Turn Back the Online Clock: Portals Are Back

March 25, 2018

Short honk: Believe it or not “portals” are once again a must have. Don’t believe it. Navigate to Menafn and read “Enterprise Portal Market Is Expected to Reach Approximately USD 41 Billion by 2023.” Sound like a bandwagon to ride? The Beyond Search goose thinks the report is precursor to one about hand cranked washing machines.

Stephen E Arnold, March 25, 2018

Governance: Now That Is a Management Touchstone for MBA Experts

February 27, 2018

I read “Unlocking the Power of Today’s Big Data through Governance.” Quite a lab grown meat wiener that “unlocking,” “power,” “Big Data,” and “governance” statement is that headline. Yep, IDG, the outfit which cannot govern its own agreements with the people the firm pays to make the IDG experts so darned smart. (For the back-story, check out this snapshot of governance in action.)

Image result for wishful thinking

What’s the write up with the magical word governance about?

Instead of defining “governance,” I learn what governance is not; to wit:

Data governance isn’t about creating a veil of secrecy around data

I have zero idea what this means. Back to the word “governance.” Google and Wikipedia define the word in this way:

Governance is all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society.

Okay, governing. What’s governing mean? Back to the GOOG. Here’s one definition which seems germane to MBA speakers:

control, influence, or regulate (a person, action, or course of events).

The essay drags out the chestnuts about lots of information. Okay, I think I understand because Big Data has been touted for many years. Now, mercifully I assert, the drums are beating out the rhythm of “artificial intelligence” and its handmaiden “algos,” the terrific abbreviation some of the marketing jazzed engineers have coined. Right, algos, bro.

What’s the control angle for Big Data? The answer is that “data governance” will deal with:

  • Shoddy data
  • Incomplete data
  • Off point data
  • Made up data
  • Incorrect data

Presumably these thorny issues will yield to a manager who knows the ins and outs of governance. I suppose there are many experts in governance; for example, the fine folks who have tamed content chaos with their “governance” of content management systems or the archiving mavens who have figured out what to do with tweets at the Library of Congress. (The answer is to not archive tweets. There you go. Governance in action.)

The article suggests a “definitive data governance program.” Right. If one cannot deal with backfiles, changes to the data in the archives, and the new flows of data—how does one do the “definitive governance program” thing? The answer is, “Generate MBA baloney and toss around buzzwords.” Check out the list of tasks which, in my experience, are difficult to accomplish when resources are available and the organization has a can-do attitude:

  • Document data and show its lineage.
  • Set appropriate policies, and enforce them.
  • Address roles and responsibilities of everyone who touches that data, encouraging collaboration across the organization.

These types of tasks are the life blood of consultants who purport to have the ability to deliver the near impossible.

What happens if we apply the guidelines in the Governance article to the data sets listed in “Big Data And AI: 30 Amazing (And Free) Public Data Sources For 2018.” In my experience, the cost of normalizing the data is likely to be out of reach for most organizations. Once these data have been put in a form that permits machine-based quality checks, the organization has to figure out what questions the data can answer with a reasonable level of confidence. Getting over these hurdles then raises the question, “Are these data up to date?” And, if the data are stale, “How do we update the information?” There are, of course, other questions, but the flag waving about governance operates at an Ivory Tower level. Dealing with data takes place with one’s knees on the ground and one’s hands in the dirt. If the public data sources are not pulling the hay wagon, what’s the time, cost, and complexity of obtaining original data sets, validating them, and whipping them into shape for use by an MBA?

You know the answer: “This is not going to happen.”

Here’s a paragraph which I circled in Oscar Mayer wiener pink:

One of the more significant, and exciting, changes in data governance has been the shift in focus to business users. Historically, data has been a technical issue owned by IT and locked within the organization by specific functions and silos. But if data is truly going to be an asset, everyday users—those who need to apply the data in different contexts—must have access and control over it and trust the data. As such, data governance is transforming from a technical tool to a business application. And chief data officers (CDOs) are starting to see the technologies behind data governance as their critical operating environment, in much the same way SAP serves CFOs, and Salesforce supports CROs. It is rare to find an opportunity to build a new system of record for a market.

