Everybody gets paid — or would like to
The disclosures in this post have been updated in June, 2008.
I’m sometimes amazed at the breathless pseudo-naivete about pundits (analysts, bloggers, whatever) and compensation. The latest round was kicked off by a WSJ article about bloggers promoting FON. A couple of years ago, Computerworld editor Maryfran Johnson was viewed as a heroine for pointing out analyst firm conflicts of interest.
Personally, I’ve been an analyst for almost 30 years; I have a strong reputation for being independent and critical; and I get most of my revenue from vendors. So perhaps I’m in a good position to clarify some of the issues.
1. Good vendor relationships are an important factor in an analyst’s success. It’s not just revenue; you also need access to information. This is true whether you’re a stock analyst or an industry analyst.
Now, if you’re a good analyst, you can work around access problems. You can talk with customers, competitors, ex-employees, and other industry players. You may have relationships that transcend the company’s communication controls. (For example, it’s a firing offense at Oracle to have unsanctioned conversations with an analyst. And Oracle isn’t sanctioning a whole lot of conversations with me these days. But for a number of reasons, such as longstanding relationships with “untouchable” higher-ups, my information flow from inside the company is still pretty good.) Still, having access is better than not having access, and companies use that as a lever.
2. Analysts typically have more confidence in the companies that are their paying clients. I honestly call ’em as I see ’em, no matter who is or isn’t paying me. But some of my calls have to do with confidence. And who will I be more confident in? Company A, which has disclosed almost all their current activities and intermediate-term plans to me, and has given serious consideration to expensive advice they’ve paid me for (and hopefully done something with the advice)? Or Company B, with whom my relationship is largely being fed marketing pabulum, with only the occasional renegade getting off the reservation and telling me what’s really going on? Obviously, it’s often Company A.
Gartner Group is no different from me in that regard.
3. There’s a reinforcement cycle that confuses questions of bias. Companies give money and attention to analysts who are positively inclined towards them. They buy consulting services from analysts whose worldviews are compatible with theirs. The resulting relationship, if it goes well, reinforces everybody’s positive opinions of each other.
Meanwhile, companies give cold shoulders to analysts who don’t like them. And that just reinforces analysts’ opinions too.
4. Experience teaches that the companies that most manipulate or hide from analysts have the most to hide. If a company feels good about its strategy, and is eager to listen and learn how to make it even better, it’s often pretty engaged with analysts. If there are some product weaknesses it would prefer not to have discovered, it may be more inclined to concentrate its efforts on only the big firms it must talk to, and cold-shoulder the others. There are exceptions, of course, based on factors such as marketing budgets or the cluefulness of the analyst relations staff. But a good analyst’s gut feel about who is or isn’t being forthright is often a pretty good indicator of how a company’s technology is doing. Indeed, I have had some famous successes in this regard over the decades (e.g., the Cullinet and Sybase stories, which I really need to write up at some point over on the Software Memories blog). And it’s not just me. David Ferris of Ferris Research led the way when he and I had a success of that kind together with respect to Critical Path, shortly before the management team was discovered to be criminally dishonest.
5. Being on advisory boards almost always involves compensation or the expectation of compensation. Anybody who asserts otherwise is dishonest or naive. But then, the only folks I’ve ever seen assert otherwise are Fabian Pascal and (sort of) Chris Date.
So here is some of my disclosure.
- SAP is currently my biggest customer. In various other years my biggest customer has been Oracle, Computer Associates, Microsoft (I think — if not so, then close to it), AOL, and a predecessor of what is now the Progress DataDirect division. And that’s by no means a complete list.
- Every white paper and every webinar I do is “sponsored”; i.e., money changes hands. (There may be occasional exceptions to that rule in the future, but it’s usually the case.)
- The companies that are currently most seriously diminishing my opinion of them via the cold shoulder they give to various analysts (not just me) are Oracle and Cognos.
- For years, I have had exactly one investment research client — a portfolio manager whose identity you could probably guess by looking at the testimonials on www.monash.com.
- I cannot commit to promptly or completely disclosing who my consulting clients are. Sometimes they want to be served in confidence. However, I always have and in the future always will disclose any kind of relationship in which I am paid to promote companies in any way.
| Categories: About this blog, Analytic technologies, DBMS vendors and technologies, Enterprise applications | 5 Comments |
The Power of Portals
I did a webinar last week on portal technology. On that webinar, I promised to post a link here to my whitepaper on third-generation analytic business processes. Done. (Scroll down to the bottom of the page.)
The webinar was pretty fast-moving, so I’d encourage you to replay it if you have a bit of time. But if you want to know just the tippy-topmost key points, the list is something like this:
- Portal technology can play a variety of different roles.
- Portals can be like an inhouse Yahoo, for static pages and knowledge management and self-service types of apps.
- Portals can be the best framework for “secondary” or “ad-hoc” operational apps and business processes, as an even lighter-weight technology than composite app development tools.
- Portals are an ideal base technology for dashboards.
- There should be much more BI-based collaboration going on, and portals are the obvious enabling technology for this.
| Categories: Analytic technologies, Business intelligence, Enterprise applications, Usability and UI | 2 Comments |
How the text technology market could ignite
Over on the Text Technologies blog, I have a series of posts arguing that the potentially huge market for enterprise text technologies is being stifled by the lack of a general-purpose ontology management system. I further argue that such a product could be constructed in such a way as to be actually usable and potentially adopted by mainstream enterprises (no, you don’t need a trained librarian to use it). So what are the chances of something like this actually working out, to an industry-changing extent?
