Great article from HBR as always: How Apple Is Organized for Innovation. In 1997, Apple’s organisational model was conventional with business units, each with its own P&L responsibilities. But Jobs believed it had stifled innovation and he put the entire company under one P&L, combined the disparate functional departments of the business units into one functional organization. Although such a structure is common for small entrepreneurial firms, Apple – remarkably – retains it today, even though the company is nearly 40 times as large in terms of revenue and far more complex than it was in 1997. “Something vital gets lost in a shift to business units: the alignment of decision rights with expertise.”
First, Apple competes in markets where the rates of technological change and disruption are high, so it must rely on the judgment and intuition of people with deep knowledge of the technologies responsible for disruption.
Second, Apple’s commitment to offer the best possible products would be undercut if short-term profit and cost targets were the overriding criteria for judging investments and leaders. Bonuses of senior R&D executives are based on companywide performance numbers rather than the costs of or revenue from particular products. The finance team is not involved in the product road map meetings of engineering teams, and engineering teams are not involved in pricing decisions.
Three Leadership Characteristics:
- Deep expertise: ”experts lead experts”
- Immersion in the details: “Leaders should know the details of their organization three levels down”
- Willingness to collaboratively debate: Because no function is responsible for a product or a service on its own, cross-functional collaboration is crucial.
And this HBR article really outlines the importance of creating an inclusive culture for innovation as a leader. To Foster Innovation, Cultivate a Culture of Intellectual Bravery: “If you want your team to innovate, you need to create a culture of intellectual bravery, in which team members are willing to disagree, dissent, or challenge the status quo even when it requires they risk being embarrassed, marginalized, or punished. As a leader, make this possible by rewarding (or punishing) vulnerability and risk-taking.” This rings so true!
On corporate innovation, McKinsey shared that business building is vital to a company’s longevity. To do it successfully, an organization needs the strengths of an incumbent and the agility of a start-up in Building a business within a business: How to power continual organic growth. An example of this was on The Venture podcast Building a start-up innovation ecosystem: A conversation with Jardine Matheson’s Anne O’Riordan and Michael Poon. It was great to hear Jardines’ CDO and Innovation chief just before we delivered Entrepreuneurship essentials to their teams across BUs at Hyper Island.
Another favorite podcast of mine is a16z as they focus on where we are on the long arc of innovation. Their 16 Minutes on the News #41: Tiktok and ‘Seeing Like an Algorithm’ with Eugene Wei who formerly led product at Hulu, Flipboard, and video at Oculus, among other things was phenomenal as they go under Tik Tok model. How does the “creativity network effects” flywheel work between video creation and distribution — from origination to mutation to dissemination? Their value proposition 101 is all about interest graph (forget about social graph). Their feedback loop is super efficient and tightly closed, which is “Algorithm friendly Design”. Kind of against design principles of reducing user friction, they’re slowing me as a user and showing 1 thing at the time and in doing so they get much cleaner feedback about user sentiment which means that the training of the algorithm happens more quickly. And training ML algorithm is usually the hardest part so here’s Tik Tok competitive advantage. Brilliant! “That is a novel new sort of design and product development paradigm which Tik Tok has created.”
“Both approaches are about building new concepts and products, learning as much as possible from users, and from what’s happening in the market. And both methodologies employ an iterative approach that consistently seeks feedback and understanding from customers in the market.”Kerry O’Connor, Design Director IDEO
Interesting to see IDEO compare Design Thinking vs Lean Startup when The Designing For Growth Field Book by Liedtka, J., Ogilvie, T. and Brozenske, R., n.d. compared Design Thinking to Linear analytics methods. The comparison from IDEO is useful and my take is that Lean Startup doesn’t mean Tech driven, it also starts as Design Thinking with empathising with customers (the “Build” can be building a prototype). Hypotheses are also part of Design thinking in my opinion (and experience) as when we iterate and test prototypes with hypothesis. The distinction from Hugh Mason presentation between Startup (Discovery) and Scaleup (Growth) spectrum (using the well-know Gartner’s diagram) is another useful lens:
At Hyper Island we use them 3, here’s What goes behind the creation of a new product in a VUCA world.
And to compare it all Design Thinking vs. Lean Startup vs. Agile vs. Six Sigma
I discovered First Round Review after a GDG re:Work webinar. Their resources, including this light-weight JTBD framework and step by step process from Facebook’s Sunita Mohanty is just great. And to complete it, going back to the original JTBD on HBR.
Why Big Data Needs Thick Data is one of the nice backstory from my Design Thinking Master module. I’m a big fan of blending qualitative and quantitative data.
“When organizations want to know what they do not already know, they need Thick Data because it gives something that Big Data explicitly does not — inspiration. Great insights inspire design, strategy, and innovation.” And “People are getting caught up on the quantity side of the equation rather than the quality of the business insights that analytics can unearth.” Tricia Wang
And like Nielsen Norman Group says: COVID-19 Has Changed Your Users so we need more research now, not less because of:
– Behavioral shifts
– Psychological shifts
– Changes in user groups (great examples like Ghostbuster disinfecting the walls a no-no during testing)
– Regional effects
– Temporal effects
As always, combine quantitative data with qualitative research
Guy Kawasaki shares How to be a Remarkable Innovator on his Remarkable People podcast:
- Make meaning
- Jump to the next curve
- Eat your cash cows
- Don’t worry be crappy
- Focus on merit
- Polarise people
- Don’t be afraid of changing your mind
- Be unique (differentiate) and valuable
- Plan for flaws, get your product out
- Churn, churn, churn
- Ignore naysayers
And as a bonus, he also shared earlier How to be a Remarkable Speaker:
- Do your homework to customise your intro
- 10/20/30 rule = 10 slides in 20 min 30pt font (ie. don’t read the slides)
- White text on black / dark bg
- Small room or classroom style
- Meet audience before your speech
- Entertain your audience, educate as a byproduct
- Cut the sales pitch, think “what’s in it for me”
- Practice (25 times for Guy for a new speech)