Partnership with Deloitte Boosts SAP-Google Cloud Combo

August 14, 2018

Google wants to be a player in the enterprise cloud. Price cuts alone may not do the job. Therefore, Google is embracing new types of partners.

Consultancy firm Deloitte has been busy. On the heels of merging their Pacific operations, we now learn, “Deloitte Deal Brings Google Cloud and SAP Alliance to Life,” courtesy of New Zealand’s ResellerNews. Now, as part of its cloud migration and management services, the company will migrate SAP apps to the Google Cloud Platform (GCP). Writer James Henderson informs us:

“Deloitte will provide a ‘full suite’ of solutions for running SAP applications on GCP, including an invoice management solution, which will automate invoice processing within an SAP environment. In addition, other offerings include a visual inspection solution, capable of automating the visual inspection process and accelerate inventory restocking. … From a technology perspective, GCP is certified to run SAP workloads, which includes S/4HANA, BW/4HANA, Business Suite, Business Warehouse, alongside applications such as Hybris, Business One, Solution Manager and Business Objects BI Suite… The alliance comes 18 months after Google Cloud announced an applications partnership with SAP, in a move designed to position the tech giant as a serious cloud contender within the enterprise.”

Further offerings include an automated visual inspection process and accelerated inventory restocking. This partnership brings more than 125 million SAP subscribers into Google Cloud’s realm, including more than 5,200 start-up developers, we’re told. Deloitte was founded long ago in 1895 in London, and is now headquartered in New York City. They also are hiring at the moment for locations in several far-flung cities.

Cynthia Murrell, August 14, 2018

Business Intelligence: What Is Hot? What Is Not?

July 16, 2018

I read “Where Business Intelligence is Delivering Value in 2018.” The write up summarizes principal findings from a study conducted by Dresner Advisory Services, an outfit with which I am not familiar. I suggest you scan the summary in Cloud Tweaks and then, if you find the data interesting, chase after the Dresner outfit. My hunch is that the sales professionals will respond to your query.

Several items warranted my uncapping my trusty pink marker and circling an item of information.

First, I noticed a chart called Technologies and Initiatives Strategic to Business Intelligence. The chart presents data about 36 “technologies.” I noticed that “enterprise search” did not make the list. I did note that cognitive business intelligence, artificial intelligence, t4ext analytics, and natural language analytics did. If I were generous to a fault, I would say, “These Dresner analysts are covering enterprise search, just taking the Tinker Toy approach by naming areas of technologies.” However, I am not feeling generous, and I find it difficult to believe that Dresner or any other knowledge worker can do “work” without being able to find a file, data, look up a factoid, or perform even the most rudimentary type of research without using search. The omission of this category is foundational, and I am not sure I have much confidence in the other data arrayed in the report.

Second, I don’t know what “data storytelling” is. I suppose (and I am making a wild and crazy guess here) that a person who has some understanding of the source data, the algorithmic methods used to produce output, and the time to think about the likely accuracy of the output creates a narrative. For example, I have been in a recent meeting with the president of a high technology company who said, “We have talked to our customers, and we know we have to create our own system.” Obviously the fellow knows his customers, essentially government agencies. The customers (apparently most of them) want an alternative, and realizes change is necessary. The actual story based on my knowledge of the company, the product and service he delivers, and the government agencies’ budget constraints. The “real story” boils down to: “Deliver a cheaper product or you will lose the contract.” Stories, like those from teenagers who lose their homework, often do not reflect reality. What’s astounding is that data story telling is number eight on the hit parade of initiatives strategic to business intelligence. I was indeed surprised. But governance made the list as did governance. What the heck is governance?

Read more

Management Expert Mines s Silicon Valley Digital Insight

June 20, 2018

I enjoy the insights of high flying authors, management experts, and academic superstars. Consider “Silicon Valley Has Become a Moral Cesspool.” I learned something surprising, no, shocking:

But Peters [management guru] is increasingly “pissed off” that people don’t seem to get the point: Businesses should enrich the lives of their customers, not just shareholders.

Subtle. Excellent choice of words. Tasty, in fact.

But there’s more to insight wordsmithing. I noted:

Peters [management guru] said that Silicon Valley, the former home of Bill Hewlett and David Packard, had become a “moral cesspool.”

Such elegance! Intellectual and olfactory associations delivered with a civilized linguistic payload.

Stephen E Arnold, June 20, 2018

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

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