The Key to Success at McKinsey & Company: The 2024 Truth Is Out!

June 21, 2024

dinosaur30a_thumb_thumbThis essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.

When I was working at a “real” company, I wanted to labor in the vineyards of a big-time, blue-chip consulting firm. I achieved that goal and, after a suitable period of time in the penal colony, I escaped to a client. I made it out, unscathed, and entered a more interesting, less nutso working life. When the “truth” about big-time, blue-chip consulting firms appears in public sources, I scan the information. Most of it is baloney; for example, the yip yap about McKinsey and its advice pertaining to addictive synthetics. Hey, stuff happens when one is objective. “McKinsey Exec Tells Summer Interns That Learning to Ask AI the Right Questions Is the Key to Success” contains some information which I find quite surprising. First, I don’t know if the factoids in the write up are accurate or if they are the off-the-cuff baloney recruiters regularly present to potential 60-hour-a-week knowledge worker serfs or if the person has a streaming video connection to the McKinsey managing partner’s work-from-the-resort office.

Let’s assume the information is correct and consider some of its implications. An intern is a no-pay or low-pay job for students from the right institutions, the right background, or the right connections. The idea is that associates (one step above the no-pay serf) and partners (the set for life if you don’t die of heart failure crowd) can observe, mentor, and judge these field laborers. The write up states:

Standing out in a summer internship these days boils down to one thing — learning to talk to AI. At least, that’s the advice McKinsey’s chief client officer, Liz Hilton Segel, gave one eager intern at the firm. “My advice to her was to be an outstanding prompt engineer,” Hilton Segel told The Wall Street Journal.

But what about grades? What about my family’s connections to industry, elected officials, and a supreme court judge? What about my background scented with old money, sheepskin from prestigious universities, and a Nobel Prize awarded a relative 50 years ago? These questions, its seems, may no longer be relevant. AI is coming to the blue-chip consulting game, and the old-school markers of building big revenues may not longer matter.

AI matters. Despite McKinsey’s 11-month effort, the firm has produced Lilli. The smart systems, despite fits and starts, has delivered results; that is, a payoff, cash money, engagement opportunities. The write up says:

Lilli’s purpose is to aggregate the firm’s knowledge and capabilities so that employees can spend more time engaging with clients, Erik Roth, a senior partner at McKinsey who oversaw Lili’s development, said last year in a press release announcing the tool.

And the proof? I learned:

“We’ve [McKinsey humanoids] answered over 3 million prompts and add about 120,000 prompts per week,” he [Erik Roth] said. “We are saving on average up to 30% of a consultants’ time that they can reallocate to spend more time with their clients instead of spending more time analyzing things.”

Thus, the future of success is to learn to use Lilli. I am surprised that McKinsey does not sell internships, possibly using a Ticketmaster-type system.

Several observations:

  1. As Lilli gets better or is replaced by a more cost efficient system, interns and newly hired professionals will be replaced by smart software.
  2. McKinsey and other blue-chip outfits will embrace smart software because it can sell what the firm learns to its clients. AI becomes a Petri dish for finding marketable information.
  3. The hallucinative functions of smart software just create an opportunity for McKinsey and other blue-chip firms to sell their surviving professionals at a more inflated fee. Why fail and lose money? Just pay the consulting firm, sidestep the stupidity tax, and crush those competitors to whom the consulting firms sell the cookie cutter knowledge.

Net net: Blue-chip firms survived the threat from gig consultants and the Gerson Lehrman-type challenge. Now McKinsey is positioning itself to create a no-expectation environment for new hires, cut costs, and increase billing rates for the consultants at the top of the pyramid. Forget opioids. Go AI.

Stephen E Arnold, June 21, 2024

Free AI Round Up with Prices

June 18, 2024

dinosaur30a_thumb_thumbThis essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.

EWeek (once PCWeek and a big fat Ziff publication) has published what seems to be a mash up of MBA-report writing, a bit of smart software razzle dazzle, and two scoops of Gartner Group-type “insight.” The report is okay, and its best feature is that it is free. Why pay a blue-chip or mid-tier consulting firm to assemble a short monograph? Just navigate to “21 Best Generative AI Chatbots.”


A lecturer shocks those in the presentation with a hard truth: Human-generated reports are worse than those produced by a “leading” smart software system. Is this the reason a McKinsey professional told interns, “Prompts are the key to your future.” Thanks, MSFT Copilot. Good enough.

