METHOD: After a short briefing the training group is divided into several teams of four or five participants. These consider the problem facing them and then use their computer to progress through a business process. Each raise different issues that must be discussed. Teams are free to do the analyses that they consider necessary and combine these with subjective views.

The data is chosen so that the "right" answer for one set will be wrong for another. Further, these simulations serve to complement traditional lectures. By using the computer to do the calculations, they ensure that participants make effective use of practice time.

The simulations may be used with any number of teams.

AVAILABILITY: These simulations are only available fully tutored.

Sales Forecasting

Participants prepare a medium term forecast based on the time-series analysis of past sales for several representative products. The analysis familiarises them with the statistical concepts, practicalities and the method's strengths and weaknesses. So, this exercise is an ideal introduction to medium term forecasting and basic statistical concepts.

The simulation is provided with a database of sales history that can be added to and changed.

DURATION: About three hours. This duration allows the simulations to fit into most course timetables.

PROCESS: Participants are taken through a medium-term forecasting cycle consisting of:

Data Cleansing
Decomposition of History
Trend Analysis
Seasonality Analysis
Residual Analysis
Sales Projection

leading to:

Actual Sales (where the next year's sales are simulated to be commented on)

TECHNIQUES USED: During the simulation participants' investigate the implications of using:

Measures of Average and Spread
The Time Series Model
Moving Annual Totals
Simple Regression & Correlation
Analysis of Erraticness
Trend Projection Models
Band Budgeting

KEY LEARNING

ANALYSIS OF SALES DATA

Participants are introduced to a general analysis of sales data covering forecasting methods (objective and subjective), types of forecast (short, medium and long term), data patterns (repeating, assessable and identifiable), stages in analysis (model development, data gathering, data cleansing, analysis and projection) and the sources of data (company sales and demand data, market and economic statistics and market event diary).

TIME SERIES ANALYSIS

Participants are introduced to Time-Series models (additive and multiplicative), their components (cycle, trend, seasonal and residual) and analysis process (decomposition, analysis of components, determination of best fit and projection).

DATA CLEANSING

As the first stage of the analysis, participants, cleanse the data of known, repeating patterns (such as the effect of moveable feasts) and exceptional, non-repeating items (such as large export orders).

DECOMPOSITION

Next, participants use the simulator to separate the sales data into moving monthly averages and a stationary time-series.

TREND ANALYSIS & MODELS

The moving monthly averages are analysed using regression analysis to determine the trend component. Three curve types (linear, compound and saturating) are progressively fitted backwards over the trend line to determine which is the best curve to use and over what period. (The curve types cover the patterns encountered in the Product Life Cycle. By fitting backwards over the sales history, the analysis takes into account changing trend patterns.)

SEASONALITY

The stationary time-series is analysed to determine the repeating seasonal pattern.

RESIDUAL PATTERNS & ACCURACY

The seasonal pattern is removed from the stationary time-series to determine the residual component. In turn, this is analysed to identify unusually large or small residuals (outliers) and to determine the average spread and so the expected level of accuracy.

SALES PROJECTIONS

After determining the Time-Series Components (trend, seasonal and residual), participants must decide which to use to prepare several forecasts.

FORECAST & CONTROL

Besides preparing a simple projection, participants are able to prepare band forecasts on a period and cumulative basis and explore the implications in terms of budgetary control, inventory management, etc..

STATISTICAL METHODS

During the exercise, participants become familiar with a range of basic statistical concepts and measures. These include mean, standard deviation, variance, regression and correlation analysis. However, they will not be expected to manually calculate these measures. Rather they will understand the implications of their use.

Sales Analysis

SALES ANALYSIS involves analysing the sales records of several sales people. From this analysis and without subjective knowledge of the sales people, the participants must identify reasons for differences between sales people, product ranges and types of customers. The analysis exercise is an ideal introduction to those basic statistical techniques that can be used to investigate sales performance. However, although the focus is on analysing sales the scope is such that it provides an introduction to basic statistics.

The simulation is provided with a database of product data that can be added to and changed.

DURATION: About three hours. This duration allows the simulations to fit into most course timetables.

TECHNIQUES USED: During the simulation participants' investigate the implications of using:

Basic statistical measures of average (mean, median & mode)
Basic statistical measures of spread (variance & standard deviation)
Histograms
Scatter graphs
Correlation Analysis
Simple Regression Analysis
Pareto Analysis

KEY LEARNING

ORGANISING & ANALYSING DATA

Participants make use of a database of sa les records that consists of customer number, industry type, product group, sales person, previous, current and potential revenue, cost of sales, debtor value and calls made. From this data, they are able to select records, create data and perform statist ical analyses. For example, they may wish to analyse the results of individual sales people, calculate sales growth and compare these.

DEFINING REPORTS

When analysing the data the participants are able to define and create reports that highlight particular aspects of the data and present different viewpoints. For example one report might concentrate on the financial aspects of the simulation

DATA MODIFICATION

Participants must manipulate the basic data to create new data. For instance, they may wish to compute the rate of sales growth (from the current and potential revenue).

SELECTING GROUPS OF RECORDS

During the analysis, to answer questions about differences between sales people, industries, products etc. it is necessary to select groups of records based on data values. For instance, to investigate relative levels of activity, it might be necessary to select all sales people separately.

SUMMARISING DATA

As part of the analysis, it will be necessary to summarise either the data as a whole or as individual groups of data. For instance, it might be useful to compare the total revenue and profits earned by individual sales people. This analysis may be expanded on using basic statistical measures (such as mean and variance).

