Tag Archives: Writing

Great vs mediocre companies

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First, ask what new stuff they have in the pipeline for the next 3-5 years?

Great companies will have tens of things in the next 1-2 years and hundreds or thousands of ideas cooking with a 3-5 year or longer launch horizon.

Mediocre companies will have a few things for 1-2 years and nothing on the drawing board after that.

Next, ask why they feel really good about those things?

Great companies will point to results from their proof of concepts, pilots, scalability and operational tests.

Mediocre companies will tell you they have a really good feeling that their new stuff will be game changers, but are short on actual, real world results to support it.

Finally, ask how of an impact do you think the ideas will have on the company’s performance?

Ask them to put some numbers to it. 1%, 3-5%, 5-10%, 10% or more growth in revenue or earnings?

Great companies will have a reasonable idea because they’ve been learning that through pilots and testing how well it will do.

Mediocre companies will tell you they hope it will be big, but we’ll just have to wait and see. But, they don’t really know because they do not piloted or tested in the real world, yet.

If I was advising a Board on hiring a leadership team, I’d advise them to look for candidates that had answers that sounded like the great companies.

I know it may not seem believable for business leaders to have the mediocre mindset above. But, I have experienced sample of about a couple dozen leadership teams at mature businesses that would give the mediocre answers and none that would give the great answers.

And, based on what I read about other businesses, gather from contacts I’ve made over the years at other places and who have come from other places, that’s pretty common.

What is AI?

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I was discussing this with a friend. He asked why AI can’t provide a definitive answer to a question like, “Who was the greatest soccer player of all time?”

He said, it will give you an answer, but the answer might be different based on who is asking it or how it is asked, so what good is AI, anyway, if it can’t give the definitive, consistent answer?

I said, I feel one shortcoming of AI is that it doesn’t do a good enough job of letting you know when the problem is the question you are asking. It has gotten better at it. It might preface an answer with, ‘it depends with what your definition of the greatest soccer player is and there is no widespread agreement, so it’s a moot point.”

But, then it usually goes on to answer it anyway.

As we were discussing this, I realized a better way to describe AI.

I explained that all AI is a much better synthesizer of existing knowledge than we’ve had before, a good synthesizer of crowd sourced data. In some cases, it’s about 10x better. In other cases, it might 100x or 1,000x better.

One example is a good illustration something that has just popped up, where people have been uploading their blood work to AI and AI has done a better job of diagnosing problems than the doctors.

That’s because the doctors are one node in a vast network of medical knowledge and while they have absorbed 100x more data than the average person to be able to interpret blood work, they aren’t capable of absorbing and keeping up with all of it. AI can absorb all of it.

So, if you have something wrong that has only occurred 100 times before, most doctors might not know about it. The issue hasn’t reached the level to enter what the typical doctor knows, because they are busy absorbing the new things that have happened thousands or millions of times before, because they are more likely to see those cases.

But, AI can find the things that have happened 100 time and synthesize that, too.

It amazes me what companies get wrong about innovation #1: They think they can predict winners and losers

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As I started writing about what companies get wrong about innovation, I realized they get a lot wrong, so it might be better to break this up into shorter posts.

This is the first of those.

By companies, of course, I mean management and employees. It’s more of a cultural thing.

It starts with overconfidence in our ability to predict winners and losers. This seems to be a natural tendency for humans and few notice that they can’t do it well.

Have you been in a meeting where the discussion turns to ideas to improve the business? I’ve been in lots of these over the years. Most turn into idea evaluation sessions and everyone wants to chime in on why they think an idea sounds good or not.

Or, maybe like me, you’ve been a part of groups that present ideas to leadership so they can pick which ones to try and not to try, as if by their position and status they know what will work. They don’t either. There may have been a few in history that seemed to, like Steve Jobs, but I think there was a lot more failure and iteration behind his success that than people think.

Few consider their track record in predicting winners and losers as they opine on why they think an idea will work and get behind it or dismiss it.

