BizIntelligence.TV

Bruno Aziza created an interesting initiative called BizIntelligence.TV, where he is a show host speaking with experts on BI issues. According Aziza, "BizIntelligence.TV is a weekly web-based show that allows leaders like you to hear from industry luminaries and interact with them via comments or emails. Each show lasts less than 10 minutes, and is designed to provide you and your employees with actionable best practices."

He already recorded some videos with Wayne Eckerson, John Santaferraro, Tony Scott, among others. The last video published is about Business Intelligence and Social Media, with John Myers, Shawn Rogers and Donald Farmer.

Strategies for Creating a High-Performance BI Team

Wayne Eckerson writes a good blog in The Data Warehousing Institute (TDWI)'s website, where he publishes posts about BI issues. Recently, he published two great posts regarding to create high-performance BI Team, entitled Strategies for Creating a High-Performance BI Team and Attracting and Retaining Top BI Professionals. In my opinion, create and maintain a high-performance BI Team is one of the most important steps to develop a successful BI initiative.

In the article Strategies for Creating a High-Performance BI Team, he defined seven guidelines that can help to create a high-performance BI team that delivers outstanding value to your organization:

1. Recruit the best people. The companies shouldn’t hire people just because they know a specific tool or programming language or have previous experience managing a specific task, such as quality assurance. If you need specialists like that, it’s better to outsource such positions to a low-cost provider on a short-term contractual basis. Although you should demand certain level of technical competency and know-how, you ultimately want people who fundamentally believe that BI can have a transformative effect on the business and possess the business acumen and technical capabilities to make that happen.

2. Create multi-disciplinary teams. The key to remaining nimble and agile as your BI team grows is to recreate the small, multi-disciplinary teams from your early stage BI initiative. Assign three to five people responsibility for delivering an entire BI solution from source to report. Train them in agile development techniques so they work iteratively with the business to deliver solutions quickly. With multiple, multidisciplinary teams, you may need to reset the architecture once in awhile to align what teams are building on the ground, but this tradeoff is worth it. Multi-disciplinary teams work collaboratively and quickly to find optimal solutions to critical problems, such as whether to code rules in a report, the data model, or the ETL layer. They also provide staff more leadership opportunities and avenues for learning new skills and development techniques.

3. Establish BI Governance. Once a BI team has achieved some quick wins, it needs to recruit the business to run the BI program while it assumes a supportive role. The key indicator of the health of a BI program is the degree to which the business assumes responsibility for its long-term success. Such commitment is expressed in a formal BI governance program.

Most BI governance programs consist of two steering committees that meet regularly to manage the BI initiative. An executive steering committee comprised of BI sponsors from multiple departments meets quarterly to review the BI roadmap, prioritize projects, and secure funding. Second, a working committee comprised of business analysts (i.e., subject matter experts who are intensive consumers of data) meets weekly or monthly to define the BI roadmap, hash out DW definitions and subject areas, suggest enhancements, and select products. The job of the BI team is to support the two BI governance committees in a reciprocal, trusting relationship.

4. Find Purple People. The key to making BI governance programs work is recruiting people who can straddle the worlds of business and information technology (IT). These people are neither blue (i.e., business) nor red (i.e., IT) but a combination of both. These so-called purple people can speak both the language of business and data, making them perfect intermediaries between the two groups. Astute BI directors are always looking for potential purple people to recruit to their teams. Purple people often hail from the business side where they’ve served as a business analyst or a lieutenant to a BI sponsor.

5. Aspire to Becoming a Solutions Provider. The best BI teams aren’t content simply to provision data. BI directors know that if the business is to reap the full value of the BI resource, their teams have to get involved in delivering BI solutions.

High-performance BI teams work with each department to build a set of standard interactive reports or dashboards that meet 60% to 80% of the needs of casual users in the department. They then train and support each department’s “Super Users” -- tech-savvy business users or business analysts--to use self-service BI tools to create ad hoc reports on behalf of the casual users in the department, meeting the remaining 20% to 40% of their information requirements.

6. Give Your BI Team a Name. A name is a powerful thing that communicates meaning and influences perception. Most business people don’t know what business intelligence or analytics is (or may have faulty notions or ideas that don’t conform with the mission of your team.) So spend time considering appropriate names that clearly communicate what your group does and why it’s important to the business.

