Big Data: The McKinsey Way
September 11, 2015
I read “6 Observations from a New Survey on the State of Big Data Analytics.” The data come from a study underwritten by a magazine outfit, a blue chip consulting firm, and a company selling storage and related bright and shiny things.
I found the write up suggestive. The first finding was a bomb shell.
The hype gone, big data is alive and doing well.
Aside from the subject-verb error coming from data is when data is the plural of datum, the information is revolutionary. Big Data is no longer subject to hyperbole. I did not know that. Topsy.com tallied 3,154 tweets about Big Data in the the 24 hours of September 8, 2015. For comparison, Big Data is in a dead heat with the tweets about the Bentley Bentayga SUV. Good company. FYI: Katy Perry managed only 1,468 tweets in the same time period. Nevertheless, in Harrod’s Creek, Big Data, expensive autos, and a musical 30 year old are buzz machines.
The write up reports:
No matter how many times you say “data-driven,” decisions are still not based on data. Sounds familiar? 51% of executives said that adapting and refining a data-driven strategy is the single biggest cultural barrier and 47% reported putting big data learning into action as an operational challenge.
Yikes. More consulting is needed to get this cultural change thing underway.
Other findings that underpin the article are:
- If the CEO is into Big Data, the company is into Big Data…mostly. If the CEO is like the airline executives in the news, the CEO may have other interests
- I love this: “Even if you have top leadership sponsorship and the right culture, getting data to drive action and strategy is a challenge. 48% of executives surveyed regard making fact-based business decisions based on data as a key strategic challenge, and 43% cite developing a corporate strategy as a significant hurdle.” Maybe Big Data is not the slam dunk consultants and journalists wish it to be?
- Brontobyte data. Hey, we have perfectly useful words to suggest unimaginably large quantities. I like yottabyte. The study sponsors seem to be okay with the brontobyte coinage. Very hip, but I would have created a variant of Diplodocus. More colorful for sure.
- There is a shortage of “big data miners.” Okay, I understand. The user friendly analytics tools are just not too helpful unless a company has someone who actually paid attention in statistics classes.
The only thing missing from this write up is links to the sponsors’ product pages. By the way, the article pumps up Big Data. Amusing stuff.
Stephen E Arnold, September 11, 2015
Who Will Be the IDC Cognitive Guru?
September 10, 2015
You remember Dave Schubmehl. He is the IDC “search” expert who recycled some of my content. He then sold a report based on my work via Amazon. My meek attorney was able to get the document removed. Not even a legal eagle could fathom how eight pages of analysis could command $3,500. Mr. Bezos knows that $9.99 is a sweet spot. I suppose the masters of management at IDC thought that $3,500 report would sell like hot cakes to the consumers of romance novels, streaming video, and household commodities.
I noted a tweet (show below) that suggests his unit at IDC is going like gang busters. New staff with undergraduate degrees are needed. Uber drivers, are you paying attention?
When a consulting firm adds headcount, that’s news. I hope that the Renaissance men and women at IDC can make sense of “cognitive computing.” Google pushes “deep learning.” I suppose there will be more buzzwords as the “experts” in enterprise search flail for purchase on the slopes of Mount Make a Sale.
Most of the experts have answers to the most difficult problems in business. The only hitch in the git along occurs when the “experts” do not have certain knowledge. Oh, another modest problem is recycling another’s information without taking the time to issue a contract.
I am confident that the customers of Amazon really did want to buy that $3,500 report. Mid tier consulting firms are the cat’s pajamas. I wonder if that comes from asking IBM Watson questions.
Stephen E Arnold, September 10, 2015
IHS Mines Gartner for Goldfire
September 10, 2015
If you want to read a “pat Goldfire on the back” statement, navigate to “IHS is Recognized as a Visionary in Gartner’s 2015 Magic Quadrant for Enterprise Search.”
I assume you, gentle reader, are up to speed on Invention Machine. No, strike that. You are up to speed on Goldfire, the IHS (Information Handling Service) enterprise search system.
