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Building a Dynamic Scenario Based Forecast 21 November 2018 Rob Torok, Senior Manager Ernst & Young, Financial Accounting Advisory Services (FAAS)

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Building a Dynamic Scenario Based Forecast21 November 2018

Rob Torok, Senior ManagerErnst & Young, Financial Accounting Advisory Services (FAAS)

Page 2

Welcome to scenario based forecasting

1. Introductions 5 min

2. Observations on rolling forecasts & scenarios 25 min

3. Creating a better periodic plan 25 min

4. Introduction to the NISP case study 15 min

5. NISP Part 1: Metrics & Volume Discussion 20 min

6. NISP Part 2: Cost Types & Work Effort Discussion 20 min

7. NISP Part 3: Discussion of Options 20 min

8. Discussion with a CFO 40 min

9. Wrap up & final Q&A 10 min

Break for Keynote & Lunch

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 3 Building a Dynamic Scenario Based Forecast

Key Steps in Forecasting

In-Year Activities

Conduct YTD Expenditure

Analysis

Estimate Non-Committed

Expenditures to Year-End

Review Operational, HR

and Performance Results

Review & Update Commitments

Update Internal Budget Re-Allocation

Update Total Expenditure

Forecasts

Update Rolling Forecast

Quarterly

Update 5 Year Plan

Update Rolling Forecast

Create Annual Plan

21 November 2018

► Retain existing processes but EXTEND to reflect quarterly rolling forecast and multi-year plans

Page 4

Current Process for In Year Forecasts

► Each update ends with the fiscal year, tied to spending authority from Parliament

► But business planning continues, both for day to day operations & projects, albeit without commitments

► One does not assume that all spending stops

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 5

Key Features of a Rolling Forecast

► Extends beyond, and can be independent of, the fiscal year

► Each forecast iteration replaces one period of forecasted data with actuals then extends the forecast by one period

► Each RFC covers the same length of time, e.g. 6 quarters

Year 2

P3 P6 P9 P12

Actuals

Budget / Forecast

Year 5 Year 6

Building a Dynamic Scenario Based Forecast 21 November 2018

Year 1

P3 P6 P9 P12 …

P0

Annual Plan

Rolling Forecast

5-Year Plan

P3Annual Plan

Rolling Forecast

P12

Annual Plan

Rolling Forecast

5-Year Plan

P6Annual Plan

Rolling Forecast

Page 6

To be Successful A Rolling Forecast Must Be …

► Cost-effective

► Actionable

► Reliable

► Timely

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 7

Factors for Successful Implementation

Integration Of

Culture

People

Participation

Systems

Process

Design

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 8

Overcoming Challenges

Challenge Solution / Idea

It’s not needed. The fiscal year iswhat we live by – parliamentary authority,

reporting, budgets, etc.“

We would need new people, skills and technology. The cost is too

high“

Forecasts will probably be inaccurate. The further out we look,

the more inaccurate we’ll be.“

The fiscal year is arbitrary and has no connection to

the underlying cycle, so why stop with a fixed date

Value – much cheaper to have greater visibility than

to react to unforeseen situations

Still better – forecasting the possible ≠ predicting the

possible

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 9

Scenarios versus Options

Scenarios Options

► Outcomes or events that might occur at some point in the near or distant future

► Often fall outside of the current business environment and challenge the norm

► May require different analytical tools and capabilities

► Key challenge is to envision them and discuss them openly, far enough in advance to be able to act

► A (more) concrete idea actively being considered and requiring analysis

► Usually seen as adjustments to the existing business, and shorter term

► Fit within current modelling and business structures / capabilities

► Key challenge is the analysis itself, since details and timing are often critical

Example

Impact of self-driving cars on traffic laws and parking enforcement

Example

Planning for an X% reduction in police dedicated to traffic laws and parking

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 10

Scenarios: A Real Example1

1 Fortune magazine, February 2018, “Shell Faces ‘Lower Forever’”2 OilPrice, March 2017, “Shell Sells Almost All Canadian Oil Sands Assets”

March 2017“Royal Dutch Shell sells almost all Canadian oil sands assets”2

Why?

Months of deliberation “conclude[d] that the energy industry was changing fundamentally – in a way that could turn the profitable oil sands operation into a liability”1

How?