If they did and were honest, they’d realize it’s not good. How many times have you thought something was a surefire winner and it flopped? How many times have you dismissed an idea at the start only to see it go on to be wildly successful?

We tend to remember the one we got right and forget the many we got wrong.

We also have a tendency to edit our track records. We may not have thought much of a new product when it first came out, but it won us over and changed our frame our reference so that we don’t even remember what we were thinking when we didn’t give it much credit.

This also happens with ideas that many folks thought were to be surefire winners but flopped. Before the idea rolled out, with glazed eyes they’d hype up what they thought was sure to be a game changer.

I call this the September effect. In September, the big idea the company is planning to roll out next year sounds great because the real market feedback is a distant thought.

Then, when it flops, they change their tune. It turns out they had concerns from the start (but didn’t bother to mention). I call this the February effect. Once the product hits shelves and customers don’t even notice, it becomes all too obvious the idea wasn’t enough better, and maybe worse, than existing options. Why would customers want it?

So, it just amazes how quickly we can get embroiled in idea evaluation without awareness that we aren’t any good at it.

And, this hurts a company’s innovation efforts in a few ways.

First, it limits the number of experiments, since they write off 95% before trying them because they don’t think it sounds good. There’s a reason ‘you never know, ’til you try’ is age old wisdom. It’s true.

Second, it causes them to bet way too big on what they think will win.

I’ve seen plenty of these where they develop a finished product and the first time a real customer sees it in the wild is when it’s rolled out nationally.

They seem unaware that they are rolling out a pilot. The product itself looks great. They pat themselves on the back for how great it looks and how well they executed it.

Then they roll it out and crickets. As Barb Corcoran railed on a former corporate dude on Shark Tank once, ‘we see this often on Shark Tank. You come from a big company. You get the house in order operationally, but you forgot the most important step, to check to see if anyone wants it.’

This is called failing at scale.

For the same investment in the big idea, they could have placed a couple hundred small bets, with maybe 10-15 of those paying off and 2-3 paying off big.

Third, it stunts the organization’s learning. As the big projects flop, leaders tend to bury results to keep it from tarnishing their careers, instead of learning from them.

This leads to a 3-4 year cycle of leadership turnover as the new leaders get 2-3 years to try their big ideas, another year to see the results and maybe another year to try to tweak it. When they fail to move the needle on company performance, they are replaced and their replacements repeat the cycle.

Contrast that with best practices innovation. Instead of filtering ideas by arbitrary judgement, they filter them by results by trying them in small ways.

When someone shares an idea in these companies, the discussion turns to how they can try the idea as cheaply and quickly as possible, instead of judging it.

I have helped companies find winners this way.

With lots of small bets, careers aren’t tarnished for failing small. There isn’t a need to place a lot of hope and hype on the one BIG idea, because there are dozens or hundreds of other ideas that could pay off.

Results aren’t buried. They often inspire new ideas or new iterations to try, moving closer to success each time.

Rather than defending their ideas to the impromptu or official idea committee, people try their ideas in the real world and learn from them and some of that learning can inspire an unexpected, subtle, and groundbreaking discovery that can turn into a real game changer.

I worked on a project where we were trying to solve one problem. We were parallel-prototyping 8 different approaches to solving it (companies usually skip this step, another thing they get wrong). In one of those approaches we had some white space to fill, so we filled it with what we thought was fluff, listing all that was included in the service.

We thought it was fluff because we all knew it inside and out and assumed customers did, too. It seemed too obvious.

It turns out, customers didn’t know and a couple of the things on the list significantly improved customers’ perception of value and made the original problem we were trying to solve seem small.

So, the final version included that discovery and it was repeated in the company’s other collateral, too, so it had an effect the reached beyond just that project.

In closing, I recommend becoming keenly aware with your track record in predicting winners and losers and don’t get caught up in evaluating ideas.

When you find yourself in an idea evaluation session, ask everyone to think about their own track records.

