Help for the brand leader on how to do forecasting, the analytics behind it as well as the importance.

1. How to do Forecasting

2. Forecasting Techniques
“Do you think the weather will stay like this? No, I don’t.
This is earth. It’s a variable temperature planet.”
Jerry Seinfeld

3. Why Do Forecasting? Basic Needs of Business.
• Forecasts are a basic need of running a company. It handles the basic ebb
and flow of demand to match it up against the product supply to ensure
we can meet the customer needs.
• Supply Chain may be defined as “flow of materials through procurement,
manufacturing, distribution, sales & disposal”. The supply chain is the
network of organizations that are involved through upstream and down
stream linkages, in different processes and activities that produce value in
the form of products and services in the hands of the ultimate customer.
• You can actually win via supply chain. If you are more efficient/faster
than your competition, you can deliver a better product, meet more needs
and beat them because you can forecast and deliver better. Wal-Mart
wins with this strategy. They sell their merchandise through in 28 days vs
paying for it in 30, whereas their competitors like Sears take 130 days to
sell through the merchandise.

4. Who is Impacted By the Forecast?
Forecasts send a signal to the entire organization:
• Senior leaders or Owners: watch the forecasts and make decisions on
performance, potential changes in strategy or tactics and potential for
added or less investment. Potential course corrections.
• Outside Investors: watch the overall projection of sales delivery to
determine whether the company or brands are worthy of investment.
• Senior Management: Supply Chain who meets demand and will buy
materials, hire staff, etc. Sales Management who align with core
customers, hire, train and motivate the sales staff.
• Functional Areas of the company, so they can do their roles effectively:
Marketing, Sales, Finance, Production, Supply chain

5. Actions Impacted by Forecasting
• Plans: Develop future plans, Plan for the future by reducing
uncertainty, Anticipate and manage change, Increase communication and
integration of planning teams
• Finance: Make best use of scarce resources, Plan cash flow to prevent
shortfalls, Support business financial objectives, Project costs of
operations into budgeting processes
• Service: Anticipate inventory and capacity demands and manage lead
times, Improve competitiveness and productivity through decreased costs
and improved delivery and responsiveness to customer needs

6. Why Measure Forecast Accuracy
• Customer service: Safety stock is used to enable the company to
maintain satisfactory levels of customer service. Safety stock also allows
you to handle any variance due to unpredictable market forces or even
the potential of a competitive response.
• Efficiency: It’s much more efficient to stabilize the manufacturing
process, which enables you to make bulk materials costs, as well as
maintain a steady workforce at the plant. Also, maintaining efficient
transportation and logistics costs.
• Planning: Forecasting comes at a cost. There are optimal safety stocks
that are balanced off by the cost of the inventory. High cost of goods on
slower moving items puts the company in a higher risk position.
• Correct causes of problems: The highlighting of the problems enables
companies to mobilize against the variances.

7. The Three C’s of Forecast Management
Communication
• Good written, verbal, and e-mail communication among functions. As the
leader, it’s important that you be the stabilizing force in a potential battle
of confusion or conflict. Ask probing questions and lay out your thinking.
One of the best questions to ask is “so what’s really changed” and you
might find that slows down and forces people to think it through.
Coordination
• The formal structure and required meetings. You should be leading a
cross functional team of supply chain, sales, finance, all with key stakes in
the outcome of your forecast.
Collaboration
• Between the forecasting function and the other functional areas that use
the forecast. Make sure everyone is on the same page, is aware of the
decisions and the logic that went into the decisions.

