Google: Tighter Time Controls
June 6, 2008
Valley Wag, one of the Web logs I enjoy immensely, reports that Google’s 20 percent free time for personal projects policy may be changing. You can read the original news story here.
The key point for me was this observation:
What we hear from Googlers is that supervisors are cracking down on use of 20 percent time when employees’ main projects are behind schedule. A sensible management move, but against the spirit of 20 percent time, which was meant to liberate creative employees from meddling middle management.
Google is now a decade old an rocketing forward in many business sectors. The implication is that Google needs more productivity. The flip side is that the idea of having the equivalent of one day each week to work on projects that interest a Googler is now public relations.
My sources tell me that this is not a change in policy, just a reaction to work load. If I learn more, I will let you know. I calculated that the 20 percent rule if applied to 12,000 engineers with an average salary of $130,000 per year including benefits added hundreds of millions of research costs to the company. This cost does not appear as part of Google’s “regular” R&D activity, but the approach has produced some interesting innovations for the company.
Stephen Arnold, June 6, 2008
Microsoft: Role-Based Approach to Enterprise Apps
June 6, 2008
Colin Barker, ZDNet UK, wrote an interesting article “Microsoft Launches Connected, Role-Based CRM.” You will want to read the full story here. The key idea is that Dynamics AX 2009 (one of the different flavors of customer relationship management software Microsoft sells) supports roles. The idea is that a user, once assigned a role, interacts with the system from the point of view of the role. The article quotes Microsoft’s Gary Turner, who makes this point:
This is different from the way in which ERP systems have worked in the past, where everyone has one ‘vanilla’ front end… A chief executive will look at the information differently from someone in marketing or whatever. Your needs and requirements will be different.
The system also supports direct connections to eBay (the troubled online retailer) and PayPal. The system, if I understand Mr. Turner correctly, supports smartphone access. The default Dynamics user-facing interface is a dense, detailed beastie. Presumably, the smartphone interface will be stripped down to fit the smartphone screen real estate. Support for Microsoft’s business intelligence tools is included.
Why’s this important in search?
My research indicates that role-based interfaces may be one of Microsoft’s weapons as it tries to expand the market for its different enterprise systems. Applied to search, each user would “see” an interface and search results tailored to his or her role. This personalization of the system allows Microsoft to shift from a one-size-fits-all interface to a more specialized approach to a complex system.
With announcements about the integration of Fast Search & Transfer with Microsoft’s own search technology, there is little hard information about role-based interfaces available. In my opinion, competitors can offer similar functionality if the feature gets traction with customers.
Oh, the other products in the Dynamics line up are Dynamics NAV, Dynamics GP and Dynamics SL. I have difficulty keeping each straight in my mind. Microsoft’s preference for multiple versions of products like five flavors of Vista, SharePoint’s ESS and MOSS, and four ERP systems sends me to Google’s Microsoft search here to keep track of the differences. I rely on Google to locate Microsoft information. Response seems quicker and the index appears to be refreshed more frequently.
Stephen Arnold, June 6, 2008
Enterprise Information’s Missing Pieces
June 5, 2008
In 2001, I found myself on a panel talking about electronic information and enterprise search. The venue was Internet World. That’s right the once dominant trade show for the brave new world of online.
I’m not sure how I ended up on the program, but I recall I was there, facing an audience of 250 people. Put the word “Internet” on a hand lettered sign in a diner’s window and a crowd would gather. The Internet has evolved but the missing pieces in the information puzzle are still with us.
Here’s an image from my PowerPoint deck.
Web log graphics are “crunched” and the result is difficult for me to read. Let me highlight each of these nine pieces of the enterprise information puzzle.
- Graphical editor
- Database engine
- Version controls
- Site manipulation tools (that is, publishing tools)
- Personalization tools
- Search engine
- Administrative interface
- Usage tracking
- Security services
Nothing is missing. The nine elements are identified in the graphic, and in your own organization you have each of these functions up and running. Some puzzle pieces work better than others. These are complex sub systems and functions. Variability and unevenness are to be expected.
