Forecasting vendors in dutch-2003

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An overview of the vendors,developments and trends in the DutchForecasting/Demand Planning market

Forecasting/Demand Planning 2003


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Forecasting / Demand Planning 2003

An overview of the vendors, developments and trends in the Dutch Forecasting / Demand

Planning market

Cap Gemini Ernst & Young

B2B Supply Chain service line


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Cap Gemini Ernst & Young Netherlands, B2B Supply Chain service line

Forecasting / Demand Planning 2003

An overview of the vendors, developments and trends in the Dutch Forecasting /

Demand Planning market

Utrecht, December 2002

ir. R.J.G.M. Lenders MTD

drs. ing. L.F.A. van Zundert CPIM

Cap Gemini Ernst & Young

B2B Supply Chain service line


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Contents

1 Introduction 4

2 Profile of the forecasting / demand planning market space 52.1 Overview 5

2.2 CGE&Ys opinion 6

3 The differences per industry 8

3.1 Overview 8

4 Who are the dominant players on the Dutch forecasting / demand

planning market? 104.1 Overview 10

5 The most important developments in the last 3 years 125.1 Overview 12

6 The most important trends for the coming 3 years 156.1 Overview 15

6.2 CGE&Y opinion 17

7 Differentiators of forecasting / demand planning software vendors 197.1 Overview 19

8 Forecasting / demand planning functionality comparison 218.1 Overview 21

8.2 Forecasting algorithms and methods 22

8.3 Event and Promotion Management 248.4 New Product Introduction 25

8.5 Relationships between different SKUs 25

8.6 Forecast Accuracy Analysis 26

8.7 Other functionalities 26

9 Cap Gemini Ernst & Young Your partner in supply chain projects 289.1 Introduction 28

9.2 CGE&Y The premier partner in supply chain package selections 28

10 Participating forecasting / demand planning software vendors 29


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1 Introduction

This report contains an overview of the leading forecasting / demand Planning software vendors

in the Netherlands. It discusses the developments that have occurred in the last three years and

analyses the trends for the coming three years. It also analyses the use of forecasting / demand

planning tools in different industries and discusses the differentiators in the market.

Forecasting / demand planning tools are used to get a better visibility of the future sales pipeline.

They essentially can work in two different ways. Sales employees can either enter their personalsales forecast (f.e. for their products, customers or projects) on different levels of aggregation

while the forecasting / demand planning tool aggregates these forecasts on a company-wide level.

Also however forecasting / demand planning tools can, without manual intervention, generate

sales forecast projections based on historic demand levels. These automatic forecasting projec-

tions can be done by using multiple forecasting algorithms, which differ in their suitability, speed,

complexity and forecast accuracy for each particular type of demand (regular demand, spare part

demand, promotion demand, irregular demand etcetera). The more advanced forecasting tools

generally differ in the number of (advanced) forecasting algorithms they support.

We have only included specialized forecasting / demand planning software vendors and not the

more general ERP software vendors which also have functionality for forecasting / demandplanning (which is generally very simple).

This report is part of a series of reports published in 2002 / 2003 around different categories of

standard supply chain software packages. Reports have been published or are planned around the

following software categories:

1. Warehouse Management Systems (WMS)

2. Product Lifecycle Management (PLM)

3. Advanced Planning Systems (APS)

4. Inventory Optimisation Tools

5. Transport Management Systems (TMS)

6. Supplier Relationship Management (SRM)7. Manufacturing Execution Systems (MES)

8. Supply Chain Event Management (SCEM) / Visibility software

For this overview CGE&Y prepared a short questionnaire which was distributed to all forecasting

/ demand planning software vendors in the Dutch marketplace. The results from the overview

were consolidated and analyzed by professionals from CGE&Y. Also CGE&Y supply chain

professionals have provided their input, analysis and market views for this report.

Many thanks to the forecasting / demand planning software vendors who have participated in this

overview.


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2 Profile of the forecasting / demand planning market space

2.1 Overview

The Benelux market for forecasting / demand planning software is not very large since only about

65 people in total are working in the Netherlands in companies which deliver forecasting /

demand planning software. The largest software vendors in terms of the number of employees in

the Netherlands are Infolog and Scanmar.

Broader software vendors are SAP (which also delivers ERP software), Ross Systems (which

also delivers ERP software), Manugistics (which also delivers APS software), OM Partners

(which also delivers APS software) and JDA (which also delivers Retail software; JDA bought

the E3 company in 2001). Ross Systems has formed a partnership in 2002 with Prescient Systems

(a US APS software vendor) in which Ross Systems delivers the Prescient XEi solution as their

iRenaissance SCM solution.

In the table below the forecasting / demand planning software vendors are ranked according to

the number of employees in their Dutch organization.

Number of employees

Vendor Name Package Name NL EUR WW

Infolog Slim4 15 25 35

Scanmar PlanCaster 13 13 13

ATIM (Business Forecast Systems) Forecast Pro (Unlimited, XE) 8 8 8

Quadriceps Products VPS2000 7 7 7

Finmatica Mercia MerciaLincs 5 1.000+ 1.200+

A3 forecast solutions A3 5 25 30

Toolsgroup DPM (Distribution Planning Model) 4 42 43

Demantra Demand Planner 2 9 70

Demand Solutions DS Forecast Management 1 15 120

FuturMaster FuturMaster Forecasting 0 20 20

Inventory Management Associates IMA Visual Forecast 0 8 10

Syncra Systems Syncra Demand 01

41

78

Wizard Information Systems Investigator - - -

Vendors of functionalities broader than forecasting / demand planning alone

SAP SAP APO 450 19.000 29.000

Ross Systems Nederland iRenaissance SCM 40 200 450

Manugistics NetWORKS Demand 16 220 1.350

OM Partners Predicast 5 80 80

JDA Software Benelux Portfolio (E3) 1 300 1.600

Table 1: number of employees per forecasting / demand planning software vendor1These are only Syncras own employee numbers. In Europe the software is distributed by Real Software which has

1700 employees in total.