8. Types of Forecasts
Intrinsic—based on historical internal patterns of the data itself from
company data
 Product life-cycle management
 Planned price changes
 Changes in the sales force
 Resource constraints
 Marketing and sales promotion
 Advertising
Extrinsic—based on external patterns from information outside the company
 New customers
 Plans of major customers
 Government policies
 Regulatory concerns
 Economic conditions
 Environmental issues
 Global trends

9. General Methods of Forecasting
Qualitative—based on intuitive or judgmental evaluation. Qualitative
forecasting techniques are subjective, based on the opinion and judgment
of consumers, experts; appropriate when past data is not available. It is
usually applied to intermediate-long range decisions.
 Informed opinion and judgment
 Delphi method: relies on a panel of experts.
 Market research
 Historical life-cycle Analogy.
Quantitative—based on computational projection of a numeric relationship.
Quantitative forecasting models are used to estimate future demands as a
function of past data; appropriate when past data is available. It is usually
applied to short-intermediate range decisions.
 Time Series: Simple Moving Average , Weighted Moving Average and Simple
Exponential Smoothing
 Last period demand
 Arithmetic Average
 Multiplicative Seasonal Indexes

10. Thoughts on Forecasting
Understand How Your Brand works: Every brand works a little bit different,
and before you even dig in, you have to understand the impact on forecasting.
 Is it seasonal business?
 Do orders come steady or in major fluctuations?
 Is it contract driven? (unpredictable results)
 Does your product have high COGs or high margins?
 What’s the life expectancy of your product?
 Is the competition fierce or passive?
 Role of your brand within the company
 State of the overall business: Is there a push on? Quarterly
pressures?

11. Understand Your Brand And the Role within the Company
• High Margins vs High COGs: If your brand has high margins, missing a sale can be
very expensive relative to the cost of carrying the inventory. Conversely, lower
margin products have high carrying costs.
• Life of the Product: If you have a longer life, you can also afford to bring in the
inventory because carrying it has less risk. However, shorter life product drives the
risk up as you might have a lot of wasted product.
• Sku Mix: When you have lots of skus, the lower selling skus carry a risk to your
mix, they may also be very difficult to forecast. Conversely, having very few skus
could also drives up the risk because all the sales rely on very few skus.
• Customer Mix: Broad customer base allows you to have a balanced approach. A
narrow customer base drives up the risk, because missed sales are difficult to cover
off. Puts the brand at the mercy of fewer customers.
• Sales Patterns: Steady sales are easier to forecast and maintain inventory against.
The irregular or infrequent sales makes it more difficult and drives up the risk of
carrying extra inventory—which could go out of date before the next order.
• The Economy: Understand where your brand sits in the economic life—is it a lead
indicator (construction) or a trailing indicator (consumer goods)

12. Seasonality
There is more seasonality than you might think: There are three types of
seasonality to understand. 1) Real Seasonality driven by customer needs
(Allergies, xmas, spring/fall) 2) Driven by Financials (Year End, New Budgets
etc) 3) Driven by Habit (this is when we always do it)
TV Business
Father’s Day
Back to School
New TV Launch
Boxing Day
How Many of
These Blips Are
Real vs Created?

13. High Medium & Low: Optimistic, Realistic & Pessimistic
• “What if”: One of the more useful exercises, even for yourself, is to do the
calculations by changing the major variable with options of “what if” that
are optimistic, pessimistic and somewhere in the middle.
• Show your work: just like on a grade 9 math test, you get extra marks for
showing your work and allowing others to see what your actual thinking
was that went into your assumptions.
• Communicating upwards allows your boss to see your logic and help make
the decision on the direction they wish to take. They may see other
constraints or issues and bring those into the decision.
• Communicating with supply chain, your logic on the high, medium and
low allows them to make a judgment call around production, whether to
bring in extra safety stock to cover the upside potential or ensure they
don’t carry too much.

14. Forecasting Techniques: Moving Averages
• Simple Moving Average is the un weighted mean of the previous data
points.
• If the data used are not centred around the mean, a simple moving
average lags behind the latest data point by half the sample width. It can
also be disproportionately influenced by old data points dropping out or
new data coming in.
• One characteristic of the SMA is that if the data have a periodic
fluctuation, then applying an SMA of that period will eliminate that
variation (the average always containing one complete cycle). But a
perfectly regular cycle is rarely encountered.

