Project Planning Package – Tableau (BI) (On Premises)

How it Works

Fill out the form below for your project planning estimate. The form does not have a “beginning or end.” The form is constantly calculating, so feel free to make constant changes and the application will auto-adjust. This the on-premises version of this project planning calculator, for the on SaaS version see this link.

Details

  • Vendor Name: Tableau (See for Vendor Rating)
  • Software Category: BI Light
  • Company Headquarters: 837 North 34th Street, Suite 200, Seattle, WA 98103
  • Site: http://www.tableausoftware.com
  • Contact number:  206.633.3400
  • Delivery Mechanism: SaaS or On Premises

Finished With Your Analysis?

Once complete, go to this link to see other analytical products for Tableau.

References

Risk Book

Software RiskRethinking Enterprise Software Risk: Controlling the Main Risk Factors on IT Projects

Better Managing Software Risk

The software implementation is risky business and success is not a certainty. But you can reduce risk with the strategies in this book. Undertaking software selection and implementation without approximating the project’s risk is a poor way to make decisions about either projects or software. But that’s the way many companies do business, even though 50 percent of IT implementations are deemed failures.

Finding What Works and What Doesn’t

In this book, you will review the strategies commonly used by most companies for mitigating software project risk–and learn why these plans don’t work–and then acquire practical and realistic strategies that will help you to maximize success on your software implementation.

Chapters

Chapter 1: Introduction
Chapter 2: Enterprise Software Risk Management
Chapter 3: The Basics of Enterprise Software Risk Management
Chapter 4: Understanding the Enterprise Software Market
Chapter 5: Software Sell-ability versus Implementability
Chapter 6: Selecting the Right IT Consultant
Chapter 7: How to Use the Reports of Analysts Like Gartner
Chapter 8: How to Interpret Vendor-Provided Information to Reduce Project Risk
Chapter 9: Evaluating Implementation Preparedness
Chapter 10: Using TCO for Decision Making
Chapter 11: The Software Decisions’ Risk Component Model

Enterprise Software TCO Calculator – Tableau (BI) (On Premises)

How it Works

Fill out the form below for your TCO estimate. The form does not have a “beginning or end.” The form is constantly calculating, so feel free to make constant changes and the application will auto-adjust. This is the SaaS version of this TCO calculator, for the SaaS version see this link.

Details

  • Vendor Name: Tableau (See for Vendor Rating)
  • Software Category: BI Light
  • Company Headquarters: 837 North 34th Street, Suite 200, Seattle, WA 98103
  • Site: http://www.tableausoftware.com
  • Contact number:  206.633.3400
  • Delivery Mechanism: SaaS or On Premises

Finished With Your Analysis?

Once complete, go to this link to see other analytical products for Tableau.

Custom TCO Estimates and Consulting

  • Want Help with TCO for your Business?

    It is difficult for most companies to estimate TCO without outside advice. Vendors and consulting companies do not want their customers to know what they TCO is. Getting TCO advice from consulting companies leads to underestimated TCO. We do offer remote unbiased multi-dimension TCO estimation.

    This article is free, we do not answer questions for free. Filling out this form is for those that have a budget. If that describes you, just fill out the form below and we'll be in touch asap.

MUFI Rating & Risk – Tableau (BI)

MUFI Rating & Risk – Tableau (BI)

MUFI: Maintainability, Usability, Functionality, Implement ability

Vendor: Tableau (Select For Vendor Profile)

Introduction

Tableau is a very similar application to QlikView — in some ways. Tableau does a very good job in the BI areas that it covers, but Tableau only covers around ½ of the complete BI functionality, and it is the premier BI Light application.

Tableau has only three offerings – a rarity in BI where vendors tend to offer a variety of applications that are often quite confusing. Tableau offers Tableau Desktop, Tableau Server, and Tableau Online – their cloud/SaaS offering. However, while they are the distinct offerings regarding how they are priced, and only Tableau Server and Tableau Online are the “full” product, they are all upgraded on the same cycle.

Application Detail

Tableau makes in our opinion the most exciting application in the BI space, and along with QlikView, it has the highest buyer satisfaction level in the BI software category. Tableau is easily the user adoption leader, with users preferring Tableau over any other BI application by a wide margin.

Tableau Matrix

Tableau’s are in our opinion the best application ever developed for analytics. Many of the changes are so simple they are effortless. For instance, with the data of Region in the Column entry and Product Category in the Row entry, the graphics that are applicable are colored, while those that are not applicable are greyed out. Dimensions and Measures may be easily pulled from the left window pane and dragged to a variety of locations – much like the PivotTable functionality in Excel. Switching between different report types is quite easy.