First and foremost — if such a product is built, there’s a clear Crossing the Chasm path to major success. There are fairly healthy (> $100 million dollars annually each, at least) technology markets for internal enterprise search, customer-facing search, electronic publishing, text mining, and so. That creates plenty of “bowling pins” for a tool to get established. What’s more, pretty much every sufficiently large enterprise needs internal search; every enterprise with a decent-sized product set needs customer-facing search; and many industries need text mining. So the opportunity for true mainstreaming of text technology is clearly there. I don’t know whether the dominant product category is more likely to be “ontology management systems” or “search whose product differentiation lies in its ontology management subsystem,” but one way or the other the market opportunity is there.
Second, the technology seems eminently buildable. The various “smarts” needed have for the most part emerged, at least in point products. The knowledge representation scheme needed seems like a straightforward extrapolation of current ones. Anything can be given a good UI. Almost anything can be made scalable, and this doesn’t seem like one of the rare exceptions.
So it all comes down to vendor will (and wallet). I’m not aware of any vendor that’s really figured this market opportunity out yet. But sooner or later, one or more of them will surely get the point. If needed, I’ll personally help them see the light …
| Categories: Analytic technologies | 1 Comment |
Oracle’s perennial confusion about analytic technology
Oracle is badly confused about analytic technology, and indeed long has been. It would be tough for me to coherently explain why without being, well, confusing. So I’ll just list a series of data points, which hopefully should suffice to illustrate the point.
- Classic BI tools have at various times fallen under the purview of the app dev tools group and the app server group.
- Data mining, stemming from a Thinking Machines, Inc. acquisition, is under a whole other group on the East Coast.
- That group is now collocated and somewhat integrated with the group that oversees the MOLAP database capability, which came in via a different Boston-area acquisition (IRI/Express).
- While Oracle brags of its integrated BI stack, enterprise reporting is an exception.
- Discoverer 1.0 (Oracle’s original BI tool), was one of the most impressive new products I ever saw. But then BI technology at Oracle almost stagnated. The reason seems to have been largely a series of platform ports – client/server, Java client, thin client, etc. Other BI vendors faced the same problems, however, and they now have products generally agreed to be ahead of Oracle’s.
- Oracle didn’t seem to have a coherent analytic apps strategy even before the Peoplesoft acquisition, which obviously just confused things further. (Of course, neither does SAP, really, Dennis Moore’s passionate insistence to the contrary notwithstanding.)
- ETL/data integration is of course a historical Oracle sore spot.
That’s even before getting to Oracle’s problems in data warehousing itself, where it can’t beat Teradata and DB2/mainframe at the very high end, and low-cost options like Netezza are a looming threat as well.
What’s particularly ironic is that some of Oracle’s core marketing pitches have a lot to do with analytics. The whole integrated stack story? Doesn’t make much sense when you’re only talking OLTP; only with analytics in the picture is it coherent. The whole scalability story? A few huge websites and the like aside, that’s mainly about data warehousing now.
Obviously, Oracle has the potential to be a titan in analytics. But it doesn’t have its act at all together yet.
| Categories: Analytic technologies, Business intelligence, Data mining, DBMS vendors and technologies, Oracle | 3 Comments |
Autonomy/Verity merger
As posted in the Text Technologies blog, I’m skeptical yet slightly hopeful about the combined Autonomy/Verity company. Each of those companies sells overall technology that’s less than the sum of its parts. Maybe the merged company will be big enough to wake up, add what’s missing, and grow the enterprise text search market beyond its current level of:
1. Collection of niche markets plus
2. Unimportant universal technology add-on
| Categories: Analytic technologies | 1 Comment |
Subjects in which I’m particularly interested
Throughout my 24-year career as an industry analyst, my top-level question has always been: “What aspects of the industry/sector/market/company are worst understood, or most overlooked?” Most commonly, the answer lies somewhere in the overlapping areas of technology, market positioning, and ongoing sector consolidation. And any discussion of technology and positioning depends heavily upon the way customers actually adopt and use new stuff.
It’s no different now. Most of my efforts recently have been devoted to DBMS (like always), text technologies, and analytics in general. In DBMS I’m making the very strong technological case that vendor consolidation is overrated, and that we’re in an era when 1000 specialty database flowers will bloom. The survivors will eventually all be tied together by XML-based SOAs. (Some of my friends at big DBMS vendors are not very happy with me right now.) My arguments against the prevailing wisdom may be found at a specialty blog on database management techology, called DBMS2. I plan to add more positive comments on the interesting new technologies soon.
In text technologies, there are a whole lot of point products. Despite booms in certain areas, such as text data mining, these are only scraping the surface of user requirements. What’s needed – and surely coming – is a dramatic evolution into one or more much larger product categories. How long that takes is unknown, however; right now the two pillars of the market (search and text data mining) are as industry segments go quite far apart. I also have started a specialty blog to track this area, with the simple name of Text Technologies.
My most active area of research these days is probably analytics. Certainly it’s my oldest interest of the three I cited, dating back to my student years, when I basically focused on decision theory for my dissertation and post-doctoral research. I think that, after decades of false alarms, the center of gravity in enterprise computing has REALLY shifed from OLTP to decision support. At least, that’s true at the larger enterprises; SMB are still playing catchup in the transactional area.
While I think there are lots of interesting technological issues in analytics – and indeed no enterprise analytics vendors’ product line is close to fully-baked – what really matters here is understanding the users. Vendors blithely claim that they’re going to foster a whole cultural transformation, in which top-to-bottom decision-making will suddenly become rational and numerate. Yeah, right. In tracking the evolution of the analytic technology business(es), nothing is more important than being realistic about how this stuff is and will be actually used.
I plan to write about these and other areas in the days and months ahead. Stay tuned – and, as always, if you would like to disagree with or add to what I have to say, please please let me know. My research, as always, depends on you.