15. Forecasting Techniques : Weighted Moving Averages
• Weighted moving average (WMA) has the specific meaning of weights
that decrease in arithmetical progression. In an n-day WMB, the latest
day has weight n, the second latest n-1 etc down to one.
• The exponentially smoothed moving average addresses both of the
problems associated with the simple moving average.
 The exponentially smoothed average assigns a greater weight to the
more recent data. Therefore, it is a weighted moving average.
 But while it assigns lesser importance to past price data, it does
include in its calculation all the data in the life of the instrument. In
addition, the user is able to adjust the weighting to give greater or
lesser weight to the most recent period's shipments

16. Forecasting Analytics
“I wish I had an answer to that because I'm tired of
answering that question.”
Yogi Berra

17. The Analytics: Get Smarter Before You Estimate
Forecasting is a judgment call. It is a “guess-timate”. But some people’s
guess are better than others—likely based on the knowledge they gain. The
Best Analysis You Can Do:
1. Have your Finger on the pulse of the business, knowing specific shares, daily
sales rate, major customer issues, competitor moves and even key deadlines.
2. Five questions that can help Frame your thinking: 1. What do we know? 2.
What do we assume 3. What we think? 4. What do we need to find out? 5.
What are we going to do?
3. Force Field Analysis focuses on the factors driving growth balanced against
factors inhibiting the brand’s growth.
4. One of the best ways is to put a stake in the ground, borrowed from
something you think is similar and then map out the plus and minus in relative
proportion.
5. Use the Brand Funnel to help drive the brand math, mapping it out from
Awareness to Purchase and Repeat.
Keep in mind the relative nature of analysis and always leverage something at
the core to draw the comparisons.

18. • Most marketers think that Monthly reports or roll-ups are a chore. Even at
the VP level, I did up my own monthly summary as a discipline to give me
the gut check to know the ebbs and flows of the business.
Know the Pulse of the Business—Write a Summary Each Month
Market Shares
Daily Sales
Contract
Deadlines
Customer
Issues
Price
Changes
Product
Launches Global
Sales
Economic News
Sales force
Feedback
As the leader, take all the information,
decipher it down to a story and steady the ship.
Trial &Repeat
Investment Level
Program
Performance

19. Key Information Needs That Can Impact Forecasting
• Market Data: category size and growth rate, share and growth rates for
each brand, average prices etc. or any expected changes to the market.
• Market Information: Major Trends, Competitor Activity,
Consumer/Customer shifts, changes to the Channel, Technology
changes.
• Economic Indicators: GDP growth rates, Import/Export, Unemployment
rates, Inflation Rate/CPI, Interest Rates, Housing Starts, Government
Investment
• Underlying Brand Funnel Data: Awareness, Consideration, Trial,
Purchase, Re-Purchase, Loyalty/Usage frequency.
• Competitive Information: Launches, price changes, promotional
activity, channel changes, discounts, advertising, stated goals.

20. 1. What do we know? This should be fact based and you know it for sure.
2. What do we assume? Your educated/knowledge based conclusion that
helps us bridge between fact, and speculation
3. What we think? Based on facts, and assumptions, you should be able to
say what we think will happen.
4. What do we need to find out? There may be unknowns still.
5. What are we going to do? It’s the action that comes out of this thinking.
• It forces you to start grouping your learning, forces you to start drawing
conclusions and it enables your reader to separate fact (the back ground
information) from opinion (where you are trying to take them)
5 Questions to Help the Thinking Time: What Do We Know?
Example of how it works:
What do we know: purchase frequency has decreased.
What do we assume: Economy making consumers to use less
What do we think: Fear making consumers conserve.
What do we need to find out? Would lower cost drive frequency.
What are we going to do? Launch 8 count test market.

21. • The simplest analytical model can help to give you a point in time look at the
issues. There are two things: things that drive and things that inhibit.
• This model helps you do a few things: 1) helps to give you a simple assessment
of how well the brand or project is doing 2) helps you to isolate where your
issues lay 3) simple list of what you need to fix.
• The simplicity is of the model is that you want to stop doing the drivers and you
want to overcome the inhibitors.
Drivers Inhibitors
New Flavours provide variety
New advertising drives usage
Awareness growing
FDM front end distribution doing ok
Poor Convenience Distribution
Repeat is declining
Price Point Too High
Younger target very fickle
Force Field Analysis focuses on the Factors driving growth
balanced against factors holding you back.

