In many industries, AI has the potential to fundamentally reshape the value chain. Retail is no exception. There are many problems that AI could potentially help solve by:

1. 1. Picking up on changes in consumer demand patterns – on a category, brand and product level. AI can aggregate data from multiple sources to identify patterns and help manage inventory to meet rising demand.
   2. Simulating impact to weigh different strategic initiatives – assessing impact on revenues of different merchandising strategies, promotions, shopper marketing, performance marketing etc.
   3. Enhancing customer relationship/increase cross-selling by predicting the Next Best Purchase – the most likely purchase given patterns from both internal and external data sources brought together
   4. Sharpening targeting through a Personalized Shopping Assistant (in-store and online) assisting with search, best fit, suggestions etc.
   5. Optimizing customer service through dynamic scripts, face and voice recognition, predictive equipment maintenance etc.

However, the real value of AI goes beyond revamping current activities – ultimately, it will be in making entirely new retail models possible, where the very relationship with the consumer is reinvented. A few examples, among many others, could be:

Creating worlds and experiences – beyond transactions
Imagine planning a dinner party. You put in a theme and receive a dinner planned by Gordon Ramsay. As you select recipes, ingredients in the right quantity for your party automatically appear in your shopping cart – and a cooking flow is set for you with videos, instructions and timely reminders. Table settings for your theme dinner are delivered right on time with suggested wine pairings. AI can help create a world of experiences – where value is derived not just from the purchase transaction, but from the experience and interactions that these enable.

Lifestyle ecosystems – beyond the category
Imagine putting in the occasion for your next office party and receiving outfit recommendations, removing the traditional consumer angst of not knowing what to wear. Imagine your style choices then connect you to a community of like-minded aficionados (Recent years have seen the formation of many such lifestyle communities, from cottagecore to farm chic or now momcore that has recently been reinvented). This lifestyle community would bring together an ecosystem of providers, from clubs to sports, leisure and entertainment, supported by a stream of “endless” content. These ecosystems will not just foster a stronger sense of belonging and loyalty – each interaction will enhance the value of interactions to come.

Co-creation: sharing creativity
In the traditional model, consumers are subjects – on the receiving end of the brands’ creativity, branding and advertising. Recently, brands have been exploring reversing that pattern – putting consumers themselves in charge of advertising the brand – from Apple featuring consumers’ photography in its ads to Yeti’s UGC campaign. With the democratization of creativity brought about by AI, this can be taken one step further – with much more ease, consumers will be able to ideate, script, design and even produce an ad – and disseminating it to their networks, creating the sort of viral effects that create exponential growth.

Every retailer knows well that beyond satisfying consumers’ functional needs, there is a large market in meeting consumers’ deeper needs of feeling seen, taking control of their narrative and connecting with others. Through data and matching algorithms, AI can give consumers the ultimate control over their narrative – expressing their values, personality and lifestyle choices. In such an ecosystem, value would be created through much more than transactions – through the interactions that will create data that will ultimately enhance the value of the ecosystem at large.

The ultimate question is how these retail models will lead to new ways to increase value – an increased customer relationship leading to higher loyalty; better targeting to increase spend; and belonging to a community leading to increased frequency. This is when the AI opportunity will become real.

The post AI in Retail – Is the Value Real or Artificial? appeared first on Vivaldi.

Kip Meyer, Managing Director, Custom Partnerships at IESE welcomed a packed room of executives at IESE Business School in New York City, inviting them to, “turn off your certainty, turn on your curiosity.”

The event had a unique three-part format: an introduction setting the context for the discussion, a moderated panel of global business leaders, and interactive small group conversations that enabled the participants to explore the implications of business reinvention, facilitated by Professor Mike Rosenberg.

Vivaldi founder and CEO, Erich Joachimsthaler, PhD, opened the door for curiosity with the introduction, highlighting a recent AlixPartners survey of 3,000 CEOs that found 98% saying they need to overhaul their business model within the next three years, but most did not know where to get started. Joachimsthaler also explained the differences between digital transformation and real business reinvention – it is about reinventing the core, not just leveraging technology but also reinventing the entire business model and even the leadership approach.

The expert panel included Krishan Bhatia, President & Chief Business Officer, NBCUniversal; Tara Bustamante, Group SVP, Business Transformation, Warner Bros. Discovery; and Andreas Fibig, former Chairman and CEO of IFF and former President & Chairman of the Board of Management of Bayer Pharmaceutical.

Over the next 90 minutes, some of the thorniest questions facing businesses today were presented by moderators Julia Prats, IESE Professor, and Anne Olderog, Vivaldi Senior Partner.

• How do you know it is time to reinvent you core and what does this imply?
• When do you integrate new technology?
• How do you navigate a changing business model?
• What are the implications for leadership?

The discussion spanned these 4 key areas:

REDEFINING THE CORE

Industry Boundaries Are Shifting

In times of disruption, industry boundaries are not what they used to be. Krishan Bhatia spoke about the example of how we’re seeing increasingly interactive commerce functionality introduced into the media and gaming sectors, as consumers look for shopping experiences that are as simple and engaging as watching their favorite shows. At Warner Bros, the recent success of the game Hogwarts World demonstrated how media franchises can span traditional media and gaming.

