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Key Words: Innovation; Innovator’s DNA – Networking, Observing, Questioning, Associating, Experimenting; Organic Growth, Culture of Innovation – Purpose, Mastery, Autonomy; Knowledge Work Productivity; Manual Work Productivity

Recently, Lydia Dishman, an innovation and entrepreneurship contributor to Fast Company, asked me to comment on a trend in the workplace – tracking of employee collaboration and productivity using wearable technology devices. You can read my comments in her Fast Company article titled: “Can Performance Be Quantified? Wearable Tech In The Office.” In this blog, I will elaborate on several of the comments I made for the article.

Problem: All the developed countries today are predominantly service / knowledge based economies. Upwards of 70% of the employees are working in these sectors. While this has been true for more than 20 years now, unfortunately, productivity in the service sector has never reached the levels of productivity in the manufacturing and/or agricultural sectors. Quantifying, capturing, tracking and improving Productivity in the knowledge sector has been even more difficult; hence the interest in this topic. Please note: I make a very clear distinction between the low-wage service jobs and the relatively higher-wage knowledge work.

Solution: Wearable Technology that tracks employees. For example, the Hitachi’s Business Microscope is a device that employees have to wear around their necks at work. It measures and analyzes the employees’ interactions and activities. When the employees come within a specified distance of each other, they recognize each other and record the face time, body and behavior rhythm data to a server. Executives can then analyze which groups tend to interact and cooperate. So, where are we heading with these sophisticated “dog tags?”

Trend: In the last 5-7 years, based on several data collection techniques, enterprises have been labeling employees as knowledge “spreaders” or “bottlenecks;” as “loners” or “connectors;” as “influencers” or “followers.” Why are firms doing this?

Challenge: Innovation that spurs organic growth is the most difficult challenge that large firms are facing in the last 15+ years. Specifically, firms realize that they need a cadre of seasoned innovators and internal-entrepreneurs (intra-preneurs) to spur innovation and organic growth. Unfortunately, except for a few, the majority of firms are struggling in their innovation efforts as well as fostering a culture of innovation where these innovators and entrepreneurs can thrive and flourish.

Innovator’s DNA: What makes innovators different? How do they routinely come up with great ideas? How do they think and act? What is their mindset? What are their behaviors? Research shows that great innovators and successful and serial entrepreneurs demonstrate five key skills – Network, Observe, Question, Associate and Experiment.[1] Firstly, they are great at networking – meeting people from diverse backgrounds and skills. They immerse themselves into situations that expose them a variety of perspectives. This in turn helps them to sharpen their observation, questioning and association skills. When thrown into uncomfortable and unknown situations, most of our senses are in a state of heightened awareness. Hence, intense networking helps innovators and entrepreneurs to become good at observing and listening; especially, they do so without prejudice. Immersion and interaction with a diversity of situations propel them to constantly question the status quo within their own areas of expertise or specialty. They are constantly trying to improve and change things for the better. This questioning leads them to associate, copy and relate ideas and experiences across functions, industries and arenas; leading to possible new ideas and solutions. Finally, innovators are great at experimenting, exploring and testing their new ideas and solutions. They just don’t talk about it. They take the initiative to test if their ideas are in fact opportunities.

Innovation and organic growth within large firms is about routinely identifying great opportunities, shaping and developing them and then capturing them. For large firms, these great opportunities lie at the intersection of disciplines, functions and/or geographies. As seen in the Innovator’s DNA discussion above, we know that great ideas and creativity happens by associating and merging disparate streams of knowledge. However, association and new opportunities emerge only when there is a lot of networking among the different disciplines and functions of their large enterprise. Networking leads to better observation and listening and that in turn drives curiosity and questioning of the status quo. Creativity can be highly individualistic. However, organic growth which is the result of innovation is still the result of a lot of collaboration within large enterprises. So you see firms are desperately trying to force networking and collaboration among employees; and trying to measure it.

Innovation is knowledge work. Unfortunately, knowledge work cannot be treated and/or captured the way we have captured manual work. The traditional ways of measuring manual productivity is more than 100 years old. It goes back to Fredrick Taylor’s scientific method on manual work. It was about defining the task, defining standards, measuring against standards, focus on quantity and minimizing worker costs for a task through command and control structures. However, we live today in Peter Drucker’s Knowledge world. Drucker knowledge worker as against Taylor’s manual worker is much more focused on understanding the task, continuously learning, teaching others and innovating. Ideally, the employees focus on quality of work, they are treated as assets and not a cost and they work in environments where there is great autonomy.[2]

Further, there are more differences between manual work and knowledge work. Manual work is visible whereas knowledge work is invisible. Manual work is highly specialized, quite stable, has structure—definite process and outcome, and is about running known tasks with the right processes and fewer decisions. On the other hand knowledge work is holistic, always changing, has no defined boundaries of process and outcome, and is about uncovering the unknown by asking the right questions and making a lot of decisions.[3]

Hence, it will be quite difficult to capture knowledge work productivity using manual work productivity tools and methodologies. We need to invent new ways of capturing the knowledge worker productivity. Innovative firms have found ways to harness the knowledge worker in multiple ways. 3M has been doing this for nearly five decades, W.L. Gore for the last 40 years and Google more recently. They energize and engage their knowledge workers with a sense of purpose; enable them to master creativity and innovation in a climate with a great deal of autonomy.

Some questions to ponder: Will these high-tech wearable tracking devices help firms become more creative and innovative? Do they foster networking, observing, questioning, associating and experimenting? Do they transmit a sense of purpose, provide autonomy and enhance mastery?

Cheers!

Jay

[1] Innovators’ DNA, HBR, Dec. 2009

[2] Source: Reinvent Your Enterprise, by Jack Bergstrand

[3] ibid

Key Words: Strategic Change, Innovation, Risk, Uncertainty, Ambiguity, Prediction Logic, Creation Logic, Planning vs. Testing, Project Management, Agile SCRUM vs. Waterfall, Lean Startup, healthcare.gov, JC Penney, Lululemon, Georgia Tech, Coursera.