22. The Stake in the Ground: A Comparison Measure
• Find a comparative stake in the ground, which will help you to make
comparisons—either above or below that stake in the ground.
• Examples could include last year’s sales, a competitive brand, a similar
program or contract from the past, or a different geography extrapolated to
the size of the market, market research projections
The + or – Analysis
• Put together a chart that shows how it might be bigger or smaller then the
stake in the ground projection.
Bigger Impact Lower Impact
Examples:
We have a relatively bigger share
More advertising dollars
Consumers like that flavour better
It has a unique positioning
More doctor support
Example:
We are last in the market.
Pricing is lower.
Not as much consumer appeal.
Canadians don’t like that flavour.
We are 4th in market.
Put a stake in the ground: Map reasons why it’s bigger or
smaller than the stake.

23. Example of Making Projections
• Brand X is a new molecule in the medical market It is a new brand
that brings new hope for doctors and pharmacists
Stake in the Ground: Brand X could be as big as Y in Year 1 which was
an 8% share and $80 Million in Sales
Bigger Impact Lower Impact
• Expected to get 25% more A&P support
then what Brand Y got
• It has 24 hour claim while Brand Y was
only 12 hours
• Doctor recommendation should add 25%
more in sales
• A 4% dollar share in month two, ahead
of the 2% share Brand Y got.
• Market is a lot more crowded than it was in
2005 when Y launched
• Launching in March, which means we missed
the Q1 sell in
• While it’s a new molecule, it really has very
little to say (congestion)
• Launching at a significant price premium
Conclusion: Brand X will be slightly bigger than Brand Y in
Year 1. It will be 10% share and $100 Million in Sales

24. Using the Brand Funnel can help to do the Brand Math.
• Leveraging the brand funnel, you can do the math.
 Purchase: 2.5 Million x $5 = $12.5 Million
 Repeat: 1 Million x $5 $ 5 Million
 Loyal: 200K x $5 $ 1 Million
TOTAL $18.5 Million
Assumptions 10 Million ppl @$5 per item
Awareness 90% 9 million aware of it
Familiar 75% 7.5 million familiar
Consider 50% Half the people consider it.
Purchase 25% 2.5 million buy it at $5 per
Repeat 10% 1 million buy it a 2nd time at $5
Loyal 2% 200k buy a 3rd time at $5

25. Last
Year
Other
Brands
Category
vs Norm
Plan
Or LE
Prior
Month
Data
Point
While we get paid in real dollars, good analysis is rooted in a
relative nature to something else.
What do we usually make
comparisons with:
• You might want to look
at all these things and
like an investigator, start
to see if there are breaks
that start to tell a story.
• If no data break, then no
need to blindly keep
telling the story using
that anchor.

26. Financial Forecasting
“Show Me the Money!”
Tom Cruise in
Jerry McGuire

27. What’s involved in the Brand’s Annual Financial Forecast?
• Sales: Project the growth rate for the year, and break it out on a quarterly
basis, and then depending on the business a monthly sales forecast.
• Market Share: This is like showing your work on the math test. It’s
important that you map out the category size with related market share
movement that helps to back up the sales call.
• Product Costs: Roll up of plant manufacturing costs, related to the
materials, production, shipping. Brands heavily reliant on materials that
fluctuate on costs should flag the risk potential.
• Marketing Spend: Mostly incremental spend by activity versus last year.
It could be to support new product launch, an awareness building
campaign or a defensive spend versus a competitor. Where it’s not
incremental, you could do a specific test market with spend or use a
comparable brand as a reference point.
• Other Forecasts: Overhead, Headcount, Seasonal needs, R&D costs,
Partnerships or Royalties and one-time investments that could be
capitalized.