Tableau is a downloadable application but in 2013 Tableau offered a SaaS-based solution.

Tableau Data Connect

Tableau does an excellent job of both connecting to multiple data sources and quickly uploading this information. The types of data sources Tableau can connect to continues to expand.

Tableau Spreadsheet

Sometimes it’s easy to forget that BI will often just connect to a spreadsheet. Sometimes a flat file is all that is required.

 

Some of the commentaries regarding the speed of Tableau raises eyebrows.

Tableau Venture Financing 1

Some BI applications claim to have the ability to create stunning reports, but Tableau is one of the few that does. Many of the reports we have seen created in Tableau deliver the ultimate objective of any analytical medium, in that they transit educational knowledge.

Tableau Venture Financing 3

Tableau allows just portions of the report to be selected, which provides targeted information on just the on the item selected.

Tableau Vehicle Fuel Efficiency

Tableau reports allow for precise detail, which allows in-depth views into detail. This type of report is groundbreaking, and the interfaces provided by Tableau is highly articulated. 

Tableau Hurricane

Tableau works very well with mapping, in fact, the best we have seen. This report efficiently shows a huge number of hurricanes, their location and their severity for 2005. 

Tableau Land Based

This report taught us which countries have the most land-based oil rigs.

Tableau Offshore Oil

We were quickly able to switch this report to show the offshore rigs, and from here it became apparent that the UK and Norway are the major European offshore oil companies.

We have learned quite a bit from various Tableau reports, both those created by Tableau for marketing purposes as well as those produced by clients that we interview. Tableau seems to have the ability to show information in a way that other BI applications cannot match. Although QlikView is close on their tails in this regard.

It should be recognized that these are sample reports from Tableau, and put together by very highly skilled Tableau resources – and the average Tableau report will be less impactful on average than these. However, users report also being quite satisfied with the daily reports that they can create with Tableau.

Something very interesting about Tableau is that they are getting into forecasting software. Forecasting relies upon a business intelligence back end and is a primary reason that the software vendor SAS is prominent in both forecastings as well as business intelligence. We cover this in our Software Selection Package for Demand Planning.

Tableau is growing faster than any other BI software vendor because of the strength of its application. We see the possibility of Tableau becoming a standard for advanced analysis to a smaller degree than Excel is today – and think the release of a less expensive desktop version of the application – with some disabled functionality would be a fine idea. Tableau is an application, which will continue to grow, benefiting from the overall growth of BI market, but also taking business, particularly from some of the large and inefficient BI applications.

Much is stated about the usability of Tableau, and the term “self-service” is an appealing term and easy to throw around as it is such a desirable objective. However, Tableau is not Excel, (although people with a significant amount of PivotTable experience will have a leg up in using the application) and requires training.

So one should not carry away with its user interface. In recorded videos, Tableau appears amazingly easy to use, however, that is in the hands of an experienced Tableau resource. The application has a high ceiling, but to do the types of powerful analytics that Tableau has become known for, it’s best if a superuser is assigned to help other business users build the reports that they need.

MUFI Scores

All scores out of a possible 10.

Vendor and Application Risk

The only real issue with Tableau is that the application can seem to be so easy to use that the project ends up being understaffed. We explain in the BI category analysis that none of the BI applications are truly self-service. Users can be expected to make variations on previously created reports when they gain the experience, but should not be expected to create new reports, particularly original reports from scratch.

Likelihood of Implementation Success

This accounts for both the application and 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.

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.

Risk Management Approach

Our staffing estimations in our Project Planning Package for Tableau provides the necessary guidelines to staff Tableau implementations, and these are based upon evaluating actual Tableau projects.

Finished With Your Analysis?

To go back to the Software Selection Package page for the BI Light software category. Or goto this link to see other analytical products for Tableau.

MUFI Rating & Risk – Tableau (Forecasting)

MUFI Rating & Risk – Tableau (Forecasting)

MUFI: Maintainability, Usability, Functionality, Implement ability

Vendor: Tableau (Select For Vendor Profile)

Introduction

Tableau is the most innovative software vendor in business intelligence. Therefore it was most interesting to learn of Tableau entering the forecasting market. One has to understand the history of forecasting software – which is explained in the introduction to this package, to appreciate why we are optimistic regarding the future of Tableau for forecasting. Forecasting software has most frequently placed the mathematics ahead of the user interface and usability, and the result has been that complex forecasting systems have not improved forecast accuracy anywhere near as much as they have been predicted to. With Tableau’s excellent user interface, they are an intriguing software vendor to enter this space.