Instead, ask how the idea can be tried and quickly and cheaply as possible to see if there’s anything to it and see what happens. I’ll write more about this in another post.

Silver bullet strategy vs exploration and discovery & exploration

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A conversation with colleagues about innovation often starts with a question like, “What one thing would you do to help the company grow?”

These folks want to hear silver bullet idea. They also believe they can judge whether that strategy is good or not just by how it sounds.

I don’t believe in silver bullet strategies. Mainly because I’ve been around for awhile and haven’t seen such things. And, if such things existed, I think we could Google them or ask ChatGPT what they are. Try it.

Grok gave a decent answer: “There’s no true ‘silver bullet’ for a mature company to spark growth, as success depends on context — industry, market and internal capabilities.”

Good start. But then it veers off into business buzzword gunk:

“However, one high impact strategy is reinvention through digital transformation. This involves leveraging data, AI and emerging technologies to optimize operations, enhance customer experiences, and create new revenue streams.”

Yes! Give that a try, whatever that means.

Though wade through that BS and I agree with the #4 recommendation: “Test and scale: Pilot new models, measure ROI, and expand what works.”

Which is exactly how I answer when someone asks me what I would do.

When I start to explain that the company should cast a wide net on new ideas and build the capabilities to pilot them on small scales and learn their way to success, they shut down. That doesn’t fit their mental model. That’s not what they want to hear.

They’ll try again, “But, what one thing would you do?”

I won’t take the bait and the conversation usually ends.

I’ll even point out that it’s not just what I think, but this is how highly innovative companies operate. This is how the startup world woks. This is how science and medicine works. This is also how finding jobs and dating works and in those domains we all naturally learn strategies that apply directly to the innovation world without realizing it. Strategies like network, apply for a lot of jobs and don’t get bummed out about a low rate of success.

Now I can say this is what AI thinks, too.

That doesn’t seem to matter. They still want your silver bullet answer.

I think part of why they want your one idea is they want to shoot it down.

Shooting down new ideas at mature companies is a common game that earns you street cred.

And that’s part of the problem with innovation at mature companies. Because of that game, new ideas are choked out before they are ever tried. Companies have to try a lot of stuff to find a few winners. This game is part of what keeps that from happening.

“Snapchat CEO teaches new employees a strict lesson” on their first day

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I saw this headline and rolled my eyes because it reminds of the clever hoops lots of companies are proud about making their new or potential employees jump through.

The first thing I do was look at their stock price to see if any of this cleverness translates to business performance. Snapchat stock price is down 30% in the last year. Strike one.

But, then I read the article and changed my mind some because I agreed with a few things he said.

He laid off 10% of his employees last year to remove hierarchy “claiming that focusing too much on job titles can hinder people from developing great ideas. The more that you focus your organization around hierarchy, I think the less you’re focusing on the right things, which is how are we making sure great ideas are coming from anywhere, getting surfaced, and being built.”

The test he gives to new employees is for them to present an idea on their first day. It likely won’t be a good idea, but it opens the door to creativity and teaches the lesson that “the best way to have a good idea is to have lots of ideas.”

He said, “only 1% of the ideas that Snapchat’s design team pitches are good.”

I agree with all that.

My guess is that employees don’t learn those lessons from that activity. They probably think it’s stupid, do what they need to do to get through it and move on and forget about it.

I do like what he said about job titles.

The natural progression of a successful company is for its purpose to transform from making stuff customers want to providing members of its bureaucracy with job progression and status.

When that happens, achievement is measured by how well you did what someone with status in the bureaucracy asked you to do, at best, or how much leverage you can get on those with status to propel your progression and job title attainment.

Making stuff that customers want becomes a distant thought.

‘Should America be run by Trade Joe’s?’ Freakonomics podcast

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I like a lot about this episode of Freakonomics.

One thing I especially liked was this part:

[Roberto] He’s a business professor at Bryant University, formerly of the Harvard Business School. There’s one lecture he likes to start by giving his students this fictional Shark Tank pitch.

