forecasting basics : what do i do to after i balanced my model
TRANSCRIPT
FORECASTING BASIC
S:
WH
AT
DO
I DO
TO
AF T
ER
I BA
LA
NC
ED
MY
MO
DE
L.
YOUR HOST FOR TODAYS WORKSHOPKevin Anderson, Kevin R Anderson Consulting
29 year veteran of gravity models. Industry experience includes analyst at Howard L Green and Manager of Location Research BI-LO Supermarkets. Familiarity with Power:Site (DOS version of SItesPlus), SitesPlus, Model II, Business Analyst Huff Model, and SAM (Site check Research Groups proprietary C-Store, Fuel gravity/forecasting model).
Kevin has an undergraduate degree in Business Administration, and a MBA from Northern Michigan University.
Email: [email protected] Cell: 864-884-3745John Hefner III, Director of Facilities Research for Schnuck Markets, Inc
48-year grocery veteran in conjunction with 32 years in site research methodologies. He presently manages a three-person department at Schnuck’s Markets . John started out using the Locus model in 1981, followed by Model I & II, Power:Site and eventually Site Pro Plus. His expertise includes site location studies, metro markets analysis, acquisition strategies and due diligence for legal projects.
John has an undergraduate degree in Accounting/Finance from the University of Missouri–St. Louis and a M.B.A. from Webster University.
Email: [email protected]
WHAT WILL WE LEARN TODAY:
What are the basic types of Forecasting?
How do other forms of forecasting come into play during the Forecasting Phase?
Model definition and purpose?
What inputs need to be set?
What is the process?
When is it a good forecast? How do I know?
Some caveats when forecasting with gravity modeling.
BEFORE WE START FORECASTING Make sure the model is balanced!
Unbalanced models produce results that are suspect. Before starting the forecasting process look one more time at the balanced model.
Collect all competitive changes and have them ready to input into the model. You can add them later, but it is always best to have your changes
laid out before hand. Although it may not be possible to collect all changes, it will
minimize the duplication of work if you collect it up front THINK
Think about what you are doing and make a list of tactics to explore. Do not dwell on what you are doing; don’t over think the problems
so much that you cannot make a decision.
OTHER R
ELATE
D
FORECASTI
NG
METHODOLO
GIES
OT
HE
R S
AL E
S F
OR
EC
AS
TI N
G M
ET
HO
DO
L OG
I ES
HOW OTHER METHODS OF SALES FORECASTING
RELATE TO GRAVITY MODELING ANALOG (or Analogous Store). In models without sister stores or new markets - analogs can give us a
basic framework to start on our understanding of the sales forecast. Comparing similar competitors with subject competitors can give us an
indication on how our store should perform when setting the Power, Curve or other model parameters.
REGRESSION (or Multiple Regression) Helps us explore correlations on what factors that make a site successful. We can take these factors and compare them to new locations to
determine would be the sites with the highest probability of success, this benchmarking can be used in other areas of the organization.
Information derived from these alternative ways of forecasting can be used to help the modeler increase the accuracy of the sales forecast within the Gravity Modeling environment.
TYPE
S OF
SALES
FORECASTI
NG
SU
BJ E
CT
AN
D C
OM
PE
TI T
I VE
ST
OR
ES
TYPES OF SALES FORECASTING IN GRAVITY MODELSSubject Stores and Competitive Stores. Subject Stores – Our or clients stores that are the target of
the sales forecast These are the stores for which the model was built Formats and Sizes can be part of the investigation
Competitive Stores – What is happening and when will happen New, remodels, expansions, closing and relocations that
will happen to competitor stores (and sister stores not part of the analysis).
Format and Sizes also can be explored. Alternative formats can also be explored.
THE O
RDER FOR
FORECASTI
NG
A B
RI E
F EX
PL A
NA
TI O
N O
F TH
E P
RO
CE
SS
.
THE ORDER OF FORECASTING IN GRAVITY MODELING – SITESPLUS• First we start with a Balanced Model in the SitesPlus Project File. • This is a fully calibrated model for the Study Area and competitors.• Once model is fully calibrated, make sure to save an backup copy.
• Second we open a new model for the competitive impacts.• Enter all competition that is projected for the model. • Enter the existing stores Loyalty Factors.• Test to see the relevance of the forecast.
• Finally, open a new model for the subject site (s)• Enter the subject stores, and open all relevant competition. • Make sure all Loyalty Factors are still relevant from the previous
model.• Double check the effects of the manual overrides.