The report consists of:

A table with the “leading” chatbots presented in random order. Forget that alphabetization baloney. Sorting by “leading” chatbot name is so old timey. The table presents these evaluative/informative factors:

  • Best for use case; that is, in the opinion of the “analysts” when one would use a specific chatbot in the opinion of the EWeek “experts” I assume
  • Query limit. This is baffling since recyclers of generative technology are eager to sell a range of special plans
  • Language model. This column is interesting because it makes clear that of the “leading” chatbots 12 of them are anchored in OpenAI’s “solutions”; Claude turns up three times, and Llama twice. A few vendors mention the use of multiple models, but the “report” does not talk about AI layering or the specific ways in which different systems contribute to the “use case” for each system. Did I detect a sameness in the “leading” solutions? Yep.
  • The baffling Chrome “extension.” I think the idea is that the “leading” solution with a Chrome extension runs in the Google browser. Five solutions do run as a Chrome extension. The other 16 don’t.
  • Pricing. Now prices are slippery. My team pays for ChatGPT, but since the big 4o, the service seems to be free. We use a service not on the list, and each time I access the system, the vendor begs — nay, pleads — for more money. One vendor charges $2,500 per month paid annually. Now, that’s a far cry from Bing Chat Enterprise at $5 per month, which is not exactly the full six pack.

The bulk of the report is a subjective score for each service’s feature set, its ease of use, the quality of output (!), and support. What these categories mean is not provided in a definition of terms. Hey, everyone knows about “quality,” right? And support? Have you tried to contact a whiz-bang leading AI vendor? Let me know how that works out? The screenshots vary slightly, but the underlying sameness struck me. Each write up includes what I would call a superficial or softball listing of pros and cons.

The most stunning aspect of the report is the explanation of “how” the EWeek team evaluated these “leading” systems. Gee, what systems were excluded and why would have been helpful in my opinion. Let me quote the explanation of quality:

To determine the output quality generated by the AI chatbot software, we analyzed the accuracy of responses, coherence in conversation flow, and ability to understand and respond appropriately to user inputs. We selected our top solutions based on their ability to produce high-quality and contextually relevant responses consistently.

Okay, how many queries? How were queries analyzed across systems, assuming similar systems received the same queries? Which systems hallucinated or made up information? What queries causes one or more systems to fail? What were the qualifications of those “experts” evaluating the system responses? Ah, so many questions. My hunch is that EWeek just skipped the academic baloney and went straight to running queries, plugging in a guess-ti-mate, and heading to Starbucks? I do hope I am wrong, but I worked at the Ziffer in the good old days of the big fat PCWeek. There was some rigor, but today? Let’s hit the gym?

What is the conclusion for this report about the “leading” chatbot services? Here it is:

Determining the “best” generative AI chatbot software can be subjective, as it largely depends on a business’s specific needs and objectives. Chatbot software is enormously varied and continuously evolving,  and new chatbot entrants may offer innovative features and improvements over existing solutions. The best chatbot for your business will vary based on factors such as industry, use case, budget, desired features, and your own experience with AI. There is no “one size fits all” chatbot solution.

Yep, definitely worth the price of admission.

Stephen E Arnold, June 18, 2024

What Is McKinsey & Co. Telling Its Clients about AI?

June 12, 2024

dinosaur30a_thumb_thumbThis essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.

Years ago (decades now) I attended a meeting at the firm’s technology headquarters in Bethesda, Maryland. Our carpetland welcomed the sleek, well-fed, and super entitled Booz, Allen & Hamilton professionals to a low-profile meeting to discuss the McKinsey PR problem. I attended because my boss (the head of the technology management group) assumed I would be invisible to the Big Dog BAH winners. He was correct. I was an off-the-New-York radar “manager,” buried in an obscure line item. So there I was. And what was the subject of this periodic meeting? The Harvard Business Review-McKinsey Award. The NY Booz, Allen consultants failed to come up with this idea. McKinsey did. As a result, the technology management group (soon to overtake the lesser MBA side of the business) had to rehash the humiliation of not getting associated with the once-prestigious Harvard University. (The ethics thing, the medical research issue, and the protest response have tarnished the silver Best in Show trophy. Remember?)


