Posted by Peder Enhorning

June 21, 2013

11:10 am

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Customers Rate BI Vendors by Cost

Gartner, one of the world’s most influential Information Technology analysts, has published new reports about the costs of business intelligence platforms for 25 leading suppliers. Gartner compared vendors on cost elements such as average implementation, license and hardware.

Key Findings

• Implementation costs can range from as much as 100% of the initial license costs in the smallest deployments to around 60% of license costs in the largest ones. The average across all deployment sizes equates to approximately 80%.
• Business intelligence (BI) platform usability (particularly for BI developers), the level of integration among platform components, the level of product quality and the complexity of migrations are all factors that affect implementation cost and effort as well as achievement of business benefits. Consider these factors in addition to cost in your vendor selection decision.
• Ease of use (for both developers and business users) of a particular platform expands the complexity of analysis that users can perform on their own and the breadth of product features used, while lowering implementation costs.

1. Overview

The survey of 1,364 BI professionals worldwide found that cost, while not a top criteria, continues to be a significant factor in their buying decisions. From discussions with clients, most BI leaders primarily equate the cost of a BI platform with what they spend on license fees. While license costs are often the most visible types of costs, in reality, license, maintenance, hardware and implementation costs combined represent less than 30% of the total three-year cost of a BI platform. Implementation costs in particular can range from as much as 100% of the initial license costs in the smallest deployments to around 60% of license costs in the largest ones. Within a broader cost context, initial implementation costs represent 5% to 10% of total three-year BI platform ownership costs (BIPOC), depending on deployment size and whether or not business user developers are included in the BIPOC calculation.

Table 1. Vendor Type: Categories of BI Platform Products
Category                Products
Megavendors IBM Cognos 8, IBM Cognos 10*, Microsoft, Oracle BI Enterprise Edition (OBIEE), SAP BusinessObjects
Large Independent Vendors Information Builders, MicroStrategy, SAS
Data Discovery Vendors Advizor, QlikTech, Tableau, Tibco Software (Spotfire)
Open-Source Providers Actuate (BIRT), Jaspersoft, Pentaho
Software-as-a-Service Vendors Birst*, PivotLink*
Niche Vendors Alteryx, AltoSoft*, arcplan, Bitam, Board International, InetSoft*, LogiXML, Panorama Software, Phocas, Prognoz, Quiterian, Salient Management, Targit

* Note that both software-as-a-service vendors, the niche vendors AltoSoft and InetSoft, and IBM Cognos 10 did not have enough data points across license, license maintenance, hardware or hardware maintenance categories in any of the individual user count categories to be included in this research.

BI leaders can use these results to evaluate the cost of BI platforms they are considering, but should not focus solely on cost. A cost-benefit analysis that includes an assessment of functional fit with requirements, usability to drive adoption and an assessment of business benefits should also be critical pieces of the purchasing decision equation. It is misguided to invest in low-cost software solely because it is inexpensive. If it does not meet business and usability requirements, it will achieve limited adoption and will fail to deliver expected business benefits. 2.

2. Implementation Costs by User Count

On average, initial implementation costs (see Figures 1 and 2), such as those for external consultants and system integrators, can represent as little as 60% of the license cost in the largest deployments (or an average of $143 per user), to as much as 100% of license cost in the smallest ones (or an average of $3,038 per user). As such, initial implementation represents a significant factor in total cost and should be procured and managed as rigorously as license costs.

Figure 1. Average Implementation Cost per User (Dollars)


N = 504 implementation cost
Chart represents customer perceptions and not Gartner’s opinion

Figure 2. Average Total Implementation Cost by Deployment Size (Dollars)


2.1 Factors that Affect Implementation Costs

The survey results imply a link between the following:
• Integration and product quality
• Ease of use for developers, platform integration and implementation cost per user
Ease of use appears to translate into lower implementation costs, in part because easy-to-use tools allow IT developers and other BI authors to develop BI content more quickly. It also allows more business users with fewer technical skills to create their own reports and analysis, thereby saving costs incurred by contracting IT specialists to design them.