Application Detail

What is most interesting is how seamlessly Tableau creates a forecast.

Tableau Produce Forecast

No particular application is required to perform forecasting in Tableau – it all comes in one application. Forecasting merely another feature of their primary application. Here we have a trendline selected. A forecast can be generated for future periods by simply performing a right mouse click and selecting Forecast from the menu.

Tableau Forecast Specifics

The forecast length and its aggregation, as well as the forecast model, can be selected in this view. One also has the option of “Fill missing values with zeroes,” which tells the application that the data periods were zero rather than non-values that changes the forecast.

Tableau Forecast Generation

Now the light blue line shows the forecasted value. Notice the forecast is picking up the declining trend that is apparent in the history and replicating this history.

Tableau Forecasting Statistics

Tableau will show some forecasting statistics – by selecting to view the Model.

Tableau Data Analysis

Probably the most exciting feature of forecasting in Tableau is the ability to perform analytics in addition to performing prediction. Here the view has been switched to provide the data points in one of Tableau’s excellent analytic views. Multiple tabs can be kept open, allowing the user to change between any analysis and forecasting.

Forecasting in Tableau is one of the most interesting things we have ever tested in software. Tableau is not a forecasting application that is a direct competitor with any of the applications on this list. A standard statistical demand planning application is designed to forecast large numbers of products and product locations combinations. Tableau is just the opposite; it has created what is referred to as an exploratory forecasting application. Tableau’s strength is not the forecasting algorithms; those can be found in greater depth in any of the significant demand planning applications – Tableau’s unique offering is the combination of statistical forecasting along with the most potent analytical front end.

Combined with analytics, it would allow an experienced user to do very detailed and in-depth analysis of various dimensions and measures. Tableau has the most flexible data environment we have tested, and applying this new technology to forecasting we predict will yield some fascinating results. Tableau can be an excellent prototype environment. Once Tableau is used to determine what to do, the improved forecasting approach can be used then configure other demand planning applications to run the same approach repeatedly. It could also lead to new ways of preparing the data before it is even entered into the forecasting system. We would look forward to using the application for uncovering forecasting relationships that have never been discovered at many companies.

This forecasting functionality is still new. Tableau will we think to develop it more in the future. Tableau does not offer a separate forecasting application, so we struggled with where to categorize this functionality, but we decided upon the demand planning area, as we wanted to make sure that those looking specifically into demand planning applications were aware of Tableau. Its forecasting functionality is just another reason to migrate to Tableau for BI.

MUFI Scores

All scores out of a possible 10.

Vendor and Application Risk

Tableau forecasting is not a separate application from Tableau “BI.” Forecasting is simply another thing that Tableau can do in addition to analytics. Forecasting is simply an addition benefit that companies that use Tableau receive from the application. The main risks with Tableau are how well the users are trained to configure and setup the application, after this the forecasting portion is simple. Tableau does not have sophisticated forecasting functionality, and this makes the use of Tableau for low forecasting risk.

Likelihood of Implementation Success

This accounts for both the application and 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.

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.

Finished With Your Analysis?

To go back to the Software Selection Package page for the Demand Planning software category. Or go to this link to see other analytical products for Tableau.

Enterprise Software TCO Calculator – Tableau (Forecasting) (SaaS)

How it Works

Fill out the form below for your TCO estimate. The form does not have a “beginning or end.” The form is constantly calculating, so feel free to make constant changes and the application will auto-adjust.

*(Note) Tableau forecasting is not developed to a point where we could see any buyer purchasing tableau just for its forecasting functionality. Rather, potential users of Tableau forecasting would be those that already own it for its traditional BI use. Therefore this analysis only includes the incremental costs of using the forecasting functionality in Tableau. This means the costs would already have been absorbed for most of the Tableau system before the buyer begins using the application for forecasting. This is why the implementation and maintenance costs below are so low. However, this is also another advantage of using Tableau for forecasting.

For the full costs of implementing Tableau, see the Enterprise Software TCO – Tableau (BI).

Furthermore, Tableau could not be used as the other forecasting applications covered in the Demand Planning software category. Instead, Tableau would be used for forecast exploration — or as an adjunct to another forecasting application. Because of Tableau’s unique visualization capabilities, it could also serve to highlight and explain forecasting concept and trends in the data to others within the buyer. For details on how Tableau could be used for forecasting see the Tableau MUFI Rating and Risk Package.