Andreas Fibig spoke of entirely shifting industries during his leadership at IFF – from chemistry to biology, from producing ingredients to co-creating entire solutions.

The Core is Not What It Used to Be

While the core of the media industry has always been defined as content – as Tara Bustamante pointed out, the definition of what content is, evolves at the speed of light. Is it content enriched by data that shows its significance and impact? Is it metadata? Is it content co-created by and with consumers, such as on social media? Is it interaction and discussion around its impact? What trusted/quality content was yesterday may not be what it is in the future, as we are headed towards immersive, engaging, interactive content where audiences are invited to participate in various forms (and share data on their preferences in the process).

Similarly, Andreas Fibig spoke of his reinvention of IFF as a CEO – and the move from ingredients to full products that fit consumer needs. An example is the reinvention of animal protein with plant protein in order to supply protein needs of a growing world population – a need that require new textures, flavors and tastes, much beyond enzymes. This move allows the tackling of big, previously unsolved problems – such as world nutrition – and reinventing taste in the process.

TECHNOLOGY

What Comes First – Technology or Consumer Changes

In that age old debate, Krishan Bhatia’s position is that consumer changes force the reinvention – making business reinvention a must. With the growth of streaming alongside linear TV, the advertising model and technology around it is being reinvented, noted Bhatia, who tested the hypotheses that advertising is best when targeted and relevant. NBCU’s One Platform, which Bhatia leads, offers advertising models – and metrics – suited to both streaming and linear TV. He sees an evolution from one standard of measurement that has been the legacy currency for the TV industry to a multi-platform multi-currency measurement giving advertisers more choice. It’s also a far better fit to measure the complexity of how people are consuming content which is increasingly across multiple platforms.

For Tara Bustamante, media and technology cannot be viewed separately anymore – they are intrinsically liked together, especially as predictive analytics allow new consumer experiences to be created, from gaming to shopping or social interactions. As Bustamante said, media and technology are now intertwined — media operates in tandem with technology to create outstanding consumer experiences, supported by data that allows for precision targeting and personalized paths.

“We view everything through the lens of technology,” she shared.

BUSINESS MODEL

The Rise of Ecosystems As a Business Model

As the core is being redefined with support from technology and data, what we monetize today can be very different than yesterday. Yesterday’s model was monetizing content as an asset to be leveraged, in a traditional pipeline value chain model. Today, as Bhatia pointed out, media companies realize that their core asset is the understanding (through data) and relationship (through technology) with consumers. First, this requires a deep understanding of audiences and their preferences and desires on their own terms – rather than simply defining audiences by product preferences (e.g. Action lovers). Second, the foundation of the business model is no longer the transaction (i.e. selling to consumers media that they consume) but a series of interactions that engage consumers across the content they choose to be a part of their lives. These interactions can include gaming, in-media shopping (or InScene Advertising that NBCU has pioneered), content co-creation, etc.

Media companies have an opportunity to redefine themselves as managers/orchestrators of immersive content organized around key media franchises (or in business terms, Interaction Fields, as Erich Joachimsthaler would call these). For the first time, as Bustamante pointed out, media companies are thinking about how to monetize these relationships as opposed to benefit from on-off transactions.

Traditional Value Chains are Pulled Apart

These ecosystems require a broad cooperation from many players across the industry and outside to be effective, as no one player will have the required capabilities. All speakers spoke of collaboration with a wide network of start-ups and other industry players from across the ecosystem. Andreas Fibig spoke of co-creation with customers – a much different model from creating an ingredient and monetizing it by selling it to customers, in a traditional value chain model. The ecosystem model allows forces and capabilities to be pulled together from across the industry to solve big problems.

LEADERSHIP

Curiosity as Core Leadership Competence

Bhatia echoed the need for inquisitiveness – he actively recruits for curiosity as a core competence, since he sees it as a key success factor for leaders in today’s world of complex ecosystems. This makes experience in the industry less relevant than the ability to calculate backwards from the desired outcome. For the ecosystem economy, leaders can be those who can ask the right questions, since nobody has the definitive answers.

In closing the event, IESE Professor Mike Rosenberg drew a further distinction between transformation and business reinvention, rooted in radical shifts in technology and the world. To cope, an ecosystem approach may be called – to push industry boundaries, search for big answers to big questions – and ultimately reinvent your business.

Is your business ready for the future?

This event evolved from a unique partnership between Vivaldi Group, a global leader in business and brand transformation, and IESE Business School, a global leader in management education ranked #3 worldwide (2022 MBA rankings.) Following the success of the event, IESE Business School and Vivaldi plan to partner to host more events together in the future.

The post Four Key Takeaways from “Reinventing Business” appeared first on Vivaldi.

I think we have now reached, as Churchill said, “the end of the beginning” when it comes to AI in the workplace. To relate how I have reached this conclusion, I would like to share with you my personal journey with AI in three vignettes.

2011: Watson’s AI Rules Jeopardy

About a decade ago I helped IBM reposition themselves for a “Smarter Planet,” which was about the possibilities presented by a world becoming instrumented, interconnected, and intelligent. A great example of these 3-I’s, was IBM’s emerging “Watson” technology, which represented a real breakthrough on the road to Artificial Intