Daily, we hear about more layoffs and downsizing. Along with this comes scrutiny of all internal budgets including learning and development. Companies are not lopping off learning as drastically as in previous recessions. Companies know that skilled employees make their business successful. But, at the same time, some budget cuts are inevitable. This is where eLearning comes in. Most organizations already have some eLearning but they are not using the full capabilities like the rapid eLearning tools or the virtual classroom from their Web conferencing provider, or the informal learning using collaboration tools like blogs, podcasts, and wikis.
Yes, classroom training will be cut since travel costs are a quick savings. But this doesn’t mean you can’t have effective learning . . . via a different approach! This is good time to take stock of what tools and features you have but haven’t used from your LMS or your online meeting providers and exploit these online synchronous and asynchronous forms of learning.
I am taking stock too through a survey to determine what companies are doing about developing or acquiring content, using learning technology and tools, and introducing Web 2.0 for learning. I want to get your input. The survey is linked to this blog (you may access it here) and I encourage you to complete it or send the survey to the most appropriate person in your company. The data from this survey will appear in my research in the coming months.
The integration software market is a busy place, with technologies such as ETL (extract, transform, and load), ESB (enterprise service bus), CDC (change data capture) and IC-BPMS (integration-centric business process management suites) crowding the landscape. The technologies within this "integration acronym buffet" address a common requirement: they either physically or virtually deliver information from point A to point B with integrity. (For more information on the variety of integration options available, see "2009 Update: Evaluating Integration Alternatives.") Some approaches, such as ETL and ESB, have developed into multi-billion dollar stand-alone markets. But other integration alternatives, while valuable, haven't survived as well as a standalone market segment. EII (enterprise information integration) is one example of this.
In a nutshell, EII -- also often referred to as data federation -- is an umbrella term that arches over a collection of technologies and best practices for providing custom views into multiple data sources as a way of integrating data and content for real-time read and write access by applications. Though integration professionals have been using EII for many years in niche applications, it has struggled to find the ideal scenarios in which it has a clear advantage over other integration approaches.
Where enterprise data warehousing (EDW) is concerned, EII provides an on-demand, decentralized "virtual" alternative, but has not dislodged ETL's role in the centralized, batch-oriented EDW architectures that predominate throughout the corporate world. For real-time and operational business intelligence (BI) requirements, EII supports low-latency queries across distributed data environments, but it competes against other approaches such as trickle-feed ETL and CDC. And for real-time read/write access across disparate databases, EII competes against more versatile approaches such as ESB and information as a service (IaaS).
In more recent years, EII has found adoption as an adjunct to enterprises' core EDW, BI, and transactional computing integration strategies--not as the main approach. When they implement EII, information architects generally use this technique sparingly, and primarily for tactical, project-based requirements -- not as an enterprise standard. So it’s no surprise that a stand-alone EII tools marketplace has failed to develop, or that most EII vendors have slowly disappeared via acquisition into larger BI, EDW, data integration, or database platforms such as Business Objects's, Red Hat's, and Sybase's acquisitions of Medience, MetaMatrix, and Avaki, respectively. Meanwhile, the remaining EII pure-play vendors such as Composite Software have wisely shifted their solutions and messaging towards a broader focus on SOA (service-oriented architecture) and IaaS.
Ironically, as the EII-branded market continues to consolidate and merge with other data management markets and essentially disappear as a recognized standalone segment, EII's earliest goal of enabling virtual data warehousing may now be poised to become reality. As the complexities of today's business operations increasingly requires real-time decision making, real-time data warehousing options are once again being discussing by data architects across industries. As Forrester analyst James Kobielus discussed in his research, "Federation: Sharpen Your Focus On Vast Constellations Of Data," multiple use cases have arisen where leveraging EII tools and techniques may be the best way to deliver information insights in a complex, heterogeneous environment. And federated use cases go beyond data warehousing and business intelligence. Architects designing solutions to manage complex enterprise content management (ECM) and master data management (MDM) strategies also consider federation as a legitimate means to bridge information siloes.