If not, you can dig into the news release for details about how Goldfire can, and I quote:
- Decrease product development cycle time
- Increase the innovation pipeline
- Accelerate market share and competitive position
- Drives top-line margin expansion, and
- Increase productivity gains
There’s not much about search and retrieval, but that’s a minor detail.
What’s important in the news release is this statement which appears in the IHS Magic Quadrant write up about Goldfire:
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
There it is. The “research” is opinion based.” I think I understand that a Gartner report is not to “be construed as statements of fact.” Okay. I did not know that because I understood (obviously incorrectly) that a rigorous analytic process formed the foundation of the vendor selection and categorization.
Guess not. Wow. Who knew? Oh, I know. The PR firms issuing news releases from enterprise search vendors who are leaders, visionaries, etc.
Stephen E Arnold, September 10, 2015
Bar Exam Brouhaha
September 7, 2015
We cannot resist sharing this article with you, though it is only tangentially related to search; perhaps it has implications for the field of eDiscovery. Bloomberg Business asks and answers: “Are Lawyers Getting Dumber? Yes, Says the Woman who Runs the Bar Exam.”
Apparently, scores from the 2014 bar exam dropped significantly across the country compared to those of the previous year. Officials at the National Conference of Bar Examiners (NCBE), which administers the test, insist they carefully checked their procedures and found no problems on their end. They insist the fault lies squarely with that year’s crop of law school graduates, not with testing methods. Erica Moeser, head of the NCBE, penned a letter to law school officials informing them of the poor results, and advising they take steps to improve their students’ outcomes. To put it mildly, this did not go well with college administrators, who point out Moeser herself never passed the bar because she practices in Wisconsin, the only state in which the exam is not required to practice law.
So, who is right? Writer Natalie Kitroeff points out this salient information:
“Whether or not the profession is in crisis—a perennial lament—there’s no question that American legal education is in the midst of an unprecedented slump. In 2015 fewer people applied to law school than at any point in the last 30 years. Law schools are seeing enrollments plummet and have tried to keep their campuses alive by admitting students with worse credentials. That may force some law firms and consumers to rely on lawyers of a lower caliber, industry watchers say, but the fight will ultimately be most painful for the middling students, who are promised a shot at a legal career but in reality face long odds of becoming lawyers.”
The 2015 bar exam results could provide some clarification, but those won’t start coming out until sometime in September. See the article for much more information on Moeser, the NCBE, the bar exam itself, and the state of legal education today. Makers of eDiscovery software may want to beef up their idiot-proofing measures as much as possible, just to be safe.
Cynthia Murrell, September 7, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Subjective Big Data: Marginalized Hype from a Mid Tier Outfit
September 4, 2015
I read “Why Gartner Dropped Big Data Off the Hype Curve.” The article purports to explain why Gartner Group, a mid tier consulting firm, eliminated Big Data from its hype cycle. Let me ask, “Perhaps Big Data reports do not sell to executives who have zero clue what Big Data means to a struggling business?” The write up is an analytics and data clean room. Facts are tough to discern.
The article included a chart without numbers to help knowledge hungry folks figure out what technology is an innovation trigger, a technology which is at the peak of inflated expectations, what technology have fallen (gasp!) into the trough of disillusionment, which are on the slope of enlightenment, and which have reached the plateau of productivity.
The write up fills the empty vessel of my mind with this insight from a mid tier wizard, Betsy Burton. She allegedly revealed:
There’s a couple of really important changes,” Burton says. “We’ve retired the big data hype cycle. I know some clients may be really surprised by that because the big data hype cycle was a really important one for many years. “But what’s happening is that big data has quickly moved over the Peak of Inflated Expectations,” she continues, “…and has become prevalent in our lives across many hype cycles. So big data has become a part of many hype cycles.”
I like that observation about Big Data becoming part of many hype cycles.
That’s reassuring. I don’t know what Big Data is, but it is now part of many hype cycles.
