higher Professional-level Span of Management
tends to favor better overall organizational
performance
55
Agenda
  • The Mgt-Complexity-Score/Headcount concept
  • Which variables drive staffing (Sensitivity
    Analysis)
  • Scenario planning tracking over time
  • What about the outliers?
  • Organizational diagnostics
  • Span of management
  • Industry groups (Example Bio-pharmaceuticals,
    what about Utilities?)
  • FM/CRE action items

56
Pharmaceutical Group
pharmaceutical firms
57
Pharmaceutical Group
Pharmas only, other firms stripped out
58
Agenda
  • The Mgt-Complexity-Score/Headcount concept
  • Which variables drive staffing (Sensitivity
    Analysis)
  • Scenario planning tracking over time
  • What about the outliers?
  • Organizational diagnostics
  • Span of management
  • Industry groups (Example Bio-pharmaceuticals)
  • FM/CRE action items

59
To-do list
  • Force automation package benefits
  • Force outsourcing management benefits
  • Separate out production-related services
  • Model the staffing impact of business changes
  • Compare divisional organizations
  • Track your progress against a changing landscape
  • Pursue high-Span-of-Mgt org models for
    professional staff
  • Join this on-going study group! -- Contact
  • Steve Westfall, President, Tradeline, Inc.
  • swestfall_at_TradelineInc.com (925) 254-1744
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