7. Position BI within an Information Management Department. The BI team should be organized within a larger information management (IM) department that is separate from IT and reports directly to the CIO or COO. The IM department is responsible for all information-driven applications that support the business. These may include: data warehousing, business intelligence, performance management, advanced analytics, spatial analytics, customer management, and master data management.

Attracting and Retaining Top BI Professionals

In the article Attracting and Retaining Top BI Professionals, he wrote that to create high-performance BI teams, we need to attract the right people, and there are a couple of ways to do this: Skills Versus Qualities, and Performance-based Hiring.

Skills Versus Qualities

Inner Drive. First, don’t just hire people to fill technical slots. Yes, you should demand a certain level of technical competence. The bottom line is that you shouldn’t hire technical specialists whose skills may become obsolete tomorrow if your environment changes. Hire people who have inner drive and can reinvent themselves on a regular basis to meet the future challenges your team will face. If you need pure technical specialists, consider outsourcing or contracting people to fill these roles.

Think Big. To attract the right people, it’s important to set ambitious goals. A big vision and stretch targets will attract ambitious people who seek new challenges and opportunities and discourage risk-adverse folks who simply want a “job” and a company to “take care” of them. One way to think big is to run the BI group like a business. Create mission, vision, and values statements for your team and make sure they align with the strategic objectives of your organization. Put people in leadership positions, delegate decision making, and hold them accountable for results.

Performance-based Hiring

Proactive Job Descriptions. We spend a lot of time measuring performance after we hire people, but we need to inject performance measures into the hiring process itself. To do this, write proactive job descriptions that contain a mission statement, a series of measurable outcomes, and the requisite skills and experience needed to achieve the outcomes. If done right, a proactive job description helps prospective team members know exactly what they are getting into. They know specific goals they have to achieve and when they have to achieve them. A proactive job description helps them evaluate honestly whether they have what it takes to do the job.

Where are they? So where do you find these self-actuated people? For example, you can find on online forums, such as TDWI's LinkedIn group, and on Twitter. You can assess the quality of advice they offer.

Retaining the Right People

Finally, to retain your high-performance team, you need to understand what makes BI professionals tick. Salary is always a key factor, but not the most important one. BI professionals want new challenges and opportunities to expand their knowledge and skills. One way to retain valuable team members is to create small teams responsible for delivering complete solutions. This gives team members exposure to all technologies and skills needed to meet business needs and also gives them ample face time with the business folks who use the solution. BI professionals are more motivated when they understand how their activities contribute to the organization’s overall success. Another retention technique is to give people opportunities to exercise their leadership skills. For instance, assign your rising stars to lead small, multidisciplinary teams where they define the strategy, execute the plans, and report their progress to the team as a whole.

Wayne Eckerson defined very well in which their articles the way to create a High-Performance BI Team. Certainly companies that create their BI teams following those guidelines will have a great chance of developing a successful BI program.

Wayne Eckerson is the author of the book Performance Dashboards: Measuring, Monitoring, and Managing Your Business (I wrote a book review on this book)

Finding the Best Dashboard Product

Dashboards are powerful tools and are being increasingly adopted as the new face of Business Intelligence, because they can communicate complex information quickly, translating information into visually presentations, providing business users view the performance of business metrics at a glance. Cindi Howson published an article in Dashboard Insight, called Finding the Best Dashboard Product, where she gives some advice on how to find the best dashboard product for your company.

First of all, you’ll want to start with some education and scope definition, Cindi said. To understand the nuances of different dashboard products, educate yourself by attending industry webinars, reading product reviews by multiple analyst firms, and test driving demo applications. Read articles and books on best practices from both a design and business perspective. She recommends Stephen Few’s and Wayne Eckerson’s books. I wrote a book review of the Wayne Eckerson's book: Performance Dashboards: Measuring, Monitoring, and Managing Your Business.

She asks if you are really looking for a dashboard, a scorecard, or a visual discovery tool; and explains the difference: A scorecard contains a list of key performance indicators (KPIs), often drillable to show root cause and interdependences. A dashboard usually does not include strategy maps, but it often includes KPIs. These KPIs can be strategic ooperational. An operational dashboard has to support near real-time data updates. Strategic and management dashboards may require less frequent updates. Visual discovery tools and dashboards are interrelated. Visual discovery tools are unique in the way they allow users to interact with data in a highly visual way.