The “scenarios” team concluded that global oil demand might peak in a decade, due to faster than expected reductions in alternatives to fossil fuels such as solar, wind, and electricity

If that scenario materialized and Shell still owned oil sands assets then “you were – gosh, forgive me – f --- ed”1

Key Takeaway

Shell did not conclude that this would happen, just that it could, and the consequences of it were massive. And Shell won’t know if it made the right decision until perhaps 2030!

Shell’s Challenge – “Minimize the Maximum Regret” 1

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 11

Scenario Planning

► Open-minded and generally long term assessment of possible outcomes

Encompasses a wide spectrum of possible outcomes, from the highly unlikely to the highly probable

Focus on the ‘the art of the possible’

Objective is to position oneself to avoid or take advantage of certain circumstances, both positive & negative

► Often best handled by a dedicated team

Avoids conflict with day-to-day challenges

Draws on different skills

Expands the analytical time horizon to years and even decades

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 12

Assessing & Planning for Options

► Understanding our current situation and planning for a better future:

How do things look ‘as is’, i.e. without options?

What do we need / want to add to (or subtract from) our business?

► Understand key business drivers

‘Levers’ that affect our performance

Getting a full range of options

What Is What Could Be

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 13

What Is

What Do You Need to Know or Have? Why?

Baseline or ‘as is’ position Must have a starting point to compare against

At the same level of detail as your impact analysis Cannot change what you don’t have

External / macro & internal metricsAct as drivers for both baseline &

options/scenarios

Options to select from Something to add to or subtract from the base

Similar time horizons

Hard to compare & select from options that are

both very short term & very long term (e.g.

price change vs. new market entry)

An open mindWillingness to consider the unlikely or

unpopular

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 14

What Could Be

► How we look at options:

Best assessed in binary fashion, i.e. include or exclude (otherwise one has a virtually infinite number to consider)

Also best assessed on a mutually exclusive basis for the same reasons

• Without this, there would be far too many options

No need to flesh each option out in full detail (i.e. budget line items) until final decisions are made

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 15

Consequences

► Consequences for Clients & Potential Clients, Suppliers, Regulators, Influencers (and more):

• Immediate to longer term actions

• Tangible & measurable vs. intangible & harder to measure impacts

• And include your planned responses to their responses (ripple effect)

Example

If the US government tightens or loosens immigration rules, how will that impact the flow of immigrants to Canada?

Services or combinations of services

Funding sources

Changing regulations

Changing macro environment

Actions of other organizations (provinces, UN, etc.)

Political influence or intervention

Considerations

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 16

Example: Marginal vs. Average based Forecasts

Existing organizational IT budget is $10M, and is currently charged to four programs / agencies (Average of $2.5M each). NISP is added, but only $500K additional IT investment is required for laptops.

Average Marginal

Current IT Budget $10,000,000

Additional IT Expenditure $500,000

Total IT Expenditure $10,500,000

Number of Programs 5

Average Exp. / Program $2,100,000

Laptop Expenditure (NISP) $500,000

Incremental IT Expenditure $0

Total IT Expenditure (NISP) $500,000

Other Considerations:

► Is there a requirement or policy for one or the other?

► Average approach triggers impacts on other programs or agencies, which is especially problematic when average costs increase

► An additional option would be to charge the average of existing IT expenditure to each of the five programs, and allocate the incremental amount to NISP (i.e., $10M/5 = $2M per program; + $500K for NISP incremental laptop expenditure).

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 17

► What decisions might the organization make based on the forecast?

► What actions might be taken?

► Who will be most impacted by the forecast?

► What if the forecast is wrong?

► Where might it be wrong?

► What can I do to improve forecast accuracy?

How do you Want to Use the Forecast?

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 18

► Variances are the inevitable result of assumptions and circumstances to matching forecasts

► But its NOT the variances themselves that need to be explained

► Rather, look behind the variances at the assumptions & drivers that drove the budget/forecast amounts and comment on why they differed:

► Compensation cost exceeded budget/forecast because headcount exceeded plan

► Compensation cost exceeded budget/forecast because several planned retirements were deferred until P6 of next year

Variances: Looking Back

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 19

Better Budgeting & Forecasting

Key Drivers of Bad Plans

► Lack of planning

► Excessive focus on financial data

► Lack of linkage to business operations

There IS a Better Way

► Draws on operational planning, capacity planning

► Incorporates performance management

► Leads to a process valuable to both the languages of operations and finance

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 20 21 November 2018 Building a Dynamic Scenario Based Forecast

