Program Management Blog Posts
See the most recent Program Management related items below.
“The enterprise software market is breaking down,” proclaimed Mark Madsen at a meeting of TDWI’s Boston Chapter yesterday. “And this opens the door for open source software.”
Madsen said the business model for enterprise software vendors has switched from selling licenses to selling maintenance and support. He said maintenance fees now comprise 45% of revenues and a lionshare of profitability. This is largely because the software market has matured and consolidated, leaving customers hostage to a few big companies, Madsen said.
Eager to echo this theme, Brian Gentile, CEO of open source BI vendor Jaspersoft, said the software market is ripe for disruption. “Oracle recently reported it delivered 51% margins for the quarter, yet I hear from countless senior executives that they can no longer afford their current software maintenance contracts and are looking for options.” Gentile said these executives often report that maintenance costs consume up to 80% of their IT budget.
(The TDWI Boston Chapter will make a copy of slides at its Web site shortly.)
As prices rise, IT executives are increasingly scrutinizing exactly what they are getting for their money. Many lament the “feature bloat” of enterprise software. “When I was a BI director,” said Madsen, “we used less than 40% of the features in our BI tools.” “And while open source products may not have all the bells and whistles, they pass the ‘good enough’ test,” said Madsen.
Will Interest Translate into Sales?
Not surprisingly, interest in open source BI tools has skyrocketed as the economy plummeted. Many BI teams are looking for ways to reduce costs while still delivering value. Speaking from the audience, Doug Newton, a data warehousing manager at the Mathworks and a coordinator for TDWI’s Boston Chapter, said that open source software makes it really easy to “kick the tires” before committing to a purchase. He told the audience that he downloaded open source software from Infobright, among others, and liked what he saw, although his company has yet to start using open source tools.
Evidently, Newton is not alone. Gentile says Jaspersoft averages 250,000 downloads a month for its free community edition and has had 9 million downloads since its inception six years ago. “Most aren’t paying us anything… yet,” says Gentile. Infobright, an open source columnar database vendor, which also presented at the event, says it has had 10,000 downloads since it's inception and expects that number to jump as more people hear about the company.
To date, there has been a lot more tire kicking than usage, although many experts (including myself) predict that that will gradually change. The TDWI chapter surveyed its users and found that 55% had yet to deploy open source software. Among those that have implemented open source BI tools, 35% have deployed MySQL, 20% Pentaho, 10% Jaspersoft, 6% BIRT, and 6% Talend. Their primary reason for deploying open source BI tools is cost (75%), followed by quick to deploy (30%) and unhappiness with their incumbent BI tools (14%).
Free Isn’t For Everyone
But not all lookers are hooked. Madsen said open source isn’t for everyone. “Just because it’s free, doesn’t mean it’s right for you.” Madsen said you still need to evaluate open source tools like any other BI tool. He said “missing features,” “lack of scalability,” “need for internal expertise” and “switching costs” are the biggest reasons why companies pass on open source tools.
Most open source BI vendors are small startups, which raises the question of vendor viability. Gentile deflected this issue by pointing to the rich community of developers that surrounds each open source product. “If Jaspersoft were to disappear tomorrow, our code would live on for a very long time because there is a strong developer community that has contributed to the code and is vested in its future.”
Leading Adopters
Small companies are leading the charge into open source BI, according to Madsen, but medium and large companies are not far behind. Small companies are deploying open source BI tools on an enterprise basis while large companies are using it in departmental pockets, usually to augment existing BI tools or fill a vacuum where no BI tools exist, Madsen says.
Kevin Haas, a partner at OpenBI, a BI consultancy that helps companies build applications with open source BI tools, says most of his clients use the free community edition of open source BI products. However, the clients with the biggest applications—those deployed on an enterprise scale—implement the commercial or premium version of the tools, which offer additional functionality for enterprise deployments as well as support, scheduled release cycles, and indemnity.
While adoption by end-user organizations is growing slowly, uptake by independent software vendors (ISVs) has been sizable. Open source makes it easy for ISVs to enrich their own applications by embedding open source reporting or analytical tools into their products. In fact, Gentile said hundreds of thousands of people are using Jaspersoft without knowing it because it’s embedded in other applications. The nascent market for software-as-a-service applications has been a particularly robust market for open source BI vendors.
Inexorable Rise
If the mantra of business today is “faster, better, cheaper” then it’s inevitable that companies need to explore alternatives to traditional enterprise software. Currently, open source BI tools offer significant cost savings over established BI vendors. As open source BI tools mature and continue to undercut established players on price and flexibility, we will see an inexorable rise in the adoption of open source BI tools.