ANALYSING DATA

The data analysis for e ither the data as a whole or individual groups of data can be extended to include graphical analysis (using scatter graphs) and regression analysis. So, for instance, it might be useful to see how percentage gross profit might be affected by sales volume.

COMPARING DATA

As part of the analysis, it will be necessary to investigate the significance of differences between groups of data. For instance participants may wish to decide who are the best and worst sales people.

Inventory Policy

INVENTORY POLICY involves deciding appropriate stock levels, reorder points and quantities. After setting stock policy its effect and cost is evaluated.

The simulation is provided with a database of product data that can be added to and changed.

DURATION: About three hours. This duration allows the simulations to fit into most course timetables.

TECHNIQUES USED: During the simulation participants' investigate the implications of using

Economic Order Quantities (EOQ)
Pareto Analysis
ABC Classification

KEY LEARNING

INVENTORY COSTS & RISKS

This provides an overview of the types of inventory cost (holding, replenishment, shortages and management) and areas of risk (customer service, production disrup tion, liquidity and cash rationing) associated with inventory.

INVENTORY HOLDING COSTS

Participants identify and investigate the factors that affect the costs of holding inventory.

REPLENISHMENT COSTS

Participants identify and investigate the factors that affect the costs of replenishing inventory.

THE COST OF SHORTAGES

Participants identify and investigate the factors that affect the costs of inventory shortages.

INVENTORY MANAGEMENT COSTS

Participants identify and investigate the factors that affect the costs of managing inventory.

ECONOMIC ORDER QUANTITIES (EOQ)

Participants use the inventory holding and replenishment costs to decide economic order quantities.

EFFECT OF PATTERNS OF USE

Participants explore how patterns of use (demand growth, seasonality and erraticness of demand) affect replenishment and inventory costs.

INVENTORY BUFFERS

Participants use the inventory holding and shortage costs with replenishment and usage patterns to decide inventory buffers.

PARETO ANALYSIS

Participants rank the products in order of importance to the company so as to identify the twenty percent that are of major importance and the eighty percent that are of minor importance.

INVENTORY CLASSIFICATION

Participants can make use of the information derived from the products' usage patterns and the Pareto analysis to classify the inventory to facilitate inventory management and minimise costs.

SET UP & LEAD TIME REDUCTION

Participants explore how set up and lead-time reduction for key products can improve inventory levels and costs.

Prospector - winning profitable projects

Prospector is designed to allow business people from organisations that search for and then bid for business to explore the commercial and financial aspects of bidding. They search for bidding opportunities and then progress the bid through evaluation, tendering and negotiation to winning and delivering profitable business.

TARGET AUDIENCE: The simulation is aimed at sales, engineering and technical support people who are involved in the contract bidding process.

DURATION: About one day. This duration allows the simulations to fit into most course timetables.

PROCESS: Participants are taken through a bidding cycle consisting of:

Opportunity Search
Opportunity Qualification
Tendering
Negotiation

leading to:

Execution (where the actual outcomes of the projects won is simulated).

KEY LEARNING

COMMERCIAL ISSUES

The simulation focuses on winning business that is profitable rather than the management of the projects. Thus it explores, on an evolving basis, how to build a portfolio of projects that have the right financial and risk characteristics to meet the commercial needs decided by the participants and justified to the senior management (the trainer).

BIDDING CYCLE

The simulation takes the participants through a typical bidding cycle where they need to build their knowledge of the client, project and risks and select the best projects to move forward. Thus the participants explore a stage gate process. At the end of the simulation, participants should have won a portfolio of projects that offer the best opportunity to earn profit and represent the smallest risk. This will be tested at that time as project outcomes are simulated.

OPPORTUNITY SEARCH

This involves searching for business opportunities that are suitable in terms of size, urgency, client type etc. Participants must search for the business opportunities that match the business' needs and complement the current portfolio of projects.

QUALIFICATION

This involves obtaining more information and refining information about the most attractive projects - information that improves the knowledge of size, schedule, client and financial terms. Based on this information, partici pants must move the most attractive projects to the tendering stage.

TENDERING

Participants obtain information about the range of project size and can explore the impact of tender price on profitability and the likelihood of winning the bid. At the end of this stage, participants submit a bid that is either accepted (allowing them to move the project to the negotiation stage) or rejected (won by a virtual competitor ).

NEGOTIATION

The participants now must agree the project and payment schedule with the project so as to ensure that, together with the other projects in their portfolio, cash flow and work load are viable.

RISK IDENTIFICATION & AVOIDANCE

Participants explore he project and commercial risks associated with bidding for projects. Where project risks are derived from the project complexity and ambiguity and mitigated by both the company's and client's prior experience with similar projects, relationship development during the bidding process and bidding effort. Project risks cause project duration uncertainty and overruns. The commercial risks are derived from inappropriately low margins, project urgency, client competency & aggression, client credit rating and the project payment style.

FINANCIAL MEASURES

The simulation treats each project as a profit centre and so measures for it revenue, costs and profit margin. Also, participants must ensure that the cash flows of individual projects support each other and ensure the optimum use of available funds and survival risk is minimal. After the execution stage, the actual results are compared with budgeted results. And an accumulated profit statement is presented and, beside actual costs the cost of funding is shown.

(BUSINESS PRESENTATION)

Optionally, at the end of the simulation, teams can be asked for make a formal board presentation covering objectives, strategies, process, the outcome and learning.

© 1999 & 2005 Jeremy J. S. B. Hall
Most recent update: 05/05/06
Hall Marketing, Studio 11, Colman's Wharf,
45 Morris Road, London E14 6PA, ENGLAND
Phone & Fax +44 (0)20 7537 2982
E-mail jeremyhall@simulations.co.uk