The Inter-Relationships of ABPB

ABPB Fundamental Concepts &

Terminology

Operations Planning & Forecasting

Current Budgeting Process

Current Performance

Reporting Process

Capacity Planning Process

Page 21 21 November 2018 Building a Dynamic Scenario Based Forecast

Shift Effort from Budgeting to Planning

Planning

Budgeting Planning

Budgeting

Current Effort Future Effort

Proportion of Benefit Realized

Page 22 21 November 2018 Building a Dynamic Scenario Based Forecast

And From Financial to Operational Planning

OperationalData

Financial Data

OperationalData

Current Effort Future Effort

Proportion of Benefit Realized

FinancialData

Page 23

Overview of The Closed Loop

Stage 1 – Operational Stage 2 - Financial

Feasible

Operational

Plan

Obtain Demands

Determine Resource

Costs

Add Non-Activity

Costs

Review Strategy

Balance Operations

Determine Activities

#

Balanced Financial

and Operational

Plans

Formal

Budget

$

Balance Financials

Begin ...

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 24

Let’s Look at Our New Agency

Finding short term accommodation for new immigrants

• Activity and resource consumption rates based on current ABC information

• Assume:

• Annual period

• Financial target is for funding to equal expenses, +/- 1%

• Homogeneous product

• Some buffer (or contingency) capacity to meet demand peaks, unplanned absences, etc. may be desirable and will be included in activity and service cost

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 25

Stage 1 – Operational Balance

Requests for ST housing

1 hour / search

= 325,000 hours

Operational Balance

Activity

Requirement

Consumption

Rate

Resource

Requirement

Labour

Consumption

Rate

Resource

Capacity

Searching for housing

Demand

Requirements

Strategy first drives ...

230 staff x 1,500 hours

= 345,000 hours

0.65 searches / application1

= 325,000 ST housing searches

500,000 immigration applications

This model includes 20,000 hours of buffer (or contingency) capacity, but we will come back to this concept later.

Building a Dynamic Scenario Based Forecast 21 November 2018

1. Applications may be for multiple persons & some applicants do not need housing, hence < 1.0

Page 26

Stage 2 – Financial Balance

Stage 1 – The Operational Loop

Requests for ST Housing

Operational Balance

Activity

Requirement

Consumption

Rate

Resource

Requirement

#

Labour

Consumption

Rate

Resource

Capacity

Searching for Housing

Demand

Requirements

Strategy first drives ...

Stage 2 – The Financial Loop

Financials

230 staff x $80,0002

= $18,400,000Resource Cost

$18,400,000 / 325,000 searches

= $56.62 / searchActivity Cost

$56.62 x 0.65 requests/app.

= $36.80 / applicationProduct Cost

Funding = $39.00 / application, total of $19,500,000Activity Costs = $56.62 / search, total of $18,400,000

Oper. Surplus = $1,100,000

Other Costs = $950,000

Net Balance = $150,000 which is < 1% of funding

1 hour / search

= 325,000 hours

230 staff x 1,500 hours

= 345,000 hours

0.65 searches/app.

= 325,000 requests

500,000 applications

Building a Dynamic Scenario Based Forecast 21 November 2018

2. Fully burdened with all benefits

Page 27

The Effect of a Changed Consumption Rate

Operational Balance

Stage 1 – The Operational Loop

Requests for ST Housing

Activity

Requirement

Consumption

Rate

Resource

Requirement

Labour

Consumption

Rate Searching for Housing

Demand Requirements

Strategy first drives ...

Change Capacity

+ 40 staff x 1,500 hours

= 60,000 hours

Shortage

Adjust Consumption

60 minutes / search

= 455,000 hours

0.65 searches/app

= 455,000 searches

700,000 applications

230 staff x 1,500 hours

= 345,000 hours

270

405,000

50

380,000

Adjust Capacity

Resource

Capacity

If we start with a

40% jump in

demand to 700K

apps, then holding

all else constant

we’ll need about

480,000 hours of

staff time (incl.

buffer) … but

1

Web search

technology or

process

improvement

allows us to reduce

search time to 50

minutes/search

2

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 28

Adding Buffer Capacity

Operational Balance

Stage 1 – The Operational Loop

Requests for ST Housing

Activity

Requirement

Consumption

Rate

Resource

Requirement

Labour

Consumption

Rate

Resource

Capacity

Searching for Housing

Demand Requirements

Strategy first drives ...