Does this mean the standalone EII market is ready for a comeback? Not quite. What it does mean is that EII may have finally found its place in the software world. Vendors building data management solutions focusing on areas such as IaaS, SOA, BI, data integration, data warehousing, and MDM should continue to invest in seamlessly integrating EII-like federation capabilities as an embedded integration technique available to their customers. An executive at a data integration software company recently shared with us his perception of how their customers have evolved to think about EII: "What was once called EII are really just a set of integrated access, abstraction, federation, and delivery capabilities behind (a) Virtual Data Federation as a complementary data integration tool in the DI project toolbox and (b) IaaS as an enterprise data virtualization architecture approach for the enterprise." So integration architects should take a step back and consider all of the options within the integration acronym buffet not as competing tools, but complementary techniques that must build the foundation for your organization’s cross-enterprise integration competency.
Now that we've published my Forrester Wave for Enterprise Data Warehousing (EDW) Platforms, you'd think I can breathe easier. Far from it. No matter how carefully one words a report, there is always the potential for misunderstanding. I'm already seeing some of that surrounding the notion of what, exactly, constitutes an EDW "niche vendor."
For starters, that term--"niche vendor"--is not in my vocabulary, and not in my Wave. In the Wave, I used the standard Forrester methodology, which, based on transparent criteria and evaluation scores, distinguishes among "Leaders," "Strong Performers," "Contenders," and "Risky Bets." Rest assured that all seven of the vendors I evaluated--Teradata, Oracle, IBM, Microsoft, SAP, Netezza, and Sybase, are either "Leaders" or "Strong Performers."
We have no formalized definition of "niche vendors" in the Wave. Instead, all of the vendors in my Wave should be understood as "enterprise" data warehousing platform providers. The qualifier "enterprise" indicates that they are all addressing a wide range of enterprise information and knowledge management (I&KM) requirements for data warehousing. However, some of them are better positioned at this time to target a broader addressable market than are others, as evidenced by the details of their current offerings, strategies, and market presence. The vendors that are addressing the widest range of EDW marketplace requirements and opportunities scored higher in the Wave.
I think the crux of the misunderstanding lies in my acknowledgement that there are in fact "niche" segments of the EDW platforms market, and that some vendors have differentiated themselves well in those niches without, necessarily, being locked into them permanently. I refer to "niche markets," "niche solutions," and "niche deployments," but never "niche vendors." I do use "niche player" at one point, but that's to reflect a vendor's strategy, not its destiny.
To reflect that nuanced understanding, I placed the following qualifying language at the intro to the "Strong Performers" section:
"Strong Performers have proven themselves in particular niches, primarily among large enterprises but also in a growing range of midmarket deployments. These vendors' substantial, loyal, and longtime customer bases suggest plenty of opportunity for well-differentiated niche products in the multifaceted and innovative EDW platforms market. I&KM professionals can rest assured that these and other substantial EDW platform vendors have the staying power, resources, and vision to weather the ups and downs in today’s turbulent IT market.
What exactly, then, is an EDW "niche solution"? Actually, before I answer that, let's discuss what's not a niche solution. Essentially, any solution portfolio that is well-suited to addressing the broadest range of EDW requirements--and in fact has production customers to demonstrate a vendor's success at doing just that--is the polar opposite of a niche solution.
In order to be "well-suited" in this regard, an EDW solution portfolio should have the comprehensive functionality, flexibility, scalability, and affordability to qualify for short-listing by I&KM professionals with the broadest range of requirements. More than that, the vendors should demonstrate considerable success in selling their solutions into the full range of customer size classes, verticals, and geographies.
It's one thing to state, in the abstract, that one's EDW solution portfolio has universal appeal, but quite another to demonstrate that a critical mass of real customers across all segments have found it appealing enough to put their money down and standardize on it. A vendor's pricing, licensing, packaging, sales, marketing, distribution, support, and professional services are critically important for them to achieve this degree of universal--or at least widespread--adoption. Also, sometimes, what holds a vendor back from broad appeal is a marketplace perception issue that may be several years out of date, but is still a tangible competitive handicap.
One way of interpreting the Wave is that the higher-scoring vendors have the least "niche-y" solutions on the market. Of course, a niche may be a large one, as measured by the number of actual or potential customers, but it's still a potential competitive handicap if a vendor is having difficulty breaking out of it--or doesn't realize it hampers their growth prospects. And a niche may be a matter of a vendor's sales strategy--e.g., selling their DW appliance primarily as an OLAP data-mart accelerator--that has paid off in sales momentum but is becoming a confining pigeonhole. Or the niche may be an architectural specialty--such as a columnar database--that has great strengths for particular EDW-node deployment roles but may be suboptimal for other roles.
Sometimes, vendors position their niche approach as the future of the market as a whole, and as the answer to every EDW requirement that every user might have. And, sometimes, the market disagrees, as expressed through customer demand, or the lack thereof, leaving vendors mystified as to why they're not becoming the pre-eminent market leader.
And sometimes, an emerging niche (i.e., vendor growth-potential-limiting constraint) may not be apparent to the vendors that, heretofore, have assumed that it constitutes the entire EDW market. One such emerging niche is for EDW solutions that have not yet attained petabyte-scale in production customer deployments, in demo environments, or in the lab. In fact, that niche includes the majority of today’s EDW solutions, and the vast majority of I&KM requirements. Some vendors (read the Wave to see who) have moved beyond that sub-petabyte niche, or are just now traversing that threshold, or are soon likely to. Interestingly, most vendors in the EDW Platforms Wave offer a credible case that they'll soon attain full petabyte-scalability, but only a few had actual customer deployments showing that they're already there.
But none of this is to be read as vendor destiny. The Wave also scores the vendor's corporate and product directions, and their momentum in selling into customer-size, vertical, and geographic segments outside their installed base. All of this is to be understood as a vendor attempting to break out of whatever niche(s) its solutions may be concentrated in.
And, indeed, that's a key take-away from the Forrester Wave for EDW Platforms. All seven of these vendors are rapidly evolving out of the various niches in which their solutions have been deployed. That includes petabyte-scalability. Consequently, you shouldn’t assume--simply because a vendor didn’t demonstrate "well-beyond" one-petabyte scalability for the purpose of gaining a "5" on that Wave criterion in Q1 09--that the vendor won’t able to demonstrate that capability for you, in their lab, next week.
The EDW market is evolving extraordinarily fast. Clearly, we’ll need to update the EDW Platforms Wave in the coming year or so to keep pace.
Okay, I have to admit it: “My name is Clay and I am a political junkie.” They say the first step to recovery is admitting that you have a problem. I am also a policy geek and I love watching C-SPAN.By now, I’m sure you’re wondering “What the heck does this have to do with I&KM pros?”
I believe last Wednesday’s House Hearing on Madoff and the SEC should be required viewing for all I&KM Pros – particularly for those of you that want to understand how BPM can keep you from getting fired.
If you caught the hearing in its entirety on C-SPAN (I had a front-row seat on my couch, thanks to being taken down by a nasty flu-like virus last Wednesday – this will become relevant a little later), you saw the whistleblower, Harry Markopoulos, rip into the SEC, FINRA, and other industry regulators. Mr. Markopoulos raised numerous red flags to the SEC about Madoff’s Ponzi scheme over an eight year period.
Pulling no punches, Mr. Markopolos called the SEC "incompetent" and FINRA "crooks" to their faces – senior representatives from both organizations were in the audience listening to the hearing and waiting for their opportunity to respond. Following Mr. Markopoulos’s testimony, I thought "Hey, its time to get some popcorn, the fight’s on!" Then I recalled why I was home in the first place – sick, right?
After a little break, the House brought out the SEC heads for their grilling. I was particularly taken by the grilling given to the heads of SEC Compliance and SEC Enforcement. My naïve assumption was that these people would have reasonable answers about why Madoff’s $50B Ponzi scheme fell through the cracks. Boy, was I wrong! They had not a single coherent answer. In fact their collective answer was (I am summarizing here for them): "I don’t understand my own process."
Rep. Gary Ackerman completely went off on all of the SEC heads testifying at the hearing. Based on Ackerman’s response, I hope all of the SEC heads started job hunting immediately following the hearing. There is no doubt left in my mind that they will all be fired summarily (looks like I moved too slow on getting this blog post out).
After watching the hearing, I thought to myself "These people could have avoided being fired if they had simply implemented a good BPM solution." Here are my Top 3 suggestions on how BPM could have kept them from getting fired (or at least kept them from appearing incompetent on C-SPAN):
Job Saver #1, Transparency – During the hearing, the SEC was grilled numerous times regarding specifics on how their compliance and enforcement processes worked. For example, several congressmen asked "How many red flags does it take before action is taken?" None of the SEC heads could answer this question. Implemented properly, BPM provides the transparency needed to answer these types of questions. Or at least it allows you to say, "We did not consider red flags as part of the process, and here is why…" The other benefit of BPM is that the SEC's visual process for enforcement and compliance could have been published on the web for all to see. Then, the SEC heads could have answered, "…as outlined in our current process, published on the Web…" This would have helped them demonstrate the greatest degree of transparency. I believe there is an opportunity here for process-wiki vendors (e.g., Lombardi Blueprint, Itensil, etc.)...
Job Saver #2, Business Rules – Many of the congressmen also asked about escalation rules for investigations in addition to several other "rules" related failures that allowed Madoff’s scheme to go undetected. My immediate thought was that most of the rules discussed could easily have been captured by a rules engine to automatically escalate and route processes accordingly. One of the congressmen asked "Do you give additional weight to tips coming from highly credible sources, like Mr. Markopoulos?" The SEC responded, "Yes, we do. However, we have to look at the history of the source." The SEC's response left me thinking this is not a "rules" governed process – in other words "you are credible, if we think you are credible." No, there should be documented and institutionalized rules that govern whether a source is credible.
Job Saver #3, Workload Management – Finally, one of the congressmen asked "How many fraud tips do you get in a given year?" The SEC response: "We get over 100,000 and there is no way we can chase down each and every one…" I thought this was the most telling response. In other words, the SEC was saying "We could not catch Bernie Madoff because we had too many fraud tips coming in..." Using BPM, they could have automatically identified tips that had a high chance of fraud and routed these tips to be vetted by staff members with the appropriate expertise.
I&KM pros should take note! If you have internal processes that are compliance-related (or otherwise), BPM is ideally suited to provide the transparency needed to make you look good in front of Congress, ahem, I mean key stakeholders, that have hard charging questions when things go haywire.
After the House Hearing on Madoff and the SEC wrapped up, I finally decided I was sick enough to take myself to the doctor. However, instead of going to my family practitioner, I decided to check out the “Minute Clinic”, CVS’s in-store quick clinic. My experience there was the exact opposite of the fiasco I had just seen on C-SPAN. I left the doctor thinking "The SEC could learn a thing or two from the Minute Clinic about how good processes work…"
In my next blog I will share more about my positive process experience at the "Minute Clinic"…
Today we published the first Forrester Wave™ specifically focused on Enterprise Data Warehousing (EDW) Platforms. The final published report is now available on Forrester’s website to clients. Information and knowledge management (I&KM) professionals will find it a timely and actionable study of the leading EDW platform vendors: Teradata, Oracle, IBM, Microsoft, SAP, Sybase, and Netezza. I urge you to download and read it, and then engage me, the author-analyst, in inquiries and advisories to help you apply it to your EDW initiatives.
The key takeaway from this Wave is that scalability, flexibility, and affordability are the dominant requirements in today’s budget-stressed EDW platforms market. I&KM professionals are under the gun, trying to keep EDW and business intelligence (BI) costs under tight control while preserving the flexibility to grow and repurpose these investments to support an ever-changing array of decision-support requirements. Hence, an EDW platform--to score well in the Wave--should address the following high-bar requirements:
Extremely scalable: The EDW platform should be scalable to support petabytes of usable data; thousand-plus distributed compute/storage nodes; tens of thousands of concurrent users and queries; many terabytes of daily or continuous data loads; and expanding mixed workloads of reporting, query, OLAP, in-database analytics, real-time analytics, ETL, data cleansing, and other transactions. It should support this extreme scalability through scale-out, shared-nothing MPP, optimized appliances, optimized storage, dynamic query optimization, and mixed workload management technologies.
Extremely flexible: The EDW platform should be flexible to support diverse applications, including business intelligence, online analytical processing, data mining, predictive analytics, text analytics, closed-loop business process management, and complex event processing; and various deployment roles, including multi-domain data hubs, subject-specific data marts; operational data stores, master data management hubs, staging nodes, analytic data marts, multi-temperature hierarchical storage management and archiving, and source and/or target repository in data federation environments. It should support this extreme flexibility by being fluid, adaptive, and virtualized; enabling data to be transparently persisted, in diverse physical and logical formats, to an abstract, seamless grid of interconnected memory and disk resources; and delivered with subsecond delay to consuming applications; and ensuring application service levels through an end-to-end, policy-driven, latency-agile, distributed-caching and dynamic query-optimization memory grid.
Extremely affordable: The EDW platform should be affordable for all customer segments and use cases. It should support this extreme affordability through flexible packaging/pricing, including licensed software, modular appliances, and “pay as you go” subscription-based SaaS/cloud offerings.
EDW platforms vendors that can’t address these key requirements--now or in their enhancement road maps over the coming 2-3 years--will not survive in this very competitive arena.
As noted above and in my blog post last week, scalability, performance, and optimization are perhaps the most important criteria in today’s EDW market. And, of course, they are quite difficult to nail down into a single yardstick that does justice to different vendors’ approaches. Nevertheless, I believe this Wave accomplishes that. I have boiled down “scalability, performance, and optimization” (SPO) into a single criterion that defines five profiles (from 5= most scalable to 1 = least scalable), focusing on the degree of parallelism in the underlying architecture.
For each of the vendors in this Wave, I got a deep dive on their SPO architecture, but I didn’t stop there. I asked each vendor for reference customers, and conducted a structured interview with each. I asked each for a list and description of their largest production customer deployments. And I asked each for published benchmarks, plus all the supporting info on how the test environments, scenarios, and criteria. In other words, I applied the standard Forrester Wave methodology.
Essentially, the customer deployment and benchmark data corroborated whether a vendor in fact earned the particular SPO score associated with their architectural approach. Clearly, there were plenty of gray areas. Also, quite clearly, vendors had plenty of comments on the definitions of the SPO scales, and on where they fell on this spectrum. And, of course, many pointed out that being scored, say, a “2” rather than a “4” or “5” didn’t necessarily mean they were slower, less efficient, or incapable of processing various EDW and BI workloads. It also didn’t mean that they couldn’t, in practice and in customer deployments, push the scalability and speed envelope that one would associate with their architecture. Architecture isn’t destiny, but it definitely sets SPO constraints, which is the whole point of the scoring on this criterion in this Wave.
All the vendor feedback was excellent and helped me tweak and tune the scale to fit the EDW market’s current and emerging state of the art. With that said, here are the final SPO scales in this Wave:
5 = scale out through shared-nothing massively parallel processing (MPP), up to 100-1000+ storage/compute nodes in single-tier grid of compute/storage nodes, and well beyond 1000s of terabytes (TBs) of online, usable production data across distributed deployment
4 = scale out in the storage tier to 100-1000+ nodes and/or up to around 1000 TBs of online, usable production data, but lacking support for single-tier-grid shared-nothing MPP and/or lacking the ability to scale out to 100-1000+ nodes in the compute tier
3 = scale-out through shared-nothing MPP and/or clustering, up to 2-100 storage and/or compute nodes and up to 100s of TBs of online, usable production data across distributed deployment
2 = scale-up through symmetric multiprocessing (SMP), and up to 10s of TBs of online, usable production data, and scale-out in a clustered deployment of 2-99 compute nodes
1 = scale-up through SMP and up to 10s of TBs of online, usable production data on a single-node deployment
To see how the vendors ranked, you’ll need to read the Wave. Or engage me in an inquiry or advisory. Or, preferably, both.
