November 19, 2007

Usability engineering is crucial

From a review of the rather powerful Fair Isaac Blaze Advisor, which will surely be far less successful than its functionality deserves:

But employing a usability expert when designing the tools and observing how users interact with them would go a long way toward improving their usefulness.

My mind utterly boggles each time I discover that a large software vendor still doesn’t seem to have realized this. Or maybe Fair Isaac did do usability engineering, but entrusted it to a blithering incompetent. That frankly would be more reassuring than them not having tried at all.

October 8, 2007

Some quick thoughts on SAP acquiring Business Objects

1. SAP needed outside talent again. In March I wrote that Shai Agassi’s departure wasn’t as a big a deal as it seemed, because guys like Dennis Moore were still there. Well, by now Dennis Moore is NOT still there, and rumor had more of the good personnel acquisitions leaving as well. And unfortunately, my personal experience of some of those remaining is that they’re ethically unfit for their roles (and that’s putting it kindly).

2. The NetWeaver strategy has been failing. Does anybody care about NetWeaver any more? The whole thing includes some great ideas, but implementation has been lacking.

3. The Business Objects guys are proven successes at integrating disparate BI product suites. The Crystal Reports acquisition proved that.

Before writing more, I should check the extremely one-sided consulting contract I had with SAP, specifically for the expiration date of the NDA. How one-sided? Well, I naively agreed to a clause that I couldn’t sue them under the contract, expecting their concern about their reputation to keep them in line. Since then, they’ve cheated me out of considerable amounts of money that they owed. Arggh. Live and learn.

July 9, 2007

Revolutionary trends in the analytics market

I just finished another Monash Letter. It was a follow-up to a previous one that discussed various strategic positioning possibilities in business intelligence. In the prior piece, I pointed out that most leading vendors were pursuing similar strategies — BI as enterprise infrastructure play. In this piece — for Monash Advantage members only — I point out how that sameness allowed for disruption and revolution, and highlight a few trends that are pointing in those directions. Specifically, the trends I cited included:

  1. The return of load-and-go. (A major current trend.)
  2. UI diversity. (An accelerating trend.)
  3. Analytic business process support. (A huge opportunity for transactional application vendors that they haven’t yet seized.)
  4. Expansion from relational/tabular/structured to text/unstructured data. (The biggest opportunity of all, although it’s still in the very early stages.)

Relevant links include:

My list of potentially major disruptors starts with Endeca, QlikTech, and the open source movement.

April 3, 2007

Business intelligence — technology and vendor strategy

The most recent Monash Letter – exclusively for Monash Advantage members — spells out some ideas on BI technology and vendor strategy. Specifically, it argues that there are at least four major ways to think about BI and other decision support technologies, namely as:

  1. A specialized application development technology. That’s what BI is, after all. Selling app dev runtimes isn’t a bad business. Selling analytic apps hasn’t gone so well, however.
  2. An infrastructure upgrade. That’s what the BI vendors have been pushing for some years, as they try to win enterprise vendor-consolidation decisions. To a first approximation, it’s been a good move for them, but it also has helped defocus them from other things they need to be doing.
  3. A transparent window on information. As Google, Bloomberg, and Lexis/Westlaw all demonstrate, users want access to “all” the possible information. BI vendors and management theorists alike have erred hugely in crippling enterprise dashboards via dogmas such as “balanced scorecards” and “seven plus-or-minus two.”
  4. A communication and collaboration tool. Communication/collaboration is as big a benefit of reporting as the numbers themselves are. I learned this in the 1980s, and it’s never changed. But BI vendors have whiffed repeatedly at enhancing this benefit.

The Letter then goes on to suggest two areas of technical need and opportunity in BI, which may be summarized as:

Good launching points for my other research on these subjects are this recent post on analytic technology marketing strategies and two high-concept white papers available here.

March 28, 2007

Shai Agassi – a contrarian view

Shai Agassi is leaving SAP because, in essence, the old guard didn’t want to turn over the reins to him as fast as he would have liked.* Often, this kind of departure is a bad thing (e.g., Ray Lane at Oracle). But I suspect that SAP may actually be improved by Shai’s leaving.

*His other stated reasons include two very good and highly admirable ones – working on energy technologies and improving matters in Israel.

SAP’s technical strategy has three core elements:

  1. Automate business processes.
  2. Provide the technical infrastructure for automating business processes.
  3. Encapsulate process and data at the object/process level.

This strategy has been heavily developed and refined on Shai’s watch, with major contributions from lots of other folks. The issue isn’t vision any more. What SAP needs to do better is execute on the vision.

Read more

March 19, 2007

Three ways to market analytics-related technology

“Decision support”, “information centers”, “business intelligence”, “analytic technology”, and “information services” have been around, in one form or other, for 35+ years. For most of that time, there have been two fundamental ways to sell, market, and position them:

More recently – especially the past five years – there’s been a third way:

as early-generation implementations get replaced by newer ones.

At the 50,000 foot level, here’s some of what I see going on:

Related links

March 16, 2007

Have analytics vendors rediscovered ease-of-deployment?

Business intelligence (BI) used to be characterized by speed and cost-effectiveness — short sales cycles, low-cost departmental purchases and deployments, evasion of IT departments’ strangleholds of data, and so on and so forth. That focus has blurred, as BI vendors have increasingly focused on analytic applications or enterprise-wide standardization sales. But increasingly I’m seeing signs that the pendulum has swung at least partway back. For example:

It’s about time.

October 5, 2006

The problem with dashboards, and business intelligence segmented

It is becoming ever clearer that dashboards aren’t working out too well, any more than predecessor technologies like EIS (Executive Information Systems) did. The recurring problem with these technologies is that if they’re mind-numbingly simple, people don’t find them very useful; but if they’re not, people are overwhelmed and still don’t find them useful. This column by Sandra Gittlen does a good job of spelling the problem out.

I think there are lots of problems like that in BI, and what we need to do is step back and consider all the different kinds of BI that enterprises value and need. More precisely, let’s consider the major kinds of use of BI, because it seems that each calls for different kinds of technological support. Here’s one possible list:

Here’s what I mean by each category. Read more

October 4, 2006

KXEN and Verix try to disrupt the data mining market

Data mining is hugely important, but it does have issues with accessibility. The traditional model of data mining goes something like this:

  1. Data is assembled in a data warehouse from transactional information, with all the effort and expense that requires. Maybe more data is even deliberately gathered. Or maybe the data is in large part acquired, at moderate cost, from third-party providers like credit bureaus.
  2. The database experts fire up long-running, expensive data extraction processes to select data for analysis. Often, special data warehousing technology is used just for that purpose.
  3. The statistical experts pound away at the data in their dungeons, torturing it until it reveals its secrets.
  4. The results are made available to business operating units, both as reports and in the form of executable models.

Each in its own way, KXEN and Verix (the imminent new name of the company now called Business Events) want to change all that.
Read more

October 4, 2006

Data mining requires data

Data mining requires and justifies huge investments. The smallest part is the data mining software itself. A much bigger part is the investment in data warehouse technology, a subject about which I’ve been posting extensively recently on DBMS But there’s yet another part to the picture, namely investing in actually gathering data for analysis, that I’ve written about, most recently in a blog I posted elsewhere and am now copying below.
Read more

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