ADDING M
ODELS
AND BUILD
ING A
FORECAST
A L
I ST
I NG
OF T
HE
IN
PU
TS
NE
ED
ED
TO
AD
D
CO
MP
ET
I TI O
N A
ND
SU
BJ E
CT
ST
OR
ES
SITES PLUS FORM: ADDING MODELS Go and start another model within the project file’ Separate models for Competitive Changes and Subject Site Forecasting. By adding in the changes in separate models we can more effectively
manage what our impacts are to sister stores and competitors
Pressing this button will add a tab (to the left)
Once tab appears fill out the form
Filling out this field names the model
This sets the opening date for the forecast
Use these fields to add subtitles to the heading
ADDING MODELS TO THE PROJECT FILE• ALWAYS start with a BALANCED model before Adding a New Model.
• Press the Calculate and Balance Icons on the Menu Bar before adding a new model to make sure it is truly balanced.
• ALWAYS start with the Competitive Changes Model. You can add all changes to this model, but only open the competitive changes. • Add all models to the Project File from the previous model.
Otherwise the changes made will not be carried forward.
Balanced Model
Competitive
Changes Model
Forecast Model 1
LOYA
LTY
FACTO
R
WH
EN
TO
US
E A
ND
NO
T U
SE
TH
E L
OY A
LTY
F AC
TO
R
THE STEPS INVOLVED FOR FORECASTING WITHIN SITES PLUS – LOYALTY FACTOR
Epicurean Delight is a specialty store
Buds is a specialty market needs special treatment
Once al changes are made press calculate to see the effects
Once all changes are made and we are satisfied with the effects, click ok and you will exit the dialog
SOME NOTES ON LOYALTY FACTORS
Add the Loyalty Factors If Needed Accessed through the Data ribbon at the top of the model. Determine which stores need loyalty curves. For rule of thumb;
all Limited Assortment/Gourmet, Supercenters, Upscale stores should be reviewed for Loyalty curves, not conventional supermarkets.
Some conventional supermarkets, however, may need a Loyalty Factor, after the first volume check, you may want to add them into the model. An example is a store that is getting impacted rather too severely, this may warrant a Loyalty Factor for that store
Stores that typically do not get impacted by conventional stores opening should also get loyalty factors.
Should be done immediately before Adding Stores. AND NOT IN THE BALANCED MODEL
ADDING S
TORES
AD
DI N
G C
OM
PE
TI T
I ON
AN
D S
UB
J EC
T S
I TE
S T
O T
HE
MO
DE
L
THE STEPS INVOLVED FOR FORECASTING WITHIN SITES PLUS – ADDING STORES First within the competitive changes model - enter the competitive
changes within the model. New Stores. These are added via the Add New button on the Store
Data Form. Remodels. These are typically added via the Rebuild function on Store
Data Form but can also be added via the Add New button Expansions. Like Remodels use the Rebuild button on the Store Data
Sheet, but can use the Add New button also. Conversions.
With the Rebuild button we keep the existing data for the store before the proposed changes. All curve, manual overrides will be added to the ‘new’ record
Add New command will not carry over all the curve and manual overrides. It maybe more appropriate for a new chain acquiring a store from a weaker competitor.
STORES DATA ENTRY SHEET - SITESPLUS
Insert New Stores
Close Existing Stores Without Removing it from the model
Remove the stores
Make changes Remodels Relocations, & Expansions
INPUTS NEEDED FOR THE SALES FORECAST.
Typical store inputs needed for sales forecast: Location, size, curve, PWTA and Power. Plus any overrides also can be added to a stores. Later we will go over tips on how and what to put in the necessary field, but it is much the same for either type of forecast that you do – Subject Stores or Competitor Stores,
Sales: $0 or $XXX
Dependent on size and location
Set by neighboring Stores; Sister Stores
Chain Average or Completive Comparisons
SPECIAL CONSIDERATIONS FOR EXISTING VOLUMESWhen making changes to stores that are in the
Balanced Model and will receive a Remodel, Conversion or Expansion the analyst needs to decide whether to keep the existing (or from the Balanced Model) volume or leave the field null in the record .
• Adding the existing volume to the store in the volume field• If store is on the periphery of the Study Area this option should be
looked at for viability. It will keep huge swings in volume to a minimum.