One of the most capable pilots found himself answering questions from a door-to-door salesman covering his territory somewhere west of Terre Haute. The pilot who has survived but sits amidst a burning experimental aircraft ponders an important question, “How can I explain that the crash was not my fault?” Thanks, MSFT Copilot. Have you ever found yourself in a similar situation? Can you “recall” one?

Now McKinsey has AI data. Actual hands-on, unbillable work product with smart software. Is the story in the Harvard Business Review? A Netflix documentary? A million-view TikTok hit? A “60 Minutes” segment? No, nyet, unh-unh, negative. The story appears in Joe Mansueto’s Fast Company Magazine! Mr. Mansueto founded Morningstar and has expanded his business interests to online publications and giving away some of his billions.

The write up is different from McKinsey’s stentorian pontifications. It is a bit like mining coal in a hard rock dig deep underground. It was a dirty, hard, and ultimately semi-interesting job. Smart software almost broke the McKinsey marvels.

We Spent Nearly a Year Building a Generative AI Tool. These Are the 5 (Hard) Lessons We Learned” presents information which would have been marketing gold for the McKinsey decades ago. But this is 2024, more than 18 months after Microsoft’s OpenAI bomb blast at Davos.

What did McKinsey “learn”?

McKinsey wanted to use AI to “bring together the company’s vast but separate knowledge sources.” Of course, McKinsey’s knowledge is “vast.” How could it be tiny. The firm’s expertise in pharmaceutical efficiency methods exceeds that of many other consulting firms. What’s more important profits or deaths? Answer: I vote for profits, doesn’t everyone except for a few complainers in Eastern Kentucky, West Virginia, and other flyover states.

The big reveal in the write up is that McKinsey & Co learned that its “vast” knowledge is fragmented and locked in Microsoft PowerPoint slides. After the non-billable overhead work, the bright young future corporate leaders discovered that smart software could only figure out about 15 percent of the knowledge payload in a PowerPoint document. With the vast knowledge in PowerPoint, McKinsey learned that smart software was a semi-helpful utility. The smart software was not able to “readily access McKinsey’s knowledge, generate insights, and thus help clients”  or newly-hired consultants do better work, faster, and more economically. Nope.

So what did McKinsey’s band of bright smart software wizards do? The firm coded up its own content parser. How did that home brew software work? The grade is a solid B. The cobbled together system was able to make sense of 85 percent of a PowerPoint document. The other 15 percent gives the new hires something to do until a senior partner intervenes and says, “Get billable or get gone, you very special buttercup.” Non-billable and a future at McKinsey are not like peanut butter and jelly.

How did McKinsey characterize its 12-month journey into the reality of consulting baloney? The answer is a great one. Here it is:

With so many challenges and the need to work in a fundamentally new way, we described ourselves as riding the “struggle bus.” 

Did the McKinsey workers break out into work songs to make the drudgery of deciphering PowerPoints go more pleasantly? I am think about the Coal Miners Boogie by George Davis, West Virginia Mine Disaster by Jean Ritchi, or my personal favorite Black Dust Fever by the Wildwood Valley Boys.

But the workers bringing brain to reality learned five lessons. One can, I assume, pay McKinsey to apply these lessons to a client firm experiencing a mental high from thinking about the payoffs from AI. On the other hand, consider these in this free blog post with my humble interpretation:

  1. Define a shared aspiration. My version: Figure out what you want to do. Get a plan. Regroup if the objective and the method don’t work or make much sense.
  2. Assemble a multi-disciplinary team. My version: Don’t load up on MBAs. Get individuals who can code, analyze content, and tap existing tools to accomplish specific tasks. Include an old geezer partner who can “explain” what McKinsey means when it suggests “managerial evolution.” Skip the ape to MBA cartoons.
  3. Put the user first. My version: Some lesser soul will have to use the system. Make sure the system is usable and actually works. Skip the minimum viable product and get to the quality of the output and the time required to use the system or just doing the work the old-fashioned way.
  4. Tech, learn, repeat. Covert the random walk into a logical and efficient workflow. Running around with one’s hair on fire is not a methodical process nor a good way to produce value.
  5. Measure and manage. My version: Fire those who failed. Come up with some verbal razzle-dazzle and sell the planning and managing work to a client. Do not do this work on overhead for the consultants who are billable.