I like subjective statements about what is moving through a hype cycle. When one hype cycle is not enough, then put the fuzzy wuzzy statement into many hype cycles. Neat.
The article explains that other “notable subtractions” took place; for example, drop outs include:
- Prescriptive analytics, which I presume are numbers which are not used in this article’s graphics. Numbers are so annoying because one must explain where the numbers came from, figure out if the numbers are accurate, and then make decisions about how to extract valid outputs from numerical recipes. Who has time for that?
- Data science. I am not sure what this means, but it’s off the hype cycle hit parade.
- Complex event processing. Sounds great but it too is a victim of the delete button.
I view the listing as subjective. Subjectivity is useful, particularly when discussing which painting in the Wildenstein Collection is the best one or which of Mozart’s variations is the hot one.
Objective analyses, in my opinion, to make a case that virtual reality is on the slope of enlightenment or that affective computing is lifting off like a hyperbole fueled rocket.
Am I the only one who finds these subjective lists silly? My hunch is that the reason concepts get added to the list is to create some demand for a forthcoming study. The reason stuff disappears is because reports about the notion do not sell.
I wonder if there are data available from mid tier consulting firms to back up my hypothesis. Well, we can argue whether pale ivory is more attractive than honey milk.
Interior design professionals will go to the mattresses tinted white wisp to defend their subjective color choice. Do mid tier consultants share this passion?
Stephen E Arnold, September 4, 2015
Do Search and CMS Deliver a Revenue Winner?
August 21, 2015
I spotted a write up called “Look for Enterprise Search, Analytics and These ECM Leaders for Your Transactional Content.” I found the article darned amazing even for public relations about a mid tier consulting firm and one of its analyses.
The main point of the article is that analysts have analyzed enterprise software and identified vendors who provide “ECM Transactional Content Services.” Fabricating collections of objects and slapping a jargon laded label on the batch is okay with me.
Empty calories await you, gentle reader.
What struck me as interesting was this statement:
Forrester Vice President and Principal Analyst Craig Le Clair points to key advancements and opportunities by the leading ECM providers to help enterprises realize greater value in these systems:
- Ramping analytics to drive insight and reduce administrative burden
- Accelerating their move to cloud
- Improved search and content sharing
- Using stronger and more open application program interfaces (APIs) that spur innovation
- Moving quickly to fill gaps in their mobile road maps.
Notice the “ECM”. The acronym refers to software which provides editing, access, and publishing functions to its users. The idea, it seems, is that an employee will write a memo and the ECM will keep track of the document. In practice, based on my experience, the ECM recipe usually fails to satisfy my hunger.
ECM and its close cousins in acronym land are similar to the approach articulated by my kindergarten teacher more than half century ago. She said, according to my mother, “Keep your mittens and lunch in your cubby.” The spirit of the kindergarten teacher lives on in enterprise content management systems.
Unfortunately those who have work to do often create content using tools suited for a specific task. For an engineer, that tool might be Solidworks. Bench chemists are often confused when an ECM is described as the tool for their work. One chemist said to me after an enthusiastic presentation by an information technology person, “I work with chemical structures. What’s this person talking about?” Lawyers in the midst of big risk litigation want to use their own and often flawed document systems. Even the marketer who cheers for ECM for Web content parks some high value data in that wonderful Adobe creative cloud with some back up data on iCloud. I have spotted a renegade analyst with an off the books workstation equipped with an Australian text processing and search system. USA.gov is notable for what is not available because executive brand entities roll their own content solutions.
I was able to review a copy of the consultant report upon which the article was based. Wowza. The write up assembled a grad bag of widely disparate companies, added three cups of buzzwords, and output mixed in one kilo of MBAisms.
To be fair, the report identified “challenges.” These items baffled me. For example, “Deep experience in key transactional applications.” This is a challenge, really?