• Leaving volume field blank will allow more volume to be ‘captured’ from beyond.• Could inflate the sales forecast by assuming more volume could
come from outside the Study Area.• If the store is in the middle of the trade area it make sense to do
this because it keeps the sales from beyond (outside the study area) will not vary greatly (no more than 10% in total given the PWTA).
THE EFFECTS OF PWTA AND OLD VOLUME ON FORECAST FOR RELO/EXPNS/REMODS/CONVS
Scenario PWTA
Old Volume
Prior Outside Sales
Projected Volume
Post Outside
SalesKeep existing Volume 85% $200,000 $30,000 $250,000 $30,000Leave Volume Field Blank 85%
$200,000$30,000 $258,824 $38,824
Variation 29%
Scenario PWTA
Old Volume
Prior Outside Sales
Projected Volume
Post Outside
SalesKeep existing Volume 35% $200,000 $130,000 $250,000 $30,000Leave Volume Field Blank 35%
$200,000$130,000 $628,571 $408,571
Variation 1260%Beware: If you keep the existing volume on the store it will increase the totals by that amount on the Projected Volume Tables
SETTIN
G THE C
URVE
MA
KI N
G S
UR
E T
HE
SA
LE
S D
EC
AY
OV
ER
DI S
TA
NC
E M
AK
ES
SE
NS
E
THE STEPS INVOLVED FOR FORECASTING WITHIN SITES PLUS – SETTING THE CURVE
Curve relates to size, but also relates to location and the type of store. In models ALDI and Save-A-Lot typically have lower curves than the default.
If a remodel: Keep the Curve the same and change it only if there are extenuating circumstances such as a total change in format.
If expansion/relocation: Change the Curve to reflect the change in size.
In new stores: Start with the Curve at default and adjust if there are sister stores nearby or the format demands it
You can change (and probably should) the Curve if the physical nature of the roadways near the store changes (i.e. from a 5 lane roadway to a 4 lane median divided).
Store Size Store Size Consider a(Total Area) (Sales Area) Curve of:
2,500 1,900 99.95,000 3,750 99
10,000 7,500 9515,000 11,250 9120,000 15,000 8830,000 22,500 8040,000 30,000 7350,000 37,500 6560,000 45,000 5870,000 59,500 5080,000 60,000 49
Suggested store curves based on store sizes.
Source: SitesPlus v.2010,4 help file
THE STEPS INVOLVED FOR FORECASTING WITHIN SITES PLUS – SETTING THE CURVE (CONT)In large models or models were the Curve was adjusted for a
number of stores beyond the default you will need to look at the stores that are going to be forecasted (whether Subject Stores or Competitors). • In cases of large models look at the like chains in the study
area to see what the average Curve is by size. This will give you a good idea what the Curve should be in the forecast.• Some chains will be well represented in an area so their Curve’s
maybe higher than defaults.• Likewise there may be few in the area and may necessitate a lower
Curve.• Alternative Formats in the balanced model will have
consistently lower curves than the default.• This should hold true in the forecasting models – Look at the average
Curve for format/chain and apply in the forecast models.
THE STEPS INVOLVED FOR FORECASTING WITHIN SITES PLUS – SETTING THE CURVE (CONT)• Special cases may exist with a Conventional store who’s image is discount and is one of only a few in an area. • The Curve may be lower than the calculated default.• If a new sister store comes to the area you may have to raise
the Curve on both stores (to show realistic impacts). • Pay attention to the market share draws past sister stores or stronger competitors. • You maybe justified in having a higher (or lower) Curve than
what is calculated based upon size. • Pay attention to any deviation beyond the default – are you
reasons still valid for the deviation from default? Or should it be changed?
SETTIN
G THE P
WTA
ES
TI M
AT
I NG
TH
E S
TO
RE
SA
LE
S F
RO
M T
HE
ST
UD
Y A
RE
A
THE STEPS INVOLVED FOR FORECASTING WITHIN SITES PLUS – SETTING THE PWTASetting the PWTA is as critical as the other factors,
but we just have more “indicators” as to the value.
• For New and Relocated/Replacement and some Conversions stores – Look at the surrounding model stores to see what are the values of PWTA.• Exceptions arise with Alternative Formats, (i.e. limited assortment,
supercenters, and upscale/gourmet).• Pay attention to the strength and placement of sister stores outside the Study
Areas (if there are considerable sister stores outside the Study Area – a higher PWTA is warranted).