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Market leader in terms of the number of implementations is Business Forecast Systems (in the

Benelux their Forecast Pro solution is distributed by ATIM). Infolog is clearly number two with

their Slim4 solution. The middle-market in the Netherlands is dominated by the Forecast Pro,

Slim4, PlanCaster and VPS2000 solutions. The high-end market in the Netherlands is dominated

by the A3, MerciaLincs, Manugistics and SAP APO solutions.

The market for forecasting / demand planning software is largely international. The only Benelux

software vendors are Infolog, Scanmar, Quadriceps Products and OM Partners.

Number of implementations

Package Name NL EUR WW

Forecast Pro (Unlimited, XE) 235

Benelux

Hundreds 10.000

Slim4 120 140 148

A3 18 56 56

NetWORKS Demand 14 231 811

SAP APO 10 160 250

PlanCaster 10 12 12

MerciaLincs 8 220 350+

VPS2000 8 8 8

Portfolio (E3) 4 (100)1

(1000) (4000)

FuturMaster Forecasting 4 140 180

Demand Planner 4 26 125Predicast 2 250 320

DPM (Distribution Planning Model) 1 145 152

IMA Visual Forecast 1 40 43

Syncra Demand 0 1 5

DS Forecast Management - 150 2100

Investigator - 125 200

iRenaissance SCM - - -

Table 2: number of implementations per forecasting / demand planning software package1JDA has 4 implementations of their E3 forecasting tool in the Netherlands, 10 implementations of their JDA retail

solution and 90 implementations of their Intactix category / space management solution.

2.2 CGE&Ys opinion

With respect to the forecasting / demand planning market place we expect the following future

developments to occur:

Specialized high-end forecasting / demand planning software vendors will become

squeezed between advancing ERP and APS software vendors and general business

margin requirements;The traditional competitive advantage for specialized forecasting / demand planning soft-

ware vendors was their advanced functionality, their lower cost of ownership and their

ease of use. While the large ERP and APS software vendors are increasing their function-

alities for advanced forecasting / demand planning and are investing in user-friendly user


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interfaces the only competitive advantage that will be left is lower cost-of-ownership.This will put (further) pressure on software prices for high-end forecasting / demand

planning tools. The mid-market forecasting / demand planning software vendors will ex-

perience limited threat from the large ERP and APS software vendors since we do not ex-

pect that the large ERP and APS software vendors will gain entry to the mid-market for

the foreseeable future.


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3 The differences per industry

3.1 Overview

In the table below the total number of implementations per industry are mentioned for the

forecasting / demand planning software vendors that participated (from those who were willing to

provide this industry-specific data).

The wholesale industry is the most important industry in the Netherlands for forecasting / demand

planning tools and is followed by the consumer products and food & beverage industries. Within

Europe the situation is different because the most important industries for forecasting / demand

planning software are not only the consumer products and food & beverage industries but also the

industrial manufacturing and pharmaceutical & biotech industries.

DISTRIBUTION OF FORECASTING / DEMAND

PLANNING IMPLEMENTATIONS ACROSS INDUS-

TRIES

Netherlands Europe

Wholesale 63 (31 %) 94 (6 %)

Consumer Products 37 (18 %) 356 (23 %)Food & Beverage 24 (12 %) 216 (14 %)

Industrial Manufacturing 11 (5 %) 199 (13 %)

High Tech 10 (5 %) 63 (4 %)

Chemicals 9 (4 %) 104 (7 %)

Automotive 9 (4 %) 103 (7 %)

Retail 6 (3 %) 47 (3 %)

Pharmaceuticals / Biotech 4 (2 %) 178 (11 %)

Energy & Utilities 4 (2 %) 7 (0 %)

Engineering & Construction 2 (1 %) 17 (1 %)

Public Transport 1 (0 %) 0 (0 %)

Distribution Industry 0 (0 %) 44 (3 %)

Other Industries 21 (10 %) 147 (9 %)Table 3: distribution of forecasting / demand planning implementations across industries

In the table below you can see the number of implementations per package per industry. It is clear

that most software vendors do not focus on any specific industry but that they deliver their

solutions to all kinds of industries. There are a few exceptions though:

A3 forecast solutions has most of its implementations in the consumer products industry.

They are known for their specific focus on the fashion industry.

Infolog has a very high focus on the wholesale industry in the Netherlands.

FuturMaster has a high number of implementations in the consumer products industry inEurope.


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OM Partners has a high number of implementations in the industrial manufacturing in-dustry in Europe.

Table 4: number of implementations per forecasting / demand planning tool per industry

INDUSTRY

SyncraSystems

Scanmar

InfoLog

A3forecastsolutions

QuadricepsProducts

Manugistics

InventoryManagement

Associates

Toolsgroup

FinmaticaMercia

DemandSolutions

FuturMaster

OMPartners

SAP

Demantra

NL 2 4 16 1 3 2 1 7 1

EUR 1 1 4 50 1 37 10 1 34 22 95 35 60 5

NL 6 3 6 2 2 3 2

EUR 3 6 91 8 12 44 19 10 13 10

NL 2 1 3

EUR 3 21 2 2 15 2 2

NL

EUR 11 26 3 2 2

NL 61 1 1

EUR 69 1 7 16 1

NL 3 1

EUR 4 3

NL 1

EUR

NL 8 1 2

EUR 11 14 5 5 24 138 1 1

NL 1 4 1 2 1

EUR 7 2 9 2 34 26 9 13 1

NL 5 2 1 2

EUR 8 1 13 5 19 15 2

NL 2 1 1EUR 2 17 2 8 48 16 20 50 12 3

NL 4 2 2 1

EUR 9 12 29 30 9 3 11 1

NL 2

EUR 2 12 3

NL 1 20

EUR 20 1 3 33 26 15 5 41 3

Consumer

Products

Food & Beverage

Retail

Distribution

Industry

Wholesale

Energy & Utilities

Public Transport

Industrial

Manufacturing

Engineering &

Construction

Other Industries

Automotive

High Tech

Pharmaceuticals/ Biotech

Chemicals


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4 Who are the dominant players on the Dutch forecasting / demandplanning market?