How Executives Get Fired

On Oct. 1, 2013 the much anticipated healthcare.gov went live. And, almost immediately, it crashed. Unanticipated surge in web traffic was blamed for most of the problems. Even those who were able to get through faced a multitude of issues and errors – confusing instructions, missing drop-down tools, unexpected hang-ups and puzzling design. Those who gave up and called the customer service reps didn’t fare any better. The reps couldn’t access the online market place either.

On Nov. 29th, 2013 JC Penny (JCP)—an original member of the S&P 500 since 1957—was kicked off the list for its sharp decline in market value. While JCP still has more than a 1000 stores and 2012 revenues stood at $17B, the historic 100+ year old U.S. mid-range department store has fallen on hard times.

In Oct. 2004, Myron Ullman, a former executive at Macy’s and LVMH was named CEO. Ullman bought in brands like Liz Claiborne and introduced mini-shops within the department store. By Feb. 2007, JCP’s shares had doubled to nearly $80; a 10-year high. The economic downturn hit JCP hard and by March 2009 the stock was trading at $14. In Jan. 2011 William Ackman, a hedge-fund manager who had built up a sizable position in JCP stock, was appointed to the board. Amid Ackman’s push for new leadership, in June that year, former Apple retail-star Ron Johnson was named JCP’s new CEO, replacing Ullman. Johnson arrived at JCP in Nov. 2011.

In Dec. 2011, JCP acquired 16% of Martha Stewart Living Omnimedia stock and planned to put “mini-Martha Stewart shops” in many of its stores by 2013. In Jan. 2012, Johnson introduced a strategy involving in-store boutiques and a pricing plan that eliminated the popular JCP coupons. Instead, it would have “Every Day,” “Monthly Value,” and “Best Price” strategies. Prices would also not end in 9 or 7, but on whole numbers instead. In May 2012, JCP announced a 20% drop in sales and a $163M loss in Q1. Suddenly in June, the Head of Marketing, Michael Francis, who had come 8 months earlier from Target, said “he was leaving.” He was blamed for the marketing messages that were not resonating with customers.

In Aug. JCP started rolling out the “Shops” strategy in stores. Simultaneously, an overhaul of the home department in 500 stores was also started. In Nov 2013, JCP reported a Q3 loss of $123M as sales fell by another 27%. However, CEO Johnson said the firm won’t diverge from the strategy he laid out. By the end of the first year of Johnson’s turnaround strategy, JCP had amassed nearly a billion dollars in losses and a 25% drop in its revenues. In April 2013, Johnson was fired and Ullman rejoined the firm as CEO.

In Feb. 2013, an online internet course offered by Georgia Tech and hosted by the leading online learning firm Coursera promised to teach 40,000 students how to create their own massively open online course. The online platform asked participants to sign up using Google Docs. When the crush of students tried to sign up the system crashed. According to Google, apparently Google Docs only allows 50 people to edit a document simultaneously. A small detail, that seemed to have been overlooked by the planners.[i]

In March 2013, the high-flying Canadian yoga apparel maker and retailer Lululemon had to recall more than $60 million worth of a women yoga pants for being too see-through. Within a month there was an announcement stating “product chief to exit.” The following month the CEO announced that she was “stepping down.”

As we all know, expressions like “to exit,” “stepping down,” and “spending more time with family,” are just euphemisms for getting fired. Why do CEOs and executives get fired? The #1 reason is Mismanaging Change.[ii]

Analytical vs. Emergent Strategies for Growth, Innovation and Change

In a press conference after Johnson was let go from JC Penney, Bill Ackman—who had pushed for Johnson’s hiring, said that Johnson deserved criticism for unleashing a series of pricing and merchandising changes without first testing consumer views. Other Penney insiders criticized Johnson for eliminating the company’s sales and coupons last year without a broad market test, a move that led to a sales slump. The key words to focus on, in the above two statements, are “testing consumer views” and “broad market test.”

In March 2013, six months before the healthcare.gov website went live, McKinsey was asked to do a risk analysis and to develop mitigating strategies. McKinsey submitted a 14-slide presentation to the White House by early April. I have pasted two key slides from that slide deck. The first slide is about “complexity” and the second is about how to manage “complex projects.”

A website like healthcare.gov is a massive and complex undertaking – too many variables and too many unknowns. When you are dealing with unknowns, one is talking about uncertainty and/or ambiguity. On the other hand, risk is about the “known” world – known variables with data from the past. You can calculate and estimate risk using analytical tools. When you know the variables and you have data from the past, one can analyze, predict, plan and then take action. Specifically, we can go into the future in primarily two ways – (1) Analysis before Action and (2) Analysis after Action.

Traditional approaches to minimize and manage risk in innovation and change management projects is by doing a lot of analysis before taking action. BHAGs (Big Hairy Audacious Goals) are announced with much fan-fare. Then, the future is approached by performing an environmental scanning (SWOT, STEP, Value Chain Analysis) and followed by the setting of a project plan to execute strategy. Trend lines are predicted based on IRRs and WACC or projected cost benefits; KPIs and milestones are set and budgets are allocated. When project performance does not meet projections, money and energy is spent to get the project back on to the predicted trend line. Unfortunately, heads roll when the predicted future fails to materialize after a couple of tries.

Below: McKinsey’s exhibit demonstrating the magnitude & complexity of the healthcare.gov website project.

 McKinsey picture 1

This approach to change and project management makes a bunch of assumptions: (1) all process and outcome variables are known and can be accounted for ex-ante, (2) existing data from past projects can be used to predict the process and outcome of this project, (3) some variation to projections can be accommodated along the way using managerial judgment, and (4) failure is not an option.

This concept of going into the future is called “predictive logic” and the method is called “analytical strategy.” I just call this the BIG BANG approach to change. Most large firms, governments and institutions predominantly still prefer this mode of going into the future. I call the firms, organizations and individuals who principally use this strategy of going into the future as “PLANNERS.”

On the other hand, all innovative and complex change management projects have a number of unknowns. Specifically, there are two types of unknowns – known unknowns and unknown unknowns. Uncertainty is about known unknowns. In these situations, you know which variables may impact the process and outcome of the project but there is no data from the past to assign probabilistic numbers. Ambiguity is a second order uncertainty. One cannot surmise as to what variables may be lurking in the background. They only appear once the project is underway. Unfortunately, analytical strategies do not account for these unknowns ex-ante. So, when there are a number of unknown variables, most analysis and hence prediction of outcomes a priori becomes a futile exercise.