Let’s look at this low calorie morsel and consider some of its constituent elements. (Have you ever seen wieners being manufactured? Fill in that gap in your education if you have not had the first hand learning experience.)

First, business users want to see a pretty dashboard, click on something that looks interesting in a visualization, and have an answer delivered. Most of the business people I know struggle to understand if the data in their system is accurate and limited expertise to understand the mathematical processes which churn away to display an “answer.”

The reference to SAP is fascinating, but I think of IBM-type systems as somewhat out of step with the more sophisticated tools available to deal with certain data problems. In short, SAP is an artifact of an earlier era, and its lessons, even when understood, have been inadequate in the era of real time data analysis.

Let me be clear: Data governance is a management malarkey. Look closely at organizations which are successful. Peer inside their data environments. When I have looked, I have seen clever solutions to specific problems. The cleverness can create its own set of challenges.

The difference between a Google and a Qwant, a LookingGlass Cyber and IBM i2, or Amazon and Wal-Mart is not Big Data. It is not the textbook definition of “governance.” Success has more to do with effective problem solving on a set of data required by a task. Google sells ads and deals with Big Data to achieve its revenue goals. LookingGlass addresses chat information for a specific case. Amazon recommends products in order to sell more products.

Experts who invoke governance on a broad scale as a management solution are disconnected from the discipline required to identify a problem and deal with data required to solve that problem.

Few organizations can do this with their “content management systems”, their “business intelligence systems,” or their “product information systems.” Why? Talking about a problem is not solving a problem.

Governance is wishful thinking and not something that is delivered by a consultant. Governance is an emergent characteristic of successful problem solving. Governance is not paint; it is not delivered by an MBA and a PowerPoint; it is not a core competency of jargon.

In Harrod’s Creek, governance is getting chicken to the stores in the UK. Whoops. That management governance is not working. So much in modern business does not work very well.

Stephen E Arnold, February 27, 2018

Big Data, Search, and Artificial Intelligence: Quite a Mash Up

January 29, 2018

I read a consultant-technology mash up marketing essay. The write up is “Big Data and Search: The Time for Artificial Intelligence Is Now.” The write up is mostly jargon. I wonder if the engineer driving the word processing train pushed the wrong button.

Image result for train wreck

Here are the “keywords” I noted in the write up:

Analytics
Artificial intelligence
Big Data
Blockchain
Business action and business use cases
Chatbots
Cognitive (presumably not the IBM which maybe doesn’t work as advertised)
Consumer services
Customer / citizen facing (some government speak too)
Digital assistants
False or biased results (yes, fake news)
Keywords
Machine learning
Natural language processing
Platforms
Real time results
Resources
SQL databases
Search
Transparency
Trust
Video

Read more

IBM Disputes Bain Claim

January 12, 2018

I don’t read the Poughkeepsie Journal very often. However, I made a delightful exception this morning. The story “IBM Disputes Report of Redeploying Staffers” reminded me of Robert X Cringely’s The Decline and Fall of IBM and its subsequent hoo-hah. My recollection is that IBM suggested that Mr. Cringely (whom I think of as X) was off base. I am not sure he was.

The Poughkeepsie article reported:

An IBM spokesman disputed an article reporting the company plans to reassign roughly 30 percent of Global Technology Services staffers through attrition this year.

A British online publication reported that Bain was likely to help IBM on its road to recovery.

IBM, according to the Poughkeepsie source, said:

“It’s not accurate,” said Clint Roswell, spokesman for IBM’s Global Technology Services business. He did not give specifics on what information was inaccurate. “The company did not make any announcement and we don’t comment on speculation,” Roswell said. He said IBM hires “many consultants, many of whom make recommendations. It’s as simple as that.”

Okay, where did the British publication’s story originate?

