Tuesday, February 14, 2012
Low Inventory Angers John Deere Customers
The readings of this focused on the 'Lean Manufacturing' concept implemented in different ways at Toyota, Starbucks and also in the non-manufacturing segment. Its successful implementation at Toyota encouraged many other manufacturers to mimic and taste success.
But I believe, it all depends on the organisation and its requirements. As we know by law, to every action there is equal and opposite reaction. Lean manufacturing influences on reducing the wastes within the supply chain and increase competency also makes the supply chain susceptible to any kind of unexpected events. The purpose behind having safety stocks in the inventory is to face a "rainy" day. It is true that the safety stock has the carrying cost and reducing the safety cost you can increase your working capital. In this way the company can become leaner. But the concern is, in case of an unplanned event you may incur greater costs than had you held the stock. This is analogues to the car or any kind of insurance. If I do not have an insurance policy in place, I will be saving my money. Until, one fine day I meet with a car accident and now I incur larger cost than had I invested in the insurance.
Few years ago Deere was converging on becoming a build-to-order company. That sustained prices and profit as by keeping smaller stocks on hand eases the amount of materials and working capital a company needs. But production cuts and the tightest inventories in the industry led to a shortage of Deere equipment as the farm economy was firming up around 2010. This was pushing the potential customers to the competitors.
Deere shrank its inventory 28% in the 12 months ended on Jan. 31 2010. As a percentage of sales reported in the year 2010, Deere's inventory was just 12.3%, the lowest among 15 farm and construction equipment makers, including Agco (AGCO) and Caterpillar (CAT).
This proves that lean management is not applicable always. It can be inferred Deere lacked inventory management with demand forecasting.