In the presence of unknowns, the way to manage projects is drastically different. Seasoned entrepreneurs, innovators and VCs test their ideas for potential opportunities predominantly through Analysis after Action. They Think Big, but Start Small. They start several small projects to test their hypotheses. They prototype rapidly and try to establish proof of concept by quick feedback from the market – voice of customer, voice of technology, voice of supply and voice of demand. They try to fail fast, fail cheap and fail smart. In doing so, they learn quickly by uncovering hitherto unknown variables and/or create data where there is none. With this new knowledge they refine their hypotheses and business models. They iterate this process of prototyping, failing, uncovering unknowns and establishing a viable business model. They pour in more resources only after a positive proof of concept has been established and the successful business model is replicated and scaled slowly. I call this approach to going into the future as START SMALL; as against the BIG BANG approach described previously. I call the firms that employ this technique as “TESTERS.”

In 2009, this method of going into the future was termed “discovery driven growth” by Rita McGrath. Decades earlier in 1978, Henry Mintzberg termed this as “emergent strategy” as against “intended or deliberate strategy” (analytical). In the mid-1990s software developers started using Agile Scrum (iterative emergent techniques) vs. the traditional Waterfall methodology (sequential analytical techniques) based on the work of Takeuchi and Nonaka in the mid-1980s. Most of today’s “Lean Startup” (Steve Blank 2012, Eric Reis 2011 and Ash Maurya 2012) concepts, principles and frameworks profess this very same emergent strategy. At Babson, our entrepreneurship and innovation faculty has been teaching this stuff for decades.

To summarize, PLANNERS usually follow the traditional BIG BANG approach that is characterized by the following sequence: Analyze > Predict > Plan > Act > Full Scale Launch. TESTERS on the other hand follow the START SMALL approach that is characterized by the following sequence: Design > Build > Test > Learn > Redesign > Scale Slow Launch.

Below: McKinsey’s slide that contrasts, the Start Small “emergent strategy” technique predominantly used by “Testers” (on the left) vs the Big Bang “analytical strategy” technique usually used by “Planners” (on the right).

McKinsey picture2

I am not suggesting that one approach is good and the other is bad. The right question to ask is: when do you use analytical strategies and when do you use emergent strategies. The Big Bang approach to change or project management works very well for version 2 or 3 of a product. For incremental innovations and for the known world – known technology, known products, known customers, known business models etc. – when we have lot of data and prior experience, the Big Bang approach still works very well. Unfortunately, in the unknown world – unproved technologies, unidentified customers, untested business models – and for radical innovation or major organizational change the Big Bang approach fails miserably. The Start Small approach works much better.

Unfortunately, healthcare.gov chose the Big Bang approach. At least 5 months prior to launch, McKinsey’s warnings were quite  clear, “…there was scant time to test the system before launch;….there wasn’t enough testing and revision;….create a Version 1.o before full launch….”

I have elaborated on these the Start Small concept in a previous blog as well:

http://innovationatwork.wordpress.com/2012/07/

Have a great holiday season!

Jay


[i] Crash sinks course on online teaching, WSJ, Feb. 4, 2013

[ii] Why CEOs get fired, by Mark Murphy, Leadership Excellence, Vol. 22, No. 9, 2005

This blog is the English version (in prose form) of my Aug. 14th, 2013 interview in Spanish by Estrategia, a leading Chilean business magazine. The original interview can be seen at:

http://www.estrategia.cl/detalle_noticia.php?cod=84245

BlackBerry contemplates selling itself!

But for a few hard-core customer fans in the corporate world, this should come as no surprise to anyone in the field of IT and Innovation. Most of us have seen this movie before; several times. While it is always impossible to predict the future of any one firm; executives and experts always anticipate these changes at the aggregate industry level. The current predicament of BlackBerry and to some extant Apple can be attributed to at least 3 reasons: Market Position, Open/Closed Systems, and Ecosystems & Network Effects. Finally, I will also provide a Historical Precedence.

Market Position
Firstly, there are only a few 100 million people on earth who are willing to pay $50-$75 per month who want access to their emails and news instantaneously anywhere and at any time. BlackBerry started out as a luxury item and continued to stay there without going down the pyramid; thus limiting itself to a specific market. Unfortunately, for BlackBerry two amazing competitors showed up on the horizon—Apple and Samsung—going after the same market. Palm fell victim to this and Apple will also if they don’t start going down the pyramid.

Closed and Open Systems
In the early stages of most industries, firms tend to be vertically integrated. Businesses have to provide complete solutions—hardware and software—to all the problems for its niche customer segments. So firms tend to develop both proprietary hardware and proprietary software that work in tandem, i.e. closed systems. However, as industries grow and become attractive, more competitors move in and one strategy for new entrants is to try to change the game by breaking ‘open’ the ‘closed’ systems. We have seen this happen repeatedly, e.g., Sony Betamax vs. JVC VHS, Apple vs. IBM PC, Microsoft NT vs. Linux. Closed systems are better for the user experience. However, Open systems are better for the industry players and thus innovation. BlackBerry and Apple are more closed as compared to Samsung and Google. Nokia used to be closed and only recently switched its Symbian system for Microsoft’s Windows Phone. The recent popularity and rise of the open system offerings has had a detrimental effect on both BlackBerry and Apple. The primary reason for the rise of the open systems is explained next.

Emergence of Ecosystems and Network Effects
One year after the launch of iPhone in 2007, Apple opened the App store. This ushered in the era of Apps and third-party content developers. Within three months, Google launched the open source Android operating system. Together, these two firms created an entire new industry of App developers for their smartphones. While BlackBerry, Nokia and Palm all followed them with their own app stores, all within the next nine months, all of their smartphones were still non-touch screen, outdated and industrial. As more and more of BlackBerry’s traditional customer base didn’t care so much about the high-security that BlackBerry claimed to offer them and switched to either Apple or Samsung devices, App developers had to choose where they should put their time and effort. As more and more app developers created content for Apple and Android operating systems, more and more customers flocked to devices offering the latest captivating apps – content and information. So, the game is not just about hardware and software, but the new battle is one of ecosystems – app developers, platform providers (Apple, Samsung) and social networks (customers).