Another question: If IBM hires lots of consultants, why did this particular Bain report trigger a response in the estimable Poughkeepsie newspapers?

My hunch is that a kernel of truth resides in the British report and the IBM denial.

IBM is going to have to do some fancy dancing. Whether Bain, BCG, Booz, McKinsey, or another of the blue chip consulting firms get the job of fixing IBM, the system and method will lead to the same changes I described in “IBM Watson: Fresh Out of Correct Answers?

For those who have made it through advanced degree programs, the blue chip consulting firm charm schools, and the on the job training with Type A “experts”—the thought processes lead to:

  • Reassessment of internal financial data
  • Calculations to identify cost savings and money making opportunities
  • Ranking of units and their people
  • Reorganizations
  • Sales of certain business units
  • Embedding of consultants in place of existing managers
  • An effort to work directly with the Board of Directors

These types of changes are ones that people working for a company rarely make without the help of outside expertise.

Maybe IBM is on its way to sustainable revenues and impressive growth dusted with healthy profits?

On the other hand, IBM admits it works with lots of advisers. One of those outfits will get the job to fix IBM. The result will be the same sequence of actions identified in the dot points above.

The third quarter earning come out during the week of January 15, 2018. Has IBM returned to its glory days? If so, forget the consultants with repair kits. On the other hand, if the numbers are not exciting, maybe the Bainies or another blue chip outfit will be able to flip on the chain saw and do what has to be done. I think I can safely assert that asking Watson will not be Job One.

Stephen E Arnold, January 12, 2018

IBM Watson: Fresh Out of Correct Answers?

January 11, 2018

As a former laborer in the vineyard of a blue chip, bit time, only slightly misunderstood consulting firm, I know when a client throws in the towel.

I read allegedly accurate write up “Black & Blue: IBM Hires Bain to Cut Costs, Up Productivity.” Let’s assume that the story has the hiring of the Bainies 100 percent correct. (If you see me at one of the law enforcement and intelligence conferences at which I will be speaking in 2018, ask me about the Holiday Inn and Route 128 meetings from the late 1970s. That’s an interesting Bain anecdote in my opinion.)

The write up informed me:

IBM has indicated to senior Global Technology Services management that that a third of the global workforce will be “productively redeployed” in 2018 with tens of thousands of personnel “impacted”. Insiders told The Reg that Big Blue had hired consultant Bain & Company to help it plot a way forward for GTS, bringing in external business consultants despite spending $3.5bn to buy PWC in 2002

Interesting.

Let me share my view of what will happen:

  1. Hiring a big time, blue chip consulting firm will lead to upper management changes. I would not be surprised to see a Bainie become the shadow CEO of the company with other Bainies advising the Board of Directors. The reason? In order to book revenues, one moves up the food chain until the blue chip outfit is at the top of the heap and has a way to punch the cash register keys.
  2. Lots of people will lose their jobs. The logic is brutal. If your unit is not making money or hitting its targets, you are part of the problem. The easiest way to solve the problem is to show the underperformers the door with a friendly “find you future elsewhere, you lucky devil.”
  3. Divestitures will play a role in the remediation effort. If the incumbent management cannot turn a sow’s ear into a silk purse, polish it up, whip out some nifty future value diagrams, and sell what Boston Consulting folks once called “dogs.” Bain, like the Boozer, borrowed the BCG quadrant thing, and it will play a part in the Bain solutions.
  4. The stock price will go up. Hey, Bain is like magic dust. Those buy backs should have been used to generate new, sustainable revenue. Now with the Bainies reanalyzing the data, some Wall Street MBAs will see gold in them thar terminations, sell offs, and reorganizations.

Worth watching. If Bain is not on board, at some point another blue chip outfit will like McKinsey & Company could implement the same game plan.

In short, IBM is over. I suppose I could ask IBM Watson, but why bother? Time might be better spent trying to land a top job at Big Blue. Are you on Bain’s radar?

