OUR COMPANY Group presentation 30th August 2011 A.Safari – J-P.Giraud M.Ledieu – G.Poirrotte 30th August 2011 1

Outline of the presentation Transportation costs determination 2) Inventory estimation 3) Initiatives propositions and assessment Key hypotheses: Assemble the components at the stores Full truckloads: 30,000 lbs/truck load 2

Transportation costs determination For each component (CPUs, TVs & Monitors, Consoles): Weight of items that needs to be transported per year # Trucks needed for that purpose Cost of shipping components to the stores (#items sold /day /store) x (#stores) x (#days /year) x (weight /item) Int(…/truck load) (+ 1) Round travel: x2 … x (av. distance between plant and a given store) x (tr. cost/mile) Total: $ 869,569 3

Inventory estimation Total: $ 2,148,740 4 Green Bay: $ 900,000 Pipeline inventory: :Little’s Law: L = λ x W λ = (#components sold /day /store) x (#stores) W = (av. distance between plant and a given store) x (distance/ day) L = # components in the pipeline -> value Plants inventories: Total: $ 2,148,740 Green Bay: $ 900,000 Indianapolis: $ 600,000 Denver: $ 50,000 30000 lbs (maximum inventory) number of corresponding items Price corresponding /2 to obtain the average inventory 4

(Invent. Green Bay + Invent. Indianapolis + Invent. Denver)*100 Inventory estimation Inventory at stores: (Invent. Green Bay + Invent. Indianapolis + Invent. Denver)*100 Total: $ 155,000,000 I.C.C 17.99% Inventory: $ 158,698,740 Inventory carrying cost: $ 28,543,650 Total Transportation costs: $ 869,569 5

Initiatives propositions and assessment WE NEED TO FIND A TRADE-OFF! To reduce the inventory carrying costs → reduce the inventory → reduce the loaded weight in each truck → but the transportation costs will rise WE NEED TO FIND A TRADE-OFF! Determine the quantity ω to load in each truck to do so Costs ($) Weight/truck (lbs) 6

Initiatives propositions and assessment Additional advantages: Smaller trucks: cheaper to borrow (or to buy), faster (decrease the time in the pipeline and thus the inventory) and fuel consumption decreases (decrease of transportation costs) ω ≈5250 lbs We can go further and calculate ω to optimise the expenses for each components: For exemple, the console is cheaper than the other items and is heavier, so it has a low impact on the inventory and thus its carrying costs, so we can privilegiate reducing the transportation costs by loading more the trucks. ω console > ω On the contrary: ω Tvs and monitors < ω 7

Initiatives propositions and assessment We can also deliver items more frequently to the shops that are the nearest to the plant, with very low quantity (as the distance is short, less transportation costs -> focus on reducing the inventory by reducing the truckloads) We can cut transportation costs loading 1 truck with ωTVs+ ωCPUs (1 truck loaded in Green Bay then Indianapolis) We have also to load trucks for several shops (special itineraries) because a full-load is ~3.5*ω 8