Regarding the scope definition, she comments on BI Scorecard’s 2009 Successful BI Survey, where 57% of companies have standardized on a BI platform. Most BI suite vendors have a dashboard capability. However, for many BI platforms, the dashboard modules are newer and less robust than what you might get in a specialty product. As part of your project planning, determine under what criteria you will also look at pure-play dashboard products.

Evaluating dashboard products is similar in process to evaluating BI platforms that includes an 9-step process. Below is a summary of the 9-steps process defined by Cindi:

1. Form the dashboard evaluation team: The selection team should be comprised of a cross-section of stakeholders that include both business and IT personnel. Even if your dashboard will be implemented for a single business unit or department, be sure to include stakeholders from the central BI or IT group to understand integration points.

2. Define target users and usage scenarios for the dashboard. Understand the different authoring and consumption roles. This also may help you better determine if the dashboard will be used for management-style applications or operational.

3. Refine information requirements. This step is different from mapping data elements and data sources to build the actual dashboard, and instead, considers how the data will be viewed and interacted with. This single requirement translates into a host of technical features such as:
- Multiple fact tables or data sources to populate the dashboard;
- Semi-additive measures to aggregate inventory across product groupings but not across time periods, and;
- Automatic aggregation of individual rows of data to view totals for the year or product group.

4. Define and rank selection criteria. There are multiple methods to capturing user requirements: individual user interviews, gap analysis, and brainstorming sessions, to name a few. This step can be particularly challenging if your company is new to dashboards and doesn’t really know what is possible. This is one reason why ongoing education is important to your selection process. Developing and ranking your selection criteria is an iterative process. Cindi said that her company(BI Scorecard) offers a complementary check list for dashboard features to consider.

5. Request for information (RFI). To improve the value of an RFI, define your requirements well to avoid misunderstandings between you and the vendor. Keep the RFI short, emphasizing the critical requirements that will be decisive in your selection. Finally, complement vendor RFI responses with a heavy dose of your own ongoing research.

6. Vendor scripted demos and discussion. Prepare a consistent agenda for each vendor to follow. In the agenda, allow time for a discussion of differentiators, strategic considerations, and items you may have overlooked in your requirement ranking. Based on your priorities defined in step 4, ask demo participants to score the vendors on their ability to meet the various requirements.

7. Determine the best fit. Determine the best fit using your requirements matrix defined in step 4, score the RFI responses and demo feedback. Incorporate strategic considerations, qualitative research, and customer feedback to determine which vendor(s) most closely matches your company’s requirements.

8. Proof of concept. You may only have one or two vendors that move onto the proof of concept stage. The proof of concept stage is your chance to test the tool in your environment. It is only a test, though. At this point, it’s important to keep the evaluation team focused on the critical requirements rather than endlessly playing with the software or designing live dashboards. The proof of concept may be a throwaway: its sole purpose is to confirm that the product works as you expect it to.

9. Negotiation and procurement. You’ve done your due diligence, investigated and tested solutions, and found your ideal dashboard. Don’t let sticker shock quell your enthusiasm. Make sure you understand the vendor’s pricing and packaging early in the process. Named user pricing is more ideal for smaller deployments, whereas server-based licensing is better suited to larger deployments.

"Dashboards are a must-have component to a total BI tool portfolio. Selecting the best dashboard for your company is important, but more important is to focus on the business value that the dashboard can bring to new classes of BI users", Cindi finished.

Cindi Howson wrote a good guide with important tips on how to choose a Dashboard product that meets your purposes. She also wrote a good book called Successful Business Intelligence - Secrets to making BI a Killer App (I commented about the book in a previous post)

Rethinking the role of BI

Increasingly, the companies have questioned the importance of the BI teams in the delivery of value to business and also to be more effective and strategic to organizations. Wayne Eckerson wrote a great post on the role of BI in his blog at The Data Warehousing Institute (TDWI), entitled Evolving Your BI Team from a Data Provider to a Solutions Provider. He commented about a Jill Dyche's presentation at TDWI’s BI Executive Summit, where she explained that BI teams can either serve as "data providers" or "solutions providers." Data providers focus on delivering data in the form of data warehouses, data marts, cubes, and semantic layers that can be used by BI developers in the business units to create reports and analytic applications. Solutions providers, on the other hand, go one step further, by working hand-in-hand with the divisions to develop BI solutions.

Eckerson believes that BI teams must evolve into the role of solutions provider if they want to succeed long term. They must interface directly with the business, serving as a strategic partner that advises the business on how to leverage data and BI capabilities to solve business problems and capitalize on business opportunities.

