Inaccurate Demand Forecasts
Firstly, the demand forecast accuracy on which decisions were based was low. Customers at the time were placing the same order with several suppliers and closing the deal with the supplier that delivered the order first. As noted in the Cisco Systems Case Study, due to this practice, an order for 10,000 routers simulated demand for 30,000 machines. Cisco’s sales force failed to account for this artificially inflated demand and for the trend in reduced technology spending, which was a major catalyst for the losses realized in 2001. The company continued to order large quantities in advance on the basis of demand projections that did not materialize.
Communication Problems Across the Supply Chain
Secondly, Cisco’s supply chain experienced communication problems. The supply chain was structured as a pyramid, in the centre of which was Cisco. Since a large part of the operations were outsourced, each supplier dealt directly with its own suppliers, hindering communication across the entire supply chain. Additionally, since contract manufacturers produced the equipment and shipped directly to Cisco’s customers, Cisco lost view and full understanding of customers’ needs. It would appear changes in demand conditions were not communicated across the supply chain and mixed messages may have interfered with accurate demand forecasts.
The Term Paper on Supply Order Purchase Tender Materials
BUSINESS MARKETING (INDUSTRIAL MARKETING) OIL AND NATURAL GAS CORPORATION (ONGC) Submitted By: - PGP MS Marketing III Semester TABLE OF CONTENTS S. NO. TOPIC 1 Introduction 2 Purchase Procedure 3 Purchase Methods 4 Bidding System 5 Invitation of Tenders 6 Opening of Tenders 7 Cancellation/Re-Invitation of Tenders 8 Clauses in Tender Supply and Reorder 9 Purchase Powers INTRODUCTION q Work in the ...
Failure to Identify Ground Level Problems
Lastly, it would appear Cisco was not monitoring key metrics for early warning signs. Due to the inaccurate demand forecasts and lack of communication across the supply chain, Cisco had begun accumulating large inventories as of 2001. This issue could have been detected early had the company noticed that the inventory cycle rose from 53.9 days to 88.3 days. This issue was not present prior to 2001 as evidenced by Cisco’s income statement – no other years had Excess inventory charges, other than 2001, at which time Cisco had to write off $2.2 billion worth of inventory. Failure to monitor mid-tier performance did not allow the company the opportunity to
look for the root causes and address the issues in a timely manner.
Question 2:
There are several metrics that Cisco would benefit from tracking:
Top Tier:
Demand Forecast Accuracy – this metric is used to assess the overall health of the supply chain by measuring the difference between forecasted and actual demand. The formula is as follows: ,where At is the actual value and Ft is the forecast value. This metric would have alerted Cisco to potential problems; had the company investigated the root causes, they would have been able to proactively address the issue and accurately allocate resources. This would have also addressed build-up of excessive inventories. Perfect Order – this metric is used to assess the overall health of the supply chain by measuring how many orders are complete, accurate, on time and in perfect condition. Cisco needs to be aware if orders are not arriving at the customer’s premises on time. Had the orders arrived on time, then customers would not have had to place several orders with numerous suppliers to ensure that equipment arrives on time. This could have possible helped Cisco anticipate inflated demand. Mid Tier:
Inventory Total – this metric is used to diagnose issues within the supply chain. Increases in inventory totals are the result of excess in raw materials, work-in-process or finished goods. If Cisco were to use the inventory total metric, it would detect high levels of supplier raw material inventories, as well as increases in the finished goods inventory. Identifying increases in inventory also highlights poor demand visibility.
The Essay on Analysis of Two Commodity Markovian Inventory System with Lead Time
These systems unlike those dealing with single commodity, involve more complexities in the reordering procedures. In the modelling of such systems, initially models were proposed with independently established reorder points. But in situations where several products compete for common storage space or share the same transport facility or are procured from the same source, the above method ...
Ground Level:
WIP and FG Inventory – these metrics are used to correct issues. If inventory totals has helped management diagnose that a problem exists, a detailed investigation into WIP and FG inventory would help define the root cause – i.e. is the supplier carrying too much inventory because demand forecasts were not communicated back to them or is Cisco carrying too much FG inventory because of inaccurate demand forecasts.
Order Cycle Time – this metric is used to correct issues. Order Cycle Time measures the time that elapses between placing two consecutive orders. If Order Cycle Time is long, the company is carrying large inventories and is exposed to risk related to decrease in demand, as well as to high inventory carrying costs.
Perfect Order Detail – this metric is used to correct issues. Perfect Order Detail provides information on how many orders were within customer specifications and which specifications were not met (e.g. order entry, warehouse accuracy, delivery on time, shipping without damage, invoice accuracy).
With visibility into customer issues, the company can improve demand forecasts, along with its Perfect Order score. Going back to the previous example, had the company known that orders are not delivered within customer specifications, Cisco may have been able to predict that customers would place numerous orders to ensure that their demand is satisfied. Combined with high levels of inventory, the company could have determined that it is holding the wrong type of inventory.