Figure 3 shows each vendor’s product quality score on the X axis, their ease of use for developers score on the Y axis, while the size of the dot represents the average implementation cost per user. The color of the dot — orange is above average; blue is below average — shows the average platform integration score (see Note 1). The data shows that vendors with strong ease of use for developers, high product quality and a good degree of platform integration tend to have lower average implementation costs per user. In general, ease of use (for developers) is in part a function of BI platform integration and BI platform developer productivity features (particularly for the full range of simple to complex types of analysis). Well integrated platforms have less platform “moving parts” and they have integrated user tools rather than multiple user interfaces, which tend to require less training even for diverse user groups.
As a net conclusion, platforms that enable easier content development tend to have lower implementation costs per user.

Figure 3. Product Quality vs. Ease of Development vs. Average Implementation Cost Per User vs. Average Integration Score


N = 504 implementation cost
Ease of use for developers is scored on a scale of 1 to 7, where a score of 1 to 2 = poor, 3 to 5 = average, and 6 to 7 = outstanding.
Product quality is scored on a scale of 1 to 7, where a score of 1 to 2 = poor, 3 to 5 = average, and 6 to 7 = outstanding.
Average integration score: see Note 1 for calculation. The orange dots are above average integration scores; the blue dots represent below average integration scores.
Average implementation cost per user is the average across deployment sizes.
Chart represents customer perceptions and not Gartner’s opinion.

The survey results also suggest that the ease of use (for both developers and consumers) of a particular platform affects the complexity of analysis users can perform on their own, as well as implementation costs and breadth of product functionality used. Enterprises tend to use BI platforms with higher scores on ease of use for a broader range of activities (for example, reporting, ad hoc analysis and dashboards) rather than for a single function. Figure 4 shows each product’s composite ease-of-use score versus complexity of analysis conducted by users. The size of the bubble represents average implementation cost per user. Orange bubbles represent those platforms with above average breadth of function use, while blue bubbles are below the survey average. Users beyond traditional power analysts adopt intuitive tools more easily and for more functions. Moreover, ease of use reduces the cost of training and change management. This is evident in the results of data discovery tools such as Tableau, which have above average ease-of-use scores, while enabling users of these platforms to conduct the most sophisticated types of analysis. This paradox — ease of use combined with support for complex analysis — has given them momentum in the market and has caused traditional vendors to attempt to imitate their success with similar offerings.
A number of factors drive ease of use:
• Many data discovery tool offerings (such as QlikView, Tableau and Tibco Spotfire) do not require a traditional IT modeled semantic layer — although they do offer optional reusable data components and metadata. These tools provide easy-to-use capabilities for business analysts to access, blend, mash up and manipulate data with minimal IT assistance or for IT to develop content more rapidly than with traditional approaches. This approach reduces the deployment and maintenance costs associated with a semantic layer, but can increase the potential for creating personal, workgroup or departmental silos, which can cost more in terms of level of effort for IT to manage from a governance perspective.
• Intuitive BI content authoring tools include a graphical user interface and design environment, and out-of-the-box objects and wizards, which reduce the coding required for all levels of analytical complexity.
• Widely available skills make it easier and often less costly to develop analytic content (certainly than for hard-to-find skills).

Figure 4. Ease of Use vs. Complexity of Analysis vs. Average Implementation Cost per User vs. Breadth of Use


N = 504 implementation cost
“Breadth of product use score” is the sum of user activity percentages across reporting, ad hoc analysis (all levels of complexity), dashboards, scorecards and predictive analytics for each vendor. Orange dots represent an above average score, while blue dots represent a below average score on breadth of use.
Composite ease of use score is a combined measure of ease of use for business users and ease of use for developers, each scored on a scale of 1 to 7, where a score of 1 to 2 = poor, 3 to 5 = average, and 6 to 7 = outstanding.
Composite complexity of analysis/usage is a weighted average score based on percentage of respondents reporting use of the platform. Activities are weighted as follows: viewing static reports = 1, monitoring performance via a scorecard = 1, viewing parameterized reports = 2, doing simple ad hoc analysis = 3, interactive exploration and analysis of data = 4, doing moderately complex to complex ad hoc analysis = 5, using predictive analytics and/or data mining models = 5.
Average implementation cost per user is the average across deployment sizes.
Chart represents customer perceptions and not Gartner’s opinion.

