Igniting New Growth is Like Falling in Love

 

‘Shall I compare thee to a summer’s day?’ William Shakespeare

As a Toyota acolyte, I experienced the power of Kaizen - continuous incremental improvement creating continuous Value (not unlike the effect of compound interest). A decade ago, a nagging doubt crept in. If Kaizen & TPS are enough, why are the market valuations of the Tech tigers so much higher than those of the great Industrials? Clearly, Kaizen is necessary, but not sufficient. And so, I went to Singapore and fell in love.

A human being drew this & wrote this

Finding the Blue Ocean

I fell in love with the mindset, skillset & processes of ‘Abracadabra’ Innovation – creating new offerings seemingly out of nothing. In earlier articles, I described my collaboration with Laurent Simon – my friend, co-author & East Asia Innovation leader. Under Laurent’s guidance I participated in Innovation sprints in a range of industries. Twenty-five years after my Toyota apprenticeship, I found myself on another steep learning curve - how to ignite new Growth.

My Sprint colleagues & I were seeking the proverbial ‘Blue Ocean’, a place where nobody else was fishing. Kaizen, by contrast, entailed making small improvements to an existing offering or process – a very different challenge, though no less profound.

Abracadabra Innovation is Like Falling in Love

Abracadabra Innovation is a journey in the dark. Our Sprint teams often have little data & thus cannot answer the most basic innovation questions:

1.     Who is the customer?

2.     What do they value?

3.     Why do they buy or not buy?

Lesson # 1: you have to create your own data. You have to learn our way up the proverbial innovation curve through quick, cheap experiments. (Lean experimentation has a bright future).

Lesson # 2: It's like falling in love. You build trust a little at a time. Coffee, then lunch, then a low-risk date, say, a bike ride or a museum visit. So far, so good? Do I know this person? Do I like & trust them? Do I want to spend more time with them? Okay, then maybe dinner? At each step, each party gives a little more, and trust grows thereby.

We want to gradually engage the customer. The stages are typically some version of: I Know, I Like, I Trust; I’ll Try, I’ll Buy, I’ll Buy Again. And if you’re really good & lucky: This is so great, I’m going to tell all my friends! At that point the proverbial Customer Funnel becomes an Hourglass.

Think of this as a process with three Phases:

·       Awareness (Who are these jokers?),

·       The Bridge (Maybe I’ll try it), and

·       The Clubhouse (I’m a fan)

The innovator’s job is to pull people from Left to Right, and into a Clubhouse full of fans. Like any process, Innovation has bottlenecks. As Eli Goldratt taught us decades ago in ‘The Goal’, our job is to 1) Identify the bottleneck(s), 2) Understanding the blockers underlying each bottleneck, 3) Remove the bottlenecks, and 4) Keep going till we have a clubhouse full of fans.

And here’s the hard part – to do so we have to generate sound data usually out of nothing.

Next time I’ll talk about common innovation bottlenecks. Stay tuned.

Best wishes,

Pascal Dennis         E: pascal.dennis@leansystems.org

Kaizen is Necessary But Not Sufficient

 

‘There are more things in Nature, Horatio, than are dreamt of in your philosophy.’ Hamlet

As a Toyota acolyte, I was focused on the factory. How could I not be? New factories & model launches, new processes & equipment, continuous problem solving in a splendid team environment. I experienced world-class management & leadership. A Toyota logo is forever emblazoned on my heart.

But I began to realize there were large gaps in my understanding. If TPS was enough, why were the Tech tigers so much more valuable than the great Industrials? And so, I went to Singapore seeking a sensei.

Finding the Blue Ocean

I found my Innovation sensei in Laurent Simon, my friend, co-author & East Asia Innovation leader. Under Laurent’s guidance I participated in Innovation sprints in a range of industries (Financial Services, Consumer Goods). We were trying to create something seemingly out of nothing – ‘Abracadabra’ Innovation. Twenty-five years after my Toyota apprenticeship began, I found myself on a new learning curve, one just as steep & just as exhilarating.

Kaizen entails making continuous incremental improvements to existing offerings & processes and can achieve seemingly magical outcomes not unlike those of compound interest. My Sprint colleagues & I were seeking the proverbial ‘Blue Ocean’, a place where nobody else was fishing – a very different challenge, though no less profound.