Within two years Android overtook Symbian as the most widely used smartphone operating system. Palm was sold to HP and Motorola Mobility to Google. Today, BlackBerry is set to meet a similar fate. It shouldn’t be a surprise if Microsoft will buy either BlackBerry and/or Nokia. Because of network effects, it will be very difficult for more than 3 eco-systems to survive simultaneously.

Google seems to be doing much better in the last one year. Google or Apple? Who will be the reigning king for the next 5-years? Where is Samsung in this picture? This is where we need to take a look at history. Long history.

Historical Precedence
Information always follows Technology. Decades ago, Peter Drucker commented on the term “Information Technology.” He argued that in all of history “Technology” has always preceded “Information.” Let me clarify what he meant. When Gutenberg invented the press, in the early days of the print world, it was the machine manufacturers who made the most money in the value chain. As the machines became more ubiquitous it was the creators of content and publishers of information that became richer than the manufacturers of the hardware, i.e., the presses. Similarly, before Mergenthaler invented the Linotype machine in 1884, no newspaper had more than 8 pages. Typesetting was a time consuming and costly activity. However, with the advent of the 90-character key board Linotype, the media revolution was born and so too the newspaper and publishing magnates. Again, the ‘technology’ preceded the ‘information.’ During the PC-era, hardware firms Apple and IBM were the first money makers and they were followed by Microsoft (in terms of market valuation) and PC-mogul Bill Gates. During the WWW boom, for a brief period, Cisco was the most valuable firm on earth. But then came the web-tycoons that build their empires based on information and content—Amazon (books), Skype (voice), Apple (music), Netflix (movies) and Facebook (social media). So, the money in the value chain or in the industry first goes to the hardware or the technology firms and then it shifts to the software / information / content firms. Hence, Information Technology should actually be read as Technology Information. While very strong on the “Technology” side, Samsung is still far behind in the “Information” game.

A brief glimpse into the future
A similar battle is brewing in the TV industry. The recent battle between CBS and Time Warner should not be surprising as well. Content bundlers and distributors (cable companies) have had a monopolistic choke on the customer end. The rise of the new internet based content distributors – Netflix, Apple, Hulu, Roku, Amazon—is providing content creators other options to reach their end customers by by-passing the cable firms. Similar to millions who cut out landlines in the last decade, younger populations are by-passing expensive cable operators and customizing their own content on their computers and TVs. The cable companies, with their hardware (cables and set-top boxes) can be seen as the “technology” firms and the content creators as the “information” firms. The tide is shifting in this very traditional business model as well.

The June 11, 2013 Wall Street Tech section on the web read: “Apple’s streak of game-changing devices has stalled and the iPhone and iPad seem stale, compared with new offerings from Samsung Electronics and others. Software blunders, like Apple’s widely panned mapping app, have raised doubts about the company’s ability to build cutting-edge mobile services.”

Apple was again in the spotlight during its week-long Developers Conference. So far, announcements about its digital radio service and an overdue overhaul of iOS7 have received negative or at best neutral reactions from analysts and experts. While investors, analysts and gurus get all the attention, I would pay more attention to what the 6 million registered app developers are saying or not saying.

There is no doubt that Apple is playing catch-up to Pandora and Spotify in the radio/streaming space and upgrading its operating system is just a part of routine incremental innovation introductions. On the other hand, the announcement of the “all-day battery life” on the MacBook Air has not received much attention. It now boasts 5 hours more of battery life for the same price. Is it incremental innovation or radical innovation? Or is Apple over-shooting the needs of the consumers? Remember the dismal performance of Nokia’s 41-megapixel Lumina 1020 smartphone? The answer will be revealed in a few months.

In any case, the world seems to be screaming for an un-ending string of radical innovations from Apple. Radical innovations are about the “unknown” world – unproven technologies, unknown markets, untested business models. Unfortunately, history shows us that radical innovations are few, far in-between and highly risky. On the other-hand, incremental innovations are about the “known” world – existing technologies, existing products and existing business models. Incremental innovations tend to be quite predictable and firms keep working on them and introducing them at regular intervals. So, they tend to be quite boring for the general populace, investors and the hype-seeking media.

All great innovators—GE, P&G, 3M, Google, Apple, Samsung, Singapore Airlines—have to carefully manage their radical and incremental innovations. Incremental innovations tend to have a certain ritual, rhyme and rhythm. On the other hand, radical innovations don’t have time-tested formulas – its proportion in the innovation portfolio, the proportion of time and money set aside for it, and the timing of its introductions.

Unfortunately, pleasing an impatient, attention-deficit, constant high-excitement seeking consumers, investors and media is definitely very challenging. I guess we need some radical innovations in expectations management!

Cheers!
Jay

This blog is the translation of a recent article of mine that appreared in Estrategia, a leading Strategy magazine in Chile. You can get the original article from:

http://www.estrategia.cl/detalle_noticia.php?cod=72739

Stop the Nonsense! Innovation is a Discipline.

A recent article in the Wall Street Journal highlighted the problem we have today with innovation. Indeed, this once worthy term is being degraded by CEOs, consultants, marketers, and journalists for whom it is the buzzword d’jour. The term “innovation” has been deeply devalued—to the point of being a slogan or aspiration. Also, for all the use of the term, it is clear that firms are having lots of problems managing innovation. They’re spending heavily and complaining about how little they are getting back. Abuse of the term “innovation” is leading to dismal outcomes, cynicism, and wasted money. Studies show that despite huge sums spent on ideation software, stage-gate systems and consultants a majority of executives are dissatisfied with the results. Dissatisfaction among employees is even higher. The reasons are many.

Firstly, most people today still associate innovation with R&D and invention. For example, in a lot of Spanish speaking countries, the governments, large enterprises and executives commonly use the expression I+D+i. In fact some governments also have special tax incentives on R&D spending; but no rewards for spending on innovations. If we really read the expression I+D+i carefully, it would mean “innovation” is less important than R&D. This is wrong.

