Business Intelligence: 10 Common Mistakes

Datamation published an article called Business Intelligence: 10 Common Mistakes, written by Larry Marion, with a list of the top 10 mistakes about BI that you should avoid, why and how (with some comments of the experts Howard Dresner, Wayne Eckerson and Mark Graham Brown):

1- Lack of executive sponsorship and active business involvement
Everyone knows that any major IT effort needs executive sponsorship, but in the case of a BI implementation the big mistake by the CFO, the chief marketing officer or other sponsor is to not be actively involved. It takes frequent injections of business process and strategy savvy to guide the IT team and prevent scope or data creep.

Without continuous guidance from the business side, "IT tries to stuff everything into a warehouse to address absolutely any question a user could conceivably ask," notes Howard Dresner.

2- Inadequate scrutiny over the data
Poor quality data can destroy the credibility and utilization of data warehouses and business intelligence systems.

3- Not easy to use
The user interface, graphics and what-if query capabilities have to be intuitive.

4- Poor performance
User expectations about query response times will be much higher than you realize. "Some organizations are cursed with success and can't seem to keep up with user demand," warns Wayne Eckerson.

5- Too many or too few tools
Both Dresner and Eckerson warn that IT has to be careful about how many tools are available. Too many tools lead to a lot of confusion and soaring training costs. Too few tools frustrate the users.

6- Going it alone
If you're in a big company, urge the CIO to develop a BI Competency Center. A core group of experts within your organization can become internal consultants to business units. The competency center approach will help avoid a huge number of mistakes and wasted money.

7- Allowing the spreadmart plague to spread
Eckerson invented the term spreadmart in 2002 as a label for the proliferation of mini-data warehouses and business intelligence systems based on spreadsheets. Eckerson wrote an article, called Reeling in Spreadmarts- The Proliferation of Spreadmarts, with a number of tips on how to combat the problem.

8- Inflexible design
Build a rigid data warehouse and business intelligence system is a sure fire route to misery. IT should consider which parts of the system are most likely to need updating or revision.

9- Ignoring external data
Mark Graham Brown, a performance management expert, says that external factors such as economic, political, regulatory and consumer trends may need to be considered and incorporated into a BI or performance management system to make it truly effective and useful.

10- Wrong customer data
If customer satisfaction is a key metric for your organization and the IT department is asked to implement a performance management system to create and track this, ignore urges to just use survey data.

When you are developing a BI/PM initiative, is very important take care with the mistakes like these. At the most times, those kind of mistakes can make the initiative fails.

Letter to Santa Claus

Rick Sherman has a different and fun way to comment what he thinks should change next year in BI area: he writes a letter to Santa Claus.

He starts the article commenting: "I've written letters to Santa before requesting gifts that data management and data warehousing managers would appreciate. With the current economic climate, many business intelligence (BI) managers, are putting together their wish lists for Santa. How many of these things are on your list?"

He writes like a little boy asking a gift: "Dear Santa, I think you'll agree that I deserve more than coal in my stocking. I've been a good BI director all year (actually for years) by working with business people, my development staff and my peers on our BI projects."

And he asks: "Could you use your holiday magic to help out with this wish list? All I want for Christmas is:" (This is a summary of his list, he comments about each item in his article)

- Business groups to commit more time (not capital budget) to our data governance efforts.
- IT management that will accept some new and more cost-effective approaches to BI.
- An adequate training budget to enable my staff to increase their skills, knowledge and, ultimately, productivity.
- More disclosure on partnerships and payments between vendors.
- Software pricing that does not inhibit pervasive use throughout our companies.
- Help us rationally deal with using many BI tools in our company.

I agree with his list and I hope Santa Claus meets his wishes.

He published the article in Search Data Management and you can read about the previous letters in his blog.

Nine Predictions for 2009 (not what you think)

Tom Asacker published a post in his blog, where he told about his article called Nine Predictions for 2009. Both post and article are interesting.

In the post, he wrote: "Someone once said that the pessimist sees the difficulty in every opportunity and the optimist sees the opportunity in every difficulty. Which one will the challenging New Year draw out of you? Do you want to know?