My point in 2001 was that each of these pieces was not fitted to the others. The parts are there, but until integration across different sub systems and functions, the puzzle is incomplete. In fact, you don’t even have a decent picture of what the integrated results will look like.
Touching Lightly on a Killer Task
June 5, 2008
A colleague sent me a link to a white paper written by Bikram Sankar Das, the head of Tata Consultancy Services Business Intelligence and Performance Management practice in the UK and Ireland. Tata is a massive conglomerate known for outsourcing and buying aging automobile companies. Its consulting unit’s tag line is “Experience certainty”.
I enjoy reading white papers about business intelligence and content processing. Good papers give me useful anecdotes for my talks. Not-so-hot papers are less useful. “Business Intelligence and SOA: Making the Jump” tips toward the useful side. The wrap up struck me as the strongest section of the paper; to wit:
At the same time, there are still a number of challenges to be faced. One of the defining characteristics of BI-PM is its hunger for accurate information. As users become more and more accustomed to relying on analytical tools, their demand for new kinds of data capture and analysis increases. This leads to rapid database growth, and accelerating demand for storage capacity – pushing up costs and clashing with green IT policies.
The author makes an important point: users are going to grouse unless the systems deliver heterogeneous information properly parsed and sorted in a timely way. When systems don’t deliver what the marketers promise, users won’t use the system. Bad things happen when users get cranky and find other ways to get the information needed to do their jobs.
The weaker part of the paper is the hippity-hop over the problem of data transformation. As much as one-third of an information technology budget can be consumed fiddling with data so a fancy-Dan system can do its song and dance act. The author put my teeth on edge when he wrote:
Instead of a centralized information store, a federated approach can work well. With this approach, although the information is stored in a number of different databases, the databases themselves share a common protocol for information exchange through an ‘information bus’ – making it simple to compare and analyse data from different sources. To create a successful federated infrastructure, metadata must be carefully standardized across all systems, and a data/information governance model must be adopted across the entire organization. This can often necessitate a cultural change in the process of information creation, storage and consumption.
We’re talking big money, mucho time, and quite a bit of work to deliver standardized information to a business intelligence system. There simply is neither the money nor the programming resources to crunch through the large amounts of digital information. Users don’t know about these costs, nor do they care.
The hurdle next-generation business intelligence systems must get over is data transformation. A failure to explain the costs and complexities of this set of tasks fertilizes the ground for user revolt to take root.
Judge for yourself. You can download the essay here. The author minimizes what may be the most complicated work required for next-generation business intelligence.
Stephen Arnold, June 6, 2008
SolveIT: Fancy Math
June 5, 2008
Several years ago I found myself in a meeting. I was paid to attend a session in North Carolina; otherwise, I wouldn’t go to Charlotte. The city is too sophisticated for this Kentuckian.
In the meeting, a soft-spoken mathematician, his son, a couple of cousins, and maybe an uncle explained sparse sets, assigning probabilities to boundaries, and ant algorithms. As I struggled to dredge definitions about these concepts from my admittedly poor memory, the soft-spoken mathematician asked me a word problem. A waiter had 12 customers and ended up with an extra dollar. Why? I just sat there and looked my normal stupid self.
Later, he explained that his inspiration was a mathematician named Stanis?aw Le?niewski. Okay, early 20th century wizard. That was the end of my knowledge. Puzzles are the key to learning math he told me. In his spare time, this fellow has set up a Web site to make this concept more widely known. You can see it here.
I had no clue who these fellows were, but I was getting paid to listen so I listened.
A Super Guru: Who Says He’s Just a Regular Guy
The super guru is a fellow named Zbigniew Michalewicz, a highly regarded mathematician everywhere except in Harrod’s Creek. The relatives were also mathematicians. The crowd could finish one another’s sentences and equations. Math, it turns out, is something that runs in the Michalewicz family and has for decades.