Details

  • Vendor Name: Tableau (See for Vendor Rating)
  • Software Category: Demand Planning
  • Company Headquarters: 837 North 34th Street, Suite 200, Seattle, WA 98103
  • Site: http://www.tableausoftware.com
  • Contact number:  206.633.3400
  • Delivery Mechanism: SaaS or On Premises

Finished With Your Analysis?

Once complete, go to this link to see other analytical products for Tableau.

Custom TCO Estimates and Consulting

  • Want Help with TCO for your Business?

    It is difficult for most companies to estimate TCO without outside advice. Vendors and consulting companies do not want their customers to know what they TCO is. Getting TCO advice from consulting companies leads to underestimated TCO. We do offer remote unbiased multi-dimension TCO estimation.

    This article is free, we do not answer questions for free. Filling out this form is for those that have a budget. If that describes you, just fill out the form below and we'll be in touch asap.

Enterprise Software TCO Calculator – Tableau (BI) (SaaS)

How it Works

Fill out the form below for a your TCO estimate. The form does not have a “beginning or end.” The form is constantly calculating, so feel free to make constant changes and the application will auto-adjust. This is the SaaS version of this TCO calculator, for the on premises version see this link.

Details

  • Vendor Name: Tableau (See for Vendor Rating)
  • Software Category: BI Light
  • Company Headquarters: 837 North 34th Street, Suite 200, Seattle, WA 98103
  • Site: http://www.tableausoftware.com
  • Contact number:  206.633.3400
  • Delivery Mechanism: SaaS or On Premises

Finished With Your Analysis?

Once complete, goto this link to see other analytical products for Tableau.

Project Planning Package – Tableau (BI) (SaaS)

How it Works

Fill out the form below for your project planning estimate. The form does not have a “beginning or end.” The form is constantly calculating, so feel free to make constant changes and the application will auto-adjust. This the SaaS version of this project planning calculator, for the on-premises version see this link.

Details

  • Vendor Name: Tableau (See for Vendor Rating)
  • Software Category: BI Light
  • Company Headquarters: 837 North 34th Street, Suite 200, Seattle, WA 98103
  • Site: http://www.tableausoftware.com
  • Contact number:  206.633.3400
  • Delivery Mechanism: SaaS or On Premises

Finished With Your Analysis?

Once complete, go to this link to see other analytical products for Tableau.

References

Risk Book

Software RiskRethinking Enterprise Software Risk: Controlling the Main Risk Factors on IT Projects

Better Managing Software Risk

The software implementation is risky business and success is not a certainty. But you can reduce risk with the strategies in this book. Undertaking software selection and implementation without approximating the project’s risk is a poor way to make decisions about either projects or software. But that’s the way many companies do business, even though 50 percent of IT implementations are deemed failures.

Finding What Works and What Doesn’t

In this book, you will review the strategies commonly used by most companies for mitigating software project risk–and learn why these plans don’t work–and then acquire practical and realistic strategies that will help you to maximize success on your software implementation.

Chapters

Chapter 1: Introduction
Chapter 2: Enterprise Software Risk Management
Chapter 3: The Basics of Enterprise Software Risk Management
Chapter 4: Understanding the Enterprise Software Market
Chapter 5: Software Sell-ability versus Implementability
Chapter 6: Selecting the Right IT Consultant
Chapter 7: How to Use the Reports of Analysts Like Gartner
Chapter 8: How to Interpret Vendor-Provided Information to Reduce Project Risk
Chapter 9: Evaluating Implementation Preparedness
Chapter 10: Using TCO for Decision Making
Chapter 11: The Software Decisions’ Risk Component Model

Project Planning Package – Tableau (Forecasting) (On Premises)

How it Works

Fill out the form below for your project planning estimate. The form does not have a “beginning or end.” The form is constantly calculating, so feel free to make constant changes and the application will auto-adjust.

*(Note) Tableau forecasting is not developed to a point where we could see any buyer purchasing tableau just for its forecasting functionality. Rather, potential users of Tableau forecasting would be those that already own it for its traditional BI use. Therefore this analysis only includes the incremental costs of using the forecasting functionality in Tableau. This means the costs would already have been absorbed for most of the Tableau system before the buyer begins using the application for forecasting. This is why the implementation and maintenance costs below are so low. However, this is also another advantage of using Tableau for forecasting.