But the vendors in the report are able to “address emerging opportunities.” Okay, so these are not opportunities. The opportunities are emerging. Hmmm. Here’s an example: “Ramping analytics to drive insight and reduce administrative burden.” Yikes. Ramping analytics. Driving analytics. Reducing administrative burden. Very active stuff this ECM. Gerund alert. Gerund alert.
What companies are into this suite of challenges and emerging opportunities? Here’s the list of the mid tier touted stallions from the ECM stable:
- EMC, a company which is considering having a subsidiary of itself purchase the parent company. Folks, when a company does this type of recursive stuff, the core business might be a little bit uncertain.
- HP. Yep, an outfit which has lost its way, suffered five consecutive quarters of declining revenue, and bought a company for $11 billion and then wrote off most of that expense because the sellers of the company fooled HP, its consultants, accountants, and lawyers. Okay. A winner for the legal eagles maybe.
- IBM. Heaven help me. IBM has suffered declining revenues for 13 consecutive quarters, annoyed me with a blizzard of Watson silliness, and spent lots of time getting rid of businesses. I have a difficult time believing that IBM can manage enterprise content. But, hey, that’s just my rural Kentucky ignorance, right?
- Laserfiche. The company offers a “flexible, proven enterprise content management system. I believe this statement. The company was founded in 1987 and sure seems to have its roots in well seasoned technology. The company has lots of customers and lots of award. The only hitch in the git along is that I never ran across this outfit in my work. Bad luck I guess.
- Lexmark. Folks, let us recall the rumor that Lexmark and its content businesses are not money makers. I heard that the content cluster achieved an astounding $70 to $80 million shortfall. Who knows if this rumor is accurate. I do know that Lexmark is cutting staff, and one does not take this drastic step unless one needs to reduce costs pronto.
- M Files. I never heard of this outfit. I did a quick check of my files and learned that the company “helps enterprises find, share, and secure documents and information. Even in highly regulated industries.” The company is also “passionate about productivity.” The outfit relies on dtSearch for information access. This is okay because dtSearch can process most of the content within a Microsoft-centric environment. But M Files strikes me as a different type of outfit from HP or IBM. As I flipped through the information I had collected, the company struck me as a collection of components. Assembly required.
- Newgen Software. Another newbie for me. The company was in my Overflight archive. The firm provides BPM (business process management), ECM (enterprise content management), DMS (I have no idea what this acronym means), CCM (I have no idea what this acronym means), and workflow (I thought this was the same as BPM). The company operated from New Delhi. My thought? Another collection of components with assembly in someone’s future.
- Hyland OnBase. This is the third outfit on the list about which I have a modest amount of information. The company says that it is a “leader in ECM.” I believe it. The firm’s url is the same as its flagship product. The company was founded in 1991 and created OnBase, which is a plus. After 25 years, the darned thing should work better than a Rube Goldberg solution assembled from a box of components.
- OpenText. Okay, OpenText is a company which has more search engines and content processing systems than most Canadian firms. The challenge at OpenText is having enough cash to invest in keeping the diverse assortment of systems current. Which of these systems is the one referenced in the mid tier firm’s report? SGML search, BASIS, BRS, Nstein, the Autonomy stub in RedDot, Nstein, Fulcrum, or some other approach? Details can be important.
- Unisys. Okay, finally a company that is essentially an integrator which still supports Burroughs mainframes. Unisys can implement systems because it is an integrator. For government work, Unisys matches the statement of work to available software. Although some might question this statement, Unisys can implement almost any kind of system eventually.
Several observations:
First, enterprise content management is a big and fuzzy concept. The evidence of this is the number of acronyms some of the companies use to explain what they do. I assume that it is my ignorance which prevents me from understanding exactly how scanning, indexing, retrieval, repurposing, workflow, and administrative functions work in a cost constrained, teleworker, mobile gizmo world.