I recently read an article about how journalists are having to change, and change fast. The gist of the article (sorry but I can't remember where I read it) is that the good old days of writing on deadline and having 24 hours or 12 hours to get your story done are dead and gone. Or as Kathleen Parker recently wrote in The Washington Post "Let me be the first in the new year to declare that the mainstream media are dead" (January 2, 2009). She added "The mainstream media aren't really dead, of course. The industry has merely transmogrified, splintered into a billion little reflections of its former self. One-fifth of the world's nearly 7 billion people are now Web-capable -- all reporting, opining, interacting, twittering, digging and blogging."
I stopped for a moment while reading this and thought it through, because in many ways they are talking about me. Heck, I'm a journalist. It's actually more complicated than that. As my husband says, he just hates it when someone at a cocktail party casually asks, "Jim, what does your wife do?" At that point he either launches into a long description of what he thinks I do (he's actually not completely sure) or, increasingly, he just says "she's a Vice President at Forrester Research," gives a little smile, and leaves it up to the listener to figure that one out. But, if I decompose my job, I spend some of my day managing, some of it writing (a la journalism), some of it consulting and some of it talking with clients. What that means to me is that my a good portion of my job--the journalist part-- is going social, whether I like it or not. The good news is that I DO like it, although it requires getting used to a very different work style and having to carve out considerably more time to focus on blogging, and reading and commenting on other blogs.
CNN has definitely gotten the message that journalism has fundamentally changed. I sometimes watch that network, not because I'm interested in the news per se (although I usually am), but because I'm watching how they have transformed from talking heads to moderators and orchestrators of a national conversation. I first noticed it on Wolf Blitzer's Situation Room. Wolf doesn't seem particularly social, but Jack Cafferty is on the program and every day Jack asks some provocative question. For example, today's question is: "is the world economy in a depression?" Listeners can go to Jack's blog and posts comments. Jack then reads some of the more provocative posts on air, and the conversation then goes back to the blog posts. It becomes a circular process. It's fascinating how CNN journalists have turned into on air, real time moderators. Sometimes Jack gets 300, 500, 700 or more blog posts within a day. He got over 900 responses to the question: "How tired are you of Blagojevich, Coleman, Franken, and Palin?" (I wonder how many he would get if he asked: "How many of you care what Dick Cheney thinks?")
The most fascinating of the CNN journalists from a social perspective is Rick Sanchez, who is on in the afternoons. Rick has 50,000 people on MySpace, Facebook and Twitter, and he interacts with some of them during the broadcast. If you watch his show, and you also see the iReports that CNN viewers send in, you realize that CNN (at least during Rich Sanchez's show) is facilitating a two-way broadcast discussion instead of merely reporting the news. Instead of the broadcaster beaming his or her message into your living room, the broadcaster is stirring the virtual pots of thousands of people who are participating in the live event. What a groundswell change.
The shift to social interaction in print and TV journalism is just the tip of the iceberg. In businesses, people want to interact with the vendors they buy from. I'll give you an example. My local pharmacy cut back its hours. A year ago they stopped opening on Sundays. I thought that was an inconvenience. Then, last summer, they went to "summer hours" in which they closed on Saturdays at 1:00 PM and closed in the evenings at 6:00 PM. This supposedly was to give their employees more time to enjoy the summer and the regular hours would start back after Labor Day. Never happened. I'm now left with prescriptions that I can't pick up because I forgot to go down there before 6:00 in the evening, or prescriptions that are still waiting for me under the counter because I forgot they weren't open on Saturday afternoon and got there at 2:00 instead of 12:30 PM. I am so irritated at this pharmacy that I've switched all my business to CVS, which has hours that actually fit into a working person's life. And I made sure my old pharmacy knew that I had stopped being their customer, although it felt like my complaint about their new hours went in the manager's one ear and out the other. I would dearly love to post a blog on that Pharmacy's non-existent site or see what other customers think.