For the full costs of implementing Tableau, see the Enterprise Software TCO – Tableau (BI).

Furthermore, Tableau could not be used as the other forecasting applications covered in the Demand Planning software category. Instead, Tableau would be used for forecast exploration — or as an adjunct to another forecasting application. Because of Tableau’s unique visualization capabilities, it could also serve to highlight and explain forecasting concept and trends in the data to others within the buyer. For details on how Tableau could be used for forecasting see the Tableau MUFI Rating and Risk Package.

Details

  • Vendor Name: Tableau (See for Vendor Rating)
  • Software Category: Demand Planning
  • Company Headquarters: 837 North 34th Street, Suite 200, Seattle, WA 98103
  • Site: http://www.tableausoftware.com
  • Contact number:  206.633.3400
  • Delivery Mechanism: SaaS or On Premises

Finished With Your Analysis?

Software Selection

  • Want Help with Software Selection for your Business?

    It is difficult for most companies to perform software selection without outside advice. It is impossible to obtain honest software selection support from consulting companies. We offer expert and unbiased remote software selection support.

    This article is free, we do not answer questions for free. Filling out this form is for those that have a budget. If that describes you, just fill out the form below and we'll be in touch asap.

References

Risk Book

Software RiskRethinking Enterprise Software Risk: Controlling the Main Risk Factors on IT Projects

Better Managing Software Risk

The software implementation is risky business and success is not a certainty. But you can reduce risk with the strategies in this book. Undertaking software selection and implementation without approximating the project’s risk is a poor way to make decisions about either projects or software. But that’s the way many companies do business, even though 50 percent of IT implementations are deemed failures.

Finding What Works and What Doesn’t

In this book, you will review the strategies commonly used by most companies for mitigating software project risk–and learn why these plans don’t work–and then acquire practical and realistic strategies that will help you to maximize success on your software implementation.

Chapters

Chapter 1: Introduction
Chapter 2: Enterprise Software Risk Management
Chapter 3: The Basics of Enterprise Software Risk Management
Chapter 4: Understanding the Enterprise Software Market
Chapter 5: Software Sell-ability versus Implementability
Chapter 6: Selecting the Right IT Consultant
Chapter 7: How to Use the Reports of Analysts Like Gartner
Chapter 8: How to Interpret Vendor-Provided Information to Reduce Project Risk
Chapter 9: Evaluating Implementation Preparedness
Chapter 10: Using TCO for Decision Making
Chapter 11: The Software Decisions’ Risk Component Model

Honest Vendor Ratings – Tableau

Introduction

Tableau is the most innovative and we think the most interesting BI software vendor. They have a very powerful application that places a great deal of functionality in the hands of users.

Quality of Information Provided

Due to how sales are structured at Tableau mean the Sales information is only moderately reliable.

Consulting and Support

Tableau has both good consulting and good support.

Internal Efficiency

Tableau has uneven management. Its technical management is excellent, however, its organizational and people management is a weakness, and Tableau does not seem to have the right team in place to grow from a company with a great technology into a bigger and more dominant software company. Tableau is in a critical time in its history – its success is attracting many new employees, partners, etc.. During this stage it is very easy to become corrupted and to lose sight of long-term sustainability.

There are some easy things Tableau could do  — keep developing a great product and begin focusing on how its employees are compensated. Considering the success of the company, the compensation offered by Tableau will bring long-term problems in both retaining and hiring new employees. Right now Tableau can get away with it because people want to get exposure to the latest hot technology, but they cannot count on that as motivator forever. Furthermore, many of Tableau’s policies are not sustainable and will bring it problems down the road. Tableau has “made it” and is now a valuable brand in BI, and has a potential to grow into other markets such as forecasting – a market for which they only currently receive a small amount of their revenues from.

Innovation

Tableau is the most innovative vendor in the BI space, and one of the most innovative vendors in all of enterprise software. Currently, only 4 software vendors rate a perfect 10 in innovation, and Tableau is one of the four. Tableau is also the only software vendor to have any substantial size and to attain a perfect innovation rating. Tableau has a nice description of its innovations on this page.

http://www.tableausoftware.com/fast-pace-innovation

Vendor Scores

Part of the Following Software Categories

Select the following link(s) if you have subscribed to the following analytical product(s).

