DRAFT

1

Report to the Futures Task Force February 9, 2009
2
Impetus

• In early 2008, JSU President Ronald Mason, Jr.
  launched the development of the 2nd strategic
  plan of his tenure, Gearing Up for Greatness.
  After accomplishing most of the priorities
  defined in the 1st plan, Beyond Survival The
  Millennium Agenda for Jackson State University
  (The Millennium Agenda), Dr. Mason and the JSU
  community realized a new set of forces were at
  work that needed to be examined and a plan
  crafted to ensure the momentum created by the
  Millennium Agenda would be sustained.

3
The Call to Arms

• Utilize the intellectual capital of the JSU
  community along with external consultants to a)
  assess the work of The Millennium Agenda b)
  define a new academic paradigm for JSU and the
  means by which to measure student success c)
  define the people, processes and systems required
  to support the New Academy and d) define the
  resources available to make this paradigm a
  reality.

4
Charter of the Fiscal Resources Working Group

• The last objective would develop analysis and
  recommendations through the Fiscal Resources
  Working Group. After much analysis, the group
  focused its effort on the following
• Construction of JSU finances
• Review the historical sources/uses available to
  JSU and how those resources have been used
• Deconstruction of JSU finances
• Model the actual cost to deliver JSU academic
  programs
• Reconstruction of JSU finances
• Recommend the tools necessary to provide JSU the
  ability to match its future needs to available
  resources

5
Financial Task Force Team Listing
5
6
Executive Summary

• Jackson State University (JSU), one of the eight
  (8) Institutions of Higher Learning (IHL) of the
  State of MS, is transitioning from a
  state-supported institution to a
  state-assisted/semi-public institution and must
  begin to better understand and manage current
  resources as well as aggressively increase
  self-generated funds.

7
Assisted to Supported/Semi-Public

• Shift occurring in JSU funding sources
• About 25 of JSU resources come from State
  appropriations, funding has been essentially
  level, but major declines are expected for the
  foreseeable future
• Sponsored Programs has become the driver of
  growth of University resources
• Tuition pricing is becoming politicized and
  cannot be dependent upon for future growth
• Auxiliary growth is hindered by debt service
  payments
• Lack of alumni wealth base and MSs historic
  racial/economic divide limit JSUs ability to
  raise a 100M endowment.

8
Understanding and Managing Resources

• Actual cost to run institution not fully
  understood
• Focus is on budgeted dollars not actual costs to
  deliver programs
• Tuition charged has little correlation to actual
  demand and/or cost of instructional delivery
• Tuition PLUS State appropriation barely covers
  fully-loaded classroom cost
• Current model of managing resources leads to
  process inefficiencies and ineffective resource
  allocation, need model that is more transparent,
  decentralized and data-driven.

9
Self-Generated Funds

• Monetization of owned/not-yet-owned assets
• Tuition pricing needs to be more
  market-based/cost-driven
• Increase sophomore-to-junior retention and
  generate more higher-value SCHs per the IHL
  Funding Formula
• Continue push to 100M goal for grant funds by
  seeding more grant development in
  colleges/departments with currently low external
  fund productivity
• Develop an entrepreneurial culture that rewards
  risk taking/informed failures
• Develop a formal business-like approach to
  monetizing several assets currently owned by JSU
  and put plan in place to secure non-owned assets.

10
Table of Contents

• Construction
• Sources
• Uses
• Balance Sheet
• Comparables
• Deconstruction
• Cost Model
• Process
• Case Study
• Reconstruction
• Resource management
• Predictive analysis
• Monetization

11
Summary on Sources

• Primary sources of JSU funding are tuition, state
  appropriations, Ayers, auxiliary, sponsored
  programs and designated
• Tuition growth comes from changes in actual
  pricing as FTE growth has been essentially flat
• State funding has increased almost 6 since FY05,
  but still remains below per FTE funding levels
  from FY00
• JSU drops over 50 in SCH production from
  sophomore to junior year, whereas the system
  average without JSU is 93 (or 7 difference in
  SCH production sophomore to junior year)
• Ayers funding declines in FY12 from 11.5M to
  7.5M
• Auxiliary has seen level growth for the last two
  years, but with new Student Center operational
  and new visitation rules with Housing, better
  growth is expected
• Sponsored programs has seen growth over 50 since
  2003 and a new Obama administration raises
  expectations that 100M in funding can be
  achieved
• Designated revenues have increased from 4.5M to
  over 8M since FY04, a 16 CAGR

12
Revenues by Category
Over the 5 year period total resources have grown
by 5.6 on avg.
13
Construction Sources

• Tuition Fees
• State Appropriations
• Ayers
• Auxiliary Enterprise
• Sponsored Programs
• Designated

14
Tuition and Fees Analysis of all Fund Sources
CAGR
48 9.8 4.7
15
Tuition vs. Enrollment
16
Enrollment Trends
17
IHL vs. JSU Enrollment and Tuition Analysis
18
Construction Sources

• Tuition Fees
• State Appropriations
• Ayers
• Auxiliary Enterprise
• Sponsored Programs
• Designated