4.1 Overview

We have asked the forecasting / demand planning software vendors for their top 3 competitors.

We also asked them which consultancies they mostly encountered during package selections andimplementations in the forecasting / demand planning market space (each vendor had the chance

to name three consultancies).

Top forecasting / demand planning software vendors

The well-known high-end software vendors like i2 Technologies, Manugistics and SAP APO are

considered the most important competitors by the forecasting / demand planning software

vendors.

Forecasting / demand planning software

vendors

Number of times mentioned as a competitor

i2 Technologies 4

Manugistics 3

SAP APO 3

SmartForecast 2

Demand Solutions 2

SAS 1

ForecastX 1

Mercia 1

Forecast Pro (ATIM) 1

Slim4 1

Scanmar 1

OMP 1

Logility 1

Table 5: top competitors in the Dutch forecasting / demand planning market space as ranked by fellow

software vendors

Consultancies involved in forecasting / demand planning package selection

Most large consultancies have been named by the software vendors when asked for consultancies

which were involved in forecasting / demand planning package selections. Cap Gemini Ernst &

Young (CGE&Y), PriceWaterhouseCoopers (PWC) and Atos KPMG were mentioned two times

each while the other consultancies were only mentioned once. Some smaller management

consultancies like S&V Management Consultants, KSA and Mbius where also mentioned.


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Consultancies involved in forecasting / demand planningpackage selection

Number of times mentioned

CGE&Y 2

PwC 2

Atos KPMG 2

S&V 1

KSA 1

Atos Origin 1

Accenture 1

Ordina 1

CMG 1

Deloitte 1

Mbius 1IBM 1

Table 6: consultancies involved in forecasting / demand planning package selection projects as ranked by

software vendors

Consultancies involved in forecasting / demand planning package implementation

The list of consultancies is smaller regarding consultancies that are involved in forecasting /

demand planning package implementations. Again the large supply chain consultancies like

PWC, CGE&Y and Accenture were mentioned while also S&V Management Consultants, Atos

Origin, Aepex (a niche player focused on the SAP SCM solutions) and Magnus (only focused on

SAP solutions) were mentioned.

Consultancies involved in forecasting / demand planning package

implementation

Number of times mentioned

PWC 3

Accenture 2

CGE&Y 2

S&V 1

Atos Origin 1

Aepex 1

Magnus 1

Table 7: consultancies involved in forecasting / demand planning package implementation projects as ranked

by software vendors


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5 The most important developments in the last 3 years

5.1 Overview

We have asked all forecasting / demand planning software vendors what they thought were the

most important developments during the last three years. In this paragraph we will analyze these

most important developments.

The most important developments have been:

Collaborative planning and forecasting;

Collaborative planning and forecasting (often called CPFR: collaborative planning, fore-

casting and replenishment) was the major development in the last few years. The idea be-

hind the CPFR concept is that companies do sales forecasting and planning together with

their customers instead of the situation in which internal sales employees forecast sales

based on the customer and market expectations that they have. With CPFR functionality

customer employees mostly have access to the sales forecasting and planning functional-

ity through the Internet. CPFR in practice is mostly done with important large customers

where the customer also has large benefits of cooperating with their supplier. Web-enabled forecasting solutions;

As with all other application categories forecasting and demand planning tools have been

largely web-enabled in the last few years. Web-enabling was also necessary because of the

trend for more collaborative ways of working.

Best-of-breed approach regarding the selection of forecasting solutions;A few years ago most industry observers had the opinion that forecasting and demand

planning functionality would be largely incorporated into the leading ERP systems. They

also had the opinion that the market for stand-alone forecasting and demand planning

tools would vanish in the long term. While the large ERP systems have indeed introduced

functionalities for forecasting and demand planning the market for stand-alone forecasting

and demand planning tools is still present. This is caused by the fact that the stand-aloneforecasting and demand planning tools are more user-friendly and mostly have more ad-

vanced functionality (multiple forecasting algorithms to cope with irregular demand, sea-

sonality, promotions, new product forecasting etcetera) and the fact that middle-market

companies mostly do not use any of the leading ERP systems. However, the high-end

forecasting and demand planning software vendors have indeed encountered high com-

petitive pressures from the leading ERP software vendors.

Forecasting has become a critical part of the long-term sales and budgeting process;The predictability of companies financial result forecasts has become more and more im-

portant. For most companies forecasting future sales is an integral part of developing a

long-term budget.


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Integrated promotions and marketing management;Especially for consumer goods companies promotions and other marketing actions have a

high impact on the sales figures. Forecasting and demand planning tools have added

functionality to cope with promotions like get 3 and pay 2 or if you buy A you get B

for free. Also product cannibalization functionalities have been introduced where the

sales of product A cannibalizes the sales of product B (where product A replaces or sub-

stitutes product B). We have also seen functionalities that make it easier to predict the ef-

fect of new product introductions or promotions by copying the sales behavior of another

comparable promotion or new product introduction to the product at hand.

Acceptance of the Bayesian forecasting approach;

In the last few years we have also seen the acceptance and introduction of Bayesian fore-casting methodologies. In Bayesian forecasting traditional analytical forecasting tech-

niques are combined with subjective input parameters. These subjective input parameters

have an effect on the forecasted sales (f.e. market indicators, the price of important raw

materials, introduction of a new sales channel).