Software Selection Package for BI Light

Software Selection Package for Demand Planning

Software Category Analysis – Demand Planning

Introduction

When forecasting applications were first developed external to the ERP system, a narrow spectrum of applications was developed for demand planning and these were primarily designed for the statistical forecasting process. However, statistical forecasting is only one of several forecasting processes, and over the years the variety of demand planning applications has increased significantly. Therefore, attempting to force all of a company’s forecasting needs through a single application is no longer necessary or desirable. The diagram below represents the various forecasting processes:

Major Forecasting Processes

A common mistake companies seem to make is trying to use statistical forecasting packages to manage the other forecasting processes. Part of the reason that companies do this is because both the major vendors (who tend to only offer statistical packages) and the major consulting companies incorrectly advise companies that statistical demand planning software can be used to manage non statistical process forecasting. This analysis package will primarily be focused on statistical forecasting applications, but where the application can branch out into other areas, we will point this out.

It is important to understand where demand planning fits among the different supply chain applications, as shown in the graphic below.

Common Supply Chain Application Categories Demand Planning

Demand planning one of the major categories of supply chain software. When companies implement an external supply chain planning module to be connected to their ERP system, they most often start with demand planning.

If you read most forecasting books they tend to focus very heavily on the mechanics of forecasting. They talk about forecasting methodologies (simple exponential smoothing, regression, etc.), however not enough get into the business process or how forecasts are used in real life. The first wave or generation of applications leveraged the ability to place not so sophisticated and quite sophisticated forecasting methods in software. These applications had high failure rates because they were generally not designed to be easily implemented or easily maintained. Applications in this category are what we refer to as first generation advanced planning products. A good marker of a first generation advanced planning forecasting application was if it expended most of the development effort in the application of complex methods and would often have a proprietary forecasting algorithm. During the period when first generation the prevailing wisdom was that the application mostly came down to how complex forecasting methods could be applied in an automated fashion. This period in software, which has been the dominant software development approach lead to some very bad habits. In fact, there little evidence that sophisticated mathematics can improve the forecast of difficult-to-forecast products, and this is a problem. Some studies do not show improvement from more advanced methods, but firstly the improvement is never very large, and secondly other studies come by later to contradict the original studies. In addition, complex methods should have to exceed a higher bar. Academics can apply complex methods in a laboratory environment over a few products far more easily than can be done by industry. This fact, along with the point that sophisticated methods are much more expensive for industry to implement than simple methods, is rarely mentioned. This point is made very well by J. Scott Armstrong:

Use simple methods unless a strong case can be made for complexity. One of the most enduring and useful conclusions from research on forecasting is that simple methods are generally as accurate as complex methods. Evidence relevant to the issue of simplicity comes from studies of judgment (Armstrong 1985), extrapolation (Armstrong 1984, Makridakis et al. 1982, and Schnaars 1984), and econometric methods (Allen and Fildes 2001). Simplicity also aids decision makers’ understanding and implementation, reduces the likelihood of mistakes, and is less expensive.

This idea, that forecasting software just came down to most sophisticated forecasting algorithm has been incredibly durable, especially since the research into this area clearly demonstrates that when actually implemented (that is not in a controlled academic environment where only a small number of items are being forecasted), more complex methods have a hard time defeating simple methods. The major limiting factor that companies face in leveraging forecasting functionality? That would be getting these types of applications to be understandable and to work consistently. That is making them easier to use. Unfortunately, statistical forecasting software vendors do not tend to compete on the basis of how easy their applications are to use, instead the competition tends to center around the sophistication of the mathematics that is within the forecasting methods. Having covered this subject extensively and worked in the field for quite a few years, we can say with confidence that simply having sophisticated mathematical forecasting algorithms/methods within the application is nowhere near enough to obtain consistent forecast accuracy. This leads many companies to have a false sense of security with regards to their statistical forecasting application – and it leads to companies asking themselves “We have statistical forecasting software, why can’t we get a decent forecast?” A certain cynicism has crept into statistical forecasting – however, forecasting is a disciplined endeavor and many implementing companies are not used to performing the type of data accuracy and discipline and testing that is required for forecasting. Forecasting vendors have also been responsible for overselling the ease by which a forecast can be improved by a system without the required work. Finally, many forecasting software vendors have been let down by major consulting companies who seem to primarily be able to staff IT resources for forecasting – that can configure the system, but lack very much experience or an understanding of forecasting beyond textbook knowledge.