19
Budgeted State Appropriations by Category
20
State Appropriations Compared to all Sources
21
Appropriations are Diminishing
IHL State appropriations vs. self-generated funds
22
State Appropriations Year-to-Year
, 000s
AVERAGE GROWTH FY04-FY09 5.9
23
Mississippi Institutions of Higher Learning
APP/FTE

24
Projecting the Cuts
, 000s JSU Appropriations exclusive of Ayers
25
Funding Formula

• The major components of the funding formula
• Credit Hour Production (Lower/ Upper Level)
• Discipline
• Retention

26
Funding Formula

• Credit hours produced are averaged over a three
  year period
• The hours are grouped by level (lower, upper,
  professional, graduate, and doctoral)
• The hours are grouped according to their CIP
  funding code
• The weighted hours are multiplied by weights
  according to discipline

27
Funding Formula vs. Actual Appropriation
12.8
-5
26.7
31
7
23
43
21
28
JSU vs. IHL SCH Production

• JSU only retains about 50 of its upper level
  credit hours produced in
• comparison to IHL schools which retain
  close to 100.
• There is a correlation between retention and
  the funding formula.

29
IHL SCH Production Percentage of Total
30
JSU SCH Production Percentage of Total
31
Percentage Differential in SCH Production
Compares percentage in difference in SCH
production between JSU and IHL average
32
Construction Sources

• Tuition Fees
• State Appropriations
• Ayers
• Auxiliary Enterprise
• Sponsored Programs
• Designated

33
Issues with Ayers Funding

• Declining funding formula, starting in two years
• Non-inflationary
• Does not address additional university costs
• Operations and Maintenance costs
• Unfunded Endowment
• costs
• Unfunded Endowment

34
Declining Ayers Funding
? 11.5M ?
? 7.7M ?
3.8M
0.00M
34
35
Construction Sources

• Tuition Fees
• State Appropriations
• Ayers
• Auxiliary Enterprise
• Sponsored Programs
• Designated

36
Auxiliary Enterprises - Revenue

• CAGRs
• Overall 9.4
• Housing 10.2
• Food services 8.3
• Dir of Aux 7.4

37
Construction Sources

• Tuition Fees
• State Appropriations
• Ayers
• Auxiliary Enterprise
• Sponsored Programs
• Designated

38
Research Funds

• Restricted type funds are used for research and
  applied research
• Indirect costs are used to leverage EG

39
Funded Research
000,
40
Research by College and Division
000,
66,733
56,908
58,687
56,041
49,151
43,361
41
Growth of Indirect Cost Recovery
, 000s
4.3 CAGR
41
DRAFT
42
Construction Sources

• Tuition Fees
• State Appropriations
• Ayers
• Auxiliary Enterprise
• Sponsored Programs
• Designated

43
Designated Funds Revenues
44
Summary on Uses

• JSU spending in certain categories is not aligned
  with IHL and SREB averages and increases over the
  years has caused a significant drain on reserves
• Since 2004, EG spending has increased 6, with
  the largest increase being in travel spending
  (19.6) and the least being a -7.4 in equipment
  purchases
• Overall salary spending increased 14M or 7.8
  since FY04
• The flawed design of the Ayers settlement has
  caused JSU to spend over 4M of its own funds to
  cover unreimbursed costs
• Compared to IHL schools, JSU spends 42 of its
  funds on core instructional costs versus a
  system average of 49 and 46 for SREB schools
• Spending increases compounded with growing
  receivables (student and grants) has caused the
  Universitys cash reserves to drop almost 40
  since FY04
• Balance sheet ratios show JSU needs to re-build
  its unrestricted cash reserves and increase its
  unrestricted net cash flow.

45
EG Expenditures by Function
000,
103,852
93,916
88,922
79,623
73,419
46
Ayers Unfunded Cost
47
Auxiliary Enterprises Expenditures
48
JSU Research Overview
Snapshot Total RD expenditures at JSU
(1999-2006)
JSU Change (1999-2006) 334 JSU Change
(2002-2006) 50
Note Dollar values in thousands. Source NSF,
Academic RD Expenditures, Table 27 (NSF 08-300).
49
Designated Accounts Spending
50
TOTAL BUDGET vs. IHL NATURAL CLASSIFICATIONS
FY07
Source JSU Financial Statements, IHL System Audit
50
51
TOTAL BUDGET vs. IHL FUNCTIONAL CLASSIFICATIONS
FY07
Core instruction JSU 41.9 vs. 49 IHL
Source JSU Financial Statements, IHL System Audit
51
52
FY08 Year End Summary
53
Accounts Receivables Analysis
54
Collection Rate
54
55
Fund Balance
258,893
249,353
186,801
183,555
188,192
56
Declining Reserves
31,593
19,993
57
Explaining IHL Ratios

• Debt Burden Ratio Debt Service/(Current
  Restricted Funds)
• Dependency on debt as a source of funding
• Lower the number, more resources available for
  general operating purposes the higher the figure
  the fewer available resources
• Current Ratio EG Assets/EG Liabilities
• Ability of JSU to cover its short term
  obligations
• Rule of thumb calls for 2.0, has to be greater
  than 1.0