What does the great reveal by McKinsey tell me. First, the baloney about “saving an average of up to 30 percent of a consultants’ time by streamlining information gathering and synthesis” sounds like the same old, same old pitched by enterprise search vendors for decades. The reality is that online access to information does not save time; it creates more work, particularly when data voids are exposed. Those old dog partners are going to have to talk with young consultants. No smart software is going to eliminate that task no matter how many senior partners want a silver bullet to kill the beast of a group of beginners.

The second “win” is the idea that “insights are better.” Baloney. Flipping through the famous executive memos to a client, reading the reports with the unaesthetic dash points, and looking at the slide decks created by coal miners of knowledge years ago still has to be done… by a human who is sober, motivated, and hungry for peer recognition. Software is not going to have the same thirst for getting a pat on the head and in some cases on another part of the human frame.

The struggle bus is loading up no. Just hire McKinsey to be the driver, the tour guide, and the outfit that collects the fees. One can convert failure into billability. That’s what the Fast Company write up proves. Eleven months and all they got was a ride on the digital equivalent of the Cybertruck which turned out to be much-hyped struggle bus?

AI may ultimately rule the world. For now, it simply humbles the brilliant minds at McKinsey and generates a story for Fast Company. Well, that’s something, isn’t it? Now about spinning that story.

Stephen E Arnold, June 12, 2024

Selling AI with Scare Tactics

June 6, 2024

dinosaur30a_thumb_thumbThis essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.

Ah, another article with more assertions to make workers feel they must adopt the smart software that threatens their livelihoods. AI automation firm UiPath describes “3 Common Barriers to AI Adoption and How to Overcome Them.” Before marketing director Michael Robinson gets to those barriers, he tries to motivate readers who might be on the fence about AI. He writes:

“There’s a growing consensus about the need for businesses to embrace AI. McKinsey estimated that generative AI could add between $2.6 to $4.4 trillion in value annually, and Deloitte’s ’State of AI in the Enterprise’ report found that 94% of surveyed executives ‘agree that AI will transform their industry over the next five years.’ The technology is here, it’s powerful, and innovators are finding new use cases for it every day. But despite its strategic importance, many companies are struggling to make progress on their AI agendas. Indeed, in that same report, Deloitte estimated that 74% of companies weren’t capturing sufficient value from their AI initiatives. Nevertheless, companies sitting on the sidelines can’t afford to wait any longer. As reported by Bain & Company, a ‘larger wedge’ is being driven ‘between those organizations that have a plan [for AI] and those that don’t—amplifying advantage and placing early adopters into stronger positions.’”

Oh, no! What can the laggards do? Fret not, the article outlines the biggest hurdles: lack of a roadmap, limited in-house expertise, and security or privacy concerns. Curious readers can see the post for details about each. As it happens, software like UiPath’s can help businesses clear every one. What a coincidence.

Cynthia Murrell, June 6, 2024

Blue-Chip Consulting Firm Needs Lawyers and Luck

May 15, 2024

McKinsey’s blue chip consultants continue their fancy dancing to explain away an itsy bitsy problem: ruined lives and run-of-the-mill deaths from drug overdoses. The International Business Times reminds us, “McKinsey Under Criminal Investigation Over Alleged Role in Fueling Opioid Epidemic.” The investigation, begun before the pandemic, continues to advance at the glacial pace of justice. Journalist Kiran Tom Sajan writes:

“Global consulting firm McKinsey & Company is under a criminal investigation by the U.S. attorneys’ offices in Massachusetts and the Western District of Virginia over its alleged involvement in fueling the opioid epidemic. The Federal prosecutors, along with the Justice Department’s civil division in Washington, are specifically examining whether the consulting firm participated in a criminal conspiracy by providing advice to Purdue Pharma and other pharmaceutical companies on marketing tactics aimed at increasing sales of prescription painkillers. Purdue is the manufacturer of OxyContin, one of the painkillers that allegedly contributed to widespread addiction and fatal overdoses. Since 2021, McKinsey has reached settlements of approximately $1 billion to resolve investigations and legal actions into its collaboration with opioid manufacturers, primarily Purdue. The company allegedly advised Purdue to intensify its marketing of the drug amid the opioid epidemic, which has resulted in the deaths of hundreds of thousands of Americans. McKinsey has not admitted any wrongdoing.”

