Innovating to what's next...

ReCirculate, a premium compost product made from unconsumed food sourced from thousands of grocery stores by Denali, a Russellville, Ark.-based recycler of organics, is now available for purchase at more than 100 Walmart locations in eight southern states. Packaged in 1-cubic-foot bags and retailing for a suggested $6.97, consistent with other products of its kind, ReCirculate will be available at 600-plus Walmart stores across the country by April, in time for peak spring planting season.

Zap’s experiments on 433 plasma shots show nearly isotropic neutron emissions, confirming the stability and scalability of its fusion process.

It may seem counterintuitive, but transactions alone don’t outweigh the importance of early-stage relationship-building. Focusing on creating connections through brand content at the top of the funnel can drive meaningful business outcomes. Those early efforts form the bedrock of strong consumer relationships. By consistently delivering personalized customer experiences, seamless service and real value, you can create memorable brand experiences, whether you’re selling ice cream or million-dollar marketing solutions.

The Chinese startup DeepSeek shocked many when its new model challenged established American AI companies despite being smaller, more efficient, and significantly cheaper. However, management theory — specifically disruption theory — could have predicted that a challenger like this would inevitably come along. After all, disruptive innovation is all about low-cost alternatives that aren’t cutting-edge but perform adequately for many users. This, it seems, is exactly how DeepSeek has created the shockwave that it has. DeepSeek isn’t sui generis. It’s operating along similar lines to many other Chinese, which differ from their American counterparts in two significant ways: 1) They often use cheaper hardware and leverage an open (and therefore cheaper) architecture to reduce cost, and 2) many Chinese LLMs are customized for domain-specific (narrower) applications and not generic tasks. Management theory also offers insight on how companies should proceed from here. On the one hand, a benefit of having multiple LLM models deployed within an organization is diversification of risk. On the other hand, a benefit of working with a single supplier is reduced administrative costs and better understanding of capabilities on both sides of the partnership. Prior management theories also suggest a third possibility: plural governance, which involves using a combination of external suppliers and internal developers to leverage an emerging technology.

We all like to think our best ideas are the product of our own brilliance. But if we’re being honest, some of the most innovative solutions don’t come from a single person—they come from a collective. The truth is, your best ideas might not even be yours, and that’s actually a good thing. Whether you’re working in a federal agency, a local government, or any other public institution, leveraging the ideas of others—especially through collaboration and crowdsourcing—can take innovation to a whole new level.

In 2023, we began experimenting with over 40 AI tools. Initially, we used AI to simulate some innovation workshops we had previously conducted with clients to compare the results. Since then, we’ve applied AI in a variety of contexts: working on all kind of challenges (de processes, HR. communication, product and service development…) in very different sectors (pharmaceutical, food, bank, cosmetics…). Through these experiences, we’ve drawn some very clear conclusions.

You were born creative. As an infant, you had to figure many things out—how to get fed or changed, get help or attention, and make a onesie covered in spit-up still look adorable. As you grew older, your creativity grew, too. You drew pictures, wrote stories, played dress-up, and acted out imaginary stories.
Then you went to school, and it was time to be serious. Suddenly, creativity had a time and place. It became an elective or a hobby. Something you did just enough of to be “well-rounded” but not so much that you would be judged irresponsible or impractical.
When you entered the “real world,” your job determined whether you were creative. Advertising, design, marketing, innovation? Creative. Business, medicine, law, engineering? Not creative.

Dig into human psychology to help people take risks and make innovation the norm within your organization. Imagine this: you’re on a game show standing in front of three doors. Behind one of the doors is a prize, behind the other two, goats. You select a door. The host then opens one of the remaining doors to reveal a goat, and offers you a choice. Do you want to stick with your original choice, or switch doors? Which option gives you a greater advantage of winning?

There is an 80 percent chance that growth “outside the box” is a top-5 priority in your company. The “box” refers to your company’s current business model, operating model, and mental model. But chances are, your company is not delivering that growth. Only 1 in 30 company startups build a new $50 million business, 29 out of 30 attempts fail. Even in good times, out-of-the-box innovation is a tough game. No one is really happy.

When brilliant people talk about things they find fascinating, it’s often because those things challenge conventional wisdom. The tension between lean efficiency and innovative learning, the role of emotion in business decisions, and the risks of playing it too safe all point to a fascinating truth: sometimes the most counterintuitive path forward is the most successful.