58
Balance Sheet Ratios
Debt Burden Ratio
Current Ratio
59
Construction Comparables

• How do we compare
• SREB (Southern Regional Education Board)
• IHL
• Moodys

60
JSU vs. SREB - Sources
61
JSU vs. SREB Natural Classification
62
JSU vs. IHL vs. Moodys
63
Table of Contents

• Construction
• Sources
• Uses
• Balance Sheet
• Comparables
• Deconstruction
• Cost Model
• Process
• Case Study
• Reconstruction
• Resource management
• Predictive analysis
• Monetization

63
64
Deconstruction Table of Contents

• Overview
• Trying to Accomplish
• Executive Summary
• Why are we doing this?
• Why change the way we look at cost budgeting
• Assumptions Rationale
• How are we going to do this The Process
• Cost Model Flow Chart
• The Decomposition of JSUs General Ledger (GL)
• Assigning GL Expenses to Departments
• Driving Cost to Department Activities
• TDABC Time Equations to reconstruct departmental
  activities time allocations
• The Load Table (department drivers)
• The Outcome (what we expect)
• The Outcome Logic Flow Chart
• Case Study Accounting Department Fully Loaded
• METRICS
• Ratios Targets
• Next Steps

65
Trying to Accomplish

• Understand true costs of the departments
  (deconstruct the university) through the
  development and use of customized Time-Driven
  Activity Based Costing Tools
• Understand specifically where support levels can
  be shifted without adversely impacting overall
  program and service quality
• Theorize ways to better utilize current resources
  (shared faculty, dynamic spacing, tiered support,
  student training, research outsourcing)
• Development of tools to Re-Construct the new JSU

66
Executive Summary

• Opportunities exist to reduce cost in the range
  of 2 - 4 million annually
• Initial target would be a small collection of
  departments yielding 1 - 3 million
• in savings

• Cost reduction opportunity departments with high
  cost and excess capacity (in other
  words, departments with above average support
  cost, low faculty to student ratio, high space to
  student ratios, and )
• The growth opportunity low cost and low capacity
  (in other words, departments with below average
  support cost, faculty and space constrained, and
  a large student enrollment)
• Strategy Focus first cost reduction
  opportunities within high cost departments, high
  support cost, low student/faculty ratio, high
  space /student
• For simplicity, we will explore three levers
• Modify service levels (e.g., IT, HR tiered
  service levels, in-house service) to reduce
  service cost
• Modify student/faculty ratio (Right-sizing
  departments) to lower direct costs
• Modify space allocations (Dynamic spacing) to
  lower space cost
• Qualifier There are some departments that are
  easier to reduce cost than others (e.g. elective
  coursework, interchangeable staff, space
  agnostic)

67
Executive Summary

• Using the JSU Cost Model Tool, departments with
  specific characteristics can now be easily
  identified for further analysis individually or
  by groups
• Above average service (i.e. IT, FCM) levels
  Executive PhD in Urban Higher Ed. Educ. Tech.
  Support
• With low student to faculty ratios Civil
  Engineering, Communicative Disorders
• With above average space to student ratios
  Executive PhD in Urban Higher Ed. Educ. Tech.
  Support
• Departmental cost ratios are revealed at a
  granulated level in the cost model
• Average Support Cost Rate For every of direct
  cost 1.60 in support
• Low Support Cost Rates School Community Rehab
  (0.53 ) Mathematics (0.55)
• High Support Cost Rates Economics (8.15)
  Educ. Tech. (3.57)
• Support Cost Rate Target for Technical
  Departments 0.53 (current average for this
  group is 0.59. This represents a 10 decrease).
  If JSU hits the 0.53 Support Cost Target for
  Technical Departments, this will equate to 2.9
  MM in savings
• Support Burden Target for Non-Technical
  Departments 1.45 (current average for this
  group is 1.61. This represents a 10 decrease.)
  If JSU hits the 1.45 Support Cost Target for
  Non-Technical Departments, this will equate to
  8.7 MM Sin savings

Data Analysis generated in the EPS
(Note An indication of High Cost is not in
itself a parallel to inefficiency. Hi/Lo
Categories are based on the average JSU
Departmental Support cost)
Sample Demonstration JSU EPS Scenario
Worksheet 1st Pass Results
68
Why are We Doing This?