• For Relocated/Remodels/Expansions – use the existing value from the balanced model. • May have to make adjustments in special circumstances, but those are few and far between.
SETTIN
G THE P
OWER
TH
I S I S
WH
ER
E Y
OU
R M
OD
EL
CA
N L
OS
E A
LL
I NT
EG
RI T
Y
One important thing to remember about Power is that it is based upon the relative position of stores within the model: all markets average Power (in the balanced model) will be 100 – this does not matter if it is an upscale or lower income area. So comparing models across markets the analyst needs to look at RELATIVE position of sister stores compared to competitors NOT ACTUAL!
Look at sister stores within the model – what is the Power? Are they lower than they should be because of customer appeal? Higher?
What is the size and the format of the stores? Usually Power is reduced for a larger store size especially in the replacement/expansion scenarios this is due to the fact that more of the sales for that store will be explained by the size.
If the remodel expands product offering and increase or decrease of Power maybe warranted (i.e. adding more extensive perishable dept. may warrant higher Power; likewise going to a limited assortment should yield a lower Power).
THE STEPS INVOLVED FOR FORECASTING WITHIN SITES PLUS – SETTING POWER
SETTING POWER – AN EXAMPLE
Here is the average Power by chain in our sample model What should be the Power?Upscale/
Service Supermarket
Conventional EDLP Supermarkets
Note: our chain is a EDLP operator and we put the site in at 120 – Where we right or wrong? And Why?
SETTIN
G THE M
ANUAL
OVERRIDES
PU
TT
I NG
TH
E A
NA
L YT
I CA
L T
OU
CH
ES
ON
TH
E S
I TE
SP
LU
S P
RO
J EC
TS
THE STEPS INVOLVED FOR FORECASTING WITHIN SITES PLUS –MANUAL OVERRIDES With both Subject Stores and Competitive stores Manual
Overrides should be used as sparingly as possible. Usually these overrides (Manual Power, Manual Curves , Sister
Store, and Directional Curves) are used to explain something unusual about the store with relationship to the sectors or other stores within the model.
When using the REBUILD button when adding a Expansion / Remodel or other capital expenditures be very careful about the manual overrides that automatically carry over to the ‘new’ record. You may want to change the overrides or delete them all
together in order to more accurately explain the changes. Is the spotting you used to calibrate the balanced model still
viable?
MANUAL OVERRIDES - MANUAL POWER
Manual Power is more effective on the ‘close-in’ sectors (less than radius distance).
They can go from 1-9999, but try to limit this value to a multiple of 4 from the default Power otherwise you may get some ‘different’ results.
Higher than default, the more volume from the sector, likewise lower power than default lower amount of volume.
When to Use? - When you want to explain more volume from a sector due to demographics or fit.
Store you
want to affect
change
The Sector you want to manipulate
The override Power
MANUAL OVERRIDES - MANUAL CURVE
Manual Curves work better beyond Radius Distance (or the ‘Outboard’ sectors).
Values are 1-99. Lower than the balance model
Curve for the store will increase volume, higher than default will decrease volume from a specific sector.
Demographic fit is the best reason to use this similar to with Manual Power.
When more than a few Manual Curves are used the analyst may want to consider a Directional Curve instead.
Stores you want to affect a change
The Sector you want to manipulate
The override Curve
MANUAL OVERRIDES - DIRECTIONAL CURVE
Directional Curves are similar to manual curves but will apply the same curve to all sectors impacted based upon compass directional and distance values.
It is an easy way to apply Curves to a large number of sectors in a model to limit or expand the stores market share along a roadway or some other physical object.
Sometimes they are used to explain Sister Store effect.
Best Use – To “force’ volume directionally to explain access, demographics, and sister store effects
The affected
Store
Compass Direction for the
Curve The override for the store
When to start the Curve
When to end
the Curve
MANUAL OVERRIDES - SISTER STORES
Sister Store Pairs command will reduce the outlets volume in sectors near sister stores from the same chain.
Although the sales will ‘pull’ past each other, volume will decline at a faster rate than without the Sister Store command implemented.
This effect can also be mimicked with the Directional Curve and increasing the default curve, but will not have the effect localized to the chain.
With the levers and button selectors we can cut volume coming from sectors that are near the sister stores almost to nothing or have it pulling past theses stores with relative strength.