I Thought I Understood the Customer

At our great Toyota factory, we thought we understood our customer, and so we did – to a point. We understood the customer’s wide range of satisfiers & dissatisfiers. We set both process & outcome targets for critical items like water leaks, engine surges & stalls, squeaks & rattles and dozens more. We focused kaizen activity on hot spots, kept improving and repeatedly won the coveted JD Power Gold Plant Quality award (still a point of great pride).

But here’s the rub: Could my Toyota colleagues & I have imagined that the automobile would evolve into a ‘smartphone on wheels’ or a ‘living space’ designed for comfort & productivity?  Could we have imagined parallel developments like the Smartphone or AI?

Kaizen is necessary but not sufficient. Abracadabra Innovation entails creating something new & useful seemingly out of nothing. We were often in the dark regarding core innovation questions like:

1.     Who is the customer?

2.     What do they value?

3.     Why do they buy or not buy?

We had to create our own data by running quick, cheap experiments. We had to learn our way up the proverbial innovation curve.

Abracadabra Innovation is a Process

What have I learned about innovation?

It’s a process through which you gradually engage a prospective customer.  Process steps typically comprise some version of:

·       I Know, I Like, I Trust; I’ll Try, I’ll Buy, I’ll Buy Again, and if you’re lucky,

·       This is great, I told all my friends!

This so-called ‘customer funnel’ has three phases:

·       Awareness – (Who are these jokers?),

·       Bridge – (Hmm, I should check them out), and

·       Clubhouse – (I’m a fan)

The innovator’s job is to pull people from Left to Right, and into the Clubhouse. Like any process, this one has bottlenecks. As Eli Goldratt taught us decades ago in ‘The Goal,’ our job is to 1) Identify the bottleneck(s), 2) Understand the blockers underlying each bottleneck, 3) Remove the bottlenecks, and 4) Keep going till everything flows.

To create ‘flow’ we have to a) develop hypotheses around the core innovation questions, b) run quick, cheap experiments, c) thereby generate sound data, and d) continually adjust our offering based on what we’ve learned, without going broke.  

Experimentation has a bright future! More to come.

Best wishes,

Pascal Dennis         E: pascal.dennis@leansystems.org

 

Innovation is Even Harder Than Baseball

 

"How do I avoid going through all this twice?" Bob Dylan

Baseball is a game of failure. Ohtani at the plate? He fails more than 70% of the time. Kaizen (incremental innovation) success rates are much higher. At my alma mater, Toyota Manufacturing, our strike out rate was much lower than Ohtani’s. Each year we hit demanding improvement targets in Safety, Quality, Delivery & Cost, which created the kind of 'Kick Ass, Take Names!' culture I enjoy to this day.

What about Abracadabra Innovation (aka creating something new out of nothing)?

Does Innovation Failure = Waste?

 Abracadabra Innovation (aka creating something new out of nothing) entails failing 90% of the time! My earliest sprints in Financial Services & Consumer Goods were a bit of a shock. Toyota's powerful methods & mindsets around Value & Waste are an indelible part of me. And here I am, part of a Sprint team whose experiments almost always fail, and whose offerings the customer almost always rejects! Surely, that's pure waste...

 The Currency of Innovation is Learning

 It's pure waste only if you learn nothing, and only if your experiment is needlessly expensive. But what if your experiment is quick & easy, say, a low-cost ad on the customer's favored channel, that tests the appetite for a critical product attribute? Or a brief online survey that illuminates an undiscovered Early Adopter group? Or a pop-up store & product mash-up that validates (or invalidates) a critical hypothesis around price point or distribution channel?

 That's a different story, no? The currency of innovation is learning. Hence the well-known mantra: ‘Fail fast, fail forward’. Each these experiments generate valuable knowledge & prevent far great waste downstream.  Like making, marketing & distributing something nobody wants. This is one waste Lean/OpEx usually misses. We're trained to look for waste in existing processes & products, not in our aggregate offerings & how they are received. The famous Wheel of Waste does not include 'making stuff nobody wants'. 