• Gain explicit insight into departmental activity
  cost details which produce a more accurate
  holistic representation of departments overall
  cost, capacity and consumption levels
• Understanding that fully loaded cost, consumption
  and capacity indirectly provides a blueprint
  based on service demand for the sizing of
  institutional support departments
• Provide the Futures Taskforce with a customized
  Enterprise Performance System (EPS) to assist in
  identifying the bucket of resources currently
  consumed by each department as well as the
  ability to predict the bucket of resources needed
  given a given set of parameters

69
Why Change the Way We Look at Cost Budgeting

• Currently institutional budgets reflect only
  Direct Cost (above the line i.e. salaries
  fringe) and Minimal Support (below the line,
  i.e. commodities, travel) Cost at the
  departmental level
• Services that support the core academic mission
  are budgeted separately, (i.e. HR, IT and FCM)
• A need to define the short-and long-term fiscal
  resources necessary for JSU to become Americas
  leading urban university
• Create the JSU cost model using the principles
  and techniques of Time Driven Activity-Based
  Costing to define where and how costs are being
  incurred, not necessarily what funds are budgeted
  to an area
• Using the cost model, the Futures Taskforce can
  project/predict expected resources needed in the
  development of multiple organizational scenarios

70
Assumptions Rationale

• Combining direct, total indirect support cost
  at the department level provides a better more
  accurate picture of the departments total true
  cost (fully loaded) and consumption level on
  institutional resources
• By allocating Shared Services Support (IT, HR
  etc.) cost to the departmental direct cost
  (current budget setup) we can get a better
  indication of the departments demand on support
  services (SS)
• Understanding the demand on Support Services
  gives insight into the optimal size of the
  support department(s) needed to meet the needs of
  the universities current operations as well as
  the ability to project SS size based on
  predictive modeling
• Using the application and calculation of the
  support data collected (shared service GL
  Accounts, FCM IT work orders, space study data,
  PC phone line counts, faculty interviews) to
  determine individual departmental allocation
  amounts

71
Deconstruction Table of Contents

• Overview
• Trying to Accomplish
• Executive Summary
• Why are we doing this?
• Why change the way we look at cost budgeting
• Assumptions Rationale
• How are we going to do this The Process
• Cost Model Flow Chart
• The Decomposition of JSUs General Ledger (GL)
• Assigning GL Expenses to Departments
• Driving Cost to Department Activities
• TDABC Time Equations to reconstruct departmental
  activities time allocations
• The Load Table (department drivers)
• The Outcome (what we expect)
• The Outcome Logic Flow Chart
• Case Study Accounting Department Fully Loaded
• METRICS
• Ratios Targets
• Next Steps

72
How are We Going to Accomplish This?
73
The Process of Fully Loading Cost
The Deconstruction Reconstruction of JSU
Budgets
(Departments)
(Time)
(Cost per Driver)
(Dollars)
74
Assigning GL Expenses to Individual Departments

• Support Departments
• (Non-Instructional Direct Indirect Areas)
• Support Departments primarily support functional
  departments, but may also support other support
  units (HR, IT, FCM, ADMIN, Provost)
• GL Expenses are allocated to functional
  departments and other Support departments
• Two tiered allocation General operational
  allocation based on Sq. ft., headcount, PC count
  and phone line count as well as
  Demand/Consumption driven allocation based on
  request and work orders
• If the Computer Science Department requires 10
  PC labs for its departments needs and as a result
  are increase building utility cost by 20 , then
  an additional 20 energy cost should be
  allocated to Computer Science

• Functional
• (Core Instructional Salaries)
• Functional Departments deliver class room
  instruction (Accounting, Biology, Computer
  Science, Art)
• Functional Departments interact directly with the
  Cost Object (i.e., Class)
• GL expenses are allocated to individual
  departments (Lease/Rent, Facilities, Headcount)
• Relative to departmental use
• If the Marketing Department accounts for 10 of
  the space in a building, then 10 of the
  facilities cost should be allocated to Marketing

75
Data Collected

• All General Ledger Data
• Financial Statements
• FCM Work Orders (Approx. 22,000)
• IT Work Orders (Approx. 5,000)
• HR PAFs
• Space Utilization Study Data
• By Building
• By Department
• Institutional Research Report
• FTE
• SCH
• Enrollment
• Student/Faculty Load
• Faculty Survey/Interviews
• Activity-Based Costing Research

76
Manage General Ledger Accounts Screen
Actual JSU Operating Expense Accounts
used directly imported from SCT/Banner General
Ledger
77
Driving Cost from Departments to Activities

• Departmental Costs are allocated to the
  activities performed
• Instruction Delivery, Testing, Grading
  similar
• Student Support Advisement Counseling
• Research Research Grant
• Service

Source Departmental Time Allocations were
completed by the Accounting Department faculty
led by Dr. Quinton Booker, Chair
78
TDABC Time Equations as a tool for
reconstruction
Work in Progress
After cost objects are defined, time equations
are used to estimate the percentage of time spent
on each activity for that cost object
79
Department Driver Load Table
Department Drivers gathered by the costing team
at JSU December 2008
80
Deconstruction Table of Contents

• Overview
• Trying to Accomplish
• Executive Summary
• Why are we doing this?
• Why change the way we look at cost budgeting
• Assumptions Rationale
• How are we going to do this The Process
• Cost Model Flow Chart
• The Decomposition of JSUs General Ledger (GL)
• Assigning GL Expenses to Departments
• Driving Cost to Department Activities
• TDABC Time Equations to reconstruct departmental
  activities time allocations
• The Load Table (department drivers)
• The Outcome (what we expect)
• The Outcome Logic Flow Chart
• Case Study Accounting Department Fully Loaded
• METRICS
• Ratios Targets
• Next Steps