Inventions and patents that are not commercialized have very little value. Since 2005, consulting firms—Booz Allen, McKinsey, BCG, CapGemini—have been publishing yearly data about innovation practices within large global firms. Data from Booz Allen shows us that there is no correlation between R&D spending and financial performance among the top 1000 global firms. Based on this they created two categories of firms – innovators and spenders. Innovators spend much less money in R&D as compared to their peers and have a better financial performance while the ‘spenders’ spend a lot of money in R&D but have poorer financial performance.

Innovation is more than R&D. Innovation encompasses R&D, products, processes, services, supply chain, marketing, business models and others. These are just opportunities for innovation activities. In fact, Innovation is a discipline. It is a discipline that can managed and mastered like other management disciplines.

Many disciplines operate in the world of business, and their evolutions provide insights into the development of innovation as a body of knowledge and field of practice. Marketing, for example, has a conceptual framework (the “4Ps”) and a unique vocabulary. It has developed practical methods (e.g., segmentation) and tools (e.g., conjoint analysis) that practitioners master through formal study. Subfields of marketing such as advertising and consumer behavior have broadened the discipline. Academic departments have formed to increase the body of marketing knowledge and to pass it on to others. Journals, professional associations, and conferences dedicated to marketing have emerged over the years.

We have witnessed a similar evolution with the quality movement. Corporations that took quality seriously made it part of their cultures—embedding the “discipline” in their thinking, planning, and behaving. Today, quality is no longer an empty buzzword or organizational aspiration, but a solid and respected discipline that produces measurable benefits for companies and their customers.

Like other disciplines, innovation can also be mastered. The good news is that the road to mastery in any discipline is the same:

 1.     Mastery is the result of leadership desire, choice and commitment.

 2.     Mastery requires years of effort.

 3.     Mastery requires a cadre of experts to lead the way.

 4.     Mastery requires a broad-based understanding of principles and methods of the discipline among employees.

Like marketing and quality, innovation has been following an evolutionary path. As a discipline, it is perhaps midway along its evolution path—where the quality movement was twenty or so years ago.

Disciplined corporate innovative efforts can be traced back to Thomas Edison’s first “invention factory” at Menlo Park, New Jersey. Bell Laboratory and the R&D centers of, DuPont, Etc were its offspring. By the 1980s other tools of the innovator’s craft were being adopted by new product developers. It wasn’t until the 1990s, however, that academics began publishing thoughtful and practical books that explained innovation as more than R&D or invention, but as a process, and told executives how to harness it in service of corporate strategy. The explosive emergence of eBay, Google, Facebook, and Amazon made it clear that innovation is not simply about physical products and technologies, but extends to services and business models. So, today the word innovation is sizzling hot and on every executive’s lips. Academics are studying and writing about it, and today’s employees have some useful principles, methods and tools to work with.

Despite the availability of principles, methods and tool, several obstacles impede progress in handling innovation as a discipline. The biggest obstacle of them all is the failure of most executives to recognize and support the “soft” side of innovation. Executives are investing substantial time, money and energy on resources, processes, and metrics but most ignore the values, behaviors and workplace climate—aspects of culture—that make those investments pay off. Several studies support the conclusion that enterprise culture is the primary driver of innovation. The fact that successful innovation is one part principles, methods and tools, and another part human creativity and insight is the greatest impediment to innovation in large companies. To capture the potential of innovation, leaders must bring these two very different parts together.

Below are some questions to think about:

Is Innovation mostly ad-hoc or is it treated as a business discipline within your firm? If innovation is not disciplined, how can you educate your executives about this? Does your firm’s culture support innovation? What are your specific challenges?

The Culture of Innovation

The Culture of Innovation

Hope you all had a great summer (in the northern hemisphere) and peaceful winter down below! Can’t believe that it is already October!

Before I took off for summer, I was hoping to finish off a task I had started in March – summarizing and giving you snippets from my recent book in Spanish. Unfortunately, that didn’t happen. Anyway, for first time readers, the book is titled (translated from Spanish), “Innovation 2.0: Why do we forget about the people when we talk about innovation? A practical way to create a culture of innovation.” Available from: (U.S. Amazon website, Spain Amazon website, Profit Editorial website, In e-book format from todoebook.com).

To help first time readers navigate and regular readers recall what we have covered thus far, I will quickly summarize my previous 5 blogs.

 March 2012 blog: My New Book

Amidst the last decade and a half of constant turmoil—dot-com boom and bust, fraud infested financial firms, and colluding corrupt governments—most executives are hoping that “innovation” will help their firms survive the tsunamis, navigate this uncertainty and prevail. In that quest, a lot of firms are overusing, misusing and abusing the “discipline of innovation.” In a sea of constant change, a firm’s culture has a much better ability to give the firm a somewhat sustainable advantage than just technologies, products, processes, markets etc. However, both terms—innovation and culture—are highly fuzzy and highly misunderstood concepts. So, this book was written to help executives start the journey to create a “culture of innovation” within their firms.

 April 2012 blog: The Nonsense Surrounding Innovation

 This blog highlighted the non-sense surrounding innovation – the rampant abuse, misuse, overuse and the misconception of innovation.

 May 2012 blog: Innovation is a Discipline

Here, I covered the fact that innovation is not a tool, it is not invention and it is not luck. “Innovation is a Discipline” – a body of knowledge; a field of study. Innovation, like all disciplines, can be: (1) taught, (2) learnt, (3) practiced and (4) mastered.

 June 2012 blog: Developing Innovation Capabilities: The Journey

Fortunately, the journey to master any discipline is the same: It starts with existing KNOWLEDGE, then putting that knowledge into PRACTICE and then through rigor and grit one masters a discipline. So, you master a DISCIPLINE (the field) through DISCIPLINE (desire and determination). Specifically, this blog talked about the Lingua Franca of the discipline.

July 2012 blog: The Practice of Innovation

In this blog, I covered several key concepts and tools of the practice of innovation. Specifically, the following were discussed: (1) incremental, platform, and radical innovation; (2) risk vs. uncertainty vs. ambiguity; (3) analytical vs. emergent strategies; and (4) predictive vs. creative logic.