 

To be fair, Lean/OpEx managers & engineers are not trained in Abracadabra Innovation. My Toyota sensei drew a circle on the factory floor & asked me to watch the process till I understood its secrets, and especially the value & waste. He did not ask me to run experiments around who is the customer, what do they value, and why do they buy (or not) from us?

 To answer such questions, I had to go to Singapore & seek out different senseis. I learned new methods & mindsets. Sometimes they overlapped with my Lean/OpEx experience, sometimes not, as is the case with the attitudes around 'failure'. Nonetheless, my Lean/ OpEx foundation was extremely helpful, especially to the many sprint team members I mentored. 

 Applied Learning Equals Value

 Top execs in major companies tend to have a background in Operations, Finance or Engineering. (It’s been my honor to have mentored many). In my experience, many leaders are vulnerable to the Innovator’s Dilemma. To wit, the ROI on innovation work will always be much less than Business As Usual – unless we accept the above adage. Ambidexterity is now an essential element in the senior leader’s repertoire. It’s no longer enough to protect the core business, we must also ignite new Growth.

 In summary, Abracadabra Innovation is harder than baseball. You have to frame success & failure in terms of learning. "What are we trying to learn with this experiment? What's our hypothesis? How will we know if we're right? What's a clever way of getting this data? How do we make it quick, cheap & easy? And most important, how do we record, make it visible & share the learning?

 Best regards,

 Pascal Dennis         E: pascal.dennis@leansystems.org

 

Kaizen & Abracadabra Innovation

 

There are more things in heaven & earth, Horatio, than are dreamt of in your philosophy.

There are two kinds of innovation: incremental improvement (aka Kaizen) and ‘create-something-new-seemingly-out-of-nothing – ‘Abracadabra’. Both are magic and essential to sustained prosperity. Our challenge is to understand the very different methods & mindsets that underlie them. Indeed, this is an essential leadership skill, and the basis for what I call ambidexterity.

Kaizen is Like Compound Interest

Kaizen is magic the way compound interest is magic.  Imagine we’re able to engage all team members in finding & implementing small improvements that contribute 1% per month for an entire year. Where are we at year-end?[1]

Doing Nothing: Year End = (1 + 0.00)¹²  = 1     

Kaizen (1% per month): Year End = (1 + 0.01)¹² = 1.127    

At year-end we’re 12.7% better than if we had done nothing.

Now imagine we sustain this for then years.

Kaizen (12.7% per month): Year End = (1 + 0.127)¹⁰ = 3.30

After ten years, we’re better by 330%

An astonishing result, no? As with compound interest, benefits compound. Skill builds upon skill, confidence & teamwork build upon the same. The power of Kaizen blew me away. When you’ve lived it, you never forget it. I remember looking around our Toyota factory, seeing the intense focus and continuous improvement, and feeling sorry for our competitors. And our competitors were smart, capable & hardworking.  But they had yet to discover and apply the power of Kaizen.

There is a rich literature describing Kaizen culture, and more importantly, its blockers. Let me add that the long latency period is an insidious blocker. Like compound interest, incremental improvements are invisible in the short term.  ‘We had a 1% improvement last month – ho hum…’  And so, most Kaizen efforts run out of gas, or more common, we get a new leader who doesn’t understand or care about Kaizen.

Perhaps the most famous practitioner of the 1% improvement principle is Tom Brady, who turned continuous incremental gains into massive competitive moats.

Creating Something Out of Nothing is a Different Kind of Magic

People love ‘Abracadabra’ innovation – creating something new (seemingly) out of thin air. Innovation masters like Steve Jobs are akin to magicians. Nothing up my sleeve, he tells us, and then Presto! - an iPhone or iPad appear.

At first I confess I was suspicious. Apple quality is not so hot, I muttered to myself, missing the magic. In an odd way, my kaizen experience was a blocker! Then I went to Singapore and began the next phase in my apprenticeship. I learned that Kaizen was necessary – but not sufficient. 

Creating something new out of nothing is the key to igniting new Growth. So-called 'exponential' technologies, of which AI is the latest & likely most powerful, expand our ability to innovate, but the underlying mindsets & methods are essentially unchanged. How do these differ from those of Kaizen? Are there any synergies?  Do you need both types of innovation? If so, what’s the leader’s role in developing them? Stay tuned. 