Developments during last 3 years Number of times mentioned

GENERAL DEVELOPMENTS WITHIN MARKET

Best-of-breed approach 2

Forecast becomes critical part of the sales & operations planning and

budgeting process

2

Formal integration / incorporation into larger systems like ERP, Demand

Planning, scheduling etcetera

1

Recognition of the precise role played by algorithms in forecasting (theadvantages and limitations thereof)

1

Supply chain planning best-of-breed vendors without supply chain

execution abilities are surpassed by supply chain execution vendors that

have developed supply chain planning functionality

1

Small supply chain planning vendors for the midsize market gained market

share by offering point solutions

1

FORECASTING / DEMAND PLANNING FUNCTIONALITY

Collaborative planning and forecasting 8

Integrated promotions & marketing management 2

Acceptance of the Bayesian approach to forecasting which allows subjec-

tive input to be made to a forecast model in a non-technical way (e.g. in 3

months time we will open a new route to market which should give usabout a 20% increase in sales)

2

Incorporation of multiple causal factors such as long-range weather and

consumer price indexes

1

Forecasting of irregulars (spare parts, maintenance etc) trend among

clients to guarantee service levels (for thousands of items) on items that sell

less then 6 times a year

1

Product / market based forecasting 1

Safety stock evaluation and planning (calculation of required safety stock

levels based on required service levels)

1

Linkage between demand forecasting and financial forecasting 1


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Low intervention statistics (as computer power increases it is technicallyfeasible to forecast more items at a more detailed level a human analyst

however can only cope with the data volume by using more sophisticated

algorithms)

1

Intermittent demand 1

TECHNICAL DEVELOPMENTS

Internet (web) enabled solutions 3

Hardware processing capacity (calculating alternative scenarios for high

volumes (>50.000 SKU) is now possible in minutes)

1

Multi-dimensional database structures 1

Table 8: developments in forecasting / demand planning market during the last 3 years as mentioned by

software vendors


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Short product lifecycle forecasting;A known problem in many forecasting and demand planning tools is that you need at least

6 months or 1 year of historic sales data to accurately generate an analytical sales forecast.

In some industries (f.e. the clothing industry) product lifecycles are shorter than 6 months

/ 1 year. The leading software vendors in these kind of industries have therefore focused

on finding forecasting algorithms which did not need many historic sales data. They have

developed specific forecasting algorithms which can work with highly volatile sales pat-

terns.

Internet-based forecasting tools;While many forecasting and demand planning tools are already based on the internet

front-end, some software vendors are still developing an internet front-end for their fore-casting / demand planning tools.

Most important trends coming 3 years Number of times mentioned

GENERAL DEVELOPMENTS WITHIN MARKET

Formal integration / incorporation into larger systems like ERP / SCE 3

Use best of breed systems, and utilize existing ERP/financial systems 2

Centralization high number of SKUs 1

Vendor Managed Inventory (VMI) / Fourth Party Logistics (4PL) 1

Supply Chain Visibility 1

Fast return on investment 1

Move to simplicity and improvement of market knowledge interface 1

Increased importance of sales and operations planning 1

Convergence of SCM with CRM (i.e. front office to back office in

seamless system)

1

FORECASTING / DEMAND PLANNING FUNCTIONALITY

Multi tier, inter-enterprise collaboration 4

Event and promotion planning / evaluation 2

Integration of promotion planning with retail Point of Sale (POS)

data (Nielsen) for even more accurate and detailed analysis (Man-

agement and Sales Windows for Retail Sector at POS level)

2

Short product lifecycle forecasting - development of technique to

model and track highly volatile sales patterns (for example a CD

release or fashion item promotion on a daily basis with very little

actual data to go on)

2

Workflow management for forecasting definition and promotionplanning and execution

1

Enterprise Profit Optimization (EPO): integrated Pricing, Promotions& Forecasting

1

Hidden statistics 1

Customer forecasting 1

Accuracy tracking 1

Highly automatic self-adaptive forecasting models 1

As Bayesian statistics get more powerful the forecasting system will

learn more about what happens to demand producing better

forecasts with less and less human intervention

1

Automatic forecasting of new product launching 1

New algorithms for seasonality calculation 1


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The development of one system that can connect strategic andoperational forecasting in a single system using specific demand

drivers at different levels

1

TECHNICAL DEVELOPMENTS

Internet based forecasting tools 2

Large scale intra-daily forecasting 1

Table 9: future developments in forecasting / demand planning market as mentioned by fore-

casting / demand planning software vendors

6.2 CGE&Y opinion

With respect to the future developments in the forecasting / demand planning market we expectthe following main future developments to occur:

Real-time forecasting / demand planning;Becoming adaptive is a key concept for tomorrows businesses. To become adaptive the

information systems used need to be able to react in real-time to events. For forecasting

and demand planning tools this means that they need to be able to adapt their sales fore-

cast on a real-time basis; for example based on real-time point-of-sale (POS) data in the

retail sector.

Integration with supply chain visibility functionalities;To be able to react in real-time on events, forecasting and demand planning tools need

real-time access to sales and supply chain data. This is where the integration with supply

chain visibility functionalities is needed. We have already seen leading companies having

real-time visibility over their worldwide supply chain (consisting of 1000+ outsourced

distribution centers where all actions are captured with RFID technology) and using this

real-time visibility in their optimization tools (f.e. forecasting and inventory manage-

ment).