Stephen E Arnold, January 11, 2018

Filtered Content: Tactical Differences between Dow Jones and Thomson Reuters

December 5, 2017

You may know that Dow Jones has an online search company. The firm is called Factiva, and it is an old-school approach to finding information. The company recently announced a deal with an outfit called Curation. Founded by a former newspaper professional, Curation uses mostly humans to assemble reports on hot topics. Factiva is reselling these services, and advertising for customers in the Wall Street Journal. Key point: This is mostly a manual method. The approach was more in line with the types of “reports” available from blue chip consulting firms.

You may also know that Thomson Reuters has been rolling out machine curated reports. These have many different product names. Thomson Reuters has a large number of companies and brands. Not surprisingly, Thomson’s approach has to apply to many companies managed by executives who compete with regular competitors like Dow Jones but also among themselves. Darwin would have loved Thomson Reuters. The point is that Thomson Reuters’ approach relies on “smart” software.

You can read about Dow Jones’ play here.

You can read about Thomson Reuters’ play here.

My take is that these two different approaches reflect the painful fact that there is not clear path forward for professional publishing companies. In order to make money from electronic information, two of the major players are still experimenting. The digital revolution began, what?, about 40 years ago.

One would have thought that leading companies like Dow Jones and Thomson Reuters would have moved beyond the experimental stage and into cash cow land.

Not yet it seems. The reason for my pointing out these two different approaches is that there are more innovative methods available. For snapshots of companies which move beyond the Factiva and Thomson methods, watch Dark Cyber, a new program is available every Tuesday via YouTube at this link.

Stephen E Arnold, December 5, 2017

Natural Language Processing: Tomorrow and Yesterday

October 31, 2017

I read “Will Natural Language Processing Change Search as We Know It?” The write up is by a search specialist who, I believe, worked at Convera. The Search Technologies’ Web site asserts:

He was the architect and inventor of RetrievalWare, a ground-breaking natural-language based statistical text search engine which he started in 1989 and grew to $50 million in annual sales worldwide. RetrievalWare is now owned by Microsoft Corporation.

I think Fast Search acquired a portion of Convera. When Microsoft purchased Fast Search, the Convera technology was part of the deal. When Convera faded, one rumor I captured in 2007 was that some of the Convera technology was used by Ntent, formed as the result of a merger between Convera Corporation and Firstlight ERA. If accurate, the history of Convera is fascinating with Excalibur, ConQuest, and Allen & Co. in the mix.

In the “Will Natural Language Processing Change Search As We Know It” blog post, I noted these points:

  • Intranets incorporating NLP, semantic search and AI can fuel chatbots as well as end-to-end question-answering systems that live on top of search. It is a truly semantic extension to the search box with far-reaching implications for all types of search.
  • With NLP, enterprise knowledge contained in paper documentation can be encoded in a machine-readable format so the machine can read, process and understand it enough to formulate an intelligent response.
  • it’s good to know about established tool sets and methodologies for developing and creating effective solutions for use cases like technical support. But like all development projects, take care to create the tools based on mimicking the responses of actual human domain experts. Otherwise, you may run into the proverbial development problem of “garbage in, garbage out” which has plagued many such expert system initiatives.

Mr. Nelson is painting a reasonable picture about the narrow use of widely touted technologies. In fact, the promise of NLP has been part of enterprise search marketing for decades.

What I found interesting was the Convera document called “Accurate Search: What a Concept, published by Convera in 2002. I noted this passage on page 4 of the document:

Concept Search capitalizes on the richness of language, with its multiple term meanings, and transforms it from a problem into an advantage. RetrievalWare performs natural language processing and search term expansion to paraphrase queries, enabling retrieval of documents that contain the specific concepts requested rather than just the words typed during the query while also taking advantage of its semantic richness to rank documents in results lists. RetrievalWare’s powerful pattern search abilities overcome common errors in both content and queries, resulting in greater recall and user satisfaction.