Products with lower migration complexity tend to realize above average business benefits and lower implementation costs per user. Figure 5 shows migration complexity scores versus implementation costs per user, while the color of the dot (orange is above average; blue is below) show average business benefits achieved by product. With the exception of Alteryx, Quiterian, Tibco Spotfire, Quiterian and Prognoz, these vendors also tend to have below average implementation costs per user.
Gartner also reported that their survey respondents rated Tableau as the lowest in migration complexity while maintaining one of the lowest scores on average implementation cost per user. This is shown in the Figure 5 below.

Figure 5. Migration Complexity, Implementation Cost Per User and Business Benefits \

N = 504 implementation cost
Business benefits score: see Note 2 for calculation
Migration complexity is calculated on a scale of 1 to 4, where 1 = extremely straightforward; 2 = straightforward; 3 = somewhat complex; and 4 = extremely complex.
Average implementation cost per user is the average across deployment sizes Chart represents customer perceptions and not Gartner’s opinion.

3. License and Hardware Cost Highlights

3.1 Key Findings

• Organizations often consider alternative platform solutions, such as those from Microsoft and open-source vendors, believing them to offer lower license costs. However, license price accounts for only a small fraction of overall cost of ownership, and low license price does not always translate into equally low business intelligence platform ownership costs (BIPOC) over time, nor the achievement of desired business benefits.
• Four factors have the biggest affect on the cost of software licenses and hardware costs: vendor pricing models, product packaging, product scalability and size of deployment. • Per-user license costs go down substantially as deployment sizes go up. This is due to deployments that are typically characterized by a higher proportion of less-expensive viewers to content authors, more cost-efficient per-user pricing models and higher price discounting as user volumes increase.

3.2 Recommendations

• When evaluating the costs of BI platforms, extend your analysis beyond initial license and hardware fees to include implementation and ongoing development administration costs, since these make up the vast majority of total BI platform ownership costs. • Evaluators of BI platforms should not focus solely on cost as a primary decision criterion. Balance any cost consideration with functional requirements, expected adoption and business benefits. Low-cost tools that do not meet requirements will not deliver the expected business benefits. • Be just as rigorous in the selection process for service providers, as implementation costs make up a sizable (between 60% and 100% of license cost depending on deployment size) component of the overall cost. • For any deployment, try to maximize the number of people who use the BI platform, such as by combining projects to increase volume and discounts, and move away from per-user pricing models to bring down per-user costs where possible. Also, factor in future expansion when evaluating hardware sizing.

3.3 License and Hardware Cost Highlights

Favorable product quality, ease of development, implementation costs and integration costs are not the complete picture. It’s important to assess initial licensing and hardware costs. Gartner rated Tableau as having above average performance scores and among the lowest license cost per user. The figure below “Average License Costs Per User (Dollars) Versus Performance Score” shows that. (Note that performance score is defined by speed of query response time.)

4. Implementation Costs by Vendor Type and Product

A high-level view of average implementation costs versus deployment size by vendor type and product shows which vendors have the largest and most costly deployments (see Figure 6). This view shows that only a handful of vendors — LogiXML, Actuate BIRT, Tableau and Jaspersoft — have customers with both above average deployment sizes and below average implementation costs. Microsoft is the only vendor with a below average number of reported users responding to the cost question, but above average implementation total costs. In general, niche vendors tend to have among the smallest average deployment sizes (outliers in this regard are arcplan, LogiXML and Prognoz) and correspondingly small implementation costs, while megavendors (with the exception of Microsoft, whose customers responding to the cost question on the survey tended to be smaller) and large independents tend to have above average deployment sizes and above average implementation costs, although ratios and rank of these measures vary widely among specific vendors.

Figure 6. Average Implementation Costs Versus Deployment Size by Vendor Type and Product

N = 504 implementation cost
Average implementation cost is the average across deployment sizes.
Average deployment size is calculated for those survey respondents that also provided implementation cost information. Average deployment sizes for each vendor for the survey as a whole may vary from this number since these respondents are a subset of the overall survey.

5. Conclusion

Implementation cost per user goes down substantially as deployment size increases. Those vendors with very large deployments tend to have skewed lower average per-user implementation costs, while vendors with smaller average deployments tend to have skewed higher average per-user costs.
When evaluating vendors on BIPOC, balance any cost consideration with functional requirements, expected adoption and business benefits. Low-cost tools that do not meet requirements will not deliver the expected business benefits.

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