Executive Summary

  • This is the Brightwork Research & Analysis software rating series.
  • We rate both the software and estimate the risk of implementing each application.

MUFI Rating & Risk for JDA Demand Management

MUFI: Maintainability, Usability, Functionality, Implement ability

Vendor: Oracle (Select For Vendor Profile)

Introduction

Oracle Demantra is yet another Oracle acquisition. In our view, Demantra was an average statistical forecasting system when Oracle acquired it in 2006. However, with little investment into the application since its acquisition, Demantra is now a severely lagging application at this point which is primarily living off of its association with Oracle. And the fact that the consulting companies recommend Demantra for the simple reason that they have people trained in the application that they can bill for. For those that do not know, the association with a major brand like Oracle mistakenly makes executives believe that the software is either better or lower risk than if independent. Secondly, after its acquisition, Demantra was pitched to any remotely appropriate Oracle account.

Application Detail

It’s difficult to believe that Oracle is going to market with the Demantra user interface without attempting any improvement whatsoever, which is rated down with SAP DP. However, it is still quite a bit more usable than SAP DP. Overall Demantra has the look and feel of an application that would be purchased off the Internet at a low price, not something one would have to navigate through the gauntlet of Oracle sales to acquire. Many of the comments from users as to why they dislike Demantra centre around its user interface.

However, beneath the covers, the Demantra story improves somewhat. Demantra has an interesting functionality in that it can fundamentally test what the appropriate level in a hierarchy in which to forecast is. We have performed this type of testing – called attributes testing in several applications – and do not recall this functionality being available in any other application we have used or reviewed. This could be a time saver as most companies guess (and do not test) what attributes to use for top-down forecasting, and by extension, what level in the hierarchy which to perform a top-down forecast. Demantra also has one of the better thought out promotional forecasting functionalities – that recognizes that a promotion has impacts on demand history after the promotion. According to research published in the Journal of Marketing Research in 2007, the following changes to consumption and stockpiling were observed in their study:

  • Yoghurt: Consumption accounted for between 49 to 65% of the promotional bump
  • Ketchup: Consumption accounted for between 30 to 58% of the promotional bump

The literature on promotions and their effect on consumer behaviour are quite impressive – but a full review of the research into the promotional effect on consumer behaviour is unrelated to the treatment of promotions in this paper. Many companies lack the knowledge and forecasting functionality to apply post promotional period changes easily. If the post-promotion period changes to demand are not accounted for, the statistical forecasting method will pick up the promotional effect as a “real” effect and attempt to replicate it into the future.

So while there are some interesting areas of functionality in Demantra, generally these areas of functionality do not work as well as advertised. Secondly, we rate Demantra consulting and advice as considerably below the average consulting that is typically available from software vendors. Demantra consultants do have a tendency to make unsupportable statements during the implementation, such as statements related to how all that is required is the “data” and Demantra can come up with the correct forecasts with very little involvement. Given these statements as well as other anecdotes regarding Oracle exposure concerning Demantra makes us question whether Oracle can successfully implement forecasting projects.

A purchase of Demantra would have to be based upon some special functionality that Demantra has that cannot be had in another forecasting application. Integration is always a bad reason to decide in favour of one application over another. As such a small percentage of the TCO of an application is required for integration (and because many of the supposedly bulletproof integrations between the applications from one vendor are so much less than advertised during the sales process), therefore buying Demantra simply because Oracle offers it would not be a good decision. Finally, demand planning applications are one of the most straightforward applications to integrate to other systems.

MUFI Scores

All scores out of a possible 10.