That's just one example of how a social site would be helpful to a business. This pharmacy could monitor what customers think before they one day belatedly wake up and realize that all the business went down the street to the other guys who are open later.
No matter what your profession--journalist or pharmacist or something else, it's time to get smart about getting social.
The economic outlook isn't all gloom and doom. Bright spots remain in some substantial IT growth sectors--most important, in the sprawling business intelligence (BI) market.
In the past month, we've seen solid financials--in some cases, record growth and profitability numbers--from leading BI vendors, including SAP (Business Objects), IBM (Cognos), and privately held SAS Institute. Oracle and Microsoft also seem to be doing fairly well with BI-related revenues. Even vendors that only participate in BI environments as a provider of data warehousing (DW) solutions (e.g., Sybase) or data integration (DI) middleware (e.g., Informatica) are reporting outstanding financials all the way through year-end 2008. That includes the period just passed when the world economy began to spiral wildly out of control.
What's going on here? Is the BI industry recession proof, or is the next soft-economy shoe--or heavy hammer--poised to drop on this segment's unsuspecting heads? To some extent, I suspect that BI's relative, perhaps short-lived, immunity from tough times is due to its use as a "recession-busting" tool for identifying areas to cut costs, consolidate operations, and boost revenues. SAS CEO Jim Goodnight articulated this view in his recent statement: “In tough times, companies focus on optimizing their businesses."
But excuse me if I take a slightly cynical perspective on any sector's claim to be recession proof. I take issue with the notion that people have no choice but to use one particular vendor's or sector's product, no matter how bad the economy gets. For example, the "people gotta eat" argument didn’t translate into general prosperity in the agricultural sector during the Great Depression. People found ways to survive on less store-bought food--or less meats and sweets--or larger backyard gardens--or handouts.
As regards the indispensability of BI, I suspect the actual market dynamic is bit more nuanced than we’ve been led to believe. What’s interesting about the latest round of BI vendor earnings numbers is that some are lackluster and/or declining. Case in point: MicroStrategy's recent report of a 12 percent decline in BI license revenues in Q4 2008, compared to the same quarter a year earlier (bear in mind that the vendor's product licensing revenues grew by 5 percent for the year as a whole, due to a strong start).
Why is MicroStrategy reporting flaccid Q4 numbers but SAP, IBM, SAS, and others are doing OK? I suspect that one of the key factors is the encroaching commoditization of "core BI" stacks, with concomitant declines in prices. Forrester defines "core BI" as solutions that incorporate any or all of the following features for information access, delivery, presentation, and user-side sharing: reporting, query, OLAP, dashboarding, Microsoft Office integration, portal integration, alerting/notification, and interactive visualization. Clearly, this particular segment is overcrowded, with dozens of vendors--including open-source and software-as-a-service providers--that are becoming as indistinguishable as polar bears in a blizzard. Though MicroStrategy is a well-established, widely adopted core-BI vendor, it does not have much beyond that common denominator feature set.
Another trend that's making it more difficult for MicroStrategy and similar vendors to grow is enterprise information managers' desire to consolidate their analytics environments down to a few core vendors--which, more often than not, provide data warehousing (DW), data mining, data quality, and other solutions in addition to core BI. MicroStrategy is mostly missing from those other markets, so it may be experiencing problems growing its footprint among existing customers.
Yet another trend that explains the soft MicroStrategy numbers may be enterprises' preference for BI vendors that can offer a full range of prepackaged "business content"--such as analytics tailored to specific vertical and horizontal requirements--to extend and leverage the core BI platform. That's where the likes of SAP/Business Objects, IBM/Cognos, Oracle/Hyperion, and SAS come into the picture--and the MicroStrategies of the BI market are mostly absent.