Our ideas never turn out like we think they will. To succeed, they must grow and adapt to the world around them. Gandhi, fresh off stunning victories gaining rights for Indians in South Africa, didn’t realize how his methods could go so horribly awry. The Otpor activists, Steve Blank, William Coley and so many others had similar blind spots.

When best practices get old, they turn into ruts of old practice. No, it doesn’t make sense to keep doing it this way, but we’ve done it this way in the past, we’ve been successful, and we’re going to do it like we did last time. You can misuse old practices long after they’ve withered into decrepit practices, but, ultimately, your best practices will turn into old practices and run out of gas. And then what?

You can’t argue with the evidence. Being easy to do business with attracts new customers, keeps existing customers and gives you a competitive advantage. Consider what we learned in our customer service and Customer Experience research (sponsored by RingCentral). Each year, convenience ranks as the most important customer service experience. These findings from the study back this up:

Last week, InnoLead published a collection of eleven articles describing the root causes and remedies for killers of innovation in large organizations. Every single article is worth a read as they’re all written by experts and practitioners whose work I admire.
I was also inspired.
In the spirit of the hustle and bustle of the holiday season, I gave into temptation, added my own failure mode, and decided to have a bit of fun.

Here’s a head-scratcher when it comes to scaling innovation: What happens when your innovative product is a hit with customers, but you still fail spectacularly? Just ask the folks behind Smashmallow, the gourmet marshmallow company that went from sweet success to sticky situation faster than you can say “s’mores.”

La start-up chinoise d'IA a dévoilé un modèle très performant avec un coût minime par rapport aux modèles américains. Une prouesse qui remettrait en cause les dépenses faramineuses des géants de la tech dans les puces.

Avec la troisième version de son grand modèle de langage, lancée en décembre, l’entreprise d’intelligence artificielle chinoise DeepSeek pourrait bien avoir battu en brèche l’idée que les meilleures IA requièrent des milliards de dollars et les puces les plus avancées. Pour seulement 5,6 millions, soit 7 % du coût du développement de ChatGPT, Pékin est parvenu à créer une IA comparable aux modèles américains.

En général, les arts et la culture sont particulièrement ouverts aux nouvelles approches, ce qui les rend plus enclins à expérimenter par rapport à d’autres secteurs. Pendant la pandémie de Covid, de nombreuses institutions culturelles ont profité de cette période pour explorer l’impression 3D, la production sur site et l’utilisation de matériaux écologiques. Cet esprit d’innovation ne se limite pas aux grandes scènes : l’impression 3D et les technologies associées ne sont pas seulement adoptées par de petits établissements en quête d’innovation, mais ont même fait leur entrée à Broadway !

Regulatory agencies of any kind know that instituting new rules often requires companies to make substantial changes to their business. The ripple effects can fan out endlessly throughout every corner of the organization, with dependencies and contingencies that disrupt even the most experienced change management gurus. But regulatory agencies aren’t intending to incite upheaval, turmoil or failure with strict deadlines or the potentially complex adjustments required for compliance. Those deadlines to comply are put in place for a reason, and eventually, the grace period extended to companies between the time a law is approved and the time it’s implemented will come to an end. For many sustainability and environmental, social and governance (ESG) regulations, that time is now.

Gen AI has several attributes that humans lack. It’s always on. It boasts encyclopedic knowledge. It generates output instantly. It can scale endlessly. This new era of AI can feel intimidating for the limited, human life forms that created it. Humans now need to look harder to see where our unique value still lies. What tasks or skills might be difficult for AI for the foreseeable future? What moat can humans continue to own and defend? In this article, the author describes four strongholds for humans, and the associated human skills that remain valuable — for now.

While AI has the potential to solve major problems, organizations embarking on such journeys of often encounter obstacles. They include a dearth of high-quality data; too many possible solutions; the lack of a clear, measurable objective; and difficulty in identifying whether a proposed solutions is “good.” In tackling these issues, Google DeepMind, Alphabet’s AI lab that is striving to solve extremely challenging real-world problems, has come up with solutions that can benefit others. And it also offers guidance in choosing which opportunities to pursue after potential projects have overcome those hurdles.