This document discusses how to tie a micro inventory forecast to a macro sales forecast. It explains that applying a business trend factor (BTF) ratio calculated from the two forecasts can align the forecasts. The BTF ratio is applied to adjust reorder points and economic order quantities for individual parts forecasts. This ensures inventory generation matches the overall sales forecast. The author provides an example of how to calculate and apply the BTF ratio to reconcile differences between a sample micro inventory forecast of $2,033.93 and a macro sales forecast of $3,000.

1. Micro to Macro Forecasting:
How to tie the Micro Forecast to the Sales Forecast.
1
Everycompany or major divisioninacompanyhasa salesforecast. Mr. D callsthe salesforecastthe
macro-forecast. SundstrandCustomerService hadasalesforecastforits’service partsbusiness - the
business Mr.D’s planningsystemmanaged.
However,inadditiontothe macro-forecast,there isasecondforecast forthe spare parts business. Mr.
D callsit the micro-forecast. The micro-forecastis the currentlevel of inventorygenerationexpressedin
dollars. It isthe sum total of the dollarvalue of all the individual partsforecasts. If the twoforecasts
are verydifferent fromeachotherthere’sgoingtobe trouble.
For example, considerabusiness withfiveitems.
Part Number
Next Year
Forecst Qty Sell Price
Extended
Value
PN1 100 10.99 1,099.00
PN2 33 5.40 178.20
PN3 2 142.99 285.98
PN4 242 1.00 242.00
PN5 75 3.05 228.75
2,033.93
Table 1 Micro-Forecast
The micro-forecastforthis business is$2,033.93. Left alone,the inventoryplanningsystemwill
generate inventorytosupportthatamountof sales. If the sales forecastis higherthanthe micro-
forecastthenthe planningsystemwill notgenerate partsata rate highenoughtosupportsales.This
will resultin poorservice andsalesshortfalls. If the salesforecastinlowerthanthe micro-forecastthen
inventorylevels willincrease. Of course,itisalwaysassumedthatthe salesforecastisaccurate. Were it
not assumedtobe accurate thenit wouldbe foolishtouse it.
Mr. D, beingastudentof statistics,knew how toalignthe two forecasts.
Mr. D knew frombasic statisticsthatif X isa random variable and “a” is a constantthen:
Xbar(aX) = a * Xbar(X) and
Sigma(aX) = a * Sigma(X)
It follows thenthatthe ratioof the macro forecasttomicro forecastcan be calculated. That ratiocan
thenbe applied tothe forecastforeach item - therebymakingthe micro-forecastequaltothe macro-
forecast. The standard deviationandthe average of the new forecastcanbe calculatedfromthe old
forecastperthe equationsabove. Thisleadstoa change inthe ROP& EOQ foreach item, and presto
changeo,the inventorygenerationisnow inline withthe salesforecast.
Mr. D callsthisratiothe businesstrendfactor(BTF). Applyingthisratio willimpactthe ROPsandEOQs
of all items,therebygeneratinginventoryinaccordance withthe salesforecast. Simplyput,if the sales