Best wishes,

Pascal Dennis         E: pascal.dennis@leansystems.org

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Soft Consensus vs ‘Prove Me Wrong’

 

Everybody knows the boat is leaking, everybody knows the captain lied. Leonard Cohen

How you think determines what you see. As a Toyota acolyte, I learned to see & think in a different way. The past decade I’ve been immersed in Innovation thinking - how to create something valuable seemingly out of thin air. This is the first of a series of articles on what I’ve learned.

A human being drew this.

Decision-Making: Consensus or Prove Me Wrong?

Soft Consensus:

When it comes to Innovation (or Strategy), avoid ‘soft consensus’. Here’s a common scenario: Our path forward is unclear. We have conflicting data or no data at all. So, let’s go around the Board room or team room & try to reach a consensus. Let’s give everyone a chance to speak & weigh up what we think it all means. Everyone’s voice gets equal weight, regardless of how much expertise or skin in the game they might have.  People who are most emotional get extra points. Sometimes this devolves further into HIPPO or ZEBRA or WOLF management.^[1]

Everybody pretends things are ‘just great’, and such sessions often end with heartfelt paeans to engagement & inclusiveness.  But to quote Leonard Cohen, ‘Everybody knows the ship is rotten. Everybody knows the captain lied.’

This is a great way to kill Innovation & destroy Value. We thereby institutionalize Confirmation Bias - the Lord Voldemort of bad thinking. New offerings sink like stones & good riddance.  Toyota acolytes are familiar with that great company’s deep understanding of Waste. Is anything more wasteful than designing & releasing an offering nobody wants?

Prove Me Wrong

If you want to innovate, encourage dissent & disagreement. Encourage those who disagree to explain their thinking. Prove me wrong conveys great benefits. For a start, it encourages people to challenge the weakest elements of your hypothesis. It compels the Innovation team to validate their ideas with data. Prove me wrong reinforces the fact that Innovation entails experimenting your way to Value, in the dark.  Rarely do we have a deep understanding of the key questions:

●      Who is the customer?

●      What does the customer value?

●      Why do they buy or not buy?

Pretending otherwise, is preparing to fail. Only through quick, smart & binary experiments can we begin to understand the problem we’re trying to solve. ‘Quick, smart & binary’ are antithetical to ‘soft consensus’, which is commonly slow, thick & data-poor.

Innovation thrives on the margins, with the oddballs, eccentrics & iconoclasts. The ones that challenge that status quo, the ornery & quirky.  Soft consensus, by contrast, cuts off the so-called ‘long tails’ of the distribution, and with them, the interesting, eccentric & profound.

Last Word

Prove me wrong is perhaps the most challenging Innovation mental model. Companies that seek to emulate Toyota rightfully emphasize ‘Respect for People’. Prove me wrong is easily mistaken for disrespect. Mature leaders will understand that the opposite is true. Another common mistake is giving a platform to ‘Grumblers’.  [Please refer to my earlier series on Fukuda’s Parable.] Grumblers and iconoclasts are not the same thing. The former are cynical & disengaged and we must ignore them. The latter are passionate, may be angry or frustrated, but are fully engaged. Listen to them.

Best wishes,

Pascal Dennis         E: pascal.dennis@leansystems.org

 

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[1] Highest Paid Person’s Opinion, Zero Expertise But Really Arrogant, Works on the Latest Fire

The Two Faces of AI

 

I’m torn…My vocation entails teaching leaders how to solve complex problems both to protect the core business, and to ignite new Growth. My avocation is music - I’m a member of an international band comprising two grizzled veterans & brilliant young players from Europe’s best music schools. In both my vocation & avocation, AI is a blessing and a curse.

Which one will prevail?

AI and My Vocation

AI helps us protect the core business by enabling our management system and helping make problems visible. AI collects data, analyzes value streams, and helps predict hot spots. At the same time, I’m painfully aware that AI agents are shrinking entry level jobs. AI agents are good at core admin tasks & the basic research & analysis new team members used to do. Nowadays, getting that crucial first job is much harder.

