When 2016 came to a close, it may go down in history as a political turning point. Contentious elections and referendums in Europe and America have provided a series of unexpected shocks. One constant theme in all these major political events has been the debate around immigration and cultural diversity. This change in political attitudes towards cultural diversity may be putting companies in a bit of bind. While multicultural living can be challenging for communities, cultural diversity can also serve as a boost to creativity and innovation. In a fast changing world, where the ability to innovate is now recognized as the main competitive edge, companies must seek to create more diverse teams. So for companies, taking an anti-diversity posture may actually hurt their long-term profitability.
But is there really evidence that multicultural experiences enhance creativity? And if they do, how does it happen? This article focuses on these two questions.
Bell Labs is historically one of the most productive R&D labs in history. A large number of the technologies we use today were invented there. Bell Labs scientists invented the facsimile machine, the first long-distance television transmission, the first binary digital computer, the transistor, the laser, cellular technology, the UNIX operating system and the first fiber-optic technologies. Fourteen scientists from Bell Labs have won Nobel Prizes, and the lab has even won Grammy and Emmy Awards. How did Bell Labs manage such feats of innovation? The answer lies in how the lab organized work among its scientists and inventors. At its Murray Hill campus, the lab was designed to ensure that people of diverse knowledge and expertise worked together, in close proximity where they could have plenty of meetings and make serendipitous connections. Theoretical science was combined with applied engineering to produce wonderful inventions.
In a previous post, I wrote about why corporate leaders may be right to shut down non-performing innovation labs. That article focused on what innovation managers get wrong when they engage in innovation theatre rather than real innovation. However, the buck for innovation success stops at the desks of the CEO and his executive team. Although there may be real challenges with poorly run labs, there are innovation managers who get it and try to do the right things. Their efforts are often frustrated by how their company makes decisions on strategy and innovation. Most of these talented innovators will quit in frustration; taking their talents to competitors or starting their own company. This article describes 10 things that companies should stop doing that may drive their innovators to quit.
In May 2017, I will be speaking at the Intrapreneurship Conference in Stockholm. I will be giving a whiteboard session on innovation accounting. In preparation, I sat down with Hans Balmaekers to discuss how innovation accounting works in practice for companies. Hope you enjoy the interview below. Don’t forget to register for the conference here. You can use the discount code intracnf-tendayi for 15% off!
Innovation labs are all the rage these days. Most companies have one, are thinking about creating one or have had employees pushing management to start one. There is also another trend that is starting to happen more and more; and this one is to much less media fanfare. Several companies are quietly shutting down their innovation labs. Over the last year, I have spoken to a couple of innovation managers who were angry that their company had decided to close down the innovation labs they were running. These managers clearly felt that the leadership in their companies were MBA types that “don’t get innovation.” But when I have drilled down into the work the so-called innovation labs were actually doing day-to-day, I have discovered that it is actually the innovation managers that “don’t get innovation”. It turns out your boss was right to shut down your lab.
After 88 years on U.K.’s high streets, British Home Stores (BHS) shut their doors for the last time on Sunday, 28 August, 2016. This was a sad occasion, especially for former employees, who are still not sure how a $747 million pensions black hole will be resolved. As the administrators continue to sell store fixtures and fittings to recoup some money for creditors, a question that has arisen among commentators is why BHS failed. The story of corporations failing to adapt and then collapsing is something that is now repeated quite often in business news cycles. It appears that an extended period of success can become an achilles for innovation in large companies. In a candid interview on Nokia with INSEAD, Olli-Pekka Kallasvuo, the former CEO describes how “it is sometimes difficult in a big successful organization to have the sense of urgency and hunger.”
It is undeniable that the world around us is changing. Technology and software have transformed large parts of business; and continues to do so in more and more dramatic ways. Corporate leadership would have to be in a special kind of denial to not see how these changes in technology and economics are impacting their businesses. There is no longer the option to keep our heads in the sand. Companies have to respond. What is more challenging now is deciding exactly what companies should do. And the challenge of how to respond to change is not new. As long ago as 1942, Joseph Schumpeter wrote about Creative Destruction as a process that refreshes economies by injecting new blood in the form of innovative new technologies and companies. But Schumpeter noted that even in the process of creative destruction there is always a chance for companies that would otherwise perish to weather the storm and live on “…vigorously and usefully”. In other words, death is not inevitable. Companies that are able to respond to change, can survive and thrive.
Over the last few years I have been traveling the world advising large companies on how to implement lean innovation methods within their companies. This work has led me to run innovation workshops, design innovation frameworks, work with management team on strategy and coach product teams in great organizations like Pearson, Airbus, Josera, Standard Bank and The British Museum. I love my work, but almost inevitably in every company I have worked with, discussions will at some point get heated. As our conversations get to boiling point someone in the meeting will inevitably say something like:
- “What we do here is not academic. This is a real business, not theory”.