2. Micro to Macro Forecasting:
How to tie the Micro Forecast to the Sales Forecast.
2
dollarsare forecastto double nextyearthenthe simple assumptionis thateverypartwill sell double
lastyear’ssalesquantity.
To work through an example of howtoapplythe BTF,assume a businesswith the five itemsas was
showninTable 1. If the salesforecastforthe nextyearis$3000 and the micro-forecastis$2034 then
the BTF is calculatedas3000/2034 which is1.47. To getthe level of inventorygeneration uptothe
level neededtosupporta$3000 saleslevel we multiplythe forecastforeachitemby1.47. Table 2
showsthe detailsforthe five items.
The micro-forecastisusually recalculatedeachmonth. Inaddition,the macro-forecastmaybe
recalculatedeachmonth,sothe BTFs couldchange monthly.
Part Number
Next Year
Forecst Qty Sell Price
Extended
Value
Lead
time
(months)
Monthly
Forecast
(xbar) Sigma
Service
Level
Basic
ROP
BTF Adj.
ROP
PN1 100 10.99 1,099.00 3 8.3 6.4 95.00% 44 64
PN2 33 5.40 178.20 2 2.8 2.1 90.00% 10 14
PN3 2 142.99 285.98 5 0.2 0.1 70.00% 1 2
PN4 242 1.00 242.00 1 20.2 15.5 93.00% 44 64
PN5 75 3.05 228.75 1 6.3 4.8 92.00% 14 20
2,033.93
Sales
Forecast 3,000.00
BTF 1.47
Table 2 Applying the BTF
Mr. D feltvery comfortable usingthismethod. The nature of hisbusiness lentitself tothisprocess.
Sundstrand’sproductswere notconsumergoodsandtheywere notsubjecttomarketingwhims.
Sundstrandrarelydidanysalespromotionsordiscounting. Consumptionof spare partswasa function
of unitreliabilityandfleetflyinghours,those twofactorschangedveryslowly,usually.
In the early1980s the CustomerService organizationcreatedagroupwhose jobwasto forecastsales
for commercial spares parts. Mostly,theywere master’slevel economicsandstatisticsguys andladies.
Theyproduceda five yearforecast. Itproved to be veryaccurate inthe firstandsecondyears. This
salesforecastwasvery granular,inthat it wasoftendownto the specificendproductlevel–
“applications”astheywere know atSundstrand. For example,the ramair turbine use onthe Boeing
767 airplane wasapplication“767RAT”.
Sometimes,the granularitywaslimited. Anexampleof this limitedgranularity wasamacro-forecastline
called“OldPumps”.Thisforecastline includedabouttwentydifferentapplications,whichwerepumps
usedon several typesof engines. These pumpswere designedand soldpriortothe moderndayera of

3. Micro to Macro Forecasting:
How to tie the Micro Forecast to the Sales Forecast.
3
computersand therefore lackedgooddataoninstallations. The lack of goodinstallation datalimited
thisgranularityto that aggregatedlevel called “OldPumps”ratherthanthe twenty individual
applications.
SometimesMr.D had to undosome of the granularity. For example,there were fourlinesof sales
forecastforthe four different ConstantSpeedDrives thatwere used onthe 707, 727, DC8, andDC9
aircraft. Mr. D knewthatthese units,exceptfortheirhousings andinputshafts,usedthe same internal
parts. The salesforecastwasgranular at the applicationlevel,butbecause of thisdesigncommonality
Mr. D reducedthatgranularityby combiningthe fourlinesof salesforecastintoaforecast family he
called“Bo60”.
Let’sget to the rat killing,andtalksome detail onhow Mr.D appliedBTF at Sundstrand.
First,everyspare itemsoldbySundstrandhadup to 30 applicationcodesassociatedwithit. These
applicationcodes indicatedthe endproduct(s)onwhichanitemwasused. For example, foranitem
usedina 707 constantspeeddrive, there couldbe fourcodes:707CSD, 727CSD, DC9CSD, DC8CSD – due
to the commonalityof design. Second,foreachcustomerthere wasa listof aircraftthey operated:707,
727, 737, etc. Whena customerorderedan item,the computersystemcomparedthesetwolistsand
foundthe firstmatch. For example,if acustomeronlyflew the DC9,thenthe applicationcode would
match and getassignedas“DC9CSD”. That applicationcode wasthenassignedtothe sales order,andit
was thatapplicationcode thatwas usedbythe salesforecastinggroup asthe basisof determining
granularity.
At the micro-forecastlevel,Mr.D usedthe firstapplicationcode foran itemas the start of his
granularity. (Justasa note,there wasa side process thatanalyzedsales dataandre-arrangedthe
item’sapplicationcodesin orderfromhighesttolowestsales.) There wasa cross reference table
createdand usedbyMr. D that definedthe relationshipof applicationcodestoforecastfamily(e.g.
727CSD  Bo60).
Here’sthe processusedbyMr. D.
1. Forecastdemandbyitem- the monthlypartsforecastingprocess.
2. Match eachitemto itsfirstapplication,extend$,andsum thismicro-forecastby
application.
3. Match application toforecastfamily,summicro-forecastby forecastfamily.
4. Match salesforecast,byapplication,toforecastfamily,sumsalesforecastbyfamily.
5. Match salesforecast andmicro-forecastbyfamily,calculate BTF foreachforecastfamily.
6. Reviewand approve forecastfamily BTFs, adjustwhere necessary.
7. Match BTF by forecastfamilytoapplicationcodes –reverse of step3.
8. Match BTF by applicationtoitem –reverse of step2.
9. ApplyBTFat itemlevel toadjustROP &EOQ.
10. QED