Second, open source is knocking on the door of this sector. At some point, organizations will tire of the cost and complexity of collections of loosely federated and integrated software subsystems and look for an alternative. Toss in the word Big Data, and there will be a stampede of New Age consultants ready to step forward and reinvent these outfits. Disruption is probably less of a challenge than the challenge of keeping existing revenues from doing the HP, IBM, and Lexmark drift down.
Third, the search function seems to be a utility or an after thought. The only problem is that search does not work particularly well in an enterprise where the workers log in from Starbucks and try to interact with enterprise software from a Blackberry.
Fourth, what an odd collection of outfits? HP, IBM, and Lexmark along with 30 year old imaging firms plus some small outfits. Maybe the selection of firms makes sense to you, gentle reader. For me, the report make evident the struggles of some experts in ECM, BPM, and the acronyms I know zero about.
In short, this mid tier report strikes me as a russische punschtorte. On the surface, the darned thing looks good, maybe mouth watering. After a chomp or two, I want a paprikahenderl.
This ECM thing is a confection, not a meaty chicken. Mixing in search does nothing for the recipe.
Stephen E Arnold, August 22, 2015
A Wit Emulates Chip Foose with a Magic Gartner Touch Up
August 18, 2015
I am out of the loop when it comes to mid tier consulting firms and analyzing their outputs on a regular basis. Much of the content is thinly disguised word play designed to generate sales leads. Think data lake and customer care.
I am out of the loop on almost everything. When my squirrel powered Internet connection works, I am lucky if I can see 10 percent of a Yahoo.com page before my connection fags out.
I was able to read a story I found subjective and (okay, I admit it) amusing. If Jack Benny were alive, his writers might have incorporated the information into a Buck Benny episode with Andy Devine explaining the Gartnerian motion.
The write up was “Yellow and Blue Circles, Red Arrows Add to Gartner’s Magic Quadrant.” To me, I thought immediately of Chip Foose and his ability to take a ho hum vehicle, add some Foose-tian touches, and thrill the owner. I see these make overs as a Foose-tian deal with the devil, however. I like the autos as they are.
The write up pivots on a person taking two Gartner magic thingamajigs and tried to figure out what changed between two reports about something called “integrated systems.” I don’t know what that means, but as previously stated, I am in rural Kentucky.
Nothing catches the eye like an annual matrix analysis touch up. These are expensive and, in the end, subjective. Congruence? Similarity?
The point of the write up struck me as:
Incidentally, Valdis Filks, Gartner’s lead on the Magic Quadrant reports, tells us how to position and interpret MQS in Gartner’s set of reports about supplier ranking and positioning: “The MQ is focused on the ability of vendors to succeed in a specific market, rather than about products. There is lots in it about understanding customer needs, direction, service, marketing, support, innovation and many other criteria.”
I think I understand. Subjective decisions. No problemo.
The plotting of two magic whatevers (MWs) revealed:
There’s been a lot of movement and five new entries. Two previous entries have disappeared as well; Bull and Unisys.
Wasn’t Bull the Amesys owner? Doesn’t Unisys maintain Burroughs’ computers? I thought IBM did Linux mainframes and Watson? And Huawei? Okay.
My take pivots on this question, “What the heck is an integrated system?” Everything, including the choice of arrow color seems somewhat arbitrary. General Eisenhower’s box, as I recall, relied sometimes on actual data.
What did that guy know? Probably not much about integrated systems.
Stephen E Arnold, August 18, 2015
Mid Tier Consulting Firm Identifies the New Economy
August 16, 2015
The information economy is officially over. There is a new economy in town, and you need to listen up. I can hear R Lee Ermey, the drill sergeant in Platoon saying, “You are dumb, Private Pyle, but do you expect me to believe that you don’t know left from right?”
I read “Big Data Fades to the Algorithm Economy.” I thought Big Data was the future. Guess I was wrong again. I learned that “Algorithms are all around us.” Gee, I did not know that.
