The management team at EBBD wanted me to look deeper into the way EEBD utilizes forecasting methods, what other techniques are out there that could be available, and how they can improve their short term forecasting on an annual, quarterly, and monthly basis. They are also interested in long-term forecasting, i.e., two or three years. Lastly, they want to know how they can generate quarterly inflation forecasts.

Assumptions:

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1. In order to maintain a proper balance between company goals and customer expectations, we must assume EBBD managers are often required to provide better service with fewer resources. 2. EBBD’s approach in forecasting is not only a projection of future business but it is also a request or resources that will ensure a supply of a product. Assuming their monthly costs and operational budget reviews are productive, this process should provide desired results. 3. Assuming this environment is constant, the importance of effective forecasting is huge. When it is decided to place a determined amount of a product on a forecast, we expect both the resources and the products to be available. It is here where forecast accuracy becomes critical to ensure that expectations will be met with minimal fluctuations. 4. EBBD management often operates under conditions of risk and uncertainty and one of the most important tools to reduce risk in decision-making is forecasting. I will evaluate the level of efficiency of current forecasting method used in EBBD. 5. There is a difference between forecasting for an existing product line and for a new product. Critical evaluation will show if the proper forecasting tool is applied to each individual situation.

Evidence

Companies that are trying to improve themselves come to the realization that in order to reach operational excellence they must both satisfy their customers as well as manage their own resources properly. When forecasting is done effectively, distribution companies are able to meet the requirements of a demanding customer as well as meeting their own expectations and the expectations of their shareholders. I will highlight the information on the different forecasting methods currently used by EBBD and my feedback on their overall impact on the company.

Observation # 1. Current products forecasting method.

The EBBD Management Team meets once a month to review the monthly financial report. The output of these meeting results in a comparison of previous months’ forecasted volume. Based on this, forecasts for the next quarter will be updated as well the forecast for next year. This current forecasting technique is a “one tool fits all” approach applied to different requirements (short term-monthly, quarterly, and long term- annual). Short Term forecast requirement is different than long term forecast requirements. The technique being used here is trying to predict future requirements by “looking back”.

Current method of forecasting used by EBBD is a Quantitative Method. This method works well when historical data is available which constructs a forecasting model using available data. It is more fit for use in short-term forecast which is driven by a robust sales and operations planning process. Data for weekly/monthly demands can be compared to previous months versus current purchase orders and will provide a good idea of short-term forecast. The disadvantage of this method would be the lack of data, which in this case, is readily available.

Observation # 2. Lack of Long Term Forecasting method.

Based on the aforementioned I can deduct their current Quantitative Method alone cannot support long-term forecasting requirement. Long term forecasting falls on the premises of strategic approach, which is, by nature a more complex process. I don’t see a long term forecasting approach that takes in consideration any additional useful information such as future economic situations, projected changes in market segment, market share, inflation, social economic factors, and consumer behavior. As it currently stands, the sole application of quantitative methodology is not optimizing long term forecasting strategy.

Observation # 3. New product forecasting strategy.

Discussions are being carried out to add new products from current suppliers but there is no strategic forecast plan in place. The decision to add new products into current product lines is based on observations from what current and other suppliers (including competition) are introducing.

The development and introduction of a new product can be a risky venture. The first method of forecasting new product would be an historical review. If EBBD has introduced similar new products into similar markets in the past, these histories can often be good predictors of future outcomes. The problem is that there are no such records of new products past performance that could help define a sound, new product forecasting strategy. Given this premise, EBBD should study the histories of similar products introduced by competitors in the past, these histories can often be good predictors of future outcomes.

Observation # 4. Determining Inflation Factors.

Currently, there is no method to accurately determine inflation factors. Most of EBBD suppliers pass along their inflation costs to EBBD on a quarterly basis. The problem is that EBBD utilizes a “guesstimate” approach to this process when it comes to factoring their own. Even a modest rate of inflation can seriously erode purchasing power over time. I will expand on this subject on my “possible solutions” paragraph.

Possible Solutions

The following are potential solutions by using different methods to be applied to the observations found during my analysis.

* Short term forecasting method. As mentioned before, EBBD is utilizing a Quantitative forecasting method that includes historical data. A possible solution that would bring optimization to this short term forecasting approach would be the implementation of a “Time Series” forecasting method. The objective of the time series method is to discover the pattern in the past values of a product. Assuming that the historical pattern will continue, this method can be extrapolated into the future and use it to predict future values. This method is very useful when historical data patterns do not change. Complementing current EBBD sales forecast approach with with the Time Series Method would allow for a better forecast assessment since both methods can be assessed, results of their values added and utilize the resulting average as a forecasting indicator.

* Long Range Forecasting. Long term forecasting is used in strategic planning. Such decision must take into account numerous variables such as market opportunities, regional market conditions, consumer behavior, and consumer expenditure by region, even environmental factors. Currently there is not a long range forecasting method used by EBBD. For the long-range approach a possible solution would be the implementation of a Consensus Forecast (Adaptive Forecasting) methodology. This approach provides predictions for the future by combining together several forecasting methods, which have often been created using different methodologies. The argument in favor of this method is that individual forecasts may be subject to numerous behavioral biases, but combining independent forecasts together can minimize these.

Combining is seen as helping to improve forecast accuracy by reducing forecast errors of individual forecasts. I would recommend two forecasting methods under the consensus forecast umbrella. The first method is Qualitative- a method that is mainly based on professional opinions of experts, and can be further divided into other methods. The second method is called an econometric model. The econometric model is one of the tools economists use to forecast future developments in the economy. They measure past relationships among such variables as consumer behavior and spending, household income, tax rates, employment, socio-economic factors, regional economy, and other factors that can be tailored to the end state. This approach would provide EBBD with the proper tools for long range forecasting.

* New product forecasting strategy. Current strategy depends on what current suppliers and others (including competition) are doing. There is no forecasting plan. A possible solution for this situation would take a two-fold approach. First, employ a Qualitative forecasting method. Qualitative forecasting methodology works well for new products. These methods are used when historical data is scarce or not available at all. Qualitative methods would include: market research: panels, questionnaires, test markets, surveys, etc., product life-cycle analogy: forecasts based on life cycles of similar products, services, or processes, and expert judgment by management, sales force, or other knowledgeable persons.

* Determining Inflation factors. Currently EBBD estimates inflation factors. Forecasting the inflation rate is critical for financial planning for both EBBD and retailers. Without an accurate gauge of the rate of inflation EBBD will be unable to accurately forecast its current and future expenses. Inflation is a steady increase in the prices of goods and services usually measured in terms of a specific annual percentage. This decreases the purchasing power of currency by reducing the amount of goods or services EBBD can get for the same amount of money. Before EBBD can come up with a measurable tool for inflation it must first determine the causes.