4. Micro to Macro Forecasting:
How to tie the Micro Forecast to the Sales Forecast.
4
There were three scenariosthatmade the BTF a valuable process toMr. D.
1. A significantchange inbusinessyearoveryear. The penultimate example of this is9/11 when
the businessdropped 40% inone day. In fact, on 9/12 the entire worldwide727 aircraft fleet
was groundedandneverflew again. (Inthatcase, Mr. D manuallysetthe BTFto zeroon the
unique parts usedonthe 727, so thatall inventorygenerationwouldstop.) Inhissix lustrums
withSundstrand,Mr. D sawat leastthree majorrecessions. The BTFprocesshelpedkeep
inventoryinline goingintothose recessions,andalsocomingoutof them.
2. Whena product experiencesanabruptpopulationshift. I.e. whenthe fleetsize of the 767
doubledyearoveryearforthe firstfive years,due tonew aircraft deliveries.
3. Specificbusinessdecisionsonproduct support. AswhenSundstrandabandoned its’ catalog
supportof some veryoldproducts,or soldoff some of itsproducts. In these situationsthe BTF
was setto zero;so the ROPswentto zero, therefore nomore inventorywasstockedtosupport
those products.
Unfortunately,the CustomerService salesforecastinggroupwas ultimately dissolved.The salesforecast
drove budgets,manpower,andthe like. Backthen,the CustomerService organizationwasnotatrue
P&L center,sothe accountingof salesof spare parts flowedbackintoothergroups. Thisimpactedthe
othergroups operations,andtheirVice presidents’ bonus,sothe situationwasalwayshighlypolitically
charged. Ultimately,the Presidentof the company became tiredof the infightingbetween the
CustomerService forecastinggroupandthese otherorganizations,andhe orderedthatthe forecasting
groupbe dissolved. Soadios tothe people whoactuallymade anaccurate forecast.
The forecastingresponsibilitywas thenassigned tosome otherpoorschmuck. He had no trainingor
skillsinforecasting. Hisforecasthadonlyone line - forthe sumof all spare parts sales. The lack of
granularitywasa bigproblem.
Afterthe salesforecastinggroupwasdissolvedMr.D continuedwiththe BTFprocess. As a
replacementforthe “late”forecastgroup Mr. D convenedagroup of customerservice persons. They
metquarterly toreviewthe “sales”situation. The groupwouldthencome toa consensuson whatthe
BTFs shouldbe foreach forecastfamily. ThisrequiredMr.D toanalyze a lotmore data andto produce a
numberof charts that were to be usedinthat groupprocess. Essentially,Mr.D was the shadow
forecastinggroup.
It isunfortunate that if no salesforecastisavailable itthenbecomesthe problemof the inventory
managerto estimate the BTFs. It’sa matterof self preservation. Goodly estimatedBTFswill help
generate the correctlevel of inventory. Sales goalswill be met,inventorywillbe low,andeveryonewill
be happy.
Inventorymanagersshouldnotexpectanypraise orotherconsiderationforthis.
Well there itis:one more tasty entrée inMr. D’s smorgasbordof ideas. Take whatyou want,andleave
the rest.

5. Micro to Macro Forecasting:
How to tie the Micro Forecast to the Sales Forecast.
5
Contact Mr. D at MisterD@windstream.net