Affected Stores
Adjustment for strength of effect
How the effect is calculated
MANUAL OVERRIDES - SOME RULES OF THUMB
Use Directional Curves to limit or expand sales in a particular compass direction. Use if the site is located on a particularly strong roadway. You
can stretch the market shares along the road so that you can more adequately explain what sectors are giving their volume to the site.
Use default value to (i.e. what was used in the competition model) as your baseline. Below or above this baseline will increase or decrease volumes.
Manual Powers and Curves should be used only to explain demographic fit and only if it is VERY necessary in the forecasted model.
Sister Stores should be used for stores within the same chain. Some experimentation with the parameters should be done to get the desired effect.
METRO, L
ARGE AND
SMALL M
ODELS
WH
I CH
IS
BE
T TE
R A
ND
WH
EN
SH
OU
L D I
US
E I
T?
LARGE (AND METRO ) MODELS VS SMALLER MODELS• Large and Metro Models typically encompass multiple sites and a
county or larger governmental unit.• Can do multiple what if scenarios to see the impacts to the store network.• Give us quick answers to questions such as; • What are the impacts from chain A coming to the area?• What are the effects of a alternative format upon our stores? What are the
optimal storing strategy for an area .• Some compromises must be made when balancing (or calibrating) these
models.• Will have to change default Curve for stores beyond what you would
normally do; or add more manual overrides to get the model to balance.• It adds complexity to the models (i.e. Power of 100 on the north side of
the model could be equivalent to a 90 on the south side of the model).• Take time to balance the model –on larger models it may take over a week
to balance.
LARGE MODELS VS SMALLER MODELS• Small Models are typically single or two site
models• With a smaller model we have some advantages:• Able to keep the stores to default values within the model.• Designed only for one or two sites so lower number of
sectors and stores to evaluate.• Easier and quicker to calibrate talking hours instead of days.• USUALLY the sales forecast is more accurate.
• But we have some disadvantages:• If area is on the border or outside the model area we have
to do a new model • If doing multiple models in an area it can be as time
consuming as building a larger model.
LARGE MODELS VS SMALLER MODELS• So which is better?• If you plan to review a large number of sites in and area or are
trying to get and idea how the competitors market shares look over distance – Use the large model. • If you are going to be looking at a large number of sites over a
given time frame (say 24 months) then use a large model. • If you only have a site or two in the area, use a smaller model
(based upon the estimated Primary/Secondary trade areas).• Even if you expect to have a large number of sites in an area
but will be spread out for the next 36 months – break them up to smaller models.• REALLY fragmented markets (Geographically or
Demographically) are also candidates for smaller models.
SALES F
ORECAST
EVALU
ATIO
N
Sales
fore
cast
nee
d to b
e re
-eva
luat
ed b
efor
e
publish
ing.
Look
at t
hree
mai
n met
rics:
Volu
me,
Compet
itive
Impac
ts a
nd Mar
ket S
hares
.
SALES FORECAST EVALUATION -VOLUME
Volume of the subject site or competitive sites should be looked at with regards to the following:
Does the volume make sense? Is it higher or lower than expected? What does our intuition say? What does the analog say? Is the store/format a match to the surrounding
demographics? Is it the only store in the segment or are there others. How
do they compare? How does the volume compare to the analog?
An abnormally high volume could be an indicator of erroneous inputs into the model. Do these make sense?
Is this a better site than what was anticipated by the analyst?
SALES FORECAST EVALUATION – COMPETITIVE IMPACTSAnother critical area to look at in evaluating a model is the
competitive impacts. This is a check on the viability of the of the sales forecast and the effectiveness of the Loyalty Factors.
Second look at the competitive impacts: Do the competitive impacts make sense? Are they to high – May have to Add/Adjust the store loyalty factor, curves or
sister store effect. Are you impacting the supercenters too much? Are you having only limited
impact upon a sister store? If they are too low – look at the other parameters in the model are they set right? The stores curve may need to be adjusted because of market changes.
Sister store closing. Sister store opening Roadway change
SALES EVALUATION – MARKET SHARESAs with a balanced model; Market Shares should be
evaluated with regard to Distance, Demographics , Natural barriers, Competitive Impacts and Sister store locations.
How do the market shares over distance look? Are they falling like expected ?