In this August2012 blog, the focus is “The Culture of Innovation.”

In the June blog, I talked about all innovations as being an outcome of culture and that a firm’s true goal, if it so desires, should be to create a “culture of innovation.” I concluded the July blog by ascertaining that the “The PRACTICE OF INNOVATION is the deliberate, relentless, and unending pursuit of revealing the UNKNOWN, redefining the KNOWN and renewing the WORN.” In doing so, there is a lot of failure, experimentation and emergent strategies embedded in the practice of innovation. Unfortunately, most firms do not accommodate such practices. Hence, culture becomes a key goal for firms that wish to master innovation.

Like all disciplines, the field of innovation has evolved over decades. In the beginning of the last century, invention was synonymous with innovation. It meant R&D, science and technology. When pure inventions and patents stopped delivering results, it paved the way for new thinking – linking new product development (NPD) activities to commercialization. Later, the quality movement was central in making process innovation popular. As manufacturing activities got commoditized during the 1980s and 1990s, the focus shifted towards bundling products with services and hence service innovations. At the dawn of the new century and dot-com boom era, business model innovation became a focal point for enterprises. Again, recently, executives seem to be changing their attention once again.

A 2007 McKinsey innovation report, based on a survey of nearly 1400 executives from around the world showed that the executives unanimously agreed (94%) that people and corporate culture were the most important drivers of innovation. In another major study of 759 firms across 17 major economies, “Corporate Culture” was found to be the primary driver of radical innovation (Radical Innovation Across Nations: The Preeminence of Corporate Culture, Journal of Marketing, Jan. 2009). Booz Allen has been surveying the Global 1000 firms and reporting on them since 2005. In their latest report (The Global Innovation 1000, Why Culture is Key, Issue 65, Winter 2011), they concluded:  

“The elements that make up a truly innovative company are many: a focused innovation strategy, a winning overall business strategy, deep customer insight, great talent, and the right set of capabilities to achieve successful execution. More important than any of the individual elements, however, is the role played by corporate culture — the organization’s self-sustaining patterns of behaving, feeling, thinking, and believing — in tying them all together.” 

Unfortunately, enterprise culture is a slippery concept. Scholars define it as the bundle of attitudes, experiences, values, norms, assumptions and beliefs embraced by managers and employees; these, in turn, guide behavior. Regrettably, these elements of the definition of culture are equally slippery, with the result that any executive who wants to create a culture of innovation will have no way to measure the current culture; and without measurement, he or she will find it difficult, if not impossible, to identify a clear point at which to intervene and create positive change. 

Recognizing this problem, in this book, I offer a model for capturing an innovative culture. I scoured the fields of organizational dynamics, leadership, behavioral science, corporate entrepreneurship and innovation to find theoretical frameworks and models that described organizational culture and culture of innovation. Specifically, I looked for instruments and assessment tools that were actionable; a primary need for all executives hoping to bring about change. In doing so, I found extensive research and models from academia, consulting firms and enterprises themselves, spanning over 30 years.  

In the book I propose a culture of innovation model with the following six building blocks:

 

The basic framework was heavily influenced by the works of Harvard’s Clayton Christensen and Ed Schein (Professor Emeritus at MIT).

 Values —What do we stand for in terms of innovation? We are not talking about the CEOs here; CEOs come and go. What will we fight for? What does the firm fundamentally believe to be true? What are our addictions? They could range from openness, sharing, teamwork, risk-taking, adore mavericks, and rewarding failure. Values are also a firm’s moral compass. Finally, Values are not what we speak—in our speeches and annual reports, but Values are how a firm spends its money and how and where the executives spend their time. We can see examples of this at companies like J&J, Southwest Airlines, Wal-Mart, IDEO.

Resources —How we support our innovation efforts? Who are the champions of innovation? Who are the experts of innovation that can help the firm navigate the journey? Who is the talent: creators, inventors, scientists, ideators and transformers? Do we provide the talent the Time, Space and Money? Time is needed to learn, experiment and pursue wild things. Space is a place to work and play with the ideas and opportunities and Money is needed to dabble in opportunities—spend a little to learn a lot. E.g., GE, IBM, P&G, 3M.

Processes —How do we get innovations done? Creating a funnel to routinely capture ideas; routinely sift ideas from opportunities; and routinely separate the weak from strong opportunities. When opportunities are found, start several small experiments, prototype rapidly, fail fast and finally, move to scale-up quickly when a golden jewel is found. E.g., P&G, IBM, Toyota, IDEO.

Behaviors — How do we think, approach and act in order to foster innovation? Everyone’s—executives and employees. Innovation Behaviors include being opportunistic, flexible, adaptive, collaborative, resilient, taking courageous decisions under uncertainty and dealing with ambiguity. One can learn, practice and coach these behaviors and best of all – no budget needed and no permission required. E.g., IDEO, Google, 3M, Wal-Mart.

Success —How do we measure our innovation output? What does success mean inside our firm? How is success measured—process and outcome? How are we rewarded? Do we tolerate mistakes? Is learning, experimentation, failure and feedback rewarded? Measures of success determine our behaviors and processes. When we feel successful, our environment, values, processes and behaviors get reinforced. E.g., Southwest Airlines, P&G, Google, GE.

Climate —What is it like to work in this firm? Is the company climate favorable to innovation? It is vibrant, and one that cultivates passion, stimulates and challenges people to take chances, fosters learning and reflection and doesn’t squash independent thinking. E.g., Google, 3M, Southwest, J&J.

Repeated success leads to further reinforcement of the building blocks and over time all these blocks get ossified and that is CULTURE! Hence, Climate and Success are outcomes/outputs. Values, Behaviors, Resources and Processes are inputs. Values, Behaviors and Climate are more right-brain oriented and Resources, Processes and Success metrics are more left-brain oriented. Most firms tend to do well on the left-brain stuff that is more tangible and easy to buy and implement. Universally most firms struggle on the “soft” right-brain stuff.

This book concludes by giving the reader how to take some concrete steps to embark on “The Journey”: Think Big, Start Small, Start Several, Scale Slowly, focus on the “soft” side first, etc.

