Warehouse Management

INVENTORY FORECASTING: ISSUES AND CHALLENGES GROUP 2 MUHAMMAD SALAHAFIZ BIN ZAKARIA MOHAMAD NASIR BIN SOH ITMAM BIN AZIZ NOR SYAIRAH BINTI MOHAMED NUR NAJLA AKMA BINTI AZMI JAMALIAH BINTI MOHAMD SITI ASIAH BINTI IBRAHIM AINA SYAHIRAH BINTI MOHAMAD SOLEH NUR RUQSHANA BINTI HABIBUR REHMAN

introduction In most business contexts, forecasts are needed to support resource allocation decisions. More accurate forecasts lead to better resource allocation and thus improved financial performance, particularly by reducing the amount of inventory that must be carried. The direct relationship that exists between forecasting and inventory management is why this course will address both key supply chain concepts together. Inventory management may be the most important “lever” in the supply chain in its overall effect on corporate profitability.

Inventory used to be regarded as an asset not as a cost, but now, the technical challenge is to identify target stock levels for your products based on numerous and moving sources of information, such as; Customer expectations Sources of potential supply Sources of potential demand Supplier lead times Available budget

Important of inventory forecasting It records forecast errors to enable management to monitor and continually minimize those errors to acceptable corporate policy settings. The system automatically recognizes seasonal variations and accommodates those variations. System is better able to predict demand it will facilitate factory scheduling. Important to forecast inventory by an accurate demand prediction. Inventory forecasting enables to produce forecasts based on sales history, and provides the tools to measure the quality of forecasts.

Issues of inventory forecasting 1). Forecasting adjustment  Forecasting??  Forecasting adjustment??  Cut the forecast so that the system uses up the excess inventory.  Disconnects inventory planning from customer, and puts customer satisfaction by risking the ability to fill orders

2). Forecasting accuracy  Forecasting accuracy??  Predicted and the actual demand for a certain period generally differ  Example is inaccurate quantity

3). UNCERTAINTY 4). INCREASE OF CUSTOMER REQUIREMEN T Unpredictable economic and socio- political environment Customer needs changes from time to time.

5). SHORT SELLING SEASON 6). LACK OF HISTORICAL DATA. Past-periods data, used usually as a basis for forecasting the future data or trends.

What is Historical Data LACK OF HISTORICAL DATA AND SHORT SELLING DATA Past-periods data, used usually as a basis for forecasting the future data or trends.

How useful of Historical Data to the warehouse 1) Better decision-making 2) Data quality and consistency

What is short selling season? short selling season are characterized by the substantial losses associated with those merchandise items which are unsold at the end of a season.

How useful of short selling season to the warehouse Requires efficient allocation More responsive replenishment

TECHNIQUE OF FORECASTING THE INVENTORY SALES FORECASTING Qualitative method Quantitative method

QUALITATIVE METHOD EXECUTIVE OPINIONS This is a method by which the relevant opinions of experts are taken, combined and averaged. These opinions could be taken on an individual basis or there could be a brain storming group session in which all members participate in generating new ideas that can later be evaluated for their feasibility and profitability. DELPHI METHOD A panel of experts is given a situation and asked to make initial predictions, on the basis of a prescribed questionnaire, these experts develop written opinions. These responses are analyzed and summarized and submitted back to the panel for further considerations.. OPINIONS OF THE SALES PERSON The sales people being closer to consumers can estimate future sales in their own territories, more accurately. Based on these and the opinions of sales managers, reasonable trends of the future sales can be calculated. CUSTOMERS’ PERCEPTIONS This method involves a survey of the customers as to their future needs. This method is especially useful where the industry serves a limited market. Based on the future needs of the customers a general overall forecast for the demand can be made.

Quantitative method TRENDS Trends reflect changes in population levels,technology and living standards. SEASONAL variation that repeat itself at fixed interval. CYCLICAL requires many years of data to determine its repetitiveness on unusual circumstance. 1-Time series model Trends Seasonal Cyclical factor that influence the demand data.

CAUSAL METHOD  2-casual model cause for demand and its relation to other viriables

CONCLUSION A forecast has to be monitored to determine whether it is performing in a satisfactory manner, if it is not then the method, assumptions and validity of the data should be re-examine, and so on; should modify as needed; and should prepare a revised forecast. Inventory forecasting is not only important to help companies maintain inventory low, but it also helps to adjust production schedules, optimize investments, and helps to fix a product’s price.

Q & A