Integration with CRM systems;Nowadays forecasting functionalities are present in dedicated forecasting tools, ERP sys-

tems, SCP systems and CRM systems. While we have already talked about the discus-

sions taking place over best-of-breed systems and integrated systems (ERP, SCP) we have

not talked yet about the forecasting functionality present in CRM systems. Most CRM

systems contain basic forecasting functionalities (mostly based on the concept that salesemployees forecast their customer and product sales manually) without analytical fore-

casting algorithms. Nowadays most large customers use both CRM and ERP systems and

some also use dedicated forecasting tools and consequently these customers have prob-

lems figuring out which tool to use for sales forecasting. We should also note that there

still is no good integration between CRM functionalities en ERP functionalities in the

leading ERP suites. We do expect that in the future more attention will be paid to inte-

grating the forecasting functionalities used in the leading CRM systems with the fore-

casting functionalities used in the leading dedicated forecasting tools, ERP systems and

SCP systems.


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Price and Revenue Optimization (PRO);A trend which Manugistics has pioneered but which we expect other software vendors to

follow. Price and Revenue Optimization is all about optimizing sales prices and revenue

in situations of volatile supply and demand. An example for this is the airline industry

where the price of an airline ticket is dependent on the time of ordering and the availabil-

ity of seats. Another example is the oil and gas industries where prices are very dependent

upon current inventory levels, availability of supply and the level of demand. In these

situations sales forecasting is not only about forecasting unit sales but also about fore-

casting sales prices. Both of these are also highly dependent upon other supply chain pa-

rameters (like for example inventory levels).

Highly automatic self-adaptive forecasting models;The leading forecasting and demand planning tools can use multiple highly advanced

forecasting algorithms where each of these forecasting algorithms is best applicable for

certain types of situations. It requires an experienced specialist to use these tools in an ac-

curate manner. For the next few years we expect that the software vendors focus more on

developing highly automatic self-adaptive forecasting models. These models can, after

initial configuration, operate without manual intervention by experienced specialists. This

kind of functionality becomes increasingly important in case of a large number of SKUs

and real-time forecasting. In these highly automatic forecasting models users only need to

focus on exceptions rather than giving the tool instructions how to perform the sales fore-

cast.

Spare parts forecasting;An area that is relatively new and very complex is the forecasting of spare parts. During

spare parts forecasting for example one needs to take into account so-called repairables

(spare parts which can be repaired after there is a malfunction) and their repair time. Also

most spare parts are used very infrequently and irregular and usually very little inventory

is maintained for spare parts. We expect that certain forecasting and demand planning

software vendors will specialize in the spare parts forecasting and inventory management

area.


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7 Differentiators of forecasting / demand planning software vendors

7.1 Overview

We have asked the forecasting / demand planning software vendors for their competitive differ-

entiators. The following competitive differentiators have been named by multiple forecasting /

demand planning software vendors:

Ease-of-use of solution;Most dedicated forecasting / demand planning software vendors use this argument to dif-

ferentiate themselves from the large ERP and APS software vendors. The goal of most

vendors is to develop a forecasting / demand planning solution for which the users do not

need to have a statistical background.

Short implementation period and fast return on investment (ROI);

Many dedicated forecasting / demand planning software vendors also use this as an argu-

ment to differentiate themselves from the large ERP and APS software vendors. The best-

of-breed versus integrated solution choice is basically a trade-off between the benefits of

integration with other supply chain functionality and the low cost, ease-of-use and more

advanced functionality of a best-of-breed forecasting solution. Demand classification / automatic best-pick forecasting method;

Highly automatic self-adaptive forecasting solutions are a key trend for the future. Somesoftware vendors already deliver forecasting solutions, which have demand classification

or best-pick functionalities. These functionalities allow the forecasting solution to auto-

matically select the best forecasting method and algorithm for a specific item. In this way

the forecasting solution is able to fully automatically generate the best sales forecasts

without manual intervention and expert statistical knowledge by the user.

Scalability to handle large numbers of SKUs;Some of the dedicated forecasting / demand planning solution vendors differentiate them-

selves by their ability to handle situations with large numbers of SKUs.

Most important differentiators Number of times mentioned

GENERAL VENDOR ASPECTS

Ease of use - no statistical background is needed 8

Short implementation period and fast return on investment 7

Long-term company stability 2

Low cost - low complexity solution 1

Track record 1

Know how of the forecasting and planning process and how to become

a demand driven company

1

High customer satisfaction levels 1

Broad functionality coverage with APS, SCEM, SCPM and SCE 1


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FORECASTING / DEMAND PLANNING FUNCTIONALITYDemand classification functionality / pick-best methodology / self-

tuning (let the solution figure out what kind of demand pattern the

product follows)

3

Event planning and evaluation 2

High forecasting quality 1

Ease of simulation 1

Comprehensive top-down and bottom-up forecasting 1

Links into CPFR tool and collaborative replenishment planning tool 1

Integrated forecasting and inventory management 1

Integrated forecasting, collaborative planning and promotions

management capabilities (consensus forecast)

1

Planning tool integrated with forecasting tool 1Combination of statistical and subjective forecasting techniques 1

Routines for dealing with all kinds of events and incidents in the

data

1

Forecasting per product / market combination 1

Very sophisticated algorithms like lewandowski for statistical

forecasting that generates a baseline forecast with very high accuracy

1

Unique frequency based forecasting technology 1

Daily, weekly, monthly forecasting system 1

Superior analytical capabilities using patent pending techniques

(multiple causal factors can be analyzed impacting the accuracy by up

to 50%)

1

Allows demand and financial forecasting, plus customer planning for

the Sales Department

1

TECHNICAL POSSIBILITIES

Scalability to handle large numbers of item-location combinations 3

Full analytical reporting / marketing decision support database 2

Fully configurable / flexible 2

Advanced technology 1

Designed for the Internet 1

Slice and dice views and graphics displays with drag and drop 1

Multidimensional database 1

Table 10: competitive differentiators as mentioned by forecasting / demand planning software vendors


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8 Forecasting / demand planning functionality comparison

8.1 Overview

We have asked each of the forecasting / demand planning software vendors whether they support

specific functionalities. In the paragraphs below you can find a functionality comparison based on

these answers. We have divided the forecasting functionalities into six different functionality

areas:

Forecasting algorithms and methods

Event and Promotion Management

New Product Introduction

Relationships between different SKUs

Forecast Accuracy Analysis

Other functionalities

To facilitate the reading of the tables in the next paragraphs we have numbered each of the

software vendors.

