Sunday, September 15, 2013

How much to stock!

With the advent of the best production technologies many firms are successful in reducing their production costs to a great extent. The key factor of reducing the costs and to increase the profit margin is to cut down the operations cost incurred in the whole business transactions. One of the practices that have been widely adaptive is predictive modeling of the demand and matching the supply chain networks accordingly. 

Companies don’t generate revenue when the goods are stocked in the ware houses, thus maintaining a higher inventory turn ratio is very important for any firm. Accurate forecasts allow a business to position itself competitively, and advance notice gives the business time to implement new strategies. Consequently, effective long-term forecasting requires not just a finger on the pulse of current events but also deep knowledge on the merging trends in any industry. 

Even though forecasting is important, the process of effectively delivering the desired results to your customers is not limited to forecasting. It includes synchronizing supply and demand, increasing flexibility, and reducing variability. A good supply chain system is the one that enables a company to be more proactive to anticipated demand, and more reactive to unanticipated demand. There are various techniques that can be used for forecasting the demand and thereby generating the appropriate supply. Some of these techniques are; qualitative analysis, time series analysis, casual and simulation analysis.

Using multiple prediction models to simulate a single data set can provide accurate results. Long term forecasting is more difficult than short term forecasting therefore firms tend to maintain an inventory that would allow them to meet the unexpected demand. Finding the right balance between the two is very important. A firm has to ensure that there is no inventory accumulation over the period of time. Inventory buildup can be unprofitable for many businesses. For the products that have a shorter shelf life, high inventory turnover ratio is a must.

One important case that truly explains the importance of accurate forecasting and matching the demand with the supply is the trouble that CISCO faced around the year 2000-2001. In spite of being a key hardware manufacturer as the world may think, CISCO did not manufacture its own products. It outsourced the manufacturing of their products to various other vendors and focused more on the design aspect. The suppliers CISCO contacted with further had commodity suppliers. This long chain of information exchange and product manufacturing caused a significant problem for them.

According to the demand projections made by the CISCO’s ‘sales-force’, they ordered large quantities to lock-in supplies as the industry expected a boom and the resources would go scarce at that time.  They made long term contracts with their suppliers for long term availability of the products. The telecom industry then saw a major hit and the sales dropped. The predictive models that had formed the basis for all supply chain decisions made by the firm did not have the right inputs only to start with. The firm went through a major crisis at that time, in the third quarter of 2003 there sales dropped by 30%, they had to write of the inventory worth $2.2 billion and had to lay of 8,500 employees as the profit margin per employee had dropped down from $700,000 to $240,000. They lost on a lot of customers as they were not able to deliver the products on time. Their inventory turnover ratio increased from 54 days to 88 days.

Prateek Arora


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