- “We need practical people in this business, not academics like you. You are too academic to succeed in business”
Over the last three years I have part of a great team working to bring lean innovation principles into Pearson, the world’s largest global education company with over 35 ooo employees. We have developed the Lean Product Lifecycle, which is Pearson’s framework for investment management and product development best practice. At a recent team off-site in London, our boss Sonja Kresojevic asked us to think about why we do the work we do. Inspired by Simon Sinek’s great TED talk on this topic, Sonja wanted us to think more deeply about the real value that underpins our work. Why do we work on lean innovation? Why is it important to Pearson and other companies around the world? This is something I had thought about often. Why do lean startup? Why build minimum viable products? Why does business model design matter? Why experiment and iterate? Do we do these things for their own sake? Cool as lean innovation might be, it is also hard grinding work. So coolness is not enough for me. There has to be a deeper underlying reason.
In my previous post, I wrote about the false choices that innovators face. These choices seem to present teams with the option of using business plans to manage innovation or just doing it without a plan, and basing decisions on vision. Often customers are excluded from the process in both cases. And this ultimately leads to innovators failing to make stuff people want. At the end of the post, I also wrote about a third way which is based on the toolbox that lean startup methods bring to the table. But to fully understand how the lean startup toolbox can help, we need a clear definition of what innovation really is. Without a shared view of what constitutes successful innovation, management and their teams will often speak at cross-purposes and conduct their work with different expectations. The goal of this post is to help provide some of this alignment.
Innovation is hard work. Creating great products that succeed on the market is a really difficult endeavor. You can ask any startup founder. But my experience so far has taught me that innovation in large successful companies is even harder work. Innovators working in these companies are often faced with a lack of urgency that views innovation as a nice to have, rather than a mission critical activity. When the times are good, innovation is a waste of time. When the company is under market pressure their first instinct is to engage in cost cutting activities. It is true that cost cutting can return a company to profitability, but it will not create new revenues. In addition to the above cultural challenges, innovators have also been presented with false choices on how to get innovation funded or how to manage the innovation process. The choice that innovators face is between two options that are equally as bad as each other. This post is about how those choices present a false narrative of what innovation really is. In a follow-up post, I will then present a definition of innovation that is based on lean startup principles
In a previous post on this topic, I argued that large companies are not startups, nor should they strive to be. My argument was based on the reality that, unlike startups, large companies tend to have products and services that are already successful in the marketplace. As Steve Blank puts it, the distinction between startups and large companies is that startups are still searching for a profitable business model, whereas large companies are mostly executing on an already successful business model.People who tell large companies to act like startups are giving them the wrong advice. Instead, the advice should be that large companies should own innovation ecosystems that contain core products as well as startup type products and services. This is a more nuanced approach that recognizes the unique situation that most large companies are in.
When running experiments on your business model it is important to identify the assumptions you want to test. However, most assumptions are vague and nonspecific. Such assumptions are not hypotheses until you set minimum success/fail criteria. The setting of minimum criteria is what turns an assumption statement into a falsifiable hypothesis. Hypotheses are specific and provide a basis upon which to decide whether or not the data supports our assumptions. Tristan Kromer has written a great post on this topic which I highly recommend. Once the need for setting minimum success/fail criteria is understood, the next question is often about how to do it. I have found three methods that work which I will now describe below.
This question is of great concern to a lot of managers. A few of them have been burnt by innovation teams who convinced them that there was no need for business plans. These innovation teams then got investment; bought foosball tables, post-it notes and bean bags; but produced not a single successful product. So now, these managers want a method that allows them to have some control over their innovation process and business planning is the only way they know how. Even though they think so, business planning will not give them the control they need. They will just be creating a framework for getting lied to. The fabrications in business plans hardly ever come true, especially for innovative products. There is a third way. When most people see business plans getting criticized, they assume that innovation enthusiasts think that innovation should not be managed. It is creativity after all. This is wrong. Innovation is NOT just creativity. Innovation is management.
This is a follow-up on my last post on business plans which argued that most large companies have processes designed to deny investment in new product ideas, if these ideas are proposed without business plans. My argument was that these processes hinder innovation, even as the company is training its employees to become more agile and use lean startup methods. This raises two important questions:
- What is wrong with business plans anyway? Large companies have used business plans successfully for decades. Why should they change now?
- If we stop using business plans, whatever shall we do? How will a company manage its investments in innovation?
The Fallacy of Planning (Part One) :- You Have NO Business Plan - How Could We Possibly Invest In Your Idea?
Steve Blank likes to joke that the two groups of people that require five year plans are Venture Capitalists and the Soviet Union. I would like to add a third group to that list, large successful companies. In order to get funding within a large corporation for any new idea you have to complete a detailed business case with three to five year projections. Employees are told that management needs and wants to know upfront whether the investment is worth making in terms of ROI, IRR, ARR and Payback Period. In other words, management wants to know on day one that the company will make a lot of money on its investment in a new product idea. The problem is, unless they have a crystal ball, there is no way of knowing on day one how a truly new idea will do in the market. This may be possible for an established product with a trading history, but it is not possible for new ideas.