Nr Software vendor

1 A3 forecast solutions

2 ATIM

3 Demand Solutions

4 Demantra

5 Finmatica Mercia

6 FuturMaster

7 InfoLog

8 Inventory Management Associates

9 Manugistics

10 OM Partners

11 Quadriceps Products12 Ross Systems / Prescient Systems

13 SAP

14 Scanmar

15 Syncra Systems

16 Toolsgroup

17 Wizard Information Systems


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8.2 Forecasting algorithms and methods

It is interesting to see how support for the different forecasting algorithms / methods differs

between the different forecasting and demand planning tools. Apparently the simple moving

average, exponential smoothing, multiple & linear regression, holt-winters and the best-fit

methods are supported by almost all forecasting solutions while the (specified) box-jenkins,

bayesian forecasting (EWMA) and the heidrich / prescott filter base volume methods are only

supported by a few forecasting solutions.

Easy algorithms / methods

Supported by almost all solutions

Average Difficult algorithms / methods

Only supported by a few solutions

Simple Moving Average Discrete Distributions Box-JenkinsExponential Smoothing (single,double, triple)

Intermittent Specified Box-Jenkins

Multiple & Linear Regression Specified Smoothing Model Bayesian Forecasting (EWMA)

Holt-Winters Rules-based Forecasting Heidrich/Prescott Filter Base Volume

automatic best fit selection forecast

method

Variable Response Smoothing

Bayesian Forecasting (ARIMA)

Croston's

Periodicity

Custom modelling language for self-

definition of forecast methods

Table 11: distinction between easy, average and difficult forecasting algorithms / methods

Only Demantra and Infolog support all forecasting algorithms / methods which are displayed in

the table below. Finmatica Mercia and the Toolsgroup have a very different forecasting approach

which does not use individual forecasting algorithms or methods but which focuses on matching

a specific distribution function to the historic sales data.

Algorithm / method 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Simple Moving Average Y Y Y Y - Y Y Y Y Y Y Y Y Y Y - Y

Exponential Smoothing

(single, double, triple)

Y Y y/n Y - Y Y Y Y Y Y Y Y Y Y - Y

Box-Jenkins N Y N Y - N Y Y N N N N N N N - N

Discrete Distributions N Y N Y - Y Y Y N N N N Y Y N - NIntermittent N Y N Y - Y Y Y Y Y N Y Y Y N - N

Specified Smoothing Model Y Y N Y - Y Y Y Y Y Y Y Y N N - Y

Specified Box-Jenkins N Y N Y - Y Y N N N N N N N N - N

Rules-based Forecasting Y Y N Y - N Y Y Y Y Y Y Y Y N - N

Variable Response Smooth-

ing

N N N Y - Y Y Y N Y Y Y Y N N - N

Bayesian Forecasting

(ARIMA)

N Y N Y - N Y Y Y N N N N N N - N

Bayesian Forecasting

(EWMA)

N N N Y - N Y Y N N N N N N N - N

Croston's y/n Y N Y - N Y N Y N N N Y N N - N

Periodicity N Y Y Y - Y Y Y Y Y N N Y Y N - N


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Multiple & Linear Regres-sion

N Y Y Y - Y Y Y Y Y N N Y Y Y - Y

Heidrich/Prescott Filter Base

Volume

N Y N Y - Y Y N N N N N N N N - N

Holt-Winters Y Y N Y - N Y Y Y Y Y Y Y Y Y - Y

Custom modelling language

for self-definition of forecast

methods

Y N Y - Y Y Y N N N N Y N N - N

automatic best fit selection

forecast method

Y Y Y Y - N Y Y Y Y Y Y Y Y Y - Y

Table 12: support of the different forecasting algorithms / methods by the different forecasting solutions

In the table below you can find information on other supported forecasting algorithms / methodsand the forecasting approach used by each of the different forecasting solutions.

Nr Software vendor Other supported forecasting algorithms / methods

1 A3 forecast solutions Brown's simple, double and triple

ROMES for new product forecasting without or based onlittle history

Fashion forecasting based on analysis of customer buying

behavior

2 ATIM Curve-fitting

Binomial distribution

Census-11

3 Demand Solutions Demand Solutions forecast management uses 20 understandable andexplainable formulae. No statistical knowledge is required to explain

the result of the calculations, ensuring buy-in of the results by the

people using the software. Filters are available and should be used

before forecasting to identify irratic demand. DSFM automatically

selects the best-fit formula but allows the user to select other

formulae if required. Additionally customer forecast can be kept

separately and compared with the system forecast / company

forecast.

4 Demantra Bayesian Combination Model

5 Finmatica Mercia The DLM is a superset of the above techniques the software will

automatically fit the best DLM (and will intervene on exceptions)

based on broad user preferences. The DLM can describe time series

at least as well as any of the mentioned specific techniques.6 FuturMaster

7 InfoLog Most important extra methods are methods to handle highly irregular

demand

8 Inventory Management Associates

9 Manugistics MLR QR Decomposition

MLR Singular Value Decomposition

Fourier

Weighted moving average

Lewandowski

10 OM Partners As for the rules-based Forecasting: OMP Forecaster uses a rules-

based expertise system


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11 Quadriceps Products Aggregation and disaggregation of child/parent forecasts

Smoothing with seasonality of other time-series (from stan-

dard season or product family)

