APEXTM

APEX™ MARKET FORECASTING

Introduction

With unprecedented accuracy, CEO’s, marketers and program managers now have the power to:

  • Forecast specific market or product marketing performance
  • Identify and anticipate immeasurable or unobservable variables that affect sales and demand for products and/or services (e.g., expectations of market participants)
  • Forecast balance sheet results, including:
    • Return on Investment (ROI)
    • Return on Assets (ROA)
    • Net Profit (as a percentage of sales)
    • Utilize any combination of marketing mix and external variables in classic "what-if" scenario modeling to accurately forecast outcomes
    • Predict new product marketing performance
    • Simulate test marketing

Following more than 13 years of research, testing and application to various product and service environments, APEX™ offers leading edge market forecasting and performance prediction. APEX™ – connoting the “highest point” of possible return on marketing investment – is the name we use to describe a proprietary marketing analysis, optimization and forecasting technology that delivers unparalleled power and accuracy to 21st Century marketing models. The acronym is derived from this tool’s underlying technology, Adaptive Prediction Estimation and Control (“X”).

APEX allows an executive to use the modeling tool to reach “apex” (or peak) company performance by optimizing all variables necessary to achieve maximum profit and marketing objectives.

This technology combines the latest market forecasting techniques and assessment technology with the leading edge of state space engineering science to deliver powerful improvement to marketing models. APEX technology allows marketers to quantify vital marketing variables which cannot be directly measured. The result is improved understanding of marketplace dynamics, forecasting accuracy, and the ability to optimize controllable variables to achieve maximum return on marketing investment.

Background Brief

After several years research and model development, APEX technology was first deployed in 1993 by Dr. Rod Freed, who currently serves as Chairman of the Department of Economics and member of the Department of Mathematics at California State University, Dominguez Hills. A widely published author and speaker at national mathematics and economics forums, Dr. Freed combined his doctorate degrees in math and economics with a “hobby horse” love of engineering (inherited from his father, a professional engineer) to discover and apply ground-breaking approaches to market forecasting and analysis.

APEX has been applied to marketplaces as complex as those served by IBM, and as variable as produce commodities with equal success. Currently, one form of the APEX model is being considered by the USDA for use as a reference standard for quantifying marketing effectiveness and performance evaluation by federal marketing orders across the country.
In the early years, some of the APEX technology description was published in academic briefs for peer review. This documentation was thorough enough to support results of one series of APEX analyses to be used in a federal court case. However, as effectiveness became proven, subsequent description and detail has remained confidential and will not be disclosed further (except as may be necessary for validation, and then only under strict confidentiality and non-disclosure agreements).

Marketing Applications

Techniques employed in APEX models offer significant advantages over the forecasting techniques usually used in the business world, which include Linear and Non-Linear Regression, Analysis of Variance, Discriminant Analysis, Canonical Correlation, Principal Components, Factor Analysis, and traditional economic forecasting, market prediction and estimating methods. APEX forecasting techniques have been effectively applied in the following areas:

MARKETING PLAN OPTIMIZATION

APEX models determine the optimal marketing mix needed to achieve specific marketing goals. Marketing optimization through APEX can evaluate any "what-if" scenario desired, incorporating internal or external variations of the total product or service environment. As current, real marketing data flows in, the model design allows for continuous updating to account for evolving external and internal variables and to maintain long-term forecasting accuracy.

TARGET OPTIMIZATION,
POSITIONING OPTIMIZATION,
PRODUCT/SERVICE OPTIMIZATION

APEX will identify optimum levels of marketing (line item) focus and budget for individual key variables to generate desired purchase behavior. Resulting forecasts offer exceptional accuracy, often within a range of 1%-1.5% of actual performance.

ENVIRONMENTAL ANALYSIS

APEX modeling and forecasting techniques offer accurate assessment of various observable and unobservable or immeasurable factors (e.g., buyer expectations, market psychology, etc.), including evaluation of both internal and external variables.

PRICING OPTIMIZATION

APEX modeling techniques provide thorough price elasticity analysis, testing pricing levels in combination with all other variables to suggest the optimum price in relation to marketing budget and mix. This allows marketers opportunity to deliver maximum profitability against specific objectives.

NEW PRODUCT MARKETING OPPORTUNITIES

The APEX model can be adapted to predict the likely purchase response for a new product or service – in spite of having no sales track record – based on sophisticated market evaluation techniques.

SIMULATED TEST MARKETING

APEX techniques offer low cost simulated test marketing with immediate results, providing similar quality of projected results similar in quality to those that would otherwise have to be drawn from actual, more expensive test market campaigns. This application can offer significant competitive advantages through cost and time savings and a supplier's ability to keep marketing intentions concealed.

APEX Functions Detailed

APEX analyzes and evaluates variables related to product or service market performance.
Once an APEX model is constructed using a company’s or product’s environmental variables, the model identifies the impact and relative importance of each variable – including those which cannot be directly observed or measured. The model tests the value and relative importance of each resource related to a product/service mix, and suggests the optimum marketing mix to achieve specific objectives. After performing its analysis of various known and unknown variables, APEX can predict probable outcomes of any combination of variables utilized in a strategic or marketing plan. These techniques offer an executive unlimited capability to test or anticipate the outcome of any marketing course proposed.
APEX can use balance sheet targets set by management to identify optimum arrangement of marketing mix variables.