81
The Outcome Logic
Acorn EPS Model built on OFV Servers hosted by
Acorn Systems in Houston, TX
82
Cost Model Results
The Results
User Input (e.g., scenarios)
Acorn EPS Engine
JSU Source Data
83
Accounting Fully Loaded Expected Pilot Outcome

• Understand the total resources consumed by a
  particular department
• Identify and understand the disaggregated cost of
  departments and why
• Better insight into program cost
• Performance by College, Department Subject
• Calculate the bucket of resources needed given a
  particular predictive scenario
• Better management of resources with granularity
  of cost and consumption

84
Accounting Fully Loaded
Structure example

• Accounting Department
• Current 2007 Budget View

• Fully Loaded Accounting
• Department 2007 Budget View

• Salaries
• Fringe
• Professional Fees
• Commodities
• Travel
• Equipment
• Total 942,752.00

• Salaries
• Fringe
• Professional Fees
• Commodities
• Travel
• Equipment
• Sub Total 942,752
• IT General (per PC Count Phone Line)
• IT Demand (work orders)
• HR General (per Headcount)
• Facilities General (per Square Ft)
• Facilities Demand (work orders)
• Total 942,752 613,716 1,556,468

Direct Support Services (DSS)
Shared Support Services (SSS)
613,716.00
The current budget view does not give
department leaders insight into the total cost of
programs
Acorn EPS Calculation
JSU Current Budget View
85
Case Study Accounting Department

• Example Accounting Department
• Square Footage 4194 (or 500 sq ft per faculty
  member) Need to be measured against industry and
  peer ratios
• Student / Faculty Ratio 45 (high/low
  designations depend on the established ratio
  benchmarks for a particular course, department or
  college which may differ from Lower UG to Upper
  UG Grad)
• Support Cost Rate (per dollar of direct cost)
  1.09
• Problem How can we add staff without spending
  money?
• Solution 1) Team up with other Business School
  Departments to hire 3.3 professors
• 2) Try to Lower the Support Cost Rate (1.09)
  to 0.80 by leveraging students for IT support

86
Metrics
There are a number of interesting observations
when we look at metrics. First, we can see the
differences between technical (i.e., STEM
Programs) and non-technical (i.e., Liberal Arts
Programs) departments. Second, we can use
metrics to help predict the cost impact of
different growth strategies. We can use the
reverse logic to think about shrinking a
department.
Computing the average for a group of departments
Non-Technical Depts. Group Average represent 23
depts.
Technical Depts. Group Average represent 10
depts.
Grouped Averages Cost Conversion
Monetizing the Technical and Non-Technical Dept.
Profile

Average Grouped Cost represents 10 depts.
Average Grouped Cost represents 10 depts.
Note Averages were generated through the JSU
Scenario Worksheet (A9-A19 B20-B43), but may
also be accomplished in the EPS Scenario Builder
Application
87
The Hypothesis
There are a number of departments which can be
restructured or served differently that will
ultimately lower the costs and free up resources
for other programs

• There are areas that we can look to identify the
  opportunities
• Departments whose average cost is 20 above the
  set benchmark
• High fully loaded cost per student
• High fully loaded cost per faculty HC
• High support/direct cost ratio
• Departments whose average support cost is 20
  lower than the set benchmark
• Low student/faculty ratio
• Low utilization of space
• High square footage/staff
• High square footage/student

88
High vs.. Low Cost Departments per student
Example Analysis (WIP)

• Departments with cost above average
• Departments with cost below the average

• Appears to be a strong inverse correlation
  between student/faculty ratio and cost/student.
  Makes sense the more faculty, the higher the
  cost.
• Next Step Explore cost savings from moving
  departments to a lower student/faculty ratio

89
Support Cost Ratio
What is the target ratio of support costs to
direct costs (e.g., faculty salaries)? Does it
vary by department? Are technical departments
more capable of handling technical issues than
non-technical ones? Does age of the department
matter? How about location? How we can help our
departments lower their ratio?

• Upon reviewing the numbers, one thing is clear
  Technical departments do have a lower support
  cost ratio (0.59) than non-technical ones
  (1.61). Other things that are obvious is that
  the age of the department and the location do not
  seem to matter
• Step 1 Establish achievable stretch
  targets/benchmarks for all departments
• Step 2 Assist Department with getting to these
  targets/benchmarks
• Examples
• Train students within the departments to provide
  technical support
• Offer tiered service levels at different rates
• Offer the option of outsourcing some of the
  services
• Foster collaboration between facilities
  management and departments to identify savings
  (e.g., maintenance, repairs, utilities,
  insurance)
• Have departments perform their own recruiting
  efforts
• Step 3 Continually monitor and report back to
  the departments

90
Implied Savings from Achieving Support Cost
Targets
Sample Analysis
Department Group 1 Technical Departments
Department Group 2 Technical Departments