I find the shift from a broad solution to a more narrow solution interesting. In the span of 15 years, the technology of search seems to be struggling to deliver.

Perhaps consulting and engineering services are needed to make search “work”? Contrast search with mobile phone technology. Progress has been evident. For search, success narrows to improving “documentation” and “customer support.”

Has anyone tried to reach PayPal’s customer support or United Airlines’ customer support? Try it. United was at one time a “customer” of Convera’s. From my point of view, United Airlines’ customer service has remained about the same over the last decade or two.

Enterprise search, broad or narrow, remains a challenge for marketers and users in my opinion. NLP, I assume, has arrived after a long journey. For a free profile of Convera, check out this link.

Stephen E Arnold, October 31, 2017

Google: What For-Fee Thought Leader Love? And for Money? Yep

July 13, 2017

Talk about disinformation. Alphabet Google finds itself in the spotlight for normal consulting service purchases. How many of those nifty Harvard Business Review articles, essays in Strategy & Business (the money loser published by the former Booz, Allen & Hamilton), or white papers generated by experts like me are labors of thought leader love.

Why not ask a person like me, an individual who has written a white paper for an interesting company in Spain? You won’t. Well, let me interview myself:

Question: Why did you write the white paper about multi-language text analysis?

Answer: I did a consulting job and was asked to provide a report about the who, what, why, etc. of the company’s technology.

Question: Is the white paper objective and factual?

Answer: Yes, I used information from my book research, a piece of published material from the “old” Autonomy Software, and the information gathered at the company’s headquarters in Madrid by one of my colleagues from the engineers. I had a couple of other researchers chase down information about the company, its products, customers, and founder. I then worked through the information about text analysis in my archive. I think I did a good job of presenting the technology and why it is important.

Question: Were you paid?

Answer: Yes, I retired in 2013, and I don’t write for third parties unless those third parties pony up cash.

Question: Do you flatter the company or distort the company’s technology, its applications, or its benefits?

Answer: I try to work through the explanation in order to inform. I offer my opinion at the end of the write up. In this particular case, the technology is pretty good. I state that.

Question: Would another expert agree with you?

Answer: Some would and some would not. When figuring out with a complex multi-lingual platform when processing text in 50 languages, there is room for differences of opinion with regard to such factors as [a] text through put on a particular application, [b] corpus collection and preparation, [c] system tuning for a particular application such as a chatbot, and other factors.

Question: Have you written similar papers for money over the years?

Answer: Yes, I started doing this type of writing in 1972 when I left the PhD program at the University of Illinois to join Halliburton Nuclear in Washington, DC.

Question: Do people know you write white papers or thought leader articles for money?

Answer: Anyone who knows me is aware of my policy of charging money for knowledge work. I worked at Booz, Allen & Hamilton and a number of other equally prestigious firms. To my knowledge, I have never been confused with Mother Teresa.

Mother Theresa A Person Who Works for Money
Image result for mother teresa seajpg02

 

I offer this information as my reaction to the Wall Street Journal’s write up “Google Pays Scholars to Influence Policy.” You will have to pay to read the original article because Mr. Murdoch is not into free information.The original appeared in my dead tree edition of the WSJ on July 12, 2017 on the first page with a jump to a beefy travelogue of Google’s pay-for-praise and pay-for-influence activities. A correction to the original story appears on Fox News. Gasp. Find that item here.

Google, it seems, is now finding itself in the spotlight for search results, presenting products to consumers, and its public relations/lobbying activities.

My view is that Google does not deserve this type of criticism. I would prefer that real journalists tackle such subjects as [a] the Loon balloon patent issue, [2] Google’s somewhat desperate attempts to discover the next inspiration like Yahoo’s online advertising approach, and [3] solving death’s progress.

Getting excited about white papers which have limited impact probably makes a real journalist experience a thrill. For me, the article triggers a “What’s new?”

But I am not Mother Teresa, who would have written for Google for nothing. Nah, not a chance.