Every person has both the dog of optimism and the dog of pessimism inside of them. The one you see most often is the one you feed most often. It really is that simple. I truly hope that you feed the hopeful one in 2009 - the one with the bright, shining eyes of possibility - and live a life of passion, not pretense."

About the article, you should read to take your own conclusions. How he said in the title of the post: not what you think.

Niels Bohr said (and Asacker quoted): "Prediction is very difficult, especially if it’s about the future." By the way, he likes to quote people.

He also published some books, his latest book is:

A Little Less Conversation: Connecting with Customers in a Noisy World

10 Principles of the New Business Intelligence by Tom Davenport

James Taylor brought an interesting article to my attention this month, called 10 Principles of the New Business Intelligence, written by Tom Davenport, and published in the Harvard Business Publishing. Davenport commented about a study entitled Linking Decisions and Information for Organizational Performance, with the sponsorship of IBM's Information Management business unit. In the study, he looked at 26 efforts to improve decision-making in organizations, and concluded that ten things about how business intelligence (BI) needs to evolve:

1. Decisions are the unit of work to which BI initiatives should be applied.

2. Providing access to data and tools isn't enough if you want to ensure that decisions are actually improved.

3. If you're going to supply data to a decision-maker, it should be only what is needed to make the decision.

4. The relationship between information and decisions is a choice organizations can make--from "loosely coupled," which is what happens in traditional BI, to "automated," in which the decision is made through automation.

5. "Loosely coupled" decision and information relationships are efficient to provision with information (hence many decisions can be supported), but don't often lead to better decisions.

6. The most interesting relationship involves "structured human" decisions, in which human beings still make the final decision, but the specific information used to make the decision is made available to the decision-maker in some enhanced fashion.

7. You can't really determine the value of BI or data warehousing unless they're linked to a particular initiative to improve decision-making. Otherwise, you'll have no idea how the information and tools are being used.

8. The more closely you want to link information and decisions, the more specific you have to get in focusing on a particular decision.

9. Efforts to create "one version of the truth" are useful in creating better decisions, but you can spend a lot of time and money on that goal for uncertain return unless you are very focused on the decisions to be made as a result.

10. Business intelligence results will increasingly be achieved by IT solutions that are specific to particular industries and decisions within them.

He mentioned a good article entitled Performance Management Links Strategy And Operations, written by Doug Henschen in Information Week, where he quoted:

BI historically has been about dashboards and scorecards developed for specific uses, says AMR Research analyst John Hagerty. But that's changing. "All of a sudden it's about integrated analytics within applications," he says. "The conversation is starting to shift to looking at information in the context of specific decisions and roles."

Tom Davenport also wrote an excellent book, with Jeanne Harris: Competing on Analytics: The New Science of Winning (I commented about this book in a post).

Technology's Top 10 Winners of 2008

CioInsight recently published their Technology's Top 10 Winners of 2008, in a slideshow format.

The names are:

1 - Steve Jobs - Apple
2 - Barack Obama - President elected
3 - Nicholas Carr - writer
4 - Dan Nye - LinkedIn
5 - Eric Schmidt - Google
6 - Ray Ozzie - Microsoft
7 - Nate Silver - FiveThirtyEight.com
8 - Marc Benioff - Salesforce.com
9 - Larry Ellison - Oracle
10 - Evan Wiliams - Twitter

In the slideshow, they explain the reason to choice each name.

They also published the Technology's Top 10 Losers of 2008.

Nine Choices on the Road to BI Solution Centers

Intelligent Enterprise published this month a good article about Business Intelligence Solution Centers, by Boris Evelson and James Kobielus, analysts of Forrester Research. This article is based on the Forrester Report Implementing Your Business Intelligence Solutions Center.

They said as BI grows more pervasive, complex, feature-rich, and mission-critical, it also becomes harder to implement effectively. Many information and knowledge management professionals question whether they architect, implement, and manage their BI initiatives properly. Doing so requires sound BI and performance management best practices — and an awareness of the myriad ways it can all go wrong.
Forrester defines a BISC as: A permanent, cross-functional organizational structure responsible for governance and processes necessary to deliver or facilitate delivery of successful BI solutions, as well as being an institutional steward, protector, and forum for BI best practices.