Enjoy the Journey!

Jay 

The Practice of Innovation

 Happy Summer to those in the Northern Hemisphere and Happy Winter on the other side! Oh well, it doesn’t change much in the tropics.

 This blog is the fifth in a series of snippets from my recent book in Spanish (that translates as): “Innovation 2.0: Why do we forget about the people when we talk about innovation? A practical way to create a culture of innovation.” Available from: (U.S. Amazon website, Spain Amazon website, Profit Editorial website, In e-book format from todoebook.com).

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In the April 2012 blog, I talked about the non-sense surrounding innovation – the rampant abuse, misuse and overuse of the term. I explained several reasons for this ubiquitous problem in my May 2012 blog. In the same blog, I talked about the fact that innovation is not a tool, it is not invention and it is not luck. “Innovation is a Discipline” – a body of knowledge; a field of study. Innovation, like all disciplines, can be: (1) taught, (2) learnt, (3) practiced and (4) mastered. Fortunately, the journey to master any discipline is the same: It starts with existing KNOWLEDGE, then putting that knowledge into PRACTICE and then through rigor and grit one masters a discipline. So, you master a DISCIPLINE (the field) through DISCIPLINE (desire and determination). In the June 2012 blog, I argued that all innovations are an outcome of culture and that a firm’s true goal, if it so desires, should be to create a “culture of innovation.” All innovation happens in a community and the fundamental basis of all cultures / communities is “language.” So, the last blog was devoted to creating a community within the firm that was conversant with the KNOWLEDGE, i.e., Lingua Franca – concepts, methods and tools – of innovation.

In this blog, I will talk about the PRACTICE OF INNOVATION and its role in a firm’s journey to create a culture of innovation.

 There are essentially 2 ways for firms to grow – buy growth (inorganic) or create growth (organic). Organic growth can happen in two ways – copy or innovate. Hence, the practice of innovation is the relentless pursuit of identifying opportunities, shaping opportunities and capturing opportunities. Unfortunately, at the center of this process is a “funnel” full of failure. Therein lays the management challenge.

 Firstly, I need to clarify what innovation is not. If the opportunity does not change the competitive dynamics of the industry over a period of time, then it is not an innovation. If the opportunity is new to the firm but not new to the industry, then it is not an innovation. It is just copying to catch up.

 Firms tend to explore for opportunities in three spaces: incremental, platform and radical innovations. Examples of incremental innovations are: Intel going from 90 nanometer to 45 nanometer technology; car manufacturers improving the gas mileage using existing technologies; a new version of Microsoft Windows etc. In incremental innovations, firms are working to continuously improving upon existing technologies, existing markets, and existing ecosystems. Here, they are working with mostly “known” variables. Further, there is data from history as to how these variables might behave.

 It doesn’t mean that there are no unknown variables in incremental innovation. For instance, the Vista version of Windows and the “New Coke” were very poorly received by the existing customers and they were either quickly replaced with a better version or pulled from the market. Hence, all innovations—incremental, platform and radical—have some known variables and some unknown variables. Incremental innovations tend to have more of the known variables and fewer of the unknown variables.

 Platform Innovations: WLGore’s polymer expanded polytetrafluoroethylene (ePTFE) was the first used in insulating industrial electric cables. Later it was transformed into Gore-Tex, the waterproof and breathable fabric that made the company famous. Using their patents and deep knowledge of ePTFE Gore has created 5 platforms – films, fibers, tubes, tapes and sheets. Via these platforms, this polymer has found its way into fuel cells (films), Glide dental floss (fibers), medical vascular graft (tubes), cable assemblies (tapes) and medical patches (sheets). While there are several competing operating systems, few have the platform characteristics of the Darwin kernel of Apple’s OSX operating system. A kernel connects the application software to the hardware and is the main component of all operating systems. The Darwin kernel cuts across telecom (iOS for cell phones), internet (OSX for PCs), media (iPad for books) and entertainment (iTV for movies and videos) applications. Similarly, P&G’s focus on connecting sciences to create domain expertise has led to dozens of products. Candle making provided the base technology for soap making. Soap making led to expertise in fats and oils (Crisco vegetable oil) and surfactants. Crushing seeds to make oil led to expertise in plant fibers (diapers, feminine hygiene, paper towels). Surfactant technology led to expertise in hard water and calcium (tooth paste and osteoporosis).

 It is well known that platform innovations are no trivial matter. The technological unknowns alone pose tremendous challenges, notwithstanding market, financial, operational, regulatory and other uncertainties. Platform innovations do work off of and exploit existing capabilities, adjacencies, technologies, markets, products, services and ecosystems. However, the ratio of unknown to known variables increases as compared to incremental innovations.

 When it comes to introducing radical innovations, as one can expect, the number of unknown variables vastly outnumber the known variables. Radical innovation is primarily about the unknown: unknown markets, unproven technologies, and untested business models. Some examples of radical innovations include the Cordis stents, Raytheon’s microwave oven, Amazon’s selling books on the internet, Apple iPhone, Grameen Bank’s microfinance and Skype.

Let us look at an example to understand the nuances involved in innovation projects. Take the case of a large U.S. multi-site, nation-wide, retailer of groceries and home products. Let us call this disguised enterprise Big Retail Chain (BRC). Until recently, BRC’s point-of-sale (POS) system was nearly 20 years old. Meanwhile, some of its competitors had already successfully installed a good number of self-check-out kiosks and their ERP and CRM systems were tightly integrated to the POS with more sophisticated features for data analytics. In updating and upgrading its POS system, BRC’s executives had three main objectives: (1) retain and improve upon some of the capabilities that BRC had built around its unique and existing customer segments, (2) catch up with its main competitors by creating a half-dozen self-check-out kiosks at each retail outlet and also copy some of the competitors POS’ features and functionality and (3) finally, leap-frog its competitors and be a pioneer in introducing customer hand-held scanners for fast and easy self-check-out. For this major project, BRC hired a very reputable, global IT firm to help them design and deliver the new POS system. 2 years into the project and $50 million later the first version of the new POS system had failed to deliver upon all three objectives. Some of the existing capabilities had been lost, self-check-out kiosks and competitors’ features were not quite well replicated and the truly innovative hand-held scanner was full of bugs and the design totally unintuitive.