Just as important to these latter vendors' ongoing success are strong professional services organizations, partnerships, and customer relationships. Only by deepening their domain expertise and customer intimacy--and pouring this new "business content" into packaged applications and solution accelerators--can BI vendors realize healthy margins going forward. Forrester refers to these packaged domain analytics applications as "business performance solutions" (BPS).
SAS' Goodnight alluded to this key BI-vendor success imperative in his recent press release: "We achieved our 33rd year of revenue growth in the worst economy most can remember. This growth is a direct result of being a stable privately held company, which allows us to invest in long-term relationships with employees and customers."
Where SAS and some other vendors are concerned, another key differentiator that's helping them stay strong is emphasis on BI's chief growth segments: most notably, advanced analytics, which encompasses predictive analytics (PA), data mining (DM), and text mining/analytics. Deep domain expertise and customer intimacy are also keys to vendor growth in advanced analytics. Indeed, the range of tailored analytic applications that leverage advanced analytics features continues to grow, though the number of PA/DM "workbench" providers on the market remains fairly stable.
At heart, BI is a relationship business. The BI solution provider should be a committed partner helping customers to address their most burning success imperatives. Customers won't forget if you helped them out of a tight situation, such as nasty patch of sluggish economy. They'll keep coming back to you time and again.
Steady repeat business--loyal customers--indispensable brands--that’s the best business model--just ask Warren Buffett.
I get tons of questions about "how much it costs to develop an analytical application." Alas, as most of us unfortunately know, the only real answer to that question is “it depends.” It depends on the scope, requirements, technology used, corporate culture and at least a few dozen of more dimensions. However, at the risk of a huge oversimplification, in many cases we can often apply the good old 80/20 rule as follows:
Components
~20% for software, hardware, and other data center and communications infrastructure
In 2003, customer data hub (CDI), product information management,
and master data management (MDM) vendors strived to differentiate
themselves by architectural style. Each approach had its advantages
and disadvantages. A religion about styles emerged overnight along
with a hard core following. Here's a quick recap (see Figure 1):
Figure 1. The Three Architectural Styles of Master Data Management
The bottom line - choose a style that aligns with your project's business driver
While these approaches still exist, leading vendors such as D&B
Purisma, IBM, Initiate Systems, Oracle, Oracle-Siebel, SAS DataFlux,
and Siperian now have offerings in more than one style. This may make
the question seem less relevant, however, its still important to
understand the trade-offs while beginning your MDM journey. In fact, it's best to align the style and approach based on your business driver. Here's a high level summary:
Cross-referenced registry delivers rapid results for operational efficiency business drivers.
This approach is best suited for rapid implementation scenarios such as
POC's that prove the value of master data. Also valuable when data can
not be stored on-site. Pro's: Rapid implementation without having to agree on a common enterprise data model. Utilize existing source systems. Con's: Deduplication of source systems not addressed. Data quality must be solved in each independent source system.
Hybrid harmonized reference enables compliance and regulatory business drivers. This
approach allows the best of both worlds, especially when moving to a
transactional operational data store is not politically feasible and
data governance and stewardship activities are just starting up. Pro's: Single master copy of reference data. Uses links to
access source system records. Model allows data quality efforts to be
applied to shared master reference data. Con's: Synchronization with source systems can create some complexity if changes are not made in the hub.
Transactional operational data store supports strategic business drivers. This approach provides a long term path for how legacy applications utilize data. Pro's: Single master copy of data. No fussing with latency or synchronization issues. Minimal mapping issues. Con's: Requires an agreed upon common enterprise data model to
be used by all applications. History must be harmonized and requires
extensive key mapping. Assumes homogeneity and requires tons of ETL
and dedupe.
Your POV.
Which MDM style are you deploying? What successes have you seen?
Post your thoughts or send me a private email to rwang0@forrester.com.
By Claire Schooley
What do you think? Does the 80/20 rule work here?