ROBERTO: “I’d like to open a new kind of grocery store. We’re not going to have any branded items. It’s all going to be private label. We’re going to have no television advertising and no social media whatsoever. We’re never going to have anything on sale. We’re not going to accept coupons. We’ll have no loyalty card. We won’t have a circular that appears in the Sunday newspaper. We’ll have no self-checkout. We won’t have wide aisles or big parking lots. Would you invest in my company?” 

And of course you’re supposed to think, “There is no way I’d invest in that company. That sounds like the stupidest company ever.”

What do I like about it?

He brings up a lot of things that people believe that you just have to do in a business. That not doing them would be crazy and it’s assumed would be bad for business.

Yet, Trade Joe’s provides a real world, living example that you can violate those and still win.

I contend that these things don’t have a positive ROI by the businesses that use them, but they are so generally accepted that questioning them puts you into crackpot conspiracy theory category.

But I think these things tend to live on because of folklore and the elusive idea that someday somehow they might pay off.

PowerPoints kill

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Another bit of Amazon culture I like is that Bezos isn’t a fan of PowerPoints. I read that he likes people to write out their proposals in a few pages because it’s better to think through what you are proposing and for others to digest it.

I can see that because I think PowerPoints can bamboozle. They have a similar effect as a well-produced documentary or well rehearsed magic show.

Or the chutes designed to calm cows down as they walk toward their slaughter. For some reason, they work.

I often see PowerPoint presentations get a lot of praise, while I’m thinking I’m not even sure what the presentation is saying.

My first experience with this was early in my career when a company I worked with hired McKinsey for a project.

I discovered if I shared a snip of a table from a spreadsheet, the big shots would take out their calculators and start checking my math and ask a bunch of questions about the data.

But, when McKinsey sent the spreadsheet to their graphic design team to turn it into a nice looking PowerPoint slide no calculators came out, no questions were asked.

Everything was accepted as if peer reviewed* proven facts and the big shots would heap on the compliments about the quality of the presentation.

If you needed a simple two column table, they’d get rid of the borders and put a thin, elongated triangle in the white space between the two columns pointing from the left to the right column and it was hypnotic magic.

I called the triangle-thingy the McKinsey Mystifier and used it a fair amount myself.

That was right at the point of where making nice looking presentations started to become a highly desired business skill.

Said differently, creating chutes that can calm executives as they pace toward their own pink slip has become a highly desired skill.

It leads them to their own pink slip because they get so mystified that they don’t ask what are often obvious and common sense questions and end up doing dumb stuff that cost them their job.

I witnessed it dozens of times.

When i tried to point out the obvious logical flaws, they’d shut me down. What are you talking about? See how nice this presentation looks?

By the way, if McKinsey ever tells you that you should open a bunch of locations to fend off competition, I can tell you how that story ends and why that doesn’t work.

*Peer review is also a joke. It doesn’t put the case or the science through the scrutiny folks assume it does. But it has a similar, deceptive quality of a nice looking presentation that keeps folks from asking obvious questions.

Amazon’s Default to Yes

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I read about it in the book, The Geek Way, which I wrote about here. But, I also experienced it for a few years in corporate culture and can vouch for how well it works.

In fact, I would say that if I could change one thing about a company’s innovation culture to dramatically improve it’s success, this would be it.

It’s very different than how most companies operate, which is a bias for No.

This Inc. magazine article sums it up well:

I feel confident saying that most of us have had the experience of pitching a brilliant new idea (at least it’s brilliant in our minds!) to our boss or manager only to see the person shake their head and say, “No, that’s not going to work.”

“But I just thought…” you might plead.

“You just leave the thinking to me,” your boss says. “Now get back to work.”

It might be worse if your manager responds by saying, “Maybe. Let me think about it. I’ll get back to you.” That’s just saying no using different words because, guess what, they will never get back to you.

