How do you measure business intelligence performance?

I think this depends on the industry. In health care we would look at increased profit margin, the ability to get details related to practitioners and service lines. I would recommend a scorecard approach with preset parameters defined. Once the BI is in place you be be able to measure and trend these parameters.

Organizational culture is key to understand "the" method to measure BI environment. If there is IT governance in place, method is set and can be considered as a guideline.
Otherwise analyzing organizational culture can help to apply "the" method to measure impacts and results. Usability is key in this matter once it can determine success or fail of a BI project.

From my perspective this is likened to forcasting. Once all of the historicals are available and the plan in implmented our true measure of success is if we are truly able to handle the volume based on the forecast that we provided or that the Client has provided.
One of the largest gaps in our industry is that we do not always take the time to insure everyone that touchs our business truly understands the profitablity of our companies. If our employees understand the business then they understand what value each minute of their day has in terms of revenue.
Once an established knowledge base is provided then we are able to recieve feedback form everyone in the chain as to the viabilty of our BI. Questionares and surveys are only effective if the audience truly understands their impact on the day to day business.

I know this is rather lengthy but I hope that you can derive some useful information from it.

BI is so difficult to measure. All the factors you mention are important as well as: Level of self-service, ability to store in the BI solution itself. ease of data collection. If the solution is to include budgeting and forecasting - is the software fully capable of this. The primary measure is: does it do everything you need and expect. The measure is Yes or No. and cost to resolve.

Ask your users whether or not they are satisfied by the insight they derive from the system (or not). Ask them also how happy they are with the response time of the supporting team with respect to changes, additions, questions etc.You could start with some interviews and depending on the size off the usergroup a (on line) questionaire.

The best approach that worked well for me is to go back to the original requirements and the business case. This will give you a very good idea of what the system needed to achieve and will give you a good framework for measures and priorities: what were the most important "hot buttons" for the project champion and sponsor? - usability? cost of implementation? cost of day-to-day reporting? ad-hoc searches? response time? scaplability?, etc. The next step will be to understand what are current goals for the system and if there are any particular critical issues that need attention and measurement.
This approach will align your measures directly to your specific implementation, your CEO/CIO objectives and you will be able to easily change your measures when priorities and objectives change.

Generally, the most common way of measuring business performance requires measurement of some type of goal or KPI, whether it is an initial or newly formed one. This normally ties in nicely with measuring ROI. Measurement parameters could include, but are not limited to: scalability, usability, reliability, quality and adoption/usage.
Before implementing a BI solution there are normally some key organizational objectives and KPIs that have been put in place to work towards. Measuring business intelligence performance based on successful completion of these goals alone is perhaps a little too rigid, but certainly using them as indicators of BI performance can be helpful. ROI, often closely related to an organization’s goals, can be used as an easily quantifiable measure of BI success, making it perhpas the “strongest” measure available.
Adoption/usage has the potential be a really good indicator, if able to be correctly quantified. A common problem with this type of parameter is that it’s sometimes quantified too late on in the measurement process to be able to make any constructive changes – for example, if very few people are using your BI system, but you don’t know why, it’s more a case of too little too late since people have already lost interest.
In terms of usability, people suggest that as long as the system is being used and is easy enough to use, then it is performing. But just because a team is using BI a lot, does this mean it performs better than a team that only use it occasionally? Or if your system is particularly simple to use, does this make it a better than a system that requires help from the IT department?
Quality could refer to the quality of data used with the system, the quality of the system itself or the quality of the results derived from the BI analysis. Data quality can highly affect the performance of the BI system as well as the outcome, placing it as a strong measure of business intelligence performance.
Reliability – everyone wants a reliable BI solution. Something that will give consistent and accurate results. A BI solution could be considered as well-performing if it always delivers what the user wants. But this measure alone is probably not enough to quantify the performance level of a business intelligence system…
It has been suggested that at the end of the day, the success of a BI initiative should be measured in terms of value creation : whether the BI solution gives the business the tools to get as much value out of their data as possible, while at the same time providing valuable insight that can be applied to leverage enough money to cover the cost of implementing the BI solution and make a profit. What we drew from our research into this topic is that there is no standard way of measuring BI performance : each organization has different ways of measuring performance and quantifying success. It is highly likely that organizations use a combination of several of the above measures, as well as others not mentioned here, to draw conclusions about the performance levels of their BI solution.

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According to me, the BI performance is based on 3 axis
- Industry, Application and IT Infrastructure.
Following my experience I propose my own study focus on infrastructure.performance
It's not easy to prove that an infrastructure gives business value to a company.
I will try to answer at this difficult question. To measure the IT infrastructure performance it is necessary to understand the performance indicators.
You can find a synthetic presentation on this subject at this address

http://www.slideshare.net/PhilippeJulio/measuring-it-business-value
http://www.slideshare.net/PhilippeJulio/businessit-alignment-methodology

I think that the ultimate measure of performance is the actual return on the BI investment.

To increase the ROI of a given investment in BI you need to maximize the extra profit (return) the company makes a result of the BI implementation.

Based on the Theory of Constraints (TOC) metrics, there are conceptually two ways to increase this extra profit:

1) Increase Sales Throughput (contribution margin) by increasing sales volume and/or price of your product or service.

2) Decrease Operating Expenses.

Note that you can decrease operating expense to a point beyond which servicing your customers would suffer. On the other hand, the potential to Increase Sales Throughput has no limit, as long as you offer products or services that create value for you customers faster or better than your competitors (like Apple, Google, Cisco). Therefore to maximize the ROI of a BI investment one should focus mainly on increasing Sales Throughput.

Unfortunately, most BI implementations aim just at decreasing operating expenses as they populate sophisticated BI software with just internal raw data from the ERP. The problem is that while this supports tactical functions, it doesn’t provide the immediate strategic analysis and direction necessary to grow Sales Throughput.

In order to increase Sales Throughput, BI needs to be implemented to provide a competitive advantage to the company. But how?

Business Intelligence should be a reliable, analytical process that transforms raw data into relevant, accurate and useable strategic knowledge.

Strategic Knowledge is the result of the seamless integration of internal transaction data with external market intelligence in order to defeat the competition.

The key is to use BI software to integrate enterprise data with market intelligence and execute this analytical process fast and effectively so strategic marketing and sales teams can focus on growing Sales Throughput and this should maximize the ROI of the BI implementation.

You can find the Company Strategic Knowledge I.Q. Test at http://www.strat-wise.com/Strategic_IQ_Test.html