MUFI Scores

Search for the vendor in this table using the search bar in the upper right of the table. Shortening Key: 
  • Ma. = Maintainability
  • Us. = Usability
  • Fu. = Functionality
  • Im. = Implementability
AppMa.Us.Ft.Im.Cat.
Average Score for Big ERP5.14.85.25.4Big ERP
Average Score for CRM6.26.25.15.9CRM
Average Score for Small and Medium ERP8.386.78.5Small and Medium ERP
Average Score for Finance8.88.888.8Finance
Average Score for Demand Planning7.67.277.1Demand Planning
Average Score for Supply Planning6.76.976.8Supply Planning
Average Score for Production Planning6.86.976.9Production Planning
Average Score for BI Heavy5.55.36.95.3BI Heavy
Average Score for PLM77.26.87.3PLM
Average Score for BI Light7.78.798.3BI Light
Arena Solutions Arena PLM 10101010PLM
AspenTech AspenOne48107Production Planning
Birst 88.5108BI Light
ERPNext10107.510Small and Medium ERP
Delfoi Planner866.57Production Planning
Demand Works Smoothie SP910710Supply Planning
Hamilton Grant RM1098.59PLM
IBM Cognos2.731.53BI Heavy
Infor Epiphany7865CRM
Infor Lawson8767Big ERP
Intuit QuickBooks Enterprise Solutions9959Finance
JDA DM97.588Demand Planning
Microsoft Dynamics CRM2322CRM
NetSuite CRM6433CRM
Netsuite OneWorld7788Big ERP
OpenERP788.587
Oracle BI4436BI Heavy
Oracle CRM On Demand4535CRM
Oracle Demantra533.54.5Demand Planning
Oracle JD Edwards World4136Big ERP
Oracle RightNow6745CRM
PlanetTogether Galaxy APS10101010Production Planning
Preactor8737Production Planning
QlikTech QlikView99109BI Light
Rootstock9899Small and Medium ERP
Sage X38878Big ERP
Salesforce Enterprise88.597.5CRM
SAP APO DP3432Demand Planning
SAP APO PP/DS2243Production Planning
SAP APO SNP3484Supply Planning
SAP BI/BW1.5242BI Heavy
SAP Business Objects32.573BI Heavy
SAP CRM4364CRM
SAP ECC336.53Big ERP
SAP PLM12.523PLM
SAP SmartOps4475.5Supply Planning
SAS BI6.5796BI Heavy
SAS Demand Driven Forecasting7897Demand Planning
Tableau (BI)9101010BI Light
Tableau (Forecasting)10859Demand Planning
Teradata86.39.76BI Heavy
ToolsGroup SO99 (Forecasting)7897Demand Planning
ToolsGroup SO99 (Supply)56107Supply Planning

Vendor and Application Risk

Oracle Demantra is an older demand planning application and is a challenging implementation. Unlike other demand planning vendors, Demantra consultants should primarily be used to configure the application rather than relying upon them for what is the best approach to demand planning generally. The information from the process side may be best filled with an independent consultant, although many buyers are given little leeway and must use one of the large consulting companies. Oracle will recommend this as they trade the consulting company’s recommendation for consulting business.

Likelihood of Implementation Success

This accounts for both the application and the vendor-specific risk. In our formula, the total implementation risk is application + vendor + buyer risk. The buyer specific risk could increase or decrease this overall likelihood and adjust the values that you see below.

Likelihood of Application Implementation Success and Failure

Estimates are for a typical project. A specific implementation requires details from the project to make a project-specific estimate.

Search for the application in this table using the search bar in the upper right of the table.
ApplicationProb of Implementation SuccessProb of Implementation Failure
Actuate0.770.23
SAP Smartops0.390.61
NetSuite CRM0.460.54
Sugar CRM0.620.48
Base CRM0.910.09
SAP CRM0.350.65
Salesforce Enterprise0.720.28
QlikTech QlikView0.820.18
Tableau (BI)0.980.02
SAP Crystal Reports0.460.54
Brist0.830.17
MicroStrategy0.70.3
SAS BI0.760.24
Oracle BI0.350.65
IBM Cognos0.230.77
Infor Epiphany0.580.42
Microsoft Dynamics CRM0.260.74
Oracle RightNow CRM0.410.59
Oracle CRM On Demand0.360.64
Teradata0.760.24
SAP Business Objects0.320.68
SAP BI/BW0.250.75
SAP PLM0.290.71
Hamilton Grant RM0.890.11
Arena Solutions0.960.04
Delfoi Planner0.70.3
Preactor0.640.36
PlanetTogether Galaxy APS0.960.04
AspenTech AspenOne0.550.45
SAP APO PP/DS0.270.73
Demand Works Smoothie SP0.930.07
ToolsGroup SO99 (Supply)0.820.18
Demand Works Smoothie0.960.04
Tableau (Forecasting)0.90.1
SAS Demand Driven Forecasting0.820.18
ToolsGroup SO99 (Forecasting)0.860.14
JDA DM0.570.43
Oracle Demantra0.330.67
SAP APO DP0.280.72
FinancialForce0.920.08
Intacct0.980.02
Intuit QB Enterprise0.80.2
ERPNext0.90.1
OpenERP0.780.22
Rootstock0.910.09
ProcessPro0.930.07
Microsoft Dynamics AX0.40.6
SAP Business One0.490.51
Sage X30.620.38
Infor Lawson0.580.42
Epicor ERP0.40.6
Oracle JD Edwards World0.310.69
Oracle JD Edwards EnterpriseOne0.360.64
SAP ERP ECC/R/30.320.68
NetSuite OneWorld0.650.35

Risk Definition

See this link for more on our categorizations of risk. We also offer a Buyer Specific Risk Estimation as a service for those that want a comprehensive analysis.

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