The chief symptoms of suboptimal BI management practices include:
- The lack of a single trustworthy view of all relevant information.
- BI applications too complex and confusing to use effectively.
- BI applications too rigid to address even minor changes.

You need to customize your BISC approach, and the intersections of these four dimensions — process, people, data, and technology — create multiple BISC scenarios and approaches that information and knowledge management pros must consider when developing a BISC most relevant to support your BI efforts.

The nine scenarios and approaches you must consider when implementing your BISC are:

1 - Strategic Or Operational Objectives?
Some organizations deploy BISCs that are purely strategic or advisory in nature. In those organizations BISC accepts the role of being a BI champion, providing subject matter experts, and overseeing BI standards, methodologies, and a repository of best practices. When these BISCs take on more operational duties they become responsible for tasks like the BI project management office (PMO), training, and vendor management.

2 - In-house or Outsourced?
Enterprises deploying BI will need help from experienced consultants and systems integrators (SIs). This expertise is critical because BI is very much an art and will remain that for the foreseeable future, since it involves engineering a complex set of systems and data to address the changing imperatives of business organizations. As a result, most of the more successful BISC organizations include both internal and external staff.

3 - Virtual Or Physical?
Organizations have a choice of leaving their BISC staff within their lines of business (LOBs) or functional departments, or moving them to a centralized physical BISC organization.

4 - Operational or Analytical in Scope?
A BISC for some may focus on addressing the front-end access, presentation, delivery, and visualization requirements of analytic applications. Alternately, others may encompass a wider scope including data warehousing; data integration; data quality; master data management (MDM); and many other analytics-relevant infrastructures, processes, and tools.

5 - Support IT only or All Stakeholders?
Information and knowledge management pros must determine whether their organizational culture is ready to support BISC beyond BI infrastructure in scope.

6 - Type of Funding Model?
BISC can be treated as a corporate cost center, and all departments across the enterprise can use and benefit from BISC services. A cost allocation model based on the actual usage of BISC services can be fairer, but detailed, activity-based cost allocation models can be tricky to set up, implement, and manage.

7 - Narrow or Broad Scope?
Forrester recommends business leadership and business-led governance orientation, not a technology-centric focus, for the BISC. The same road map principles that apply to the best practices of implementing BI apply to the BISC: strategy first, architecture next, technology last.

8 - Performance Measurement Approach?
BISC stakeholders require transparent measurements of the success of the BISC program in order to support ongoing momentum and funding. BISC leaders must establish a clear set of BISC performance metrics and clearly communicate them on a periodic basis.

9 - Isolated or Aligned With Other Solution Centers?
No BI environment is an island from the rest of the data management infrastructure. Just as BI applications touch, depend on, and overlap with many related processes and technologies, BISCs cannot exist in isolation from other competency centers, solutions centers, or centers of excellence. Federation between the BISC and other data management competency centers is a best practice.

The Forrester wrote a good report, and I think this report can help companies to implement an effective BI Solution Center.

BI: Is One Version of the Truth Still Out There?

I read an article called BI: Is One Version of the Truth Still Out There? , in CRM Buyer, written by David Hatch, vice president and principal analyst of Aberdeen Group's business intelligence practice. He talks about the common issue that the organizations have, when spend months and endure significant costs to obtain the reporting and analysis capabilities that BI (business intelligence) technology promises, only to find that different "versions of the truth" still exist without any definite way of determining which one is real or accurate.

He answered "Yes" to the question: Is "One Version of the Truth" achievable?, based on a research from The Aberdeen Group.

Managers are questioning their level of trust in corporate data: Do the reports, charts and analytic tools in use today represent "the truth?" During August and September 2008, Aberdeen Group surveyed over 200 professionals from 155 companies and interviewed a diverse range of senior executives and operational management professionals working in different industries and geographies. Aberdeen published the research study, called One Version of the Truth 2.0: Are Your Decisions Based on Reality?.