Change Capacity

+40 staff x 1,500 hrs

= 60,000 hours

Shortage

Adjust Consumption

Adjust Capacity

60 minutes / search

325,000 hours

0.65 searches / app

= 455,000 searches

700,000 applications

230 staff x 1,500 hours

= 345,000 hours

270

405,000

50

=380,000

Then we add 16-17

staff as a buffer 3

KEY POINT:

Buffers are added ‘at the end’

rather than at each stage. Imagine

the resource need if we added

10% to demand, searches per app,

minutes per search, and hours per

FTE ….. We’d need dozens more

FTE and then buffer that !!

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 29

Operational and Financial Balance

Stage 1 – The Operational Loop

Operational Balance

Activity

Requirement

Consumption

Rate

Resource

Requirement

#

Consumption

Rate

Resource

Capacity

Demand Requirements

Strategy first drives ...

Stage 2 – The Financial Loop

Financials

270 staff x $82,000

= $22,140,000Resource Cost

(incl. plan for increase next year)

$22,140,000 / 455,000 searches

= $48.66 / searchActivity Cost

$48.66 / search * 0.65 searches/app

= $31.63 / application Product Cost

Funding = $39.00 / application, total of $27,300,000

Activity Costs = $48.66 / search, total of $22,140,000

Oper. Surplus = $5,160,0000

Other Costs = $2,000,000

Total Surplus = $3,160,000 or 11.6% of Funding

325,000 hours

455,000 searches

700,000 applications

230 staff x 1,500 hours

= 345,000 hours

270

405,000

Change Capacity

+ 40 staff x 1,500 hours

= 60,000 hours

Shortage

Adjust Capacity

50 minutes / search

100,000 calls / campaign

Target

Results

Requests for ST Housing

Labour

Searching for Housing

380,000

Adjust Consumption

Building a Dynamic Scenario Based Forecast 21 November 2018

Financial Loop Update – The improved consumption rate allows

funding to be reduced to just about $35 / application !

Page 30

More Realistic: Two Activities & Services

Resource

Capacity

Labour

Initial Searches

Demand Requirements

Follow-up Searches

Requests for ST Housing Requests for LT Housing

Activity Requirements

700,000 applications 700,000 applications

Resource Consumption Rate:

minutes / search

Activity Consumption Rate:

ST searches / appl.

Resource Requirements

0.65

50 m/s

0.10

90 m/fus

554,000 hours

263,000 hours

= 817,000 hours

455,000 searches

210,000 searches

= 665,000 ST searches

0.15 0.30

105,000 searches

70,000 searches

= 175,000 LT searches

Resource Consumption Rate:

minutes / f/up search

Activity Consumption Rate:

LT searches / appl.

700,000 applications @ 0.65 ST searches/application plus 0.30 searches for longer term accommodation/resettlement

700,000 applications @ 0.15 FOLLOWUP ST searches/application plus 0.10 FOLLOWUP searches for longer term

accommodation/resettlement.

665,000 initial ST searches at 50 minutes/search ÷ 60 minutes per hour = 554,000 hours.

175,000 follow-up searches at 90 minutes per search ÷ 60 minutes per hour = 263,000 hours.

1

2

3

1 2

3

Building a Dynamic Scenario Based Forecast 21 November 2018

SIMPLIFYING ASSUMPTION: all initial searches are equal,

as are followups (i.e. no difference in effort between ST & LT

searches)

Page 31

Where Traditional Approaches Go Wrong

► As underlying or external demand changes, that

knowledge is not cascaded to lower-level units

► Consider the iimigration center:

► Does HR know that 30 or 40 staff need to be hired?

► Is IT aware of the new telephony needs?

► Is the training group ready to handle the growth?

► Is there office space for 30 or 40 more people?

► Without this ‘cascading’ significant operational and

financial problems may arise

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 32

The 5 Levers of Budgeting

Stage 1 – The Operational Loop Stage 2 – The Financial Loop

Products & Services

Cost

Assignment

$

Adjust Resource Cost$

Adjust Funding

Financial

Balance

Adjust Consumption

Operational BalanceShortage or Excess

Activity

Requirement

Consumption

Rate

Resource

Requirement

#

#

... and also dictates

Consumption

Rate

Cost

Assignment

Resource

Capacity

Activities

Adjust Capacity

Target

ResultsFinancial ResultsAdjust Demand Demand Requirements

Strategy first drives ...