He wrote that historically, many BI teams become data providers by default because business units already have reporting and analysis capabilities, which they've developed over the years in the absence of corporate support. These business units are loathe to turn over responsibility for BI development to a nascent corporate BI group that doesn't know its business and wants to impose corporate standards for architecture, semantics, and data processing.

However, this separation of powers fails to deliver value, he commented. The business units lose skilled report developers, and they don’t follow systematic procedures for gathering requirements, managing projects, and developing software solutions. They end up deploying multiple tools, embedding logic into reports, and spawning multiple, inconsistent views of information. Most of all, they don’t recognize the data resources available to them, and they lack the knowledge and skills to translate data into robust solutions using new and emerging BI technologies and techniques, such as OLAP cubes, in-memory visualization, agile methods, dashboard, scorecards, and predictive analytics.

A corporate BI team needs to rethink its mission and the way it's organized. It needs to actively engage with the business and take some direct responsibility for delivering business solutions. To provide solutions assistance without adding budget, it will break down intra-organizational walls and cross-train specialists to serve on cross-functional project teams that deliver an entire solution from A to Z. The BI team will become more productive and before long eliminate the project backlog.

He commented about some successful cases where the companies have a high performance BI team. In one of them, for example, the BI is housed in an Information Management (IM) organization that reports to the CIO and is separate from the IT organization. The IM group consists of three subgroups: 1) the Data Management group, a data integration team that handles ETL work and data warehouse administration 2) the Information Delivery group, a BI and Performance Management team which purchases, installs, and manages BI and PM tools, provides training and solutions using reporting, OLAP, and predictive analytics capabilities; and 3) the IM Architecture group, that builds and maintains the IM architecture, which consists of the enterprise data warehouse, data marts, and data governance programs, as well as closed loop processing and the integration of structured and unstructured data.

Eckerson finished the article with the statement: "The message is clear: if you want to deliver value to your organization and assure yourself a long-term, fulfilling career at your company, then don’t be satisfied with being just a data provider. Make sure you evolve into a solutions provider that is viewed as a strategic partner to the business."

I agree with him, the BI team as a data provider can meet organizations, but the role of BI team as solution provider allows a more strategic role for BI and facilitates the delivery of value to business.

Teradata Partners User Group Conference 2009

The Teradata Partners User Group Conference 2009 happened last week (October 18-22, 2009 in Washington D.C), with some interesting announcements: an Enterprise Analytics Cloud initiative and the plan to launch a release of an Extreme Performance Appliance based on solid-state drives (SSDs). A lot of people wrote about the event, here are some links with news, posts and articles about the conference:

- This Week at the Teradata Partners User Conference - Curt Monash
- Teradata Taps the Cloud, Announces Solid-State Appliance - Doug Henschen
- More on Teradata's SSD Speedster and (Cautious) Public-Cloud Offering - Doug Henschen
- Teradata the Wise - Wayne Eckerson
- Teradata Partners: A Retrospective - Jill Dyché
- Teradata Partners - Richard Hackathorn did a very nice coverage, with several posts
- Stein tells of doom and hope for the future - Evelyn Hoover - Editor-in-Chief Teradata Magazine

Business Intelligence Usability

The Data Warehousing Institute (TDWI) published a Technology Poster entitled Business Intelligence Usability, designed by Wayne Eckerson, director of TDWI Research at The Data Warehousing Institute.

According TDWI: "Systems theory provides a "limits to growth" archetype that we can apply to BI. It consists of two adjacent feedback loops: one that inhibits growth (a negative reinforcing cycle) and another that accelerates it (a positive reinforcing cycle). Both hinge on a condition called "business outcomes" that represents the BI solution's value to the organization.

In the world of BI, each element within the feedback loops (usability, reputation, spreadmarts, sponsorship, funding, and projects) is a leverage point that BI teams can use to alter the cycle of growth or decline. Usability is perhaps the most critical and the most challenging.

TDWI's BI Usability poster details the four main components and subcomponents that affect usability. BI teams should apply these components and practices to ensure their BI initiative remains in a positive reinforcing cycle."


The four main components and subcomponents that affect usability are:
- Analysis/Design (Roles, Requirements, BI Frameworks)
- Architecture (Data, Performance, Flexibility, Delivery)
- Change Management (Management Expectations, Marketing, Leadership)
- Support (Feedback, Training, Services, Rapid Development)

You can request a free print copy (US and Canada Only) or download a PDF version, in the TDWI website.