Posted by Wayne Eckerson on July 22, 20090 comments
I recently reviewed the course materials for a class titled “A Step by Step Guide to Enterprise Data Governance” taught by Mike Ferguson at the TDWI Munich conference in June. Mike did a tremendous job covering the full scope of the data governance topic.
Mike defines enterprise data governance as “the set of processes by which structured and unstructured data assets are formally managed and protected by people and technology to guarantee commonly understood trusted and secure data throughout the enterprise.”
The elements that Mike puts in the data governance bucket are: data definitions and shared business vocabulary; metadata management; data modeling, data quality; data integration; master data management; data security; content management; and taxonomy design and maintenance.
This is a big vision, and certainly elevates the discussion to its proper perspective: that is, data is a business asset and it’s the responsibility of business to oversee and manage this resource. The corollary here is that IT plays a supporting, not supervisory, role in managing the company’s data.
Central to Mike’s vision of enterprise data governance is a Change Control Board, which is the “gatekeeper” for the shared business vocabulary. This board, which is comprised of data stewards from the business, is responsible for approving requests to change, add, or decommission data items. Implicit in this is that the Change Control Board manages data names and definitions, transformation rules, and data quality rules. And these get baked into data models, BI metadata, MDM models, and taxonomies.
Given how fundamental data is to a business (whether it knows it or not), it’s imperative that a senior executive oversee the data governance team that is comprised of senior business managers and stewards. Maria Villar, owner of MCV LLC, writes, “A business data steward is a leadership position…. who understands the importance of data to their part of the business.” (See “Establishing Effective Business Data Stewards” in the spring 2009 edition of the BI Journal.)
Villar says a business data steward “understands the priorities and strategies of the business unit, commands respect within the organization, builds consensus across a varied set of business priorities; influences and drives changes to business processes, enjoys strong support from senior business leaders, can communicate to business and technical teams, and builds a diverse team of technical and business data experts.
Now that we have the verbiage straight, we have to execute on the vision. And that will keep us busy for years to come!
Posted by Wayne Eckerson on July 14, 20090 comments
Let’s face it. Most of our BI programs could use a little boost. Despite our best intentions, our BI programs aren’t getting the traction we (or our sponsors) anticipated. Performance is too slow or the data is suspect or we didn’t deliver exactly what users wanted. Or maybe, after years of disappointment, bungled communications, or cost overruns, the business simply doesn’t trust IT to do anything right.
If this describes your situation, it’s time for a quick win. You’re stuck in a perpetual negatively reinforcing loop and you need something dramatic—but quick and cheap—to get you and your team out of its rut. You need to do something that will bring a smile to their face and make them see you as an ally who can solve their problems. If your quick win succeeds, the business will shower you with money to fund more projects, including extensions to your data warehouse.
Of course, there is a catch. A quick win usually requires you to work outside of established platforms, processes, and procedures. While those things ensure that IT delivers stable, scalable solutions, they often impede quick action. A quick win often requires you to build something outside the existing architecture (especially if your existing data warehouse isn’t properly designed or supported.) As such, you need enough seniority or clout to bend the rules and make things happen.
This week I talked with a veteran BI director at a company who inherited a stalled data warehouse and a culture of distrust between business and IT. To gain credibility for the BI program and bridge the business-IT gulf, he sought a quick win. To scope his project, he met informally with business managers and executives to discuss their frustrations and needs. (As a former accountant he could “talk the talk” of business which helped immensely.) He learned that the company suffered from the “dueling spreadsheet” syndrome where executives from different departments couldn’t agree on basic sales numbers because they defined “product” differently. He got approval for a project that would track three “product” metrics through product development and launch. (Phase two will track product performance after launch.)
The project took six months from start to finish for approximately $75,000 (although this company doesn’t track costs for internally used resources. The solution enabled the company’s top executives for the first time to monitor a process that cut across departmental boundaries using standardized metrics. Needless to say, the solution was a big success and garnered the BI team much needed credibility. The caveat here is that he did not build the application on top of the existing data warehousing platform which has stringent change control processes which would have delayed deployment and increased costs. But with this quick win under his belt, the manager is now securing support and funding to overhaul the data warehouse. Eventually, he will retrofit the quick win application to run within the data warehousing environment.
The moral of the story is that a quick win can help build goodwill with the business and galvanize support that is needed to turn around a sagging data warehousing initiative. But to achieve a quick win, you often have to break the rules and work outside of standard architectures, processes, and procedures. If you are willing to take a risk, the rewards can be significant.
Posted by Wayne Eckerson on July 10, 20090 comments