And what happens when your brilliant new idea gets rejected? You feel dejected and disengaged. All that energy and excitement you had ebbed away. It will likely be a long time, if ever again, before you bring a new idea forward.

I think we all can identify with that. IMO this is where most ideas die, well before a customer sees the idea and based on the highly invalid opinions of one person.

Also wanted to point out that last sentence. The bias for ‘no’ also tends to kill ideas on the vine, because people don’t have the incentives to bring their ideas forward because they know nothing will happen.

The article goes on:

Amazon’s policy of defaulting to yes is to unlock its workforce’s creativity and innovative thinking. It’s also connected to the company’s other leadership principles like “ownership,” “bias for action,” and “customer obsession.”

It’s quite literally the rule at Amazon that when an employee brings a new idea to their manager, the manager has to say yes unless they are prepared to defend their reasoning behind saying no.

In other words, they have flipped the script by putting the onus on managers to hear every new idea.

The policy doesn’t say that every idea gets the green light to be fully implemented or invested in. Rather, it’s about giving the idea enough oxygen to see if it has the potential to catch fire.

It’s like one of the fundamental rules of improv comedy where every player embraces the line “Yes, and … ” Think about it: When anyone says no, the scene ends. But by saying “Yes, and … ” they can find themselves heading in unpredictable and often hilarious directions.

I can’t vouch all the details on how it works at Amazon, but when we did it we did more than just hear out the idea.

I will say, I’m skeptical of this part, “…unless they are prepared to defend their reasoning behind saying no.” That’s a big in for letting bias for no back in.

When we defaulted to yes, we encouraged the person with the idea to experiment with it to prove it out. I would ask them:

  • What can you do to prove to yourself that you’re onto something?
  • What would you have to see to believe that your idea would work?

Then I might encourage them to run those experiments, suggest ways they might do so, do research or connect them with someone that had P&L responsibility in the right area that might be willing to fund a pilot to prove it out.

If the idea person had P&L responsibility, I’d ask if they’d be willing to fund a pilot of the idea to prove it out. I thought it was funny that it hadn’t already occurred to them to fund a pilot on their P&L.

I found all this does a few things.

First, it forces people to imagine what their idea would look like in the real world and 50-80% of the time causes them to douse their own idea’s flames with water.

This appears to be a huge mental step that’s similar to being asked to make a bet. It’s easy for us to spout of about how we think our sports team is going to dominate in an upcoming game when we face no tangible consequence for being wrong.

When someone offers to put our money where our mouth is and make a bet, that tends to crystalize how confident we really are, which is usually not nearly as confident as before the offer was made.

Similarly, it’s easy for us to be enamored with our ideas when they only live in our own minds. I’m guilty of that.

And likewise, when I am forced to think of putting my idea for a new business, product or charity event into the real world, that naturally causes me to imagine how customers might respond and realize my idea isn’t far different from what’s already available.

That’s something I encounter when folks give me their our ideas. It’s far less effective for me to point out that their idea pretty much already exists than it is to get them to start to take this mental journey and have them realize that on their own.

If my idea already exists in some form or fashion, I ask myself what would make a customer choose the new product over what already exists and if I can’t come up with clear answers, I realize that maybe my idea isn’t so great after all.

It turns out, this first step of thinking about how you would prove your product out in the real world serves as a good first filter for ideas.

That’s good, because only about 1% of ideas at this stage will work.

Second, if my idea passes the first filter and it seems reasonably probable in my own mind that it’s different enough from what’s already available and solves a big enough problem that customers might be interested in it, I go to the next filter: is it worth my time to do something with it?

I imagine the effort I’d have to put out to prove it and that turns out to be a good first ROI calculation.

It’s easy for us to advocate for ideas when it’s someone else’s job to prove them out. We all love to toss ideas over the silo to the innovation group at work, pat ourselves on the back for having such a great idea and, well, if the innovation group never tries it, they just don’t what’s good.

But, it changes the calculus if I have to determine myself if I even believe that my own idea has enough legs to be worth my own time to prove it out.