Are you pulling from a wrong demographic segment too strongly? Are there any unusual blips (market shares higher/lower than what
you would expect)? Are you pulling strong market shares past sister stores? Are you pulling strong market shares past alternative formats or
stronger competitors? If any of the previous items do not appear to be normal review the
impacts. Could the inputs need adjustment? Might you need to add sisters stores or directional curves to adjust market shares?
TOOLS
TO U
SE TO H
ELP
WIT
H THE F
ORECAST
HO
W O
TH
ER
TO
OL S
HE
L P W
I TH
TH
E S
AL E
S
F OR
EC
AS
T
GIS – GEOGRAPHIC INFORMATION SYSTEMSSince its common adoption in the earlier adoption in the
early 80’s it has helped sales forecaster get a handle on the demographics and physical geography of an area (and to produce colorful maps!)• Thematic mapping is invaluable for reviewing
market shares on large and small models. • Running two themes together gives you a good idea
of sister store effects.• Your competitive database can show you were stores
are outside of the study area – allowing you to confirm or adjust the study area.
Map showing market shares and tapestry clusters
SPREADSHEETS AND STATISTICAL PROGRAMSExcel and SPSS help us conduct preliminary analysis on our
competitive and customer database, along with refining our presentation materials for the Gravity Model output.
Excel can take the sales forecast data from the gravity model and develop our ROI and ROIC calculations.
Excel can also be used for adding additional information to the SITESPLUS report output.
SPSS and other statistical programs help us determine our benchmarking with regards to customer typology and can be used to help us to determine what is exactly an acceptable market share from a sector for a store.
Alteryx, Tableau and other programs help bring various data sources together for developing actionable presentation materials for the big data era.
THE GROWTH CURVE
Growth Curves are a good way to “Step” sales up over a period of time
You can have more than one curve to use for forecasting.
Having a Do Nothing curve aids in showing projected sales declining over time with respect of a lack of capital spend.
New Store Curve can allow you to ramp up sales for a particular unit, especially if you include PHARMACY sales in the SitesPlus volumes.
Above all else should use store data vs industry standard curves.
GRAVIT
Y MODELIN
G
CAUTIONS
SO
ME
CA
VE
AT
S T
O C
ON
SI D
ER
WH
EN
MO
DE
L I NG
…
THE CAVEATS• Although Gravity Modeling is objective it is not totally objective forecasting
tool.• Subjectivity is introduced by the analyst during balancing and forecasting phase –
these can affect the accuracy of the forecast.• Subjectivity is also introduced during the data collection phase of the project which
will also affect the sales forecast
• Basic knowledge of stores (competitors and subject stores) is necessary.• Intimate knowledge probably not critical, but a knowledge of format and how the
format will be accepted by customers is a necessity.• Are you using Total Sales vs Net Sales (AWV less Pharmacy, Gas, and other non food
sales ), for the stores in the analysis? If you are using Total sales make sure the impacts make sense and the forecasted volume makes sense because Pharmacy sales mature at a much slower rate than grocery sales.
• Knowledge of the study area (demographics , geography, etc.) • The macro factors within a model (sector radius, barriers, leakages and potential),
should be set during the balancing phase and should not be changed during forecasting.
• However, new changes (i.e. adding a bridge or cross point to a river or barrier) will change the dynamic of the market area.
AFTER T
HE FORECAST
TH
E N
EE
D F
OR
CO
NT
I NU
OU
S I
MP
RO
VE
ME
NT
S
WHEN TO CONDUCT THE POST MORTEM
• Post Mortems are necessary for the continued success of the analyst, department, and company.• A look at the viability of the assumptions will help in future
projects.• When reviewing the model; look at the inputs for the new
stores (both competitors and subject stores).• Where were the errors?• Are the sales right for the wrong reasons or wrong for the
right reasons• Once the Post Mortems are complete; publish out to the
relevant individuals.• Make sure there are qualitative as quantitative analysis. • Steps for improving on the quality of the work.• Don’t just blame operations – take some responsibility.
CLOSIN
G
SU
MM
AR
Y O
F TH
E M
AI N
PO
I NT
S I
N T
HE
WO
RK
SH
OP
SUMMARY
• Establish a process for the developing sales forecast • Look at all the data inputs for both competitor stores and
subject site.• Make sure they are logical and can be defended to an
outside person.• Review them with a colleague.
• Review the market shares, volume and competitive impacts for anything out of the ordinary.• Make sure Alternative formats in the model behave in a
way that is expected.• Make sure you start the forecasting process with a
balanced model.