 This example has some form of incremental, platform and radical innovations. Also, it highlights the differences between Risk, Uncertainty & Ambiguity.

 Risk is about known variables and with historical data about their distributions. Enterprises minimize and manage risk in its innovation projects by doing analysis before taking action. The future is approached by performing an environmental scanning (SWOT, STEP, Value Chain Analysis) and followed by the setting of a project plant to execute strategy. Trend lines are predicted based on IRRs and WACC or projected cost benefits; KPIs and milestones are set and budgets are allocated. When project performance does not meet projections, money and energy is spent to get the project back on to the predicted trend line. Unfortunately, heads roll when the predicted future fails to materialize after a couple of tries.

 This approach to project management makes a bunch of assumptions: (1) all process and outcome variables are known and can be accounted for ex-ante, (2) existing data from past projects can be used to predict the process and outcome of this project, (3) some variation to projections can be accommodated along the way using managerial judgment, and (4) failure is not an option.

 This concept of going into the future is called “predictive logic” and the method is called “analytical strategies.”

 Unfortunately, all innovation projects have a bunch of unknowns. Specifically, there are two types of unknowns – known unknowns and unknown unknowns. Uncertainty is about known unknowns. In these situations, you know which variables may impact the process and outcome of the project but there is no data from the past to assign a probabilistic numbers. Ambiguity is a second order uncertainty. One cannot surmise as to what variables may be lurking in the background. They only appear once the project is underway. Unfortunately, analytical strategies do not account for these unknowns ex-ante.

 Entrepreneurs and innovators approach the future very differently when they know that there are many unknown variables in the environment. They believe that predictions and trends based on analyzing the wrong variables will turn out to be fallacious or misleading. So, when dealing with “known unknowns” and “unknown unknowns,” they do not rely on analysis and analytical models to take action. Rather, they first take action to create the data that does not exist. They tend to start small with the resources they have on hand. They may even start several projects simultaneously. They prototype rapidly to test what is real. They try to establish proof of concept via quick feedback loops between the voice of demand, voice of customer, voice of technology and voice of supply. They minimize losses by failing fast, failing cheap and learning quick. They uncover the unknown variables as the project proceeds. They rapidly change directions when reality does not match assumptions. They acquire resources and assets to scale only when some proof of concept is established and success materializes.

This concept is called “creative logic” and the method is called “emergent strategy.”

 Those in software development recognize these two very different approaches to managing projects as Waterfall (predictive) and Agile (emergent) strategies.

 Unfortunately, very few people are well versed in the creative logic concept and emergent strategies. Most enterprises overwhelmingly tend to adopt analytical strategies over emergent strategies when it comes to managing their innovation projects or for that matter any major change initiative.

 I am not suggesting that one approach is good and the other is bad. The right question to ask is: when do you use analytical strategies and when do you use emergent strategies. The analytical strategies work great when we know the variables in our environment and we have historical data that can guide us to take action. It is still a very valid approach when the projects are predominantly incremental innovations, e.g., version 2 or version 3 of any software. Incremental innovations in general follow the principles and methods from “Kaizen,” i.e., continuous improvement. So, a majority of the techniques of quality, lean, TQM and 6-sigma have been adopted into incremental innovation.

 However, using these methods and tools when there are a lot of unknowns (as in most platform or radical innovation projects) will result in these projects pursuing the wrong strategies for longer periods of time and wasted resources. The only way to uncover the “unknown” is through a different set of concepts and tools, i.e., continuous experimentation. Continuous experimentation is the core methodology of emergent strategies. Unfortunately, “failure” is also at the heart of experimentation.

 Continuous experimentation is eschewed in most firms, except in some very limited areas of the enterprise, i.e., R&D. What happens in most enterprises is closer to what I call the “Big Bang” approach to managing innovation projects and change management initiatives. BHAGs are announced with much fanfare. Lots of analysis is performed and outcomes are predicted. Leaders and team-members are assigned to these projects—most of them reluctantly—with specific KPIs. They are then asked to march off into the future to realize and deliver upon the predictions. Religion takes over when people are asked to “buy-in” to the predicted future or “get-out” of the way. When the predicted future does not materialize and the firm loses millions, a few underlings are scapegoated and all issues are “pushed under the rug.” It is because of such repeated offenses in the past—across several firms in their careers—that executives are very reluctant to embark on any innovation activities or for that matter start any major change initiatives.

 Where there is uncertainty and/or ambiguity, predictive “Big Bang” approaches don’t work. Emergent strategies fare much better: Think big. Start small. Start several projects. Prototype rapidly. Fail smart – cheap and quick. Spend a little to learn a lot. Uncover unknown variables. Change strategies quickly to respond to new data. Pour resources to scale when there is a positive proof of concept. Celebrate Success and Celebrate Failure.

 Unfortunately, emergent strategies are not accommodated in most enterprise cultures. It takes a special climate where one can fearlessly experiment and fail without repercussions. It takes a special culture that values curiosity to pursue the unknown, stimulates a hunger to create and cultivates the courage to fail and learn. Such cultures are few and far in-between. So, the real purpose of the deliberate practice of innovation is to ultimately create a culture of innovation that accommodates both predictive and emergent strategies for growth.

 In summary, the practice of innovation falls on a spectrum of “continuous improvement” at one end and “continuous experimentation” on the other end, i.e., incremental to radical. Over the last 25 years most firms around the world have learned the concepts of Kaizen and continuous improvement. However, very few firms have mastered the continuous experimentation philosophy.

 What type of innovation to practice – incremental or radical or both – is a choice. No one is forcing a firm to do both, especially its competitors. In almost all situations, incremental is necessary, but not sufficient.

 In my next blog, in August, I will talk about the culture of innovation. In the meantime, I would love to hear how your firms are approaching the practice of innovation and its innovation initiatives.

 Cheers!

 Jay

 “The PRACTICE OF INNOVATION is the deliberate, relentless, and unending pursuit of revealing the UNKNOWN, redefining the KNOWN and renewing the WORN.”

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