Dr. Michalewicz is an expert in generic algorithms and data structures. When added together, the mathematical recipe yield evolution programs. You can read more about this approach to some tough data problems in Genetic Algorithms + Data Structures = Evolution Programs, published by Springer-Verlag ISBN: 3-540-60676-9. No, your local book store won’t stock it. Amazon does.
The group sold its US enterprise and Dr. Michalewicz and a family member or two moved to Australia.
After losing track of these fellows, I learned that Dr. Michalewicz, his son, and a handful of mathematical gurus set up shop as SolveIT Software. Click here to navigate to the company’s Web site.
The new company uses new math to solve old problems. The company is in the business of delivering solutions that deliver “adaptive business intelligence”. The company’s range of technology is remarkable and it may be meaningless to you unless you took a couple of advanced math classes; for example:
- Agent-based systems
- Ant systems (my favorite)
- Evolutionary strategies
- Evolutionary programming
- Fuzzy systems
- Genetic algorithms
- Neural networks
- Rough sets (great stuff!)
- Swarm intelligence
- Simulated annealing (does with math to data what oil quenching does to low-grade steel)
- Tabu search (I have no clue what this numerical method yields).
You can figure out most of these notions by dipping into Peter Norvig’s Artificial Intelligence or E. J Borowski’s and J. M. Borwein’s Web-Linked Dictionary Mathematics. (Note: there is a subtle difference between the Norvig approach and the Michalewicz method. Google uses humans. Humans play an optional role in the Michalewicz recipes. No big deal, but you can explore the differences yourself by reading each guru’s text book.)
A Case Example
Equations are not likely to raise my Google ranking. Let me describe an outcome of Dr. Michalewicz’s skills.
Here’s the set up. You are Ford, Honda, or Toyota. Each week you get a couple of thousand lease cars back. You want to sell the cars quickly. You want to minimize how much you have to spend to truck these white elephants to a location where a particular model will sell. Pink convertibles don’t fly in Nome, Alaska, but are hot items in Scottsdale, Arizona. Your resale team would rather go to a bowling convention that work Excel models.
You want to maximize return, minimize expenses, and get the decisions out of your resale team’s “instinct” and into something fungible like a SolveIT solution.
SolveIT’s analysts beaver their way through the data, the work flow, and the exogenous factors that you and your resale team did not consider. The company builds from its mathematical Lego blocks, a computerized system that prints out a map and report telling your sales team where to ship which car.
You use the SolveIT system for a couple of months, and you notice that your expenses go down and your net goes up. SolveIT removed the guess work and let the “fancy math” do the heavy lifting. When I spoke with the company several years ago, one beta client was generating cash positives in six figures within six weeks.
Like most sophisticated companies run by serious math geeks, there’s not much information available on the company’s Web site. I did dig through my files, and I found an example of the company’s outputs. Keep in mind that this diagram is probably out of date, but it will give you a flavor of what the SolveIT operation does.
The system “shows” the resale team where certain cars will sell. Then the system prints out a report that says, “Send the pink convertible to Chicago and the truck to Paducah.” The math does the heavy lifting. The resale team looks at simple diagrams. The math remains safely hidden away.
Observations
SolveIT is one of a handful of companies pushing the envelope in analytics. If you want to tap into some serious math, contact this company. I have one tip. Don’t ask, “How does this work?” The explanation requires a solid foundation if traditional mathematics and post-doctoral work in set theory. How complicated is the math. I found in my files one example which I had to scan and convert to an image. I kept it as a reminder of how little I know about the next big things in mathematics; for example, in my notes I had this pair of statements:
If these statements speak to you, then you can dig more deeply into the SolveIT systems and methods.
Based on my personal experience with Dr. Michalewicz, he’s a capable mathematical thinker. For more about his company’s approach to problem solving, you will find useful How to Solve It: Modern Heuristics, also by Springer Verlag. You can get a copy here.