Resources

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 33

Case Overview & Instructions

NISP:

- New immigration program and the CFO has asked for your help to prepare a budget

- Case highlights

Now:

- Read case study document & review excel exhibits

- Think about two topics: building a budget/forecast and then factoring in options

Before & After lunch:

- Work in table groups

- Respond to each of the questions in the case

- Groups can present solutions then full room discussion

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 34

NISP Planning Request #1

METRICS: What are the top 3 metrics to project client & service level demands?

Exhibit 3 listed 8 metrics (top 3 bolded):

General Inflation

Consumer Purchasing

Nominal GDP Growth

Real GDP Growth

Housing Cost Growth

Unemployment Rate

Global Migration Growth

CDN Attractiveness Rank

Picking 3 requires that we know the intended use of each metric

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 35

NISP Planning Request #2

VOLUMES: Projecting client and service level volumes

See Solutions Exhibit #1

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 36

NISP Planning Request #3

COST TYPES: How does each admin cost type relate to service volume?

Exhibit 2 shows the 8 cost types (comments bolded):

Fin'l Acctg & Reporting: Fixed

Risk & Compliance: Fixed

FP&A - Short & Long Term Accomm'n: Step

FP&A - Lang/Cult: Step

FP&A - Employment: Step

FP&A – General: Step

HR – Office: Step

HR - Client Service: Step

Fixed – does not change with volume ‘over the relevant range’

Linear – changes with each discrete volume increment/decrement

Step – changes with volume but not by individual unit

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 37

NISP Planning Request #4

VOLUMES: Projecting work effort & head count

See Solutions Exhibit #2

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 38

NISP Options Analysis

1. CHANGES IN VOLUME: How can NISP adjust its plans if one type of application grows much faster than planned?

2. SHIFTS IN VOLUME: How can NISP adjust its plans if one type of application grows much faster than planned while others grow much more slowly?

3. GEO-POLITICS: How can NISP flex its plans to accommodate global trends?

4. ROLLOVER OF PLANS: How does NISP ensure that prior agency plans roll over to NISP?

SUGGESTION – Lets have each table discuss one of the 4 questions for 10 minutes, then pick one table per topic to present its ideas.

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 39

NISP Options Analysis, discussion #1

1. CHANGES IN VOLUME: How can NISP adjust its plans if one type of application grows much faster than planned?

Assessment of cost types and trends is key: which costs change on linear vs. step bases, or are fixed?

Is funding tied to volume or must NISP constrain its services or operate differently?

Can components of its budget be shifted to other areas?

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 40

NISP Options Analysis, discussion #2

2. SHIFTS IN VOLUME: How can NISP adjust its plans if one type of application grows much faster than planned while others grow much more slowly?

Usually a much simpler situation to face

Can components of its budget be shifted to other areas?

But need to assess resource skills to ensure service s are delivered by appropriate personnel.

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 41

NISP Options Analysis, discussion #3

3. GEO-POLITICS: How can NISP flex its plans to accommodate global trends?

Reflect back on Shell Oil – does NISP require ‘scenario planning’ resources to pro-actively ‘look outside’ and ‘look [far enough] ahead’ to see potential changes in trends

Is funding tied to volume or must NISP constrain its services or operate differently?

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 42

NISP Options Analysis, discussion #4

4. ROLLOVER OF PLANS: How does NISP ensure that prior agency plans roll over to NISP?

This is a topic for YOU, the experts in the room!

Building a Dynamic Scenario Based Forecast 21 November 2018

Page 43

Initial Questions for our CFO

1. As a CFO how do you assess the completeness &

reasonableness of a forecast/plan submission?

2. Can you describe 3 essential skills that a Financial

Advisor and a CFO must have to perform their role?

3. How do you see the role of a Financial Advisor?

4. In your opinion, how a Financial Advisor can contribute

to better manage the forecasting process and reduce the

financial risks?

5. As a CFO, What do you expect from financial advisors to

help you to manage the initial budget allocations and

initial financial pressures?

Building a Dynamic Scenario Based Forecast 21 November 2018