Attribute-based Forecasting

Attribute-based forecasting is one of the most important developments since enterprise demand planning software began being used. I know this is a big statement to make, but I make it based upon research into the history of demand planning and in light of my research I am quite confident that my statement is true. After one uses an application capable of attribute-based forecasting, it’s difficult not to come to the same conclusion. And perhaps most interesting is the fact that attribute-based forecasting is still only used in a minority of companies (even though so many vendors say their applications are good at dealing with attributes). Attribute-based forecasting can allow different groups and departments to perform forecast aggregation as they are interested in seeing the data, and does not require that one single static hierarchy be used for all users. With attribute-based forecasting systems, the implementation approach for forecasting and analytic projects, which currently focuses on the technical details of complex database setup, can be changed. Instead of explaining the concept of realignment and spending seemingly endless hours debating what the “one” static hierarchy should be, that time can now be refocused onto determining and explaining how the business can get the most out of the forecasting application. This is an enormous benefit to forecasting system implementation projects, which have tended—along with many other supply chain planning software implementations—to become overly technical affairs with more emphasis on meeting deadlines and IT objectives than on adding value to the business.

Is the Word Out on Attribute-based Forecasting?

I cannot find a good explanation for why the term is searched for in search engines so infrequently. According to SEOMoz.com, the number of searches typed into Google per month for either the term “attribute forecasting,” or “attribute-based forecasting” or other derivations of these terms is negligible. There few Internet articles on this topic as well. Even a search through Google Books does not bring many results (this is usually a very comprehensive way to search for a topic). Attribute-based forecasting may not be used that commonly now; but I predict it will be in the future.

Forecast Disaggregation

Every statistical forecasting vendor that I am aware of states that they can perform forecast aggregation and disaggregation; however, there is a large gap between statistical forecasting vendors in terms of capability. This functionality is too important for clients to simply accept the statement from a vendor that “our product can do that.” In fact, aggregation and disaggregation should both be extensively demonstrated and tested by the company’s planners prior to selecting an application for purchase, in order to discern how easy the aggregation functionality is to use in competing systems. Aggregation and disaggregation capability cannot be an afterthought. Instead these capabilities must be designed into the application from the database layer up. The following quote on this topic is instructive.

Demand Sensing

We point out all trends in each software category that we cover, the valid and invalid. One of the invalid trends that we have been tracking is called demand sensing. The information on the definition of demand sensing is currently and primarily controlled by software vendors. Demand sensing did not come out of the academic community, so there have been few unbiased descriptions of what demand sensing is. Demand sensing is the adjustment of forecasting inside of the lead-time of the product, and therefore when the supply plan cannot respond. If our lead-time is 2 weeks, then demand sensing means changing the forecast less than 14 days out. Demand sensing is the adjustment of forecasting inside of the lead-time of the particular product, and therefore when the supply plan cannot respond. Because demand sensing changes the forecast within the lead-time, demand sensing cannot be considered a forecasting approach. To understand this, its important to understand that while broadly speaking a forecast is a prediction of a future event; in practical terms a forecast is a prediction of a future event that is given with sufficient advanced notification to be worthwhile. For instance, a forecast could be improved for a football game by waiting until 1/2 the game is over. However, when half the game is over, it’s too late to place a bet on the game. Therefore the forecast is not particularly useful because it occurs within the lead-time of when a some benefit from be received from it. The forecast of the game could be further improved by waiting until the minute before the game ends, but again its hard to see how anyone would accept this as a forecast. One could not want to compare the forecast accuracy of a person who forecasts games while in progress versus those that forecast the game before the game begins. This of course brings up the topic of demand sensing and forecast accuracy “improvement.”

So Where Does Demand Sensing Belong?

Instead, it is a method of creating the illusion of improving the forecast accuracy by change the forecast in way that can never translate into an improvement in supply chain performance. This is extremely appealing to any demand planning group that cannot meet its forecasting goals (which is not to say they are realistic or unrealistic).  Interestingly, the vast majority of articles on demand sensing describe it as a method of improving the forecast, and categorize it as a forecasting approach. While its true that forecast accuracy can be improved by waiting until the last minute, this is blurring the line of what forecasting actually is. Vendors and IT analysts like Gartner have completely confused the issue by combining demand sensing with demand shaping.

The list of basic things that most companies cannot do in their forecasting systems is often amazing. A company that should start with doing proven things like those above to improve the forecast, will instead choose to go with the latest “trend,” and buy demand sensing software. They prefer to use an approach that is untested and has no academic research to support the contentions that the vendors in this area (notably Terra Technologies and SAP) make about it.