Stephen Arnold, June 6, 2008
Google: No Game Changer … Just Yet
June 5, 2008
Imagine my surprise when Computerworld picked up on information in my April 2008 Gilbane Group study, Beyond Search. You can read the Computerworld story here. (Hurry. Computerworld content can be hard to find if you dally. I won’t try to summarize the article nor will I comment on it beyond one modest observation.)
The GOOG bought Transformic. Transformic has some very prescient innovations. These are not new. In fact, the core insights date from the early 1990s. With the Google plumbing in place, XML and semi structured content processing in the bag, Google has to look beyond today. Never mind that Google’s competitors don’t have a clue what Google does on a day-to-day operational basis. The GOOG is the future.
The killer comment in the nice article by Chris Kanaracus is:
Inside an enterprise, and maybe unlike the Internet, you can know a lot about a user,” such as who they report to, said Matthew Glotzbach, director of product management for Google’s enterprise division. “There’s a lot of empirical information you can derive. All of that can be used to create a very, very rich profile about the user, which can then be used to create a really rich search experience.” Do not expect Google to suddenly bring a game-changing product to market, according to Glotzbach. “The model is not these kind of big-bang approaches where we work for multiple years and then roll something out. In terms of what we do in enterprise search, you’ll see a constant flow, as opposed to one sort of big bang — here’s a whole new thing,” he said.
Mr. Glotzbach was on a panel billed as a debate late last year. Ah, he’s a canny wordsmith that wizard be.
Mr. Glotzbach’s comment comes from the belly of a company planning to start building housing in the year 2013 on prime NASA real estate in Mountain View, Calif.
Time, to Google, means right now and really fast. Time also means the drip drip of incremental functions slipstreamed in apparently meaningless droplets. The pace will be Googley slow. You will need a time lapse camera to note the changes.
Should IBM, Oracle, and other giants in data management worry? Nope, executives at the companies told me that their knowledge of Google is rich, deep, and wide. I do have a nifty briefing about the Transformic technology. Interested? Write me at sa at arnoldit dot com.
A chipper quack to Computerworld for the reference to my new study.
Stephen Arnold, June 5, 2008
More Google Transparency… A Googley Transparency
June 5, 2008
I loathe search engine optimization, the folks who sell snake oil to hapless souls desperate for traffic, and the media for covering this alleged discipline. But I’m 64 and schooled in Model T notions like consistent content, meaningful indexing, and regular additions to the information stock pile.
For the 99 percent of the people who love SEO, you will want to read this Googley post from super Googler Matt Cutts. He provides some candor, some new information, and some spin. The full post is here. The Web log post is “Improved SEO documentation galore!”
The Googler writes:
Google just added a bunch of nice documentation in various places. We even did it in official places — much better than doing it on my personal blog.
Then in the comments, a person identifying himself / herself as “James” cut right through the Googzilla’s clouds of steam. “James” wrote:
What about a place a webmaster can go to communicate with Google about said penalties or changes? Check out webmaster central. It’s littered with webmasters who had great organic traffic one day.. and none the next. This has got to be the most frustrating thing for webmasters trying to do the right thing and follow all Google’s guidelines
Not long ago, a journalist with a nationally-syndicated column called me. The parent company had received some legal instruction to remove a certain article from the Google index. Why this person called me I don’t know. The caller–an ace reporter, mind you–could find the name, email, or phone number of a person at Google to discuss this issue. In fact, the ace reporter told me, “I called a dozen numbers. No one calls back.”
So that’s standard Googley procedure for people who aren’t Googley. The GOOG wants to vaporize Harrod’s Creek geese like me, and it has ignored my requests for comments, queries, and input for several years. But I do keep a collection of super-Googlers on my trusty Treo 650. I was a good person. I provided the ace reporter with some names of people who, in theory, might recall my name much in the way I remember that my barber’s name.
Well, one of my magic Googley names worked. The GOOG listened and allowed the ace reporter to dodge a coronary.