Our new Growth work is focused largely on the consumer goods & financial services industries. AI agents enable our sprints. We can run many more experiments & harvest learning quicker.  AI agents also help us analyze & repurpose the existing assets. Years worth of social media content, for example, can be quickly analyzed & reused for new sprints.  We ‘fail fast, fail forward’ with breathless ease.  New assets can be developed & tested while we sleep.

As an engineer, I’m admire & celebrate the splendid engineering & continuous problem solving around neural networks the past twenty years.  Bravo!

I’m also aware that my fellow engineers & I lack the moral & philosophical chops to grapple with the biggest moral challenge of our age: How to deploy the AI genie so as to enhance our lives and reduce suffering while sustaining our core values?

AI and My Avocation

As a musician, I’m acutely aware of AI’s devasting effects on the creator economy. Musicians, writers, journalists, graphic designers, filmmakers and other creators have largely been obsolesced.  Tech companies ‘scrub’ everything they can find and thereby train their ML monsters.  Then they resell us AI slop at twenty bucks a month. Some say we are witnessing the greatest theft of IP in history,

I try to be a good mentor for our young players. One of my core messages is: “AI has destroyed the willingness to pay for creators’ work. We have to accept that hard fact & adapt.  How do we adapt? By becoming ambidextrous.  Develop a second capability that will put food on the table. Be a carpenter, electrician, engineer, teacher, lawyer etc. I do not want you to end up homeless.”

Our band does not use AI to create music – that is unthinkable. We play our instruments with our own hands, we will never use autotune or anything like it. But AI does reduce hassle in the studio. For example, AI can handle the tedious task of eliminating overly loud breathing between vocal phrases.  (I’m a loud breather…).

AI agents help us curate & repurpose our social media assets, as we do in my day job. I engaged a young engineer to develop an AI agent that selects potentially viral content, creates thumbnails & templates for the channels we’re targeting (e.g. YouTube, Instagram, TikTok). AI analyzes a given musical piece’s performance according to our key metrics (Streams, Click-through rate, average watch duration etc.).  Needless to say, I also use him in my day job.

In summary, AI is both a blessing and a curse - in my vocation and avocation.  No wonder I’m torn.

Best wishes,

Pascal Dennis         E: pascal.dennis@leansystems.org

Respect for People in an AI World?

 

Is ‘Respect for People’ possible in the age of AI? A generation ago, the Toyota Production System (TPS) doubled down on this idea and changed the world. Their revolutionary idea was to release the ‘genius of the organization’ through ‘Total Involvement’.  Nowadays, more than a few Tech leaders envision billion-dollar companies with ‘very few people – ideally just one.’ Is ‘Respect for People’ a dead idea?

Middle Management is Over…(?!)

At recent conference a well-known Tech leader opined that, ‘Middle management is over.’ His plan to ‘create value’ amounts to 1) continually replace people with AI agents, and 2) maintain a skeleton crew to ‘manage the work’. 

Avarice & nihilism aside, this hare-brained plan ignores uncomfortable facts, the most obvious being: If we fire everybody, who is going to buy our stuff? Other problems include:

·       Work is messy. You have to deal with internal & external customers, supply chain partners, regulators, banks & insurers, and eccentric, quirky people up & down your value streams and customer journeys. How will you sustain these relationships without people?

·       People are good at building essential relationships – AI agents are not. People mentor younger team members. They know the company’s work better than anyone. As Toyota observed, if you release smart, well-trained people on big problems, they’ll release a tsunami of value.

·       AI agents are expensive and can mess up big-time. The question is not ‘Can an AI agent do this for us?’ The question is: ‘Can an AI agent do it better & cheaper than a human, and with less hassle & risk?

The World is More Than Databases & Loops

‘Software Brain’ seeks to flatten the world and all human experience into a series of databases and loops. Big AI agents can then, presumably, issue instructions and ‘manage the work’.  Here’s the underlying mindset: If the word does not align with the database – change the world. 

In fact, all these things that look like a computer are nothing like a computer. The Law, for example (an early, seemingly easy target for AI agents), is much more than databases and loops. It’s messy, ambiguous and full of grey areas. You can argue different sides and come to different conclusions. The same is true of Medicine, Engineering, Accounting, and Actuarial Science, not to mention the Arts including the visual arts, music, creative writing, theatre and film-making.