Of course not. We learn McKinsey raked in about $86 million working for Purdue, most of it since the drug firm’s 2007 guilty plea. Sajan notes the investigations do not stop with the question of fueling the epidemic: The Justice Department is also considering whether McKinsey obstructed justice when it fired two incautious partners—they were caught communicating about the destruction of related documents. It is also examining whether the firm engaged in healthcare fraud when it helped Purdue and other opioid sellers make fraudulent Medicare claims. Will McKinsey’s recent settlement with insurance companies lend fuel to that dumpster fire? Will Lady Luck kick her opioid addiction and embrace those McKinsey professionals? Maybe.

Cynthia Murrell, May 15, 2024

McKinsey & Co. Emits the Message “You Are No Longer the Best of the Best”

April 4, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

I love blue chip consulting firms’ management tactics. I will not mention the private outfits which go public and then go private. Then the firms’ “best of the best” partners decide to split the firm. Wow. Financial fancy dancing or just evidence that “best of the best” is like those plastic bottles killing off marine life?

I read “McKinsey Is so Eager to Trim Staff That It’s Offering Some Employees 9 Months’ Pay to Go and Do Something Else. I immediately asked myself, “What’s some mean?” I am guessing based on my experience that “all” of the RIF’ed staff are not getting the same deal. Well, that’s life in the exciting world of the best and the brightest. Some have to accept that there are blue chippers better and, therefore, able to labor enthusiastically at a company known as the Big Dog in the consulting world.


Thanks MSFT Copilot. (How’s your security today?)

The write up reports as “real” NY news:

McKinsey is attempting  to slim the company down in a caring and supporting way by paying its workers to quit.

Hmmm. “Attempting” seems an odd word for a consulting firm focused on results. One slims down or one remains fat and prone to assorted diseases if I understood my medical professional. Is McKinsey signaling that its profit margin is slipping like the trust level for certain social media companies? Or is artificial intelligence the next big profit making thing; therefore, let’s clear out the deadwood and harvest the benefits of smart software unencumbered by less smart humans?

Plus, the formerly “best and brightest” will get help writing their résumés. My goodness, imagine a less good Type A super achiever unable to write a résumé. But just yesterday those professionals were able to advise executives often with decades more experience, craft reports with asterisk dot points, and work seven days a week. These outstanding professionals need help writing their résumés. This strikes me as paternalistic and a way to sidestep legal action for questionable termination.

Plus, the folks given the chance to find their future elsewhere (as long as the formerly employed wizard conforms to McKinsey’s policies about client poaching) can allegedly use their McKinsey email accounts. What might a person who learns he or she is no longer the best of the best might do with a live McKinsey email account? I have a couple of people on my research team who have studied mischief with emails. I assume McKinsey’s leadership knows a lot more than my staff. We don’t pontificate about pharmaceutical surfing; we do give lectures to law enforcement and intelligence professionals. Therefore, my team knows much, much less about the email usage that McKinsey management.

Deloitte, another blue chip outfit, is moving quickly into the AI space. I have heard that it wants to use AI and simultaneously advise its clients about AI. I wonder if Deloitte has considered that smart software might be marginally less expensive than paying some of the “best of the best” to do manual work for clients? I don’t know.

The blue chip outfit at which I worked long ago was a really humane place. Those rumors that an executive drowned a loved one were just rumors. The person was a kind and loving individual with a raised dais in his office. I recall I hard to look up at him when seated in front of his desk. Maybe that’s just an AI type hallucination from a dinobaby. I do remember the nurturing approach he took when pointing at a number and demanding the VP presenting the document, “I want to know where that came from now.” Yes, that blue chip professional was patient and easy going as well.

I noted this passage in the Fortune “real” NY news:

A McKinsey spokesperson told Fortune that its unusual approach to layoffs is all part of the company’s core mission to help people ‘learn and grow into leaders, whether they stay at McKinsey or continue their careers elsewhere.’

I loved the sentence including the “learn and grow into leaders” verbiage. I am imagining a McKinsey HR professional saying, “Remember when we recruited you? We told you that you were among the top one percent of the top one percent. Come on. I know you remember? Oh, you don’t remember my assurances of great pay, travel, wonderful colleagues, tremendous opportunities to learn, and build your interpersonal skills. Well, that’s why you have been fired. But you can use your McKinsey email. Please, leave now. I have billable work to do that you obviously were not able to undertake and complete in a satisfactory manner. Oh, here’s your going away gift. It is a T shirt which says, ‘’

Stephen E Arnold, April 4, 2024

An Allocation Society or a Knowledge Value System? Pick One, Please!