• Support Cost Rate Target for Technical
  Departments 0.53 (current average for this
  group is 0.59. This represents a 10 decrease).
  If JSU hits the 0.53 Support Cost Target for
  Technical Departments, this will equate to 2.9
  MM in savings. WE CONSIDER THIS MORE ACHIEVABLE
  BECAUSE THESE DEPARTMENTS ARE MORE LIKELY TO HAVE
  STUDENTS WHO CAN FULFILL TECHNICAL ROLES
• Support Burden Target for Non-Technical
  Departments 1.45 (current average for this
  group is 1.61. This represents a 10 decrease.)
  If JSU hits the 1.20 Support Cost Target for
  Non-Technical Departments, this will equate to
  8.7 MM in savings. THIS MAY BE TOUGH TO ACHIEVE
  BECAUSE THE STUDENTS OF THESE DEPARTMENTS MAY NOT
  BE EQUIPPED OR EAGER TO ASSIST WITH TECHNICAL
  SUPPORT

91
Deconstruction Table of Contents

• Overview
• Trying to Accomplish
• Executive Summary
• Why are we doing this?
• Why change the way we look at cost budgeting
• Assumptions Rationale
• How are we going to do this The Process
• Cost Model Flow Chart
• The Decomposition of JSUs General Ledger (GL)
• Assigning GL Expenses to Departments
• Driving Cost to Department Activities
• TDABC Time Equations to reconstruct departmental
  activities time allocations
• The Load Table (department drivers)
• The Outcome (what we expect)
• The Outcome Logic Flow Chart
• Case Study Accounting Department Fully Loaded
• METRICS
• Ratios Targets
• Next Steps

92
Next Steps
Validation Review
Analysis
Phase III

• Review Second Pass numbers
• Formal Value ID
• Present Findings
• Value Capture
• Develop road map for campus rollout

• First pass at the numbers in test mode
• Review Fully-loaded department process costs
• Re-run first pass in production mode
• Define key Performance Metrics to analyze

• Make changes based on 1st pass results
• 2nd Pass at the numbers
• Analyze next opportunities to focus on
• Present finding to Execs Value ID

Mar 09 - June09
Jan09
Jan09 - Feb09
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Table of Contents

• Construction
• Sources
• Uses
• Balance Sheet
• Comparables
• Deconstruction
• Cost Model
• Process
• Case Study
• Reconstruction
• Resource management
• Predictive analysis
• Monetization

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Reconstruction

• Developing the New Academy (reconstructing the
  institution) requires a series of tools to
  better understand current resources as well as a
  systematic means to identify new revenue
  opportunities
• Resource management
• Develop organizational models and processes that
  encourage transparency and inclusiveness
• Predictive analysis
• Build the organizational capacity to develop the
  models necessary to predict appropriate spending
  and revenue patterns
• Monetization
• Develop systemic means that encourages
  entrepreneurship/informed failures and means to
  evaluate new revenue opportunities on assets
  owned and currently not owned by JSU

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Resource Management

• Recommendations
• Make budget development and review more
  transparent, strategic and inclusive
• Engagement of Budget Committee in budget
  development and quarterly review of actual
  results
• Include all funds (including JSUDF) in budgeting
  process
• Develop both a spending budget for the upcoming
  fiscal year and a strategic budget for next 2-3
  years
• Create role of Business Unit (BU) Managers
  decentralize business functions
• BU Managers will be responsible for all fiscal
  and personnel matters
• Once approved by BU Manager, request is processed
  without any further signatures
• Centralized functions focus on resource
  allocation, controls and overall spending and
  revenue patterns
• Budget reviews should include comparisons to
  peers, management to key balance sheet ratios and
  use of benchmarks to ensure efficient use of
  resources is occurring
• JSU should target performing at least at the
  80-85 percentile on IHL fiscal ratios and key
  peer group measures within 5 years

96
Predictive Analysis

• Use predictive modeling tools
• EG Gap model uses macro level assumptions to
  predict overall EG revenues vs. expenses
• Three Scenario models allow JSU to rebuild
  departments using various micro assumptions
• Inputs can be FTEs, faculty, square footage,
  shared service levels to predict departmental
  cost and/or overall University costs
• Need fully loaded cost model
• University data sources need consistency and
  validation performed continually

97
EG Gap - Pessimistic Model

• 0 expense growth FY10-FY14, 2 thereafter
• State Approp declines of 3-7 from FY10-FY14, 2
  increase thereafter
• Tuition fees 1 increase, 0 FTE growth
• Ayers settlement stays as is
• Deficit of 4.4M in FY10 growing to 26M in FY24

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EG Gap - Realistic Model

• -3 to 1 expense decline/growth FY10-FY14, 3
  thereafter
• State Approp declines of 0-6 from FY10-Fy14, 3
  increase thereafter
• Tuition fees 3-5 increase, 2 FTE growth
• Ayers settlement stays as is
• Deficit of 12.4M in FY12, all other years
  generate surpluses as high as 4,5M in FY17

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Scenario Analysis Getting to the Optimal Solution
The problem Development of a tool which could
help JSU EASILY visualize and compute the true
cost impact of different growth scenarios (e.g.,
changes to the number of professors, students,
square footage, terminals, support level). This
will help the University optimize its use of
resources.