So, this thing [Life] that looks like a computer is not at all like computer. Not everything is a loop. Not everything humans experience can be captured in a database. Trying to flatten people & life in this way is the polar opposite of ‘Respect for People’.

People do not consider code-writing to be a blessing. The idea of linking all their databases & automating their lives with Claude Co-work frightens & disgusts them. People hate AI because it flattens them. It's not a marketing problem or a bug - it's a center feature of Software Brain.

TPS remains a sharp rebuke to those who dream of a ‘billion-dollar company of one person’. Is eliminating middle management & destroying entire industries something to brag about?  Big Tech leaders are now routinely booed off the stage. Is it any wonder?

Best wishes,

Pascal Dennis         E: pascal.dennis@leansystems.org

The Trouble with OKRs – part 2

 

Does the OKR approach to strategy deployment reflect the 'top-down' mentality of Big Tech? Does OKR reflect the debilitating phenomenon called ‘Software Brain’, and its core premise - Life is just a series of loops & databases…?

Strategy is a Messy Human Thing

As with many fallacies, ‘Software Brain’ contains a significant element of truth. Life is indeed a ‘series of loops & databases’. Study & understand these loops & databased and you acquire a superpower, which used wisely can greatly reduce human suffering.  But life is much more than this.

But if you try to flatten life in this way you may end up becoming hated, no? Life also comprises messy, unpredictable, thorny, comical things like human beings, their memories, emotions, ideas & intuitions; their dreams, aspirations, religious beliefs and shared conscious & unconscious minds; the cycles & rhythms of nature including human nature, animals & the forces of physics, chemistry, biology, the pure ideas of philosophy and mathematics.

Aristotle described the two Worlds of Necessity and Contingency. Software brain seeks to flatten the world to match algorithms, loops and databases, which is a paltry & incomplete reflection of one of Aristotle’s worlds. Does OKR do the same?

The Essence of Strategy Deployment & Execution

Strategy deployment entails engaging the genius of the organization.  The Leader’s most important job is developing a questioning culture, one in which healthy push-back is encouraged.  “Here’s our Aspiration & Winning Logic.  What do you think? Help us understand what we’re missing; give us fresh perspectives and your ideas on how to get better.”

To be sure, I’ve encountered OKR companies with questioning cultures wherein healthy dissent in encouraged, but they’re a minority.  More common is the superficial, unimaginative Aspiration & Winning Logic, mechanically pushed down with little reflection, testing or validation. People tune out – (‘Here’s one more dumb thing I have to do…’). Do they sense that their humanity is being flattened into loops and databases?

The W-V model attributed to the great Shoji Shiba is a fine example of a healthy Strategy Deployment system. Hypotheses continually bounce back and forth between management levels.  “Here’s what we think? Are we on the right track? If so, please translate our shared thinking into tactics for your team, department or site.”

Most importantly, this back & forth between and among management levels continues into & throughout the strategy execution cycle.

Key Attributes of World Class Strategy Systems

When I’m asked by a Board or Senior Team to ‘assess our strategy & management system’, a key step is to walk the value stream backwards, starting with the customer, and moving upstream one step at a time till you get to raw material suppliers. A parallel step entails walking the customer journey backstream, starting with the top of the proverbial funnel.

In my value stream walks, I ask questions like:

·       Are problems visible (even to an outsider like me)?

·       What do people talk about in their huddles (from senior leaders to the front-line)?

·       What’s the organization’s attitude to problems? Are problems hidden, a sign of failure? Or are they, to quote W. Edwards Deming, ‘the process speaking to us’?

·       Do teams have a standard approach to problem solving?

·       How good is the data? Is it complete, end to end, and of high quality?

·       Does the team develop ‘Your Own Data’ (YODA) as required? Or do they passively wait for corporate data?

These are all messy questions that engage both hemispheres of the brain and both of Aristotle’s worlds. Does your OKR process foster a healthy, pushback culture that can sustain & engage? Or does it flatten corporate life?

Best wishes,

Pascal Dennis         E: pascal.dennis@leansystems.org