28. Approaches to Financial Forecasting
Historic Trend
• Useful only with at least a two years of historic data
• Requires relatively stable sales or growth (doesn’t work too well if sales
spiking or plummeting)
Share of Market
• Very difficult without market research
• Need to know buyer incentive to get market share
• Need to know buyer loyalty
Pro Forma
• Applies to new product/service forecasts
• Requires a lot of assumptions and margin for error
• Strongly recommended to do a low/mid/high forecast
• Anticipate low, be able to deliver high

29. What to do with your forecast?
Sensitivity Analysis
• A very good practice to test for the strength of forecast and its assumptions
• Assume that a key component/driver of the forecast is wrong by
10/20/30, even 50%. What happens?
Break even calculation
• Identify what amount of sales in $/units are required to break even on
investment/running costs
Risk Modeling
• Identify what are the sunk costs of product/project/company
• Determine at what point is there sufficient incentive to go ahead and proceed:
sufficient demand/orders, economies of scale, timing with a marketing
campaign
• How much do you need to spend in market research to increase certainty by
X%? Determine if it worth the opportunity cost of the research to avoid higher
losses

30. Zero Based Forecasting—start fresh each year
• Zero Based Budgeting (ZBB) is a method of budgeting which requires
you to justify all planned expenditures for each of your new business
period. It defers from traditional incremental methods which may only
require you to explain the amounts you need in excess of the previous
period's funding.
Unique characteristics
• Requires you to justify and prioritize all activities before allocating any
resources.
• All your business forecasts should start from a zero base by justifying all
expense requests in complete detail. The zero base is indifferent to
whether the total forecast is increasing or decreasing
• Requires you to group all relevant activities into decision packages. You
justify each in terms of the companies’ overall business objectives.

31. Zero Based Forecasting—Pros and Cons
Advantages
• Results in efficient allocation of resources as it is based on needs and
benefits
• Drives managers to find out cost effective ways to improve operations
• Helps Detects inflated forecasts
• Identifies and eliminates wastage and obsolete operations.
• Can encourage managers to look more critically at the way in which
services are provided.
Disadvantages
• Difficult to define decision units and decision packages, as it is very time-
consuming and exhaustive.
• Forces you to justify every detail related to expenditure. As a result
activities like research and development are threatened whereas
activities like production benefit.

32. 2008 2009 2010
Price
Increase
Net Sales 21,978 24,616 27,569 30,326
Cost of Goods Sold 12,866 14,925 17,313 17,313
Gross Margin 9,482 9,862 10,256 13,013
43% 40% 37% 43%
Total SG&A 3,444 4,202 5,127 5,127
Contribution Income 5,763 5,244 4,772 7,886
26% 21% 17% 26%
• By increasing the price by
10% and holding units
steady, we see profit go up
to $7.8 Million. The risk is
that volume could go down.
• By cutting spend, we see
that profit goes up to $6.8
Million. The risk is that the
overall volume and sales
level could go down.
Pro Forma Financial Statements: Changing One Factor at a Time
2008 2009 2010 Cut Spend
Net Sales 21,978 24,616 27,569 27,569
Cost of Goods Sold 12,866 14,925 17,313 17,313
Gross Margin 9,482 9,862 10,256 10,256
43% 40% 37% 37%
Total SG&A 3,444 4,202 5,127 3,444
Contribution Income 5,763 5,244 4,772 6,812
26% 21% 17% 24%

34. There’s Eight Areas on the P&L that you need to dig in
to uncover the story.
Pricing Price cut? Customer discounts to drive volume?
Trading Up/Down Product Mix Changed? More lower margin sales?
Product Costs COGs went up due to supplier or materials?
Marketing Costs Spend is up? Launching? Stealing share?
Stealing Other Users Investing to steal competitive users? Defensive stance?
Get Users to Use More Discounts to encourage volume per customer?
New Category Investment to Enter into a new category?
New Uses Education investment on potential uses?
The Good News: to simplify your thinking and make it easier on you,
these are Eight key Levers of the P&L that you need to focus on.
1
2
3
4
5
6
7
8