The following companies are sponsors of this technology poster: Bi3 Solutions, Incisive Analytics, MicroStrategy and Talend.

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.

BI Predictions for 2009

In the end of last year and in the first days of this year, I have read several articles and posts about BI predictions for 2009. I mentioned in my Twitter.

I think to make predictions is not easy, mainly in Information Technology, and the history shows several examples where the predictions failed. Niels Bohr said: "Prediction is very difficult, especially if it’s about the future."


Below are some summaries and comments about posts and articles that BI experts wrote with predictions for 2009:

Ken Rudin wrote his predictions in Lucidera's blog:
- Cloud computing will cause a shift in the BI balance of power from IT to business users
- Simplicity will be the driving mantra for both consumers and vendors of BI
- The continued drive for simplicity will cause a shift towards prebuilt analytic solutions with best practices built in, and away from generic toolsets
- Data interpretation will become a significant challenge for new BI users

He concluded: "So, BI is facing new users and new challenges. With the impact of cloud computing, a shift in the balance of power for BI, additional focus and urgency on delivering simple solutions, and a few new challenges arising around data interpretation, 2009 is going to be a very interesting year for BI."


Neil Raden published his predictions in his Intelligent Entreprise's blog, in a post called Surround the Warehouse: Prediction for 2009. Below is the summary of his predictions:
- The data warehouse has been positioned as the sole source of analytical data in organizations, but that is changing.
- BI tools like Microstrategy have to retool to be able to query multiple sources to satisfy a single query .
- There will be a lot of talk about this and the use of unstructured content, too, but I don't see that happening in '09.
- There will be a lot of noise about the Cloud and x-aaS (SaaS, PaaS, DaaS, etc.), but I don't see that gaining as much actual revenue as it will airtime
- The organizations may see the potential utility of revivifying their data warehouse strategy, but they just don't know how to do it. So despite all of the innovative and useful things the industry comes up with, the data warehouse legacy is like a big boat anchor.

He finished with: "And that's why I see the "surround strategy" of augmenting BI with operational data while leaving the data warehouse in place as the best opportunity right now."


Ted Cuzzillo wrote a post in Enterprise Systems, and said: "A variety of sources tell me that the financial crisis will be 2009's primary driver, as trends from early this year accelerate."

His predictions are:
- The few big tools will start giving way to many small tools
- Business users will take more of BI back from analysts
- Analytics will gain new importance
- BI's focus will sharpen on the human factor
- BI will surge in the mid-market


James Taylor wrote his Predictions for 2009 in his blog on December, focused on Decision Management, and also compared with some BI predictions (Ken Rudin and Ted Cuzzillo, both commented above):
- Cloud computing will impact decision management
- More use of analytics by systems rather than people
- More focus on rules from application and platform vendors
- More business rule vendors
- More rules in Business Process Management
- Business rules to decision management
- Pre-built decisioning components
- Simulation and scenario management
- More business user control


IDC published its Predictions for 2009, I already commented in a previous post.


Colin White wrote a post called BI Predictions for 2009: What Ever It Takes to Get the Job Done, in his B-Eye-Network's blog. I highlight:
- The business intelligence (BI) marketplace has often been immune to industry downturns. This is because companies often turn to BI in difficult times to help them identify areas where revenues can be increased and costs can be reduced. This is especially the case in front office sales, marketing, and support organizations. Given the potential size of the coming downturn, however, can even BI be immune? I doubt it.
- The BI solutions that will have the most impact in 2009 will be those that provide IT and business users quick and low-cost approaches for discovering, accessing, integrating, analyzing, delivering and sharing information in a way that that helps business users become more productive and more self-sufficient.
- open source software, BI software-as-a-service, low-cost application appliances, search, the integration of BI with collaborative and social computing software, rich internet applications, web syndication, and data and presentation mashups.
- line-of-business IT rather than the enterprise IT organization. This could result in a turf war where enterprise IT tries to control and govern the use of these new technologies by the business.


Krish Krishnan commented about data warehouse appliances, in a post in his B-Eye-Network's blog:
"my predictions about data warehouse appliances going mainstream is indeed happening. Year 2009 will be a significant year for all types of data warehouse appliances and their vendors"


Timo Elliott wrote a different kind of prediction, called Why Will 2009 be a Great Year for Business Intelligence?, where he analyzed the situation, based on data from IDC, Gartner and others articles, and divided in topics:
- The Economy is Awful
- IT Spending is Still Increasing
- Business Intelligence Spending Even More Robust
- Which Vendors Will Do Best?