Many ideas don’t make it pass this filter because they don’t seem like good uses of our time.

In the bet analogy, we’ve decided to make a bet, now we are deciding how much to bet.

Though, even if an idea doesn’t pass this filter, I might keep them in the back of my mind in an idea parking lot, keeping an eye out for low calories ways to try them if opportunities present themselvs. I’ll also keep an eye out if competitors are trying it and see how it works for them.

I believe ideas that make it past these first two self-imposed filters stand a better chance of success than ideas that bypass these filters. It might increase the chance of success from less than 1% to somewhere between 1% and 10%.

It’s also fun to watch what people do when you expose their ideas to the sunlight of their own thinking.

Try it. Next time someone gives you an idea, follow the steps above and see what they do.

Most of the time it creates cognitive dissonance, that is one part of their brain still loves their idea while another part of their brain begins to realize that their idea isn’t all that it’s cracked up to be.

Cognitive dissonance can cause different reactions in different folks.

Some people will get mad at you and blame you for saying no to their idea, even though you didn’t. They are just transferring their own their own ‘no’ to you.

Or they reach for excuses to keep them from having to imagine their idea in the real world. One person said, “Well, it’s not my job, I’m not the innovation group. That’s for someone else to decide.”

Many times, people are fairly rational and think through what they would have to believe would need to happen for their idea to work and they say, “Oh well, I can’t see that happening, maybe that’s not such a great idea after all.”

And a few times, people said, yes, I will it a try.

A couple of those ended up being the most successful thing I worked on in my career.

‘Just in time’ is a recipe for constantly operating in fire drill mode

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In my experience with mature companies, it seems common that they operate in fire drill mode even though they have been producing and selling the same products for decades and are supposedly run by top-notch managerial talent.

I trace some of it back to the ‘just-in-time’ revolution of the 1990s. The idea was to cut the supposed fat out of the supply chain and shorten the time it took to get products from production, to shelf to sell.

Sounds good until your realize that Murphy’s Law is real. A ‘just in time’ supply chain assumes everything runs smoothly.

Every hiccup along the way in a trimmed out supply chain can cascade and cause major disruptions.

But management doesn’t want to question the sacred cow of tight supply chain management, so they keep putting out fires assuming the future will smooth sailing.

It’s not, so they are always trying to put out fires.

I know this is heresy, but a little fat in the supply chain can absorb some of the unexpected disruptions and maybe even pay off in terms of not missing as many sales or upsetting as many customers.

The heartbeat of business: how needs are met changes

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This if from “The Geek Way” by Andrew McAfee (emphasis added):

Former Google CEO Eric Schmidt explained to me one of the biggest consequences of this shift: “In the classic corporate model, everything is run in a hierarchical way, the office gets bigger over time, and bureaucracies abound. Companies like this were actually successful for a long time because they have some strengths: they’re predictable and they serve their customers well, as long as customers keep needing the same thing. The reason that culture doesn’t work very well in the information age is that the customers need changes, and you have to be able to change more quickly than, you know, every five years.”

from “the geek way” by andrew mcaffee

I liked this because it simply and clearly identifies a main driver of business.

Though I would add something. Often, people’s needs don’t change, but how they satisfy those needs do.

Think of the pager.

It served a need to let you know that somebody wanted to contact you even when you weren’t close to your landline telephone.

It served that need well in its day and age.

That solution was part of an environment where phones were stationary objects.

Pagers aren’t needed anymore, but the need for somebody to instantly contact you remains.

What changed is how that need was met.

Nobody set out with smart, intentional Harvard Business School strategy to disrupt pagers or capture that market.

How that need was met naturally evolved as the environment changed to where phones became mobile and we have them with us most of the time.

The instant contact need also got solved in different ways as those phones evolved capabilities to connect people in more ways. So much so, that phone calls have become almost as much of a relic as pagers, as a good chunk of our communication has shifted to texting and messaging apps.