Nor should they strive to be. In fact, most startups want to become successful companies. It might be cool to be a founder, but very few people want to live in that trough of misery forever. The Lean Startup movement has been great for startup ecosystems. It has resulted in some of the best thinking in a century around how you develop and launch new businesses. And now everybody wants to ‘act like a startup’. But lets not forget what motivated this movement in the first place; the high failure rates of startups.
This post is a brief follow-on to a great post by Tristan Kromer in which he describes what he calls the Lean Waterfall. In the lean waterfall, large organizations still maintain their silos (e.g. design, engineering and marketing). Within each silo, they practice agile and lean. However, between the silos there are still handoffs and large specification documents. As such, in the end what you have is an organization that looks like the graph below; with each departmental silo claiming to be lean, but at the super-ordinate level the organization is still functioning as a waterfall.
The pace of change in the current business environment is staggering. It has become difficult for monolithic large organizations to keep pace with this change. At the same time, it appears that quick and nimble startups are emerging with breakthrough products, services backed by equally interesting business models. The quick emergence of a fast moving startup can catch a sleepy large organization, and quickly put it out of business. Blockbuster Inc. is a good case to illustrate this point.
At Leancamp Stuttgart, we had a number of interesting sessions. One session in particular focused on corporate accelerators as a means to help large enterprises develop innovative new products. A corporate accelerator would be similar to other accelerator programmes such as Y-Combinatorand Tech Stars. The difference would be that these programmes are run for internal innovation teams working on products or services, rather than standalone startup companies.
Since publishing my last essay critiquing the representation of startups and innovation as an experiment, I have been racking my brain thinking of what the equivalent of innovation within the sciences might be. This representation would have to be large enough in scope and impact to represent the unique contribution that a truly successful innovation makes to the lives of people and society in general.
The concept of the minimum viable product is now part of the popular lexicon within the lean startup movement. As with most terms that become over-used most people still misunderstand what an MVP really is. Since most people assume “lean” means cheap, they also assume the MVP means “crappy version of future product”. However, lean startup has nothing to do with being cheap. As with Lean Manufacturing the focus is on reducing all activities that don’t add value to customers. By that logic, the goal of a startup is to maximise learning by discovering what customers find valuable and a sustainably profitable way for the company to deliver that value to customers.
Various critiques of the Lean Startup method have been published in various outlets over the past few months. What is interesting is that most of the criticism actually results either from not understanding the approach or from examples of startups that are implementing Lean Startup the wrong way.
In Running Lean, which is a great book that I use in my own work, Ash Maurya defines an experiment as one full circle through the build-measure-learn loop. This is scientifically not correct. I think a successful circle through the build-measure-learn loop is better conceptualised as validated learning. This is because you can go through the build-measure-learn loop several times, all the way to successfully achieving product-market fit without ever running a single experiment. However, you will run successful studies and you will learn a tonne about your customers’ problems and your proposed solution.
Alex Osterwalder’s business model canvas is a powerful tool. Its power has been demonstrated in a variety of contexts including large organizations and charities working in Africa (e.g. BalloonKenya). The value of business models in general cannot be denied. Business models are important as way of describing how an organization creates, delivers and captures value. However, given what we know about the complexity of business in the real world, is the business model canvas too simplistic?
In a recent paper, Frankish and colleagues reported research showing that entrepreneurs do not really learn, they just claim they do. They analysed data from 6854 firms and found no connection between previous business ownership and likelihood of future success in a new venture. People who have previously owned a business had the same failure rates as people who are just starting out. Frankish et al. attribute this finding to the strong role played by chance in entrepreneurial success (i.e. you can't really learn to play the lottery).
"Scratch your own itch" is advice that you hear a lot in startup circles. According to this advise, when deciding what product to build you should build something that solves your own problems and worry about customers later. This view was made highly popular by the folks at 37Signals. However, this is a good example of entrepreneurs giving people advice on the basis of what worked for them. "Scratching your own itch" is not really a repeatable formula for startup success. If there are people who have succeed using this formula its probably mostly based on luck. Below are five reasons why you can build a product that scratches your own itch and still fail:
If you listen carefully you can hear it. The sound of marketers and product developers bemoaning the usefulness of their focus group research data, and the stifled groans of companies falling on their metaphorical swords. These noises are not going unheeded. The ground swell of opinion among marketers and researchers alike is that all is not well with focus groups, and that something needs to be done about it.
As a metaphor for innovation teams, the marshmallow challenge is fantastic. Teams compete to build, within 18 minutes, the tallest free standing structure with spaghetti sticks and a single marshmallow placed on top. The best way for teams to build a good structure is to quickly begin experimenting with various prototypes, each time making sure the marshmallow is on top. However, very few teams do this. Instead, most teams spend a lot of time planning, and then build their structure without ever touching the marshmallow. Only when time is running out do the teams remember the marshmallow. They place it on top of their spaghetti stick structure and drumroll…., the structure collapses!!
The more I do this work, the more I am convinced that you can develop MVP experiments for almost any product. I was walking around a university campus the other day and saw a woman running a cake shop out of a caravan! I just had to take pictures! She was speaking with customers, probably learning what sells and doesn't sell; and she was doing it cheaply.