Stephen E Arnold, July 14, 2017

Booz Boo Boo: Blue Chip? Maybe Not

June 1, 2017

I read “Booz Allen, NGA Probe Intel Leak.” Let’s assume that the information in the write up is “sort of” accurate. I suggest this because the article invokes the name of “Edward Snowden” and the name of “Hal Martin.” Both of these individuals allegedly behaved with a bit of professional “looseness.”

But the write up does more than remind me that the once highly regarded blue chip management consulting firm has become an example of how not to manage its own employees and contractors.

Too bad. I worked at Booz, Allen & Hamilton when the firm’s reputation was reasonably well regarded. Today I am not so sure I would place the Booz Allen outfit identified in the FCW article in my “I want to work their” Top 10.

The main point of the write up seems to me to be:

Edward Snowden, Hal Martin and now another Booz Allen Hamilton employee could be involved in the leak of sensitive intelligence data — though in the latest case, it appears it could be accidental.

The information, according the FCW, was sensitive. The error was a result of a misconfiguration error.

Nevertheless, a company charged with working within the constraints set forth by the client should have management procedures in place to prevent alleged security issues.

Booz, Allen & Hamilton once kept a low profile. Now the firm finds itself making headlines.

FCW is not the grocery store tabloid-type of “real news” outfit, of course. However, I ask myself, “Management or mismanagement?”

And from an outfit which once provided management consulting services to the world’s leading organizations.

Interesting.

Stephen E Arnold, June 1, 2017

Forrester: Enterprise Content Management Misstep

April 14, 2017

I have stated in the past that mid tier consulting firms—that is, outfits without the intellectual horsepower of a McKinsey, Bain, or BCG—generate work that is often amusing, sometimes silly, and once in a while just stupid. I noted an error which is certainly embarrassing to someone, maybe even a top notch expert at mid tier Forrester. The idea for a consulting firm is to be “right” and to keep the customer (in this case Hyland) happy. Also, it is generally good to deliver on what one promises. You know, the old under promise, over deliver method.

How about being wrong, failing, and not delivering at all? Read on about Forrester and content management.

Context

I noted the flurry of news announcements about Forrester, a bigly azure-chip consulting firm. A representative example of these marketing news things is “Microsoft, OpenText, IBM Lead Forrester’s ECM Wave in Evolving Market.” The write up explains that the wizards at Forrester have figured out the winners and losers in enterprise content management. As it turns out, the experts at Forrester do a much better job of explaining their “perception” of content management that implementing content management.

How can this be? Paid experts who cannot implement content management for reports about content management? Some less generous people might find this a minor glitch. I think that consultants are pretty good at cooking up reports and selling them. I am not too confident that mid tier consulting firms and even outfits like Booz, Allen has dotted their “i’s” and crossed their “t’s.”

Let me walk you through this apparent failure of Forrester to make their reports available to a person interested in a report. This example concerns a Forrester reviewed company called Hyland and its OnBase enterprise content management system.

The deal is that Hyland allows a prospect to download a copy of the Forrester report in exchange for providing contact information. Once the contact information is accepted, the potential buyer of OnBase is supposed to be able to download a copy of the Forrester report. This is trivial stuff, and we are able to implement the function when I sell my studies. Believe me. If we can allow registered people to download a PDF, so can you.

The Failure

I wanted a copy of “The Forrester Wave: ECM Business Content Services.” May I illustrate how Forrester’s enterprise content management system fails its paying customers and those who register to download these high value, completely wonderful documents.

Step 1: Navigate to this link for OnBase by Hyland, one of the vendors profiled in the allegedly accurate, totally object Forrester report

image

Step 2: Fill out the form so Hyland’s sales professionals can contact you in hopes of selling you the product which Forrester finds exceptional

image

Note the big orange “Download Now” button. I like the “now” part because it means that with one click I get the high-value, super accurate report.

Step 3: Click on one of these two big green boxes:

image

I tested both, and both return the same high value, super accurate, technically wonderful reports—sort of.

Read more

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