He said that the majority of problems arise at the data source and integration levels, which explains why master data management (MDM) and data warehousing technologies and services are at the forefront of technology investment today, and also emphasized the importance of "data stewardship."

He recommended some actions:
- Start with end-user information requirements
- Build a working group or committee
- Focus on understanding data relationships to the end application
- Establish a formal data stewardship role
- Apply integration techniques to all data types from internal and external sources
- Security is not a job
- Develop and manage milestones.

In my opinion, the main challenge to the companies obtain a single version of the truth is to have a data management well implemented, it includes the concepts of data governance, data integration, data quality, and master data management.

The Value of BI in a Weak Economy

Today, Michael Corcoran published a very nice article in The Data Warehousing Institute (TDWI) called The Value of BI in a Weak Economy, where he talks due the financial situation, the CIOs must control spending and many of them are turning to business intelligence (BI) to derive maximum value from their existing assets. He offers several examples that demonstrate why BI is so valuable in a weak economy.

He divides the article by topics, and I would like to highlight some parts of the article:

Using Employee Metrics to Motivate Performance

One way to motivate positive performance is to make employees aware of how they compare to their peers. This information helps these workers make better decisions, and encourages them to work harder to improve their standing in the organization.

SwiftTrade, a financial services firm operating in the North American, European, and Asian markets, reveals how BI holds the key to productivity in lean times. Benson Chung, a member of SwiftTrade’s business process management team, created a BI system that automatically updates a reporting database whenever designated revenue and trading milestones are reached. Additionally, using BI technology, he has created several dynamic reports to motivate trader performance.

Using BI to Identify Cost-Saving Opportunities

One of the ways BI reduces costs is by shortening the time it takes people to get information. At the Hillman Group in Cincinnati, Ohio, a BI application is shrinking that process from weeks to minutes. Nearly 600 sales representatives use BI software to track sales transactions and see if they’re meeting quotas.

Helping a Dealer Network Reduce Costs

Few markets are experiencing economic doldrums like the U.S. automotive industry. As the industry expands to include new Chinese exporters, along with established players from Japan, Germany, and South Korea, one U.S. auto manufacturer used BI technology to create a dealer reporting system that saves $60 million each year. The system identifies excessive repair costs by monitoring how much each dealer’s warranty performance varies from the average performance of other dealers in the same geographic region.

Using BI as a Profit Center

BI can also uncover previously untapped revenue. The genesis of these initiatives is often a desire to fully analyze data about customers, products, and sales. Data visualization software can help

Consider the Commercial branch of Air Canada, which is chartered with understanding how revenue is generated for Canada’s largest commercial airline. To do its job more effectively, managers created an Advance Booking Report (ABR) that calculates revenue and yield for each of the airline’s major markets, sorted by week and month.

Air Canada used this report to answers questions such as the following: Do declines in bookings indicate a trend (such as a mitigating issue with one of the international markets)? Do we have excess capacity, or are the flights likely to be overbooked? Should our sales force investigate a bookings problem?

Air Canada’s data visualization software uses geographic displays to reveal point-of-sale data on a world map. Multiple views are just a click away simply by highlighting a specific data element. Linking interactive graphs makes it easier to detect correlations in the data. For example, they can select a time period and display a scatter plot of routes clustered according to profitability (low bookings with low fares). One more click produces a report that instantly identifies the issue in a single page. This leads to more productive meetings, better understanding of the issues, and more clearly defined follow-up activities.

Positioned for Growth

Many business leaders are looking to BI for near-term solutions, but BI delivers high-value returns on many levels. BI enables companies to work smarter, even when tight financial times mean smaller IT budgets and leaner staffs. Market-leading companies in every industry are turning to this software to stay ahead. When the economy turns—as it inevitably will—these are the firms that will be in the best position to seize the next wave of opportunities.

It is a very nice article, and I also believe that with the weak economy and recession around the world, to use BI is the right way to help companies to make decisions smarter and faster.

Cool BI: Rating The Latest Innovations

Cindi Howson published yesterday in Intelligent Enterprise, a good article called Cool BI: Rating The Latest Innovations, where she examines the BI innovations thinking about them in terms of maturity, value, and pervasiveness:

Maturity: Consider the technology's maturity, particularly in its integration with BI. Some innovations have been making inroads into BI for years, whereas others are more recent.