• By leveraging Acorns EPS system, the team now
  has a more accurate view of the true cost of
  departments which incorporate support costs
  (e.g., IT Support, Facilities Management,
  Finance, HR). The problem is that the analysis
  is time consuming and overly manual.
• Three solutions
• Use the Scenario Worksheet (Excel-based)
• Use the Existing Scenario Builder in EPS
• Wait for Acorns New Simulation Analyzer that is
  currently being piloted at several clients

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Scenario Analysis Getting to the Optimal Solution
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101
Scenario Worksheet - Original Data
Solution 1
101
102
Scenario Worksheet - Input Screen
Solution 1
102
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You Can Create Different Scenarios in the EPS
Scenario Builder

• Through the Enterprise Performance System (EPS)
  Multi Budget Scenarios can be created and
  managed.
• After your default model is created to
  reflect the current organizational make-up and
  number of child model versions may be created
• A version of your default model can be
  created to test the implication of new business
  rules and re-engineered processes
• Model Versions can be used to test
  hypothetical situations with live institutional
  data

Solution 2
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Scenario Simulations Department Attributes
Capability to change budget/forecast scenario
data through Acorn EPS User interface
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105
JSU 2008 Acorn Cost Traceback View
JSU 2008 Acorn Cost model
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106
JSU 2008 Acorn Cost Traceback- Drill-Down by
Account
Ability to view department attributes through
Acorn trace back screen.
Drill down into specific accounts to determine
which cost centers they are allocated and the
fully loaded costs of each activity they
perform. Can also right pull up the department
attribute values to validated fully loaded dept
cost results.
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JSU 2008 Acorn Cost Traceback- Drill-Down by Dept
Cost Center
Capability to drill into any department to review
the accounts that are allocated to it as well as
the fully loaded costs of the activities they
perform.
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The New Acorn Simulator
Solution 3
Currently being piloted at several clients.
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Challenges with Data Gathering

• GL Departmental Names listing contained a mixture
  of old department names no longer in use and new
  dept names. The old data had to be manually
  extracted
• Departmental Names appear differently in the
  system than the course catalog and the internal
  academic affairs list. Additional research to
  identify and validate the true listing and proper
  name of academic and support departments
• Departmental Names are also in conflict with
  Institutional Research Department Name Listing.
  Matching Data conflict required internal
  calculations and validation of FTE, headcount,
  Sq. ft. and capacity.
• Sample data indicated some part-time staffers as
  a full FTE rendering the data somewhat
  unreliable. Could only rely on Student FTEs

110
Challenges faced with Gathering Data Data
Integrity
2007 GL Snapshots
Institutional Research Sem. Credit Hr Production
Table
2007-2009 Course Catalog Snapshot

• Nomenclature Challenges
• Three examples of issues that arise when
  collecting data across systems and publications
  are as follows
• The GL Department title Physics, Atmospheric
  Sciences and Geosciences does not match the
  course catalog listing of the same year but
  matches the Institutional Research (IR) online
  table names.
• Institutional Research table names do not match
  the all GL departmental names as with Management
  Marketing 2007 GL listing and the IR report for
  2007.
• Departments appear in the course catalog but are
  not found in the GL as with Aerospace Studies.

Note Internal Master Listings for Academic
Departmental Names are not a 100
match for the course catalog, banner GL names, or
Institutional Research Tables. No
two are an exact match!
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Monetization

• Restructure tuition model to reflect cost, demand
  and availability
• Tuition PLUS state appropriation only covers 90
  of actual cost/FTE
• Growing FTEs does not necessarily grow revenues
• Explore new tuition models including using yield
  management principles that better match
  instructional cost to tuition charged
• Understand IHL Funding Formula and gain
  additional revenues through SCH audits, retention
  and higher-value courses
• Monetize owned/non-owned assets
• Encourage entrepreneurial/informed failures
• Create the Office of Strategic Initiative, a
  University-wide effort focused on monetizing
  currently owned assets, creating risk/reward
  culture (i.e., use extra services) and developing
  long-term growth plans of owned/non-owned assets

112
How do we make it Balance
112
113
How we Balance
To leverage shortfalls we subsidized with
reserves, indirect cost, and other sources
113
114
Tuition Appropriation leads to Gap
6,311
5,678
633
115
Growing FTEs Deficits Created

• Average faculty salary 55K, 488 faculty
  positions (from Jan09 positions report), 26.6
  FTE/faculty ratio
• Need to create additional 3.75 positions to
  maintain FTE/faculty ratio and grow 100 FTEs
• Cost to grow those 3.75 positions, 2500/FTE
• Collect 1900/FTE after allowances and other
  deductions
• Lose 600/FTE

116
Tuition Pricing

• Differentiated Tuition
• Credit Hour Charge
• JSU 5/1 Plan
• Yield Management principles

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Tuition Pricing Differentiated Tuition

• Differentiated Tuition (DT) proposal calls for
  an approximate one to 15 percent increase for
  full time graduate students taking between nine
  and 13 hours. The percentage level is determined
  by the tier level assigned to a particular
  program. At the high-end of the adjustment
  range, the 15 percent allocation tier represents
  the highest resources consumption/cost level and
  one percent allocation representing the range
  base which indicates a minimal level of resource
  consumption/cost program association

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Tuition Pricing Differentiated Tuition Example
119
Tuition Pricing Institutional Wide SCH

• Institutional Wide Semester Credit Hour (SCH)
  adjustment is another component of the proposal
  that focuses on the credit hour charge for
  courses university-wide. JSU proposes to shift
  from full-time packaged tuition bundled charges
  for undergraduate and graduate students to a SCH
  charge of 185 and 274 respectively. Full-time
  UG and G students pay a bundled price for a range
  of hours under the full time student label. For
  example UG student currently pays 2,216 for 12
  to 19 hours. Under the new proposal there would
  be a base charge per credit hour which would
  break even at the nine hour mark and slide upward
  with each additional credit hour taken.