His Conclusion: "So despite a weak economy, IT spending growth remains positive. Within IT, software spending is the healthiest. And within software spending, BI is a top priority."


Lyndsay Wise wrote a post in his blog, I highlight:
"However, one good thing about business intelligence and performance management in general is that because of the promises of helping increase performance while potentially lowering costs, organizations that tend to over spend and under perform will need to account for their spending more than in the past. Consequently, the role of BI may become more important in many organizations..."


Search Data Management published yesterday an excellent article called Experts forecast business intelligence market trends for 2009, by Jeff Kelly, where Wayne Eckerson, James G. Kobielus and Gartner's analysts shared their BI forecasts.

Wayne Eckerson, Director of research and services for The Data Warehousing Institute (TDWI):
- Analytic database platforms go mainstream
- Open source BI gets evaluated
- Packaged analytic applications gain traction
- Software as a Service (SaaS) picks up in the midmarket
- Next-generation dashboards emerge
- Analytical literacy improves
- More analytical sandboxes come to the fore
- BI goes green
- Advanced visualization corrals BI
- Event-driven analytic platforms hit the scene

James G. Kobielus, Senior analyst at Cambridge, Mass.-based Forrester Research covering BI and data warehousing:
- BI moves into the cloud
- BI adopting Web 2.0 development paradigm
- BI growing more federated
- BI evolving into advanced analytic applications

Gartner Inc. - Various Gartner Inc. analysts covering BI, including Bill Hostmann, Kurt Schlegel, Mark A. Beyer, Rita L. Sallam, Bill Gassman, Nigel Rayner, Neil McMurchy, Neil Chandler, Matthew W. Cain:
- By 2012, business units will control at least 40% of the total budget for BI
- Through 2012, more than 35% of the top 5,000 global companies will regularly fail to make insightful decisions about significant changes in their business and markets
- By 2010, 20% of organizations will have an industry-specific analytic application delivered via SaaS as a standard component of their BI portfolio
- In 2009, collaborative decision making will emerge as a new product category that combines social software with BI platform capabilities
- By 2012, one-third of analytic applications applied to business processes will be delivered through large-grained application mashups.


Despite the economic crisis, and based on predictions of those experts, I think 2009 will be a good year for Business Intelligence. I'm optimistic about it.


P.S.: The Crystal Ball picture is just for illustrate the post, I know that the experts mentioned here made their predictions based on data, information, and their expertise and knowledge of BI market.

Eight business technology trends to watch

The McKinsey Quarterly, the business journal of McKinsey & Company, published recently a good article called Eight business technology trends to watch, where they talk about the eight technology-enabled business trends will really matter.

They start the article talking that technology alone is rarely the key to unlocking economic value: companies create real wealth when they combine technology with new ways of doing business.

They divide the eight trends in three groups: Managing relationships, Managing capital and assets, and Leveraging information in new ways. They mention several books as further reading in each trend, these are good trends and also a very good list of reference for further reading.

Managing relationships
1- Distributing cocreation
The Internet and related technologies give companies radical new ways to harvest the talents of innovators working outside corporate boundaries.
Further reading:
Yochai Benkler, The Wealth of Networks: How Social Production Transforms Markets and Freedom, New Haven, CT: Yale University Press, 2006.
Henry Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology, Boston: Harvard Business School Press, 2003.
James Surowiecki, The Wisdom of Crowds: Why the Many Are Smarter than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations, New York: Doubleday, 2004.
Eric von Hippel, Democratizing Innovation, Cambridge, MA: MIT Press, 2005.

2- Using consumers as innovators
Consumers also cocreate with companies, and the differences between the way companies cocreate with partners, on the one hand, and with customers, on the other, are so marked that the consumer side is really a separate trend. These differences include the nature and range of the interactions, the economics of making them work, and the management challenges associated with them.
Further reading:
C. K. Prahalad and Venkat Ramaswamy, The Future of Competition: Co-Creating Unique Value with Customers, Boston: Harvard Business School Press, 2004.
Don Tapscott and Anthony D. Williams, Wikinomics: How Mass Collaboration Changes Everything, New York: Portfolio Hardcover, 2006.