February 20, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

I get random inquiries, usually from LinkedIn, asking me about books I would recommend to a younger person trying to [a] create a brand and make oodles of money, [b] generate sales immediately from their unsolicited emails to strangers, and [c] a somewhat limp-wristed attempt to sell me something. I typically recommend a book I learned about when I was giving lectures at the Kansai Institute of Technology and a couple of outfits in Tokyo. The book is the Knowledge Value Revolution written by a former Japanese government professional named Taichi Sakaiya. The subtitle to the book is “A History of the Future.”

So what?

I read an essay titled “The Knowledge Economy Is Over. Welcome to the Allocation Economy.” The thesis of this essay is that Sakaiya’s description of the future is pretty much wacko. Here’s a passage from the essay about the allocation economy:

Summarizing used to be a skill I needed to have, and a valuable one at that. But before it had been mostly invisible, bundled into an amorphous set of tasks that I’d called “intelligence”—things that only I and other humans could do. But now that I can use ChatGPT for summarizing, I’ve carved that task out of my skill set and handed it over to AI. Now, my intelligence has learned to be the thing that directs or edits summarizing, rather than doing the summarizing myself.


A world class knowledge surfer now wins gold medals for his ability to surf on the output of smart robots and pervasive machines. Thanks, Google ImageFX. Not funny but good enough, which is the mark of a champion today, isn’t it?

For me, the message is that people want summaries. This individual was a summarizer and, hence, a knowledge worker. With the smart software doing the summarizing, the knowledge worker is kaput. The solution is for the knowledge worker to move up conceptually. The jump is a metaplay. Debaters learn quickly that when an argument is going nowhere, the trick that can deliver a win is to pop up a level. The shift from poverty to a discussion about the disfunction of a city board of advisors is a trick used in places like San Francisco. It does not matter that the problem of messios is not a city government issue. Tents and bench dwellers are the exhaust from a series of larger systems. None can do much about the problem. Therefore, nothing gets done. But for a novice debater unfamiliar with popping up a level or a meta-play, the loss is baffling.

The essay putting Sakaiya in the dumpster is not convincing and it certainly is not going to win a debate between the knowledge value revolution and the allocation economy. The reason strikes me a failure to see that smart software, the present and future dislocations of knowledge workers, and the brave words about becoming a director or editor are evidence that Sakaiya was correct. He wrote in 1985:

If the type of organization typical of industrial society could be said to resemble a symphony orchestra, the organizations typical of the knowledge-value society would be more like the line-up of a jazz band.

The author of the allocation economy does not realize that individuals with expertise are playing a piano or a guitar. Of those who do play, only a tiny fraction (a one percent of the top 10 percent perhaps?) will be able to support themselves. Of those elite individuals, how many Taylor Swifts are making the record companies and motion picture empresarios look really stupid? Two, five, whatever. The point is that the knowledge-value revolution transforms much more than “attention” or “allocation.” Sakaiya, in my opinion, is operating at a sophisticated meta-level. Renaming the plight of people who do menial mental labor does not change a painful fact: Knowledge value means those who have high-value knowledge are going to earn a living. I am not sure what the newly unemployed technology workers, the administrative facilitators, or the cut-loose “real” journalists are going to do to live as their parents did in the good old days.

The allocation essay offers:

AI is cheap enough that tomorrow, everyone will have the chance to be a manager—and that will significantly increase the creative potential of every human being. It will be on our society as a whole to make sure that, with the incredible new tools at our disposal, we bring the rest of the economy along for the ride.

How many jazz musicians can ride on a particular market sector propelled by smart software? How many individuals will enjoy personal and financial success in the AI allocation-centric world? Remember, please, there are about eight billion people in the world? How many Duke Ellingtons and Dave Brubecks were there?

The knowledge value revolution means that the majority of individuals will be excluded from nine to five jobs, significant financial success, and meaningful impact on social institutions. I am not for everyone becoming a surfer on smart software, but if that happens, the future is going to be more like the one Sakaiya outlined, not an allocation-centric operation in my opinion.

Stephen E Arnold, February 20, 2024

The US Government Needs Its McKinsey Fix

February 20, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

Governments don’t know how to spend their money wisely. Despite all its grandness, the United States has a deficit spending problem. According to Promarket, the US has a spends way too many tax dollars at McKinsey and Company: “Why The US Government Buys Overpriced Services From McKinsey.” McKinsey and Company is a consulting firm that provides organizations and the US government with advice on how to improve operations.