Value: Consider the value of the innovation, either to reduce BI's cost of ownership, improve productivity, or increase BI's contribution to business performance. Some BI deployments focus on the value of a single, big decision. At these companies, BI is often deployed first to the experts and analysts. Other firms look for improvement on all the little decisions that may have a small individual impact yet a huge aggregate contribution to results.

Pervasiveness: While many vendors have trumpeted the rallying cry for "mainstream BI" or "pervasive BI," BI adoption even among established practitioners is relatively low at 25 percent of employees within the company. In evaluating innovations, recognize that each will appeal to different user segments as illustrated in the chart at right. Advanced visualization, for example, is powerful for business analysts, whereas BI search is ideal for casual users, and embedded BI helps front-line workers. Mobile BI has big potential for executives and front-line workers, but the business analysts who are currently the largest BI constituency may say it's not at all important. Innovations that make BI more pervasive are not necessarily more important than those that benefit power users; the point is to recognize that different user segments will benefit more from certain innovations.

She defines a quadrant chart with several BI innovations according to these three factors. Maturity is along the X axis, pervasiveness is along the Y axis, and the size and color of the bubble indicates the financial value:


She describes some of them and also a bottom line about the innovation:

Rich Reportlets

The term "rich reportlets" refers to the influence of rich internet applications (RIA) in the BI world.
Bubbles and trend lines dancing across a page may not seem essential to BI techies, but ask business users which tool they'd rather use and they'll vote for a rich reportlet. When you are trying to change the way people work, don't underestimate the power of the cool factor in getting them to try new tools.
Beyond the appeal of these interfaces, rich reportlets contribute substance to BI.

Bottom line: embrace rich reportlets and interfaces for their ability to make BI engaging to existing users and more appealing to new classes of users.

In-Memory Analytics

In-memory analytics has been around for years, so why the recent buzz? The answer lies in a combination of:
- Increasing adoption of 64-bit operating systems and greater availability of addressable memory
- Lower costs for random access memory (RAM )
- How in-memory analytics are used and delivered
- Shifts in user expectations for speed-of-thought analysis

Bottom Line: There was a time when users were happy to get a weekly report. Today, the pace of business demands fast data access and even faster insight. 64-bit technology provides greater scalability to in-memory tools and is gaining greater adoption and support.

Web 2.0 Meets BI

The collaborative side of the Web is so prevalent and accepted by a new generation of workers that we have to contemplate the effects on BI. She suggests that social networking could solve some of BI's greatest challenges:

- Information overload
- Information hoarding
- Providing insights to the most appropriate people to decrease the time to decision

Bottom Line: Some of social networking's influence on BI certainly has a high "cool" factor, but the business value is not yet proven. Nonetheless, the potential to extend the reach of BI, reduce information overload and give users greater autonomy make this an important area to watch.

She also talked about a few other innovations: Open Source BI, Software as a Service, BI Search, Mobile BI and Predictive Analytics.

About Predictive Analytics, she said: This is a mature capability but one that continues to remain a specialist tool and task. Encompassing predictive analytics within a total BI deployment means more people can benefit from predictive discoveries and insights. This is both a strategic issue and a technical issue. With SAS and Teradata closely partnering and SPSS striking deals with Business Objects and Cognos, the convergence of BI and predictive analytics continues to gain momentum.

Cindi Howson is an expert of BI Industry and this is a good article about the BI innovations. She is the founder of BIScorecard, a Web site for in-depth BI product reviews.

Transitioning Toward Operational Business Intelligence

This month, DM Review published a nice article entitled Transitioning Toward Operational Business Intelligence, written by Lyndsay Wise. She talks about why the concept of operational BI is becoming more realistic with the shift in the BI scenario, considering the BI expansion in the organizations and an approach to apply the concept of BI for the masses.

She considers that mass deployments and embedding BI within daily operational processes are becoming the goals of many organizations that are ready to move beyond online analytical processing (OLAP) and ad hoc reporting. Operational BI is being pushed on the market to increase the overall use of BI within the organization.