But until the average goose can access lines of communication that work, I’m skeptical. When I read a reassuring statement, I’m inclined to put my head under my wing. Here’s a snippet from Mr. Cutts’ essay:
We do appreciate getting suggestions and feedback from users, webmasters, and SEOs. I’m especially interested when people want to report spam, including paid text links….No search engine is perfect, and everyone will have different opinions about what a search engine should focus on. But I appreciate the feedback that we get from users, webmasters, and SEOs. I know that the suggestions that we get help to make Google a better search engine.
I’m not ready to believe that James’ rejoinder is not dead on and completely transparent. Does the GOOG talk to you? Can you get a Googler on the phone? Does your Google engineer call you back to explain why your Web site has been put in purgatory? Let me know in the comments section of this Web log.
Stephen Arnold, June 4, 2008
Ontos: a Text Processing Company, Not a Weapon
June 5, 2008
In a conference call yesterday (June 4, 2008), someone mentioned “Ontos”. Another person asked, “What’s an Ontos?” I answered, “An anti-tank vehicle” What I remembered about the Ontos is that it was a tank loaded down with so many weapons I a turtle was speedier. Big laugh. Ontos is a company engaged in text and content processing with a product called ObjectSpark. To fill in the void in my knowledge, I navigated to the GOOG, plugged in “Ontos” and found a link to a 2001 article in Intelligent Enterprise, a very good Web site now that the print magazine has been put out to pasture. You can read the description here.
The company’s English language Web site is at www.ontos.com. The product line up no longer relies on the ObjectSpark name. You can license:
- OntosMiner, which “analyzes natural language text. It recognizes objects and their relations and adds them as annotations to the related text parts. The technology is based on semantic rules, i.e. NLP (Natural Language Processing). It uses ontologies to define the area of interest.”
- LightOntos for Workgroups, which “helps to organize and search information and documents. It allows the user to process and annotate PDF, Word, RTF, Text or HTML files using OntosMiner.”
- Ontos SOA, which “realizes the whole cycle of semantic-syntactical processing, management and analysis of unstructured information located in the Internet and large corporative data banks.”
- TAIS Ontos, which is “created as an Application Package using ORACLE technologies and Java. The system uses a semantic designed for building and maintaining object oriented databases. Additional components are effective engines for the search of explicit and hidden relations between objects. A visualization environment (interface) supports the analysts when analyzing a domain of interest. The product is adapted for the segment of law enforcing structures and attributed to the class of anti-criminal analytical systems”
The display of tagged text uses color to identify specific elements. When I saw this display, it reminded me to the output from Inxight Software’s text processing system.
The company’s Russian partner–ZAO AviComp Services–participated in the recent German technical extravaganza, CEBIT 2008.
You will find a handful of white papers on the Ontos Web site. I found “Ontos Solutions for the Semantic Web” quite interesting and informative. You can download it here.
I wasn’t able to locate any pricing or licensing information. If you have some of these data points, please, use the comment form below this essay to share the information with other readers. My email to the company went unanswered.
Based on my clicking through the Web site, you might want to take a look at this system. The white papers and technical descriptions use the buzz words that other vendors bandy about. The one drawback to a system that lacks a high profile in the US is this question, “Does the system meet US security guidelines?” My hunch is that the system is industrial strength; otherwise, the Brussels customer would not have signed a deal to use the Ontos technology.
Stephen Arnold, June 5, 2008
Blekko: More Dough, Same Splash Page
June 5, 2008
In a phone call today, a 20-something complained about my failure to write about Blekko. I said I would check my files. There’s not much information about this new search engine. The few facts in my files peg the company to Rich Skrenta. He was involved in a news site called Topix.net that I used a couple of years ago and then dropped from my “A” list. (More about this above my signature block.)
His new company attracted some Silicon Valley incredible hulks with money; for example, Marc Andreessen (Netscape, Ning, and several other high profile ventures).
The major news, which I overlooked until today, is that the company has raised about $3 million. Among the backers are Baseline Ventures and some ex-Googlers (a better term is Xoogler, which some Googlers prefer). This information came from the very useful Web log PaidContent.org here. TechCrunch does it usual very good job of providing the basics with some intriguing color here.