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Tuition Pricing Institutional Wide SCH Example
121
Tuition Pricing 5/1 Plan

• JSU 5/1 Plan-An entering cohort is given a
  maximum tuition per year amount guaranteed over a
  five-year span. The guaranteed maximum amount is
  determined by a rolling four year average of the
  HEPI index. If the actual JSU tuition is less
  than the guaranteed amount, the student is
  charged the JSU tuition amount (the lesser of the
  two). If students take more than five years to
  complete the degree, the student would be charged
  whatever the tuition would be for that year or
  years.

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Tuition 5/1 Example
123
Yield Management

• Understanding, anticipating and influencing
  consumer behavior in order to maximize revenue or
  profits from a fixed, perishable resource (such
  as airline seats or hotel room reservations)
• The challenge is to sell the right resources to
  the right customer at the right time for the
  right price. This process can result in price
  discrimination, where a firm charges customers
  consuming otherwise identical goods or services a
  different price for doing so

124
Airlines vs. Higher Education

• Key elements of yield management used by airlines
• Fixed amount of resources available for sale
  (seats)
• Resources sold are perishable, there is a time
  limit to selling the resources, after which they
  cease to be of value (once the plane takes off,
  the value of the seat is gone)
• Different customers are willing to pay a
  different price for using the same amount of
  resources
• Costs are relatively high compared to the
  variable costs. The less variable cost there is,
  the more the additional revenue earned will
  contribute to the overall profit
• For JSU
• There are a fixed amount of resource/seats/section
  s available
• Once the semester starts, the seat starts to lose
  value
• Pricing is the same regardless of when seat is
  purchased
• The various differentiated tuition models can
  help develop different price points for the
  same resource
• Fixed cost structure with step variable costs
  need fully loaded cost model

125
Revenue Lost via Funding Formula

• Analysis of SCHs done by JSU vs. IHL reveals
  3.3M not appropriated for FY09 due to
  misalignment of SCHs
• IHL has 157 PhD SCHs within Doctoral Health
  Services and 9 PhD SCHs of Home Economics being
  taken
• Negative differences in Urban Planning (672 for
  IHL vs. 903 by JSU), Business Admin (23,811 vs.
  27,210), Liberal Arts (63,657 vs. 67,539) and
  Science and Math (39,207 vs. 42,089)
• Positive variances only in Engineering (3,083 vs.
  2,491)

126
Revenue Opportunity via Funding Formula

• 1 increase in SCH production of
  sophomore-to-junior year would have provide
  300-400K in additional funds in FY09
• 1 increase in SCH production in higher-valued
  courses would have generated 400-500K in FY09

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Other Sources

• Current trends are leading more institutions to
  focus on strategic planning processes that
  coincide with
• More careful articulation of business and
  market strategy
• More vigilant management of operations and
  balance sheets
• Prioritization of capital requirements and more
  disciplined approach to investment decisions
• Comparison of asset deployment versus financial
  performance
• Evaluation of re-allocation and monetization
  opportunities
• Creation of a risk taking culture that rewards
  entrepreneurial behavior

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Other Sources

• Asset Monetization Opportunities

• Asset Monetization Opportunities

• Assets we currently own
• Athletics
• Core curriculum
• Daycare-Aftercare
• e-Center
• JSU Licensing
• Small Business Development Center
• Land

• Assets we do not own
• Corporate sponsors
• Other curriculum
• Tow truck service
• Research foundation

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Revenue Sources 2 by 2 MATRIX
EASY to Monetize
Low Hanging Fruit
Realistically Thinking
JSU OWNED ASSET
NON OWNED ASSET
If only
Time-Bomb
HARD to Monetize
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Data Resources Gathered Products
Developed

• Interviews
• Financial task Force Members
• Accounting Department Faculty
• Information Management
• Data Collected
• 2000 -2008 JSU Financial Statements
• All General Ledger Accounts
• Space Utilization Study
• IT Work Orders
• FCM Work Orders
• HR PAF count
• Student Data
• SCH
• FTE
• Discipline
• IHL Data
• Appropriations
• Funding formula
• Annual System Reports

• EG Gap Model
• Department Cost Model Tool
• Space Study
• Reconstruct Models
• Worksheet Model
• Scenario Manager
• Simulation Analyzer
• Ayers Cost Model
• Monetization Matrix
• IHL Modified Funding Formula Model