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


One Response to “What Is McKinsey & Co. Telling Its Clients about AI?”

  1. A Fancy Way of Saying AI May Involve Dragons : Stephen E. Arnold @ Beyond Search on June 14th, 2024 6:05 am

    […] First, the confessions of McKinsey’s AI team make it clear that smart outfits may not know what they are doing. The firms just plunge forward and then after months of work recycle the floundering into lessons. Presumably these lessons are “hire McKinsey.” See my write up “What Is McKinsey & Co. Telling Its Clients about AI?” […]

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