I learned:
For organizations, the opportunity will first center on monetizing their proprietary algorithms by offering licensing to other non-competing organizations. For example, a supply chain company can license its just-in-time logistics algorithms to a refrigerator manufacturer that seeks to partner with a grocery chain to automatically replenish food based on your eating habits. Why invent or slowly develop sophisticated algorithms at huge cost when you can license and implement them quickly at low cost?
There is “fevered questioning” underway. Gee, I did not know that. In my experience, I see more “fevered confusion.”
But the fix is “proprietary algorithms.”
Okay, what is an algorithm?
A formula or set of steps for solving a particular problem. To be an algorithm, a set of rules must be unambiguous and have a clear stopping point. Algorithms can be expressed in any language, from natural languages like English or French to programming languages like FORTRAN.
It seems to me that a procedure qualifies as an algorithm if it works. A proprietary algorithm is, I assume, a trade secret.
I am delighted that math is not involved; otherwise, there is the problem with companies built on procedures endlessly recycled from books like Algorithms in a Nutshell, Algorithms, The Art of Computer Programming, and other standard texts with loads of numerical recipes.
I understand. The mid tier consulting firm is defining a business process as an algorithm. Magic. Well, if Big Data won’t sell – If enterprise search won’t sell — If content management won’t sell, just go with algorithms.
How quickly will McKinsey, Bain, BCG, Booz, and SRI pick up on this conceptual breakthrough? Any moment now. I assume each company’s blue chip consultants know left from right — usually. Other outfits may get confused. Left? Right?
Stephen E Arnold, August 16, 2015
Enterprise Search: You Cannot Do It Yourself, People.
July 31, 2015
I love write ups like “Don’t Settle When It Comes to Enterprise Search Platforms.” These articles are designed to make consulting firms with the marketing flim flam which positions each as an “expert” in enterprise information access. I would not be surprised to find copies of this article in the peddler kit of search sales professionals.
The main point of the write up is that enterprise search is a “platform.” Because there are options, no self respecting company will try to implement search without the equivalent of the F Troop in mid tier or below consultants.
I noted:
Let’s look at two very common workarounds some have tried, and then we will talk about why you must go with a reputable developer when you make your final decision.
When I read this, I wondered if the “expert” were familiar with the Maxxcat line of enterprise search systems or the Blossom hosted solution.
The write up dismisses an open source solution apparently unaware of research by Diomidis Spinellis and Vaggelis Giannikas work published in Journal of Systems and Software, March 2012, pages 666 to 682. That’s okay. My hunch is that those finding the “Don’t Settle” article compelling are not likely to be interested in researchy type stuff.
One of the more interesting segments in the write up is the assertion that scalability is a “given.” Hmmm. In my experience, there are some on going enterprise search challenges: Scalability is one facet of a nest of vipers which includes my favorite reptile indexing latency.
The article states:
Open source platforms are only as scalable as their code allows, so if the person who first made it didn’t have your company’s needs in mind, you’ll be in trouble. Even if they did, you could run into a problem where you find out that scaling up actually reveals some issues you hadn’t encountered before. This is the exact kind of event you want to avoid at all costs.
I don’t want to rain on this parade of “information,” but every enterprise search system which I have had the pleasure of procuring, managing, investigating, and analyzing has scalability problems.
The reason is simple: The volume of changed information and the flow of new information goes up. Whatever one starts with is rather rapidly choked. The solutions are painful: Spend more or index less.
I am not confident that one who follows the advice of certain experts will find his or her enterprise search journey pleasant. On the other hand, there are opportunities as Uber drivers one can pursue.
Stephen E Arnold, July 31, 2015
PowerPoint Enabled Big Data Presenters Rejoice
July 27, 2015
Navigate to “A Plethora of Big Data Infographics.” Note that the original write up misspells “plethora” at “pletora” but, as many in Big Data say, “it is close enough for horseshoes.”
I quit browsing after a baker’s dozen of these puppies. If you want to be an expert in Big Data, these charts will do the trick. I would steer clear of a person with a PhD in statistics, however.
Stephen E Arnold, July 27, 2015
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