177 Wc r eo ausl de sycoous et ,vdeer cwr eaanstetsowboe rak ipnagr tc aopf iat apl r, oa jnedc tr et hdautciens- oi mr dpel er mr eel ni at bi ni lgi t tyr?a Id ti thi ionnka nl po lt a, nb nu it nt gh itsa xi so tnhoems iaeds rf oe ar l ai t yg l oo fb - al supply chain. The unfortunate truth is most companies want to implement this faster. Even contemplating adding generative AI. Laughing yet? bb ea cs ea dmoe nmt oh reeavsas ruima bpl tei,oonpot ifmi ni zi tai tailovna el unegsi ;nceos mr apna - nies did not adapt. • Environmental Impact. 72% of the environmen- tyaelt stuhpepr el yi sc hnaoi ne ai ms ypsaocltuitsi oonu tt os i dd er i vt heeneent wt eor rpkr iisne-, teroperability. (Each network is a self-serving enti - ty. As a result, there is no interoperability between Ariba and E2open or Elemica and GT Nexus/Infor. Today’s planned investment in network capabili- taise sa ifso cl ouws . a(rLeeas isnt hd ai gni t3a%l t roafnrsef sopr mo nadt ieonnt se hf faovr et st. )h i s • Increase in Bullwhip. The supply chain is a ci novme np tl eexd, inno1n9- l8i n0e, adre ms yos nt esmt r.aTt ehsetBh ue lilmw ph ai pc tgoa fmt eh,e bullwhip effect on the supply chain. ERP and APS an mo l po lgi yf yr tehpeo br tusl ltwh eh ibpuilml wphaicpt ,i my ept ancot apnl adn un si ne sg itte ac sh - a planning parameter. • Rise in Inventories. Across industries, we carry 2in8vemnotorerydays of inventory. Yet, only 15-20% of the is safety stock. Few companies measure at onrdy md ea cni as gi oenisn. -At rnadn, swi t hi ni l ve ecnotmo rpi ea sn ioers chyacvl ee ipnuvre- n - chased Multi-Enterprise Inventory Optimization tme cahnna go il no gg ieens .t eTrhper issoel us taifoent ydsetpolcoky mi n ev ne nt tf oo rc yu s e s o n , which, by definition, is less and less effective.
Table 4.2. Demand Planning Basics
Model Types
Engine Options
Demand Shaping
Locations Data
Attach-rate Forecasting Attribute- Based Forecasting
Price Management New Product Launch
Ship-to- Location
Orders
Bayesian
Shop From
Fourier
Shipments
Profile Planning
Channel Locations
Lewandowski Promotions
Channel Data
Item-based Planning Product- family Forecasting Causal Factor Forecasting
Holt-Winters Advertising
Weather
Product Positioning
Market Drivers
Poisson
Moving Average
Demand Drivers
Exponential Smoothing
Probabilistic
Event Data`
Economic Factors
Seasonal
Narrow AI
Government Subsidies
Generative AI
There is a fivefold impact. • Rise in Cost and Decrease in Planning Effec- tiveness. Over the past five years, the supply chain pe vl aennntihnoguhseaanddcso. uOnnte ocf opml apnanneyr si ngcrreewa s teod ht uh ne d r e d s , number of planners from 400 to 1300 post-COVID. I know. It defies logic. We are rewarding reactive behavior. • Decrease in Order Reliability. No company ao dn j ul esat de dt i smuep pv al yr icaht ai oi nn . pAl as nl enai ndgt iemn eg si nsehsi fbt ae sdeadn d
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