Once BI is implemented within the organization, various departments begin to see the benefits of its use. This coupled with an existing framework and general architecture creates an environment where BI can be expanded upon without initial rework. By expanding data sharing and collaborative efforts across the organization, there exists the ability to integrate BI use into existing processes and to identify where BI might fit within overall business processes in general.

With more end users accessing BI applications and BI’s extended reach toward multiple decision-makers, organizations begin to take a more forward looking approach to BI and, more importantly, to organization-wide decision-making. When looking at a BI for the masses approach, the question becomes “What is the best manner to deploy this type of expansion?” The problem with many traditional BI solutions is the inability to use them without training and some general technical knowledge, for instance understanding how different sets of information interrelate.

I think the use of operational BI in the companies is an interesting approach for spreading the use of BI throughout the organization.

How to Select the Right Business Intelligence Vendor

eWeek published yesterday an interesting article called How to Select the Right Business Intelligence Vendor, written by Ted Cuzzillo. He talks about the three advantages that he considers to select an independent BI vendor, instead to buy an integrated suite of the Big Four (IBM, Microsoft, Oracle and SAP).

The three advantages are:

1 - The ability to mix and match
As a CIO, you can build your own optimal set of tools for your organization's unique needs—with tools you know will work the way you need them to.

2 - Freedom to apply leverage with a vendor, and ultimately, the freedom to walk away
The freedom to adopt better, more advanced tools is critical in the rapidly evolving state of technology. There's a lot on the horizon and plenty of reason to stay open.

3 - Customer influence
During rapid change, independent vendors have to listen to customers. Even veterans cannot ignore their customers. Customers tend to be able to influence product direction (of independent vendors) more easily.

He also considers that there's a downside to buying from independents. Even so, the advantage of an open system is clear. While supposedly "integrated" platforms might serve for today, open systems serve today's needs and also tomorrow's—as they leave a path open for rapid and unpredictable evolution.

I agree with him, when you are choosing BI tools, you should choice the better tools to attend your company, whatever the tools are the same vendor or not.

Five Steps to Optimizing BI and Data Warehouse Performance

David Stodder published today in Intelligent Enterprise, an interesting article called Five Steps to Optimizing BI and Data Warehouse Performance. He is vice president and research director at Ventana Research and the article is an executive summary of the resulting report entitled Optimizing BI and Data Warehouse Performance.

Stodder talks that with the pressure is on business intelligence and data warehousing professionals to handle ever-higher data volumes and ever-more-complex queries while reducing decision latency.


Optimizing BI and data warehouse performance is vital to meeting business objectives. Based on the results of Ventana's recent research, and on knowledge of best practices involving people, processes, information and technology, Ventana Research recommends the five following steps toward BI and data warehouse performance improvement:

1. Let business drivers and benefits direct performance improvement efforts. Before taking steps to improve BI and data warehouse performance, make sure you understand the purpose of these systems, the objectives they serve and the benefits that your organization expects to derive from optimization. This knowledge will help you set priorities for tuning current systems and augmenting them with new systems.

2. Improve information assets for analyzing and tuning performance. Determine early on what information sources your organization uses to understand performance. In most organizations, the sources are diverse and include both people and systems.

3. Use performance demand to guide deployment of appliances, specialized databases and query accelerators. Determine your strategy for deploying appliances, specialized databases and query accelerators based on analysis of performance demand. A growing trend is use of BI and data warehouse appliances, which offer preconfigured combinations of software, hardware and storage systems.

4. Reduce the time it takes to remedy unsatisfactory performance and implement information change requests. Make it a goal for your organization to improve your users' experience by addressing problems and implementing information change requests rapidly. A critical factor in improving response time is to know when performance demands will be at their highest so you can plan resources accordingly.

5. Assess your organization's maturity and invest for improvement.
Ventana Research measures organizational maturity using a four-level scale. In this benchmark research, most participating organizations rank at the middle levels, with 38 percent at the third-highest Strategic level and 29 percent one step down at the Advanced level.
Use these results to assess your own maturity and to determine where you can apply improvements in terms of your people, processes, information and technology.