The Blekko Web site here features a modest amount of information. There’s a link for the press and one for jobs. Oh, the Web site has a snapshot that puts my data bunny to shame. My hunch is that the whimsical will annoy certain tight collar MBAs, but I like the picture.
This is either a “blekko” or a very interesting programmer from MIT or CalTech.
I haven’t been given a demo. I did hear that the company will be using “advanced algorithms” and “semantic technology”. I’m not sure what this means exactly, but I have added Blekko.com to my watch list.
Attensity: Packaging Text Processing for Higher Value Applications
June 5, 2008
Enterprise search is like a poinsettia three weeks after the holidays. The form of the lovely plant remains, but the color is gone. Poinsettia look unhealthy, and my mother callously tossed them in the trash.
Attensity has been working to take its core content processing technology and apply it to problems where search-and-retrieval won’t work or have already failed. With a modest cash infusion from the CIA’s not-so-secret venture arm, Attensity refined its “deep extraction” technology and looked for big problems remained unresolved by other vendors.
For example, customer support is a sore spot. It’s expensive. It’s hard to manage because turnover often soars to 50 to 60 percent per year. Automation remains blind to import clues in a customer email or voice call. Many systems can figure out that “I’m going to sue you” is a negative message. But most don’t know what 🙁 means.
Attensity has taken its rocket science technology and created MarketVoice. According to Insurance Technology, a CMP Publication, and created:
a new solution enabling insurers to track, analyze and act on customer conversations in blogs, Web forums, product review comments, and other forms of online customer exchanges
Please, read the original story by Kristi Cattafi here. Do this quickly. CMP, like other traditional publishers, takes some interesting angles on its own search and retrieval system. Sometimes it is very good. Other times, it is a bit disappointing.
MarketVoice uses the deep extraction technology, but the system figures out where problems may be warming to a boiling point. Attensity has made its system easier to set up than some of the others that claim to do similar functions. You may be familiar with ClearForest, now part of Reuters, which is now part of Thomson, a multi-national professional information company. Attensity’s appraoch strikes me as easier to set up and more nimble. Your perception may differ from mine, but I think Attensity’s MarketVoice is a wake up call to vendors of text processing systems that are designed to do one function, leaving the licensee to the job of integrating the system’s outputs. Attensity delivers a product. Others deliver programming tool kits.
The company has also swizzled its deep extraction invention to process content on Web logs. Web log content is often hard to figure out. Some comments are declarative. Some are tongue in cheek. Others are spoofs; for example, today I received a comment from a person claiming to be a Googler. Google does not interact directly with me. This is an “old” Google-conceived rule. This spoofer tipped his hand by contacting me directly. That type of context is beyond the ken of text processing systems. Not even Attensity can figure out the sub text for the alleged Google post and my remarks in this paragraph.
Most text processing systems can’t figure out the context of the information, so indexing these primary and secondary components of an article and figuring out what the link means is not trivial. Atensity’s system grinds through text on a Web log and generates reports about customer sentiment. Attensity’s approach is useful, and it works quite well. You can read more about this system here. If the link 404s, just navigate to www.attensity.com and poke through the information on the site.
Dr. David Bean, a wizard with a passion for language, has been aggressive in his push to make rocket science useful to mere mortals.
Attensity’s productizing of content analysis is a good example of how to grow a market without making your customers withhold their licensing fees. The company is focusing on large back office specialists. More information about this MarketVoice application is here.
As the screws tighten on vendors of pure search or stand alone text processing software, studying Dr. Bean’s retooling of his rocket science technology may be useful. Attensity is a bit ahead of some of its competitors. Companies will sagging revenues may want to bone up on Attensity’s business model sooner rather than later.
I flagged Attensity as a company to watch in my April 2008 study Beyond Search.
Stephen Arnold, June 5, 2008
-
- Subscribe to Beyond Search
Feature archive
News archive
-