12 Ross Systems / Prescient Systems

13 SAP

14 Scanmar Subjective forecasting methods supporting forecasting by

account management

Targeting & Allocation techniques

15 Syncra Systems

16 Toolsgroup The Distribution functions used by DPM are proprietary. The

software decides automatically which distribution function to apply

when calculating forecasts. The objective is not only to reduce the

error but to ensure a stable forecasting function and to monitor thedemand phenomenon itself (demand modeling) for correct safety

stock calculation. Demand behavior is modeled through a special,

proprietary, probability distribution function which can assume an

infinite number of shapes depending on a certain number of relevant

parameters (such as quantity, customer order frequency, demandvariability, demand granularity). This allows management of any

item in any stage of its life cycle with a self-adapting, seamless

model which guarantees high degrees of stability and is the basis for

management by exception (allowing automatic forecasting). The

model is reviewed and adjusted (automatically) every month in a

continuous manner to ensure stability. Our approach is to avoidbest fit modeling as isolated changes in the demand can cause the

system to change the distribution function introducing instabilityinto safety stock and forecast.

17 Wizard Information Systems

Table 13: support for alternative forecasting algorithms / methods by the different forecasting solutions

8.3 Event and Promotion Management

Apparently all forecasting solutions support promotion and event management. Only A3 forecast

solutions, Scanmar, Toolsgroup, ATIM and Wizard Information Systems lack some support for

specific event and promotion management functionalities.

Functionalities 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Promotion / event manage-

ment

Y Y - Y Y Y Y Y Y Y Y Y Y Y - Y Y

Promotion kits Y Y - Y Y Y Y Y Y Y Y Y Y Y - N -

Replacement promotions N Y - Y Y Y Y Y Y Y Y Y Y Y Y N -

Automatic analysis of the

impact of historicalpromotions based on a set of

algorithms (the user only has

to define if there was a

promotion / event and the

system will quantify the

impacts)

N Y - Y Y Y Y Y Y Y Y Y Y N - Y Y


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For future promotions/eventsthe user can refer to

historical promotions on the

same product or any other

product of choice and apply

the pattern of the historical

promotion to the new one

Y y/n - Y Y Y Y Y Y Y Y Y Y Y - Y N

Table 14: support for event and promotion management functionalities by the different forecasting solutions

8.4 New Product Introduction

All forecasting / demand planning solutions support functionalities for new product introduction.Only A3 forecast solutions, ATIM and Wizard Information Systems do not fully support all listed

functionalities regarding new product introduction.

Functionalities 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

New product introduction

can be handled by copyingthe behavior and parameters

of a certain product into

another (new) product

Y Y - Y Y Y Y Y Y Y Y Y Y Y Y Y Y

Supersession is supported

(link between phase-out of

old product and phase-in ofnew product)

Y N - Y Y Y Y Y Y Y Y Y Y Y Y Y Y

Supersession functionality

which allows you to

combine the data from

multiple products into a new

product is supported

y/n N - Y Y Y Y Y Y Y Y Y Y Y Y Y Y

At period end the history

from the predecessor can be

automatically copied to the

successor in case of

supersession

Y N - Y Y Y Y Y Y Y Y Y Y Y Y Y N

Table 15: support for new product introduction functionalities by the different forecasting solutions

8.5 Relationships between different SKUs

All forecasting / demand planning solutions can cope with forecasting hierarchies which allow

multi-dimensional aggregations and re-conciliations. A3 forecast solutions is the only software

vendor which does not support cannibalization (f.e. sales of product A has a cannibalizing effect

on the sales of product B). Options and component forecasting (used in Build-To-Order (BTO) or

Configure-To-Order (CTO) environments) however is not supported by multiple software

vendors: A3 forecast solutions, ATIM, Quadriceps Products and Scanmar.


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Functionalities 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17Cannibalization N Y - Y Y Y Y Y Y Y Y Y Y Y - Y Y

Options and component

planning (BTO/CTO

forecasting)

N N - Y Y Y Y Y Y Y N Y Y N - Y

Forecasting hierarchies

allowing multi-dimensional

aggregations / reconcilia-

tions

Y Y - Y Y Y Y Y Y Y Y Y Y Y Y Y Y

Table 16: support for different SKU relationships by the different forecasting solutions

8.6 Forecast Accuracy Analysis

Apparently forecast accuracy analysis is pretty well covered in todays forecasting and demand

planning solutions. While some software vendors have indicated that specific reports need to be

developed during an implementation most software vendors already offer standard reports for

most standard forecast accuracy measures.

Availability of standard

reports for forecast

accuracy analysis

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Forecast method analysis Y Y Y - - Y - Y Y Y Y Y Y Y Y - Y

Forecast accuracy Y Y Y - Y Y - Y Y Y Y Y Y Y Y - Y

Standard deviation forecasterror

N Y Y - Y Y - Y Y Y Y Y Y Y Y - Y

Mean absolute error (MAD) Y Y Y - - Y - Y Y Y Y Y Y Y Y - Y

Root mean squared error

(RMSE)

N Y - - - Y - Y Y Y Y Y Y N Y - N

Mean squared error (MSE) Y N Y - - Y - Y Y Y Y Y Y Y Y - N

Mean percent error (MPE) N N Y - - Y - Y Y Y Y Y Y Y Y - Y

Mean absolute % error

(MAPE)

N Y Y - - Y - Y Y Y Y Y Y Y Y - Y

WAPE by time period

(weighted absolute

percentage error by test

period)

N N - - Y N - Y Y N Y Y Y N Y - N

Table 17: support for forecasting accuracy analysis by the different forecasting solutions

8.7 Other functionalities

What-if scenario analysis can be done in all forecasting / demand planning solutions. Collabora-

tive forecasting however is not supported by A3 forecast solutions and Scanmar. ATIM is the

only software vendor that does not support financial forecasting. Telescopic buckets are not fully

supported by A3 forecast solutions, ATIM, Quadriceps Products and Wizard Information Sys-

tems.