The complete "Optimizing BI and Data Warehouse Performance" report, which is available for purchase from Ventana Research, offers extensive detail on its benchmark research, including 15 charts and graphs, on the demographics and people, process, information and technology maturity of survey participants.

This is an interesting article and I think the report is also an interesting benchmark research about this important issue.

The Four Components of BI Governance

I read in Business Intelligence Best Practices, an article called The Four Components of BI Governance, written by Deanne Larson and Denise Matney, where they talk about the concept of BI Governance.

They define that BI governance builds in flexibility by creating robust processes capable of scaling to any size and scope, and all aspects related to the approach of BI efforts are clearly defined. Along with a mechanism to manage your BI strategy, BI governance provides measurements for gauging success. One non-tangible benefit: improved morale as the staff involved builds their knowledge base and shortens their learning curve.

What is BI governance? It’s the process of defining and implementing an infrastructure that will support enterprise goals. Jointly owned by IT and its business partners, the process evolves the direction and the value of BI as a strategy.

According them, there are four components to BI governance:
- A BI governance committee
- A framework for the BI lifecycle
- An end-user support structure
- A process to review BI programs

The main point of a BI governance committee is to provide greater visibility to all of the enterprise initiatives —aligning with overall business goals and providing value to each participating entity.

The BI lifecycle is a consistent framework that supports BI efforts end to end and is agreed to by IT and the business users. The framework has six sections: Tool selection, Data integration, Analytics, Custom BI tool work, User acceptance and Training.

End-user support focuses on providing assistance and education from a technical, functional, and data standpoint, always keeping the enterprise goals in mind.

One of the most challenging parts of BI implementation is the review — measuring success and understanding value. BI is not always quantifiable and its role as an enabler does not easily fit into an ROI calculation. Even when you do have quantifiable metrics, your next step may not be clear. The BI review can help you to determine your BI maturity level, identify meaningful metrics, and capture opportunities.

They conclude that BI governance is a framework that helps identify, deliver, and maintain the BI strategy.

In my opinion, the main role of BI governance framework is to ensure that BI initiatives are aligned with business priorities and the corporate strategy.

Agile BI Governance

I read in Jorge Fernández González's blog (written in spanish), some interesting texts and saw some slides about Agile BI Governance. He joins the principles of agile manifesto and BI Governance, and defines what he calls Agile BI Governance Framework.


According his presentation, Agile BI Governance is the process of definition and implementation of infrastructure that will support the objectives of company. The four values of Agile BI Governance are: continuous adaptability, work together, flexible hierarchies, and people over processes.

He defines some changes of paradigm to use the Agile BI Governance:
- Changing the management style from "order and control" to "leadership and partnership"
- Changing the corporate culture from "focusing on the process" towards "people-oriented"
- Changing not crucial knowledge management from "explicit" to "tacit"
- Changing the communication from "formal" to "informal"
- Changing the role of the end user from "important" to "fundamental"
- Changing the structure of the organization from "hierarchical" to "organic"
- Changing the "strict roles" with "interchangeable roles"

In his blog, you can read articles that he published in magazines (english and spanish), watch a presentation (spanish), and also see some slides (spanish).

He also publishes articles in B-Eye-Network (spanish edition).

Pervasive Business Intelligence: Are organizations really ready?

Search Data Management published an article last month, called Pervasive business intelligence: Are organizations really ready?, by Jeff Kelly, Search Data Management's News Editor, where he commented the new features launched by Business Objects, and questioned if the companies are ready to use pervasive BI.

According the Business Objects' executives:
"IT departments have invested huge sums to upgrade their data management and business intelligence infrastructure – building massive data warehouses, for example – and are anxious to capitalize on their investments by spreading analytics capabilities throughout organizations, and Business Objects is committing significant resources to making its tools easier for non-BI experts to use.
The challenge for us is to develop more and more applications that have analytics under the covers so the end user doesn't know there are in fact some algorithms going on behind the scenes."

I agree when they said: "For most organizations, extending BI and analytics capabilities to business users is, in fact, a significant cultural change. Even Business Objects customers that have embraced the concept of enterprise-wide BI recognize that making the transition requires considerable effort, namely employee training, both on the front and back ends."