If a company has a specific balance sheet objective (such as a Return on Assets [ROA] ratio), APEX will suggest an optimum mix of variables under possible macro-economic or competitive scenarios to achieve those specific objectives. In addition, APEX models offer the relative probability of occurrence for any scenario. For example, if a company wants to achieve a 10 percent ROA, APEX might suggest an optimum strategy and marketing mix which offers a 98 percent probability of achievement. Targeting is fully scalable along a probability curve. For example, if a company wanted to achieve a 30 percent ROA, APEX will suggest the best possible arrangement of variables to achieve this objective while noting that even the best combination of variables might have only a 15 percent probability of achievement versus the 98 percent probability to achieve a 10 percent ROA. An executive can therefore choose an appropriate level of risk/reward to achieve given targets.
APEX recognizes and forecasts the law of diminishing returns.

The model recognizes the limits inherent in a particular marketing environment and will identify limits to the revenue increase possible through each variable. For example, if the model determines that within an optimum marketing mix each advertising dollar spent generates $4.32 in increased revenue, APEX can also show how additional increases in the advertising investment will subsequently generate less revenue (e.g., $3.00, then $2.00, then less than $1.00 in additional revenue as advertising spending rises). Additional increases would reflect further declines in revenue-generating value. The cost/benefit analysis of any variable can be tracked to any spending level. Unlimited evaluations can be conducted testing the limits of various marketing mix options.

Results to date demonstrate the value of APEX as a marketing planning and prediction tool. No limitations to potential applications have yet appeared as the model's value to a broad range of industries and company sizes is being demonstrated. The effectiveness and results of APEX modeling to date are described briefly below.

Marketing and Missile Guidance – How APEX Works

The distinctive techniques employed in APEX modeling have been utilized over the past 40 years with great success by aerospace engineers in aircraft and missile guidance systems. In addition, the APEX modeling technology has been applied by electrical engineers to filter “noise” out of complicated electromagnetic radiation analysis, as well as to design controllers for robots and sophisticated prosthetic devices.

Until now, these techniques have had few applications in marketing, management, and economics – mainly because marketing executives and managers do not often communicate with mathematicians and engineers. Dr. Freed, however, has bridged this gap with a modeling technique that offers a true break-through in applied information science.
Because the complexity and sophistication of APEX models can be difficult to grasp in a marketing or management context, a simplistic review of missile guidance applications might aid in understanding the model's marketing application logic:

Marketing, Management and Missiles Seek to Hit Targets

As demonstrated in the Gulf wars, a Cruise missile targeted to hit a building in Baghdad and launched from its mother ship over 1000 miles away had only partial “understanding” of the forces it would encounter along its intended flight path. However, it was equipped with the resources needed to reach its target and accomplish its mission, including: fuel, a flight plan and its “APEX-type” missile guidance system.

The missile's program anticipated most of what could be expected en route to its target: gravity, atmospheric resistance, curvature of the earth, and so on. However, wind could prove to be a very significant “environmental variable” which had to be incorporated into the missile's guidance on a constant basis – even though the missile had no way of measuring wind speed or direction. It could only detect the wind's effect, i.e., course deviation, or how some group of variables was affecting its ability to accomplish its mission of reaching its desired target.

The missile relied on its APEX-type guidance system to tell it that something was having an effect on its mission. By measuring progress against its course, the missile discovered if this “something” was affecting its objective (reaching its goal/target) and by how much. It then incorporated this “learning” into current and continuing corrections needed to conclude its mission. The missile adjusted its strategy (long-term trajectory) or tactics (short-term fin and rudder adjustments) in response to its “environment” or “situation” – hundreds or thousands of times per second.

As a result of its remarkable market-type intelligence system, the Cruise missile can travel hundreds of miles only a few feet off the ground, dodging hills, mountains, structures or other obstacles while it measures and anticipates the effect of some forces it cannot see or otherwise observe, and adjusts its execution to accomplish its mission: hitting a target within inches of center.

APEX uses the same analytic logic for assessing market and product internal and external environments – especially those which cannot be directly measured – as it zeros in on specific marketing and management objectives. Application to marketing environments represents a logical and rational innovation of this engineering principle to the world of marketing.

Recent Examples of the Model's Effectiveness

  • Faced with devastating red ink, IBM used APEX modeling during 1993-94 to optimize the $500 million business of its Personal Systems Solutions/Western Division group. Using the strategy and tactics prescribed by the model, the PSS group increased revenues by 17% as the rest of IBM continued to lose money. Only a massive reorganization resulting in thousands of lay-offs interrupted plans to roll out and apply APEX to the entire personal computer group of IBM.
  • Since 1993, APEX has been used to create a crop return forecasting and marketing optimization model for California’s growers of peaches, plums and nectarines, represented by the California Tree Fruit Agreement. The model has correctly predicted actual market returns by applying its techniques to data on crop size, price and marketing mix, as well as to data on behavior of consumers, retailers and wholesalers and the national economy. The model has forecast crop returns within 1.5% of actual per month, in spite of dramatic price swings over 12-month periods.
  • In Los Angeles' “South Bay” region, it is impractical to try to create a retail price index or an index of quantity of goods sold by retailers. However, APEX modeling produced an accurate price index and quantity index by applying its techniques to the retail sales data which is available for Los Angeles' South Bay.
    Result: APEX identified the unobservable factors and accurately forecast (+/- 1.5% per month) economic performance for the South Bay area.
  • An APEX model created an index of investor expectations. This test model has proved highly predictive by applying its techniques to data on investors' observed behavior, along with data on technical factors, market fundamentals, and other economic data to predict investor behavior under various conditions. Application of APEX modeling in the equities marketplace is continuing.
  • In addition, APEX models have been used to:
    • Construct a portfolio choice model which optimizes investment groupings (stocks, bonds, etc.) to achieve targeted rates of return
    • Develop a financial model which a firm can use to simultaneously control profit (as a proportion of sales), return on assets, and return on equity
    • Predict regional macroeconomic performance of Los Angeles' South Bay.
      Possible applications seem vast at this point and the model is currently being applied to a wide range of goods and services providers.

 
 


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