3- Tapping into a world of talent
Top talent for a range of activities—from finance to marketing and IT to operations—can be found anywhere.
Further reading:
Richard Florida, The Rise of the Creative Class: And How It’s Transforming Work, Leisure, Community, and Everyday Life, New York: Basic Books, 2004.
Daniel H. Pink, Free Agent Nation: How America’s New Independent Workers Are Transforming the Way We Live, New York: Warner Books, 2001.

4- Extracting more value from interactions
Companies have been automating or offshoring an increasing proportion of their production and manufacturing (transformational) activities and their clerical or simple rule-based (transactional) activities. As a result, a growing proportion of the labor force in developed economies engages primarily in work that involves negotiations and conversations, knowledge, judgment, and ad hoc collaboration—tacit interactions, as we call them.
Further reading:
Bradford C. Johnson, James M. Manyika, and Lareina A. Yee, “The next revolution in interactions,” mckinseyquarterly.com, November 2005.
Scott C. Beardsley, Bradford C. Johnson, and James M. Manyika, “Competitive advantage from better interactions,” mckinseyquarterly.com, May 2006.
Thomas W. Malone, The Future of Work: How the New Order of Business Will Shape Your Organization, Your Management Style, and Your Life, Boston: Harvard Business School Press, 2004.

Managing capital and assets
5- Expanding the frontiers of automation
Companies, governments, and other organizations have put in place systems to automate tasks and processes: forecasting and supply chain technologies; systems for enterprise resource planning, customer relationship management, and HR; product and customer databases; and Web sites. Now these systems are becoming interconnected through common standards for exchanging data and representing business processes in bits and bytes. What’s more, this information can be combined in new ways to automate an increasing array of broader activities, from inventory management to customer service.
Further reading:
John Hagel III, Out of the Box: Strategies for Achieving Profits Today and Growth Tomorrow through Web Services, Boston: Harvard Business School Press, 2002.
Claus Heinrich, RFID and Beyond: Growing Your Business with Real World Awareness, Indianapolis, IN: Wiley Publishing, 2005.
Jeanne W. Ross, Peter Weill, and David C. Robertson, Enterprise Architecture as Strategy: Creating a Foundation for Business Execution, Boston: Harvard Business School Press, 2006.

6- Unbundling production from delivery
Technology helps companies to utilize fixed assets more efficiently by disaggregating monolithic systems into reusable components, measuring and metering the use of each, and billing for that use in ever-smaller increments cost effectively. Information and communications technologies handle the tracking and metering critical to the new models and make it possible to have effective allocation and capacity-planning systems.
Further reading:
Robert D. Hof, “Jeff Bezos’ risky bet,” BusinessWeek, November 13, 2006.

Leveraging information in new ways
7- Putting more science into management
Just as the Internet and productivity tools extend the reach of and provide leverage to desk-based workers, technology is helping managers exploit ever-greater amounts of data to make smarter decisions and develop the insights that create competitive advantages and new business models. From “ideagoras” (eBay-like marketplaces for ideas) to predictive markets to performance-management approaches, ubiquitous standards-based technologies promote aggregation, processing, and decision making based on the use of growing pools of rich data.
Further reading:
Thomas H. Davenport and Jeanne G. Harris, Competing on Analytics: The New Science of Winning, Boston: Harvard Business School Press, 2007.
John Riedl and Joseph Konstan with Eric Vrooman, Word of Mouse: The Marketing Power of Collaborative Filtering, New York: Warner Books, 2002.
Stefan H. Thomke, Experimentation Matters: Unlocking the Potential of New Technologies for Innovation, Boston: Harvard Business School Press, 2003.
David Weinberger, Everything Is Miscellaneous: The Power of the New Digital Disorder, New York: Times Books, 2007.

8- Making businesses from information
Accumulated pools of data captured in a number of systems within large organizations or pulled together from many points of origin on the Web are the raw material for new information-based business opportunities.
Frequent contributors to what economists call market imperfections include information asymmetries and the frequent inability of decision makers to get all the relevant data about new market opportunities, potential acquisitions, pricing differences among suppliers, and other business situations. These imperfections often allow middlemen and players with more and better information to extract higher rents by aggregating and creating businesses around it.
Further reading:
Hal R. Varian, Joseph Farrell, and Carl Shapiro, The Economics of Information Technology: An Introduction (Raffaele Mattioli Lectures), New York: Cambridge University Press, 2004.
Carl Shapiro and Hal R. Varian, Information Rules: A Strategic Guide to the Network Economy, Boston: Harvard Business School Press, 1999.