I think the cultural change in the organizations is the main challenge to implement pervasive BI.

Can Web 2.0 save BI?

The Computerworld published a couple of days ago, an article called Can Web 2.0 save BI?, about the use of Web 2.0 technologies in BI applications.

Although the article is interesting, I didn't like the title, because I think the Web 2.0 are not saving the BI. The concepts of Web 2.0 working together with the concepts of BI are creating an evolution, called BI 2.0, a new generation of BI, more pervasive, intuitive, interactive, collaborative, process-driven, and also responsible for a new way of thinking. The BI 2.0 allows a BI for everyone and provides a new way for the companies improve their results.

Corporate Decision Support Still Shaky

Today, Business Finance published an article called Corporate Decision Support Still Shaky. This article is about a new benchmark research survey from Ventana Research, sponsored by Business Finance. According the survey, many executives lack confidence in the effectiveness of their organization's analysis and planning processes and doubt the reliability of the data contained in presentations.

You can access an executive summary of the Ventana Research report (requires free registration).

I think when a company is implementing a BI/PM, one of the most important concerns is data quality. To be a successful BI/PM, the company needs to have data accurate, because it can have a Data Warehouse correctly modeled, a well implemented BI/PM using good tools, but if its data are not accurate, the company will make decisions using unreliable information. It is very important the companies create a policy of Data Governance.

Google Chrome: a browser by Google

Google launched today Google Chrome, a new open source browser. According Google, the new browser is intended to create a better web experience for users around the world.

The browser was launched in over 100 countries and more than 40 different languages.

Google Chrome can be downloaded here.


The Wired also published today an interesting article entitled Inside Chrome: The Secret Project to Crush IE and Remake the Web.

This is more a good initiative provided by Google, and get to the established niche of browsers, dominated by Internet Explorer and Firefox.

Distilling Raw Data into Useful Information

Industry Week published an article entitled Business Intelligence: Distilling Raw Data into Useful Information, by Chris Rafter, Vice President Consulting Services of Logicalis, where he talks mainly about the important issue that is the alignment between IT and the business.

He makes a question (and also replies): Are your business users able to obtain accurate, timely and reliable reporting information about how the business is doing? You often hear "Yes" from an IT manager, but you almost never hear "Yes" from a business manager.

He defines some opportunities to leverage BI on the company and he also makes some questions to help the definition to help the evaluation of the intelligence potential:
- Is your data quality at an acceptable level?
- Do you have a plan to manage your data to ensure quality?
- Can you rely on your data to make business decisions?
- Does your organization have access to all the reports needed?
- Can you easily see a 360-degree view of your customers?
- Can you afford to answer "no" to any of the above?

The summary of text is defined in this phrase: The disconnect between business managers and IT needs to be resolved before information can be distilled from data.

I think people need to understand their business issues before implement a BI initiative, aligning the business goals with the BI strategy, creating a solid partnership with the business and IT. The alignment between IT and the business is one of the most important issues that should be solved when the company is implementing Business Intelligence.

Is Excel a Complete BI Solution?

Today, Rajan Chandras wrote a nice piece in his blog on Intelligent Enterprise, entitled Is Excel a Complete BI Solution?, where he poses some arguments about to consider Excel as a BI tool, based on Forrester report The Forrester Wave: Enterprise Business Intelligence Platforms, Q3 2008, with free copy courtesy of SAS. The report, written by Boris Evelson, does not include Excel as one of the 12 solutions.

Rajan asked: Should Excel be considered a BI tool, worthy of inclusion in surveys such as the Forrester Wave?

Boris is also the author of an interesting report last year on the use of Excel as a BI tool, called Ouch! Get Ready — Spreadsheets Are Here To Stay For Business Intelligence.

Boris Evelson wrote both reports, and answered in his blog.

I agree with Boris when he said: "I vote for Excel as a BI UI, or Excel as a lightweight, departmental or SMB BI solution. But stand-alone Excel cannot be one and only BI tool to fulfill complex and broad BI requirements in large enterprises."