Software Category Summary

All companies would like to improve their forecast accuracy. Forecasting continues to be one of the great areas of opportunity within companies. Many companies are still using some combination of ERP (which is not a good platform for forecasting) combined with Excel. This is a difficult way to improve forecast accuracy. There have been many mistakes made on demand planning projects, and gaining value from a demand planning application means analyzing those mistakes and adjusting the implementation methodology. Application of the same approaches will lead to the same outcomes.

Overall this software category has several very compelling applications, and also a growing application where we are not sure how it will develop in the future.

The links to the specific research you have paid for is included at the beginning and end of this Software Category Analysis. You will only be able to access the pages that apply to your subscription.

MUFI Rating & Risk

See the MUFI Ratings & Risk below for all of the applications we cover.

Vendor NameApplication
Big ERP
SAPMUFI Rating & Risk – SAP ECC
OracleMUFI Rating & Risk – JD Edwards EnterpriseOne
EpicorMUFI Rating & Risk – Epicor ERP
SageMUFI Rating & Risk – Sage X3
InforMUFI Rating & Risk – Infor Lawson
Small and Medium ERP
SAPMUFI Rating & Risk – SAP Business One
OracleMUFI Rating & Risk – JD Edwards World
ProcessProMUFI Rating & Risk – ProcessPro
RootstockMUFI Rating & Risk – Rootstock
ERPNextMUFI Rating & Risk – ERPNext
OpenERPMUFI Rating & Risk – OpenERP
MicrosoftMUFI Rating & Risk – Microsoft Dynamics AX
Financial Applications
IntacctMUFI Rating & Risk – Intacct
IntuitMUFI Rating & Risk – Intuit Quickbooks Enterprise Solutions
FinancialForceMUFI Rating & Risk – FinancialForce
NetSuiteMUFI Rating & Risk – NetSuite OneWorld
PLM
SAPMUFI Rating & Risk – SAP PLM
Arena SolutionsMUFI Rating & Risk – Arena Solutions Arena PLM
Hamilton GrantMUFI Rating & Risk – Hamilton Grant Recipe Management
Demand Planning
SAPMUFI Rating & Risk – SAP APO DP
TableauMUFI Rating & Risk – Tableau (Forecasting)
Business Forecast SystemsMUFI Rating & Risk – Forecast Pro TRAK
Demand WorksMUFI Rating & Risk – Demand Works Smoothie
JDAMUFI Rating & Risk – JDA Demand Management
ToolsGroupMUFI Rating & Risk – ToolsGroup SO99 (Forecasting)
Supply Planning
SAPMUFI Rating & Risk – SAP SNP
SAPMUFI Rating & Risk – SAP SmartOps
ToolsGroupMUFI Rating & Risk – ToolsGroup SO99 (Supply Planning)
Demand WorksMUFI Rating & Risk – Demand Works Smoothie SP
PlanetTogetherMUFI Rating & Risk – PlanetTogether Galaxy APS Superplant
Production Planning
SAPMUFI Rating & Risk – SAP APO PP/DS
DelfoiMUFI Rating & Risk – Delfoi Planner
PreactorMUFI Rating & Risk – Preactor
AspenTechMUFI Rating & Risk – AspenTech AspenOne
PlanetTogetherMUFI Rating & Risk – PlanetTogether Galaxy APS
BI Heavy
SAPMUFI Rating & Risk – SAP BI/BW
SAPMUFI Rating & Risk – SAP Business Objects
OracleMUFI Rating & Risk – Oracle BI
SASMUFI Rating & Risk – SAS BI
MicroStrategyMUFI Rating & Risk – MicroStrategy
IBMMUFI Rating & Risk – IBM Cognos
TeradataMUFI Rating & Risk – Teradata
ActuateMUFI Rating & Risk – Actuate ActuateOne
BI Light
SAPMUFI Rating & Risk – SAP Crystal Reports
QlikTechMUFI Rating & Risk – QlikTech QlikView
TableauMUFI Rating & Risk – Tableau (BI)
CRM
SAPMUFI Rating & Risk – SAP CRM
OracleMUFI Rating & Risk – Oracle RightNow
OracleMUFI Rating & Risk – Oracle CRM On Demand
InforMUFI Rating & Risk – Infor Epiphany
Base CRMMUFI Rating & Risk – Base CRM
SalesforceMUFI Rating & Risk – Salesforce Enterprise
SugarCRMMUFI Rating & Risk – SugarCRM
MicrosoftMUFI Rating & Risk – Microsoft Dynamics CRM
NetSuiteMUFI Rating & Risk – NetSuite CRM