McKinsey is comparable to the IRS conducting a tax audit on the US government. The company is supposed to help the US implement social justice, diverse, and other political jargon into its business practices. The Clinton administration first purchased the over zealous services from McKinsey. Unfortunately McKinsey doesn’t do much other than repackage mediocre advice with an expensive price tag. How much does McKinsey charge for services? It’s a lot:

“Such practices used to be called “honest graft.” And let’s be clear, McKinsey’s services are very expensive. Back in August, I noted that McKinsey’s competitor, the Boston Consulting Group, charges the government $33,063.75/week for the time of a recent college grad to work as a contractor. Not to be outdone, McKinsey’s pricing is much much higher, with one McKinsey “business analyst”—someone with an undergraduate degree and no experience—lent to the government priced out at $56,707/week, or $2,948,764/year.”

McKinsey can charge outrageous prices because the company uses unethical tactics and they can stay because the General Services Administration gets a 0.75% cut of what contractors spend. It is officially called the “Industrial Funding Fee” or IFF. The GSA receives a larger operating budget whenever it outsources to contractors.

Will changes be made for the next fiscal year? Unlikely.

Whitney Grace’s February 20, 2024

The Cost of Clever

January 1, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

A New Year and I want to highlight an interesting story which I spotted in SFGate: “Consulting Firm McKinsey Agrees to $78 Million Settlement with Insurers over Opioids.” The focus on efficiency and logic created an interesting consulting opportunity for a blue-chip firm. That organization responded. The SFGate story reports:

Consulting firm McKinsey and Co. has agreed to pay $78 million to settle claims from insurers and health care funds that its work with drug companies helped fuel an opioid addiction crisis.


A blue-consultant has been sent to the tool shed by Ms. Justice. The sleek wizard is not happy because the tool shed is the location for severe punishment by Ms. Justice. Thanks, MSFT Copilot Bing thing.

What did the prestigious firm’s advisors assist Purdue Pharma to achieve? The story says:

The insurers argued that McKinsey worked with Purdue Pharma – the maker of OxyContin – to create and employ aggressive marketing and sales tactics to overcome doctors’ reservations about the highly addictive drugs. Insurers said that forced them to pay for prescription opioids rather than safer, non-addictive and lower-cost drugs, including over-the-counter pain medication. They also had to pay for the opioid addiction treatment that followed.

The write up presents McKinsey’s view of its service this way:

“As we have stated previously, we continue to believe that our past work was lawful and deny allegations to the contrary,” the company said, adding that it reached a settlement to avoid protracted litigation. McKinsey said it stopped advising clients on any opioid-related business in 2019.

What’s interesting is that the so-called opioid crisis reveals the consequences of a certain mental orientation. The goal of generating a desired outcome for a commercial enterprise can have interesting and, in this case, expensive consequences. Have some of these methods influenced other organizations? Will blue-chip consulting firms and efficiency-oriented engineers learn from wood shed visits?

Happy New Year everyone.

Stephen E Arnold, January 1, 2024

Why Stuff No Longer Works Very Well

December 28, 2023

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

Own a Tesla? What about those Southwest flight delays? Been to a hospital emergency room in DC? Tried to get a plumber on a holiday? Yep, systems work … sometimes, sort of, or mostly. Have you ever wondered why teens working at a fruit market cannot make change, recognize a fifty cent piece, or know zero about when the grapes were put on display?

I think I have found the answer to these and other questions about modern life. Navigate to “Become an Expert in Less Than an Hour.” The write up is a how to be superficially smart. Now, don’t get me wrong, superficiality is an important characteristic. People decide whether a person is okay or not in seconds, maybe less. Impressing a person to whom one is selling a used car relies on that instant charm feature of some people. The skill of superficial smartness is important to those who want to pick up a person of interest in a bar, a consultant at a blue chip firm, a lawyer explaining his fees to a trust customer, and political advisors who shift from art history to geopolitics over lunch.

The write up reduces superficial intelligence to a cook book, and I think quite a few people will find the ideas in the essay of considerable value. Here’s an example:

“anthropologists frequently have to learn how to grok an entire subfield in under an hour. Yes, real expertise takes years of hard work, but identifying the key works and ideas that define a subfield can be done quickly if you know where to look.”


Stephen E Arnold, December 28, 2023

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