They concluded the article with: "Creative leaders can use a broad spectrum of new, technology-enabled options to craft their strategies. These trends are best seen as emerging patterns that can be applied in a wide variety of businesses. Executives should reflect on which patterns may start to reshape their markets and industries next—and on whether they have opportunities to catalyze change and shape the outcome rather than merely react to it."

This is a good article, and this is also a very good list of reference for further reading, but I would like to add two interesting books in the list:

- trend 5- Expanding the frontiers of automation
James Taylor and Neil Raden, Smart Enough Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions, Prentice Hall PTR , 2007.


- trend 7- Putting more science into management
Wayne W. Eckerson, Performance Dashboards: Measuring, Monitoring, and Managing Your Business, Wiley, 2005.


I think with these two books, the list is more complete.

DM Review presents live Web broadcast about Performance dashboards

Today, July 17th, at 3:00 PM ET, will happen a live Web broadcast presentation about Performance dashboards, provided by DM Review, in its initiative called DM Radio.

The subject is: What's Behind the Dashboards, hosted by Eric Kavanagh with Jim Ericson


According DM Review:
"Performance dashboards deliver what executives want and need: timely and useful indicators of corporate performance. Yet the beauty of dashboards is anything but skin deep. The magic that drives these decision-enabling tools lies beneath the surface in the carefully-constructed integration that delivers critical data.

Tune into this episode of DM Radio to hear some of the industry’s leading visionaries discuss the trends, tactics and technologies behind dashboards. We’ll hear from TDWI Research Director Wayne Eckerson, who wrote the book, Performance Dashboards: Measuring, Monitoring and Managing Your Business; we’ll also hear from Shadan Malik, CEO of iDashboards; and a special guest to be announced.

Attendees will learn:
- Data sources of key performance indicators
- Tips for designing a sustainable integration infrastructure
- What to look for in a dashboard product
- How savvy Web developers can use a browser as a dashboard
- How dashboards are really used in day-to-day operations."

In the DM Review website, you can register for this live Web broadcast.

The DM radio is an excellent initiative by DM Review to spread knowledge in interesting subjects, with expert professionals.

Performance Dashboards: Measuring, Monitoring, and Managing Your Business

Performance Dashboards: Measuring, Monitoring, and Managing Your Business - Wayne W. Eckerson

In the preface of the book, Wayne Eckerson wrote his original focus to write this book was Performance Management, but in his initial research he realizes PM meant different things to different people. Just as well that he decided to write about performance dashboards, because he did a great job and wrote an exceptional book.

The book is well defined, he divides into three sections. In the part one, "The Landscape for Performance Dashboards", he explains in details what are performance dashboards, the role of Performance Management and Business Intelligence, and also the architecture and the framework to implement a Performance Management.

He shows performance dashboards is more than just a screen with fancy performance graphics and also shows why is very different from plain dashboards or scorecards.

A performance dashboard is a multilayered application built on a business intelligence and data integration infrastructure that enables organizations to measure, monitor, and manage business performance more effectively. Performance dashboard is a powerful agent of organizational change. The performance dashboard is considered the new face of BI, because can transform BI from a set of tools used by business analysts and power users into information available to everyone in a company.

He defines performance dashboards as three applications in one, woven and working together:
- monitoring application: convey information at a glance
- analysis application: let users analyze exception conditions
- management application: improve alignment, coordination and collaboration

He also shows performance dashboards have three layers or views of information:
- summarized graphical view
- multidimensional view
- detailed reporting view


He defines three types of Performance Dashboard: strategic, tactical and operational. Each applies the three applications and layers described above in slightly different ways.

In the Part two, "Performance Dashboard in action", he explains in details the three types of Performance Dashboard: strategic, tactical and operational, and how to implement which one, with cases study detailed, using real-world examples.

In the Part Three, called "Critical Success Factors: Tips from the Trenches", there are recommendations and guidance from dozens of performance dashboards projects that the author has researched, and define how to start the project, how to create effective metrics, how to design effective dashboard screens, how to link and integrate performance dashboards, how to align business and IT, and the strategies to ensure adoption and manage performance.

There is an useful appendix with the criteria for evaluating performance dashboards.

This is an exceptional book, that defines and explains which the role of Performance Dashboards as factor of success to focus business people to drive to a well managed performance of their business.