35. Summary
“Forecasts are Always Wrong. The only question is "how
wrong is it?”.

36. Laws of Forecasting
1. Forecasts are always wrong. The only question is "how wrong is it?" The goal
is to get it accurate enough that it doesn't hurt the business too much when it
is within its normal variation. That can usually be accomplished either through
better forecasting methods or changes to the business to make it less sensitive
to a bad forecast.
2. Correct forecasts are not proof that the forecast method is correct. It could
have been luck. Don't just look at the results, look at the methodology.
3. All trends eventually end. No matter how accurately the trend is forecasted, at
some point in the future it will be wrong. Consider what might cause a trend
to change (seasonality, new competition, saturated market, etc.) when
evaluating a forecasted trend.
4. Complicated forecast methodologies can be dangerous. Simple forecast
methods are easy to explain, understand, analyze and debug. Complicated
methods tend to obscure key assumptions built into the forecast, which can
lead to unexpected failures.
5. The underlying data in the forecast are nearly always wrong to some degree.
It is just a question of how far off it is. Therefore, the more data that is in the
forecast, the more likely some important error will be missed.

37. Laws of Forecasting
6. Data that has not been regularly used is almost useless for forecasting Data
quality is usually directly proportional to the amount it has been used.
Without regular usage, errors remain undetected and inconsistencies develop.
It's better to use solid data in a forecast even if additional assumptions have to
be made in order to use it.
7. Most forecasts are biased in some way -- usually accidentally. It is very
difficult to eliminate all bias in a forecast, since the forecaster always has to
make certain assumptions about which factors to include, how strongly to
weight them, and which to ignore. And sometimes the bias is intentional.
8. Technology will not make up for a bad forecasting strategy. Create an
appropriate strategy first, then use the technology to make it better.
9. Adding sophisticated technology to a bad model makes it worse. If the model
is bad, anything you add to it -- statistical methods, time-series methods,
neural networks, etc. -- will make it worse. And it will be more difficult to
figure out what is going wrong.
10. Large numbers are easier to forecast than small ones. Everything gets easier
as the numbers get bigger. A forecast of unit sales where there is an average of
1,000 units sold per month is a lot easier to get right than one where average
sales are 2 per month.

38. Summary Tips for Being Better at Forecasting
Know your Business: Monthly Report is Good Practice.
• As the leader you need a finger on the pulse of the business. You should know the
underlying key performance indicators, match those up to the in-market realities
of customer market orders on the surface and in the near future. Stay close to
your sales team. Know what your competitors are doing and how it can impact.
Be Aware of How Seasonality Can Drive Your Brand.
• Understand the impact of the three types of seasonality: 1) Real Seasonality
driven by customer needs (Allergies, xmas, spring/fall) 2)Driven by Financials (Year
End, New Budgets etc) and 3) Driven by Habit (this is when we always do it)
As the Leader, you have to Steady the Ship
• As the leader, you need to make sure that you steady the ship and avoid creating
your own fluctuations. A great question is “so what’s changed since last month”.
You’ll find that many times, less things have changed even though everyone in
your group has changed the forecast.
Be a Good Communicator of Your Thinking Behind the Forecast
• Communicate upwards so that your boss can understand your logic behind your
thinking, helping make a decision. Communicate with supply chain your
high/medium/low thinking so they can make a decision on inventory to avoid
missed sales vs excess inventory. Help them manage the risk.

39. “If you don’t love the work, how do you
expect the consumer to fall in love with
your brand?”
Graham Robertson
Beloved Brands Inc.

40. Beloved = Power = Growth = Profit
© Beloved Brands Inc.

41. We help Brand Leaders to realize their full potential.
• Better Strategic Thinking
• Writing a Brand Plan
• Developing a Brand Positioning Statement
• Writing a Creative Brief
• Conducting a Deep Dive Brand Analysis
• Getting Better Advertising
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• Managing Your Marketing Career
Visit the Beloved Brands blog at beloved-brands.com
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