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Functionalities 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17What-if scenario analysis Y Y - Y Y Y Y Y Y Y Y Y Y Y Y Y Y

Collaborative forecasting N Y - Y Y Y Y Y Y Y Y Y Y N Y Y Y

A financial forecast can be

calculated based on the unitforecast, budgeted unit sales

prices and cost of sales

Y N - Y Y Y Y Y Y Y Y Y Y Y - Y Y

Telescopic buckets (starting

with weeks, then months)

y/n N - Y Y Y Y Y Y Y N Y Y Y Y Y N

Table 18: support for different functionalities by the different forecasting solutions


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9 Cap Gemini Ernst & Young Your partner in supply chain projects

9.1 Introduction

Cap Gemini Ernst & Young (CGE&Y) is the largest supply chain management consultancy in the

Benelux, Europe and worldwide. Within our worldwide organization we recognize the service

line B2B Supply Chain Management which contains the following service offerings:

Sourcing and eProcurement

Manufacturing and Operations

Logistics and eFulfillment

Supply Chain Strategy

Demand and Supply Planning

Product Lifecycle Management

Asset Lifecycle Management

B2B Marketplaces

9.2 CGE&Y The premier partner in supply chain package selections

Our package selection consultants all have multi-year experience with package selection projects.

They know the supply chain software market and know the main differentiators of each vendor.

All our package selection consultants use our award-winning ERNIE software selection tool. This

tool contains, among others, a detailed database on all the vendors present on the Dutch (and

European) market within specific software categories. We have ranked these vendors against

detailed critical functional requirements lists which we have developed based on our worldwide

experiences with package selections in these software categories.

For information regarding our package selection services and our supply chain services pleasecontact CGE&Y on +31 (0)30 689 8845 or through e-mail on

Logistiek&[email protected].
mailto:Logistiek&[email protected]:Logistiek&[email protected]:Logistiek&[email protected]


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10 Participating forecasting / demand planning software vendors

Company name A3 forecast solutions B.V.

Address Postbus 98

Postal code and city 3640 AB MIJDRECHT

Contact person Mr. Z. de Baat

Application name A3

Version number 3.1

Company name ATIM

Address Togenaarstraat 6

Postal code and city 5244 HK S HERTOGENBOSCH

Contact person Mr. R. van Stratum / Mr. R. van Luxemburg

Application name Forecast Pro(Unlimited, XE)

Version number Unlimited 4.00B - XE 4.20

Company name Demand Solutions (Europe)

Address Rippingstraat 2Postal code and city 2651 EZ BERKEL EN RODENRIJS

Contact person Mr. R. van der Heiden

Application name DS Forecast Management

Version number 8.4

Company name Demantra

Address Place Constatin Meunier 1

Postal code and city Brussels (Belgium)

Contact person Mr. M. Swerdlow

Application name Demand Planner

Version number 5.2

Company name Finmatica Mercia

Address Siriusdreef 17-27

Postal code and city 2132 WT HOOFDDORP

Contact person Mr. S. Tonks

Application name MerciaLincs


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Company name FuturMaster

Address 257 avenue Le Jour se Lve

Postal code and city 92100 BOULOGNE FRANCE

Contact person Mr. J.R. Gard

Application name FuturMaster Forecasting

Version number 4.50

Company name InfoLog Benelux B.V.

Address Keulenstraat 8D

Postal code and city 7418 ET DEVENTERContact person Mr. E. van Dijk

Application name Slim4

Version number 3.1

Company name Inventory Management Associates Limited

Address Peachey House Bepton Rd

Postal code and city GU28 0JS MIDHURST W SUSSEX - UK

Contact person Mr. T. Dear

Application name IMA Visual Forecast

Version number 3.8

Company name JDA Software

Address Churchill Court, Hortons Way

Postal code and city TN16 1BT WESTERHAM, KENT - UK

Contact person Mr. P. Carter

Application name Portfolio

Version number 2003.1

Company name Manugistics

Address Marcel Thirylaan 79

Postal code and city B-1200 BRUSSELS BELGIUM

Contact person Mr. R. van Delden / Mrs. A. Roelandts

Application name NetWORKS Demand

Version number Version 7

Company name OM Partners N.V.

Address Michielssendreef 39-48

Postal code and city B 2930 BRASSCHAAT BELGIUM

Contact person Mr. W. Blondeel

Application name Predicast

Version number Version 11.5


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Company name Quadriceps Products B.V.

Address Energieweg 4

Postal code and city 4231 DJ MEERKERK

Contact person Mr. H. de Kok

Application name VPS2000


Company name Ross Systems Nederland B.V.

Address Postbus 2817

Postal code and city 3500 GV UTRECHTContact person Mr. J. Steenbakkers

Application name iRenaissance SCM


Company name SAP

Address Bruistensingel 500

Postal code and city 5232 AH DEN BOSCH

Contact person Mr. J. Wouters

Application name SAP APO

Version number 3.1

Company name Scanmar

Address De Haag 1

Postal code and city 3993 AV HOUTEN

Contact person G..J. de Nooij

Application name PlanCaster

Version number V 2.25

Company name Syncra Systems

Address Abbey House, 18-24 Stoke Rd

Postal code and city SL2 5AG SLOUGH UK

Contact person Mr. R. Downs

Application name Syncra Demand

Version number 1.2 (new product)

Company name Toolsgroup

Address Weesperstraat 118

Postal code and city 1112 AP DIEMEN

Contact person Mr. P. Kelly / Mr. R. Wallis

Application name DPM (Distribution Planning Model)



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Company name Wizard Information Systems B.V.

Address Pioenroosstraat 26

Postal code and city 5241 AB ROSMALEN

Contact person Mrs. G. Marques

Application name Investigator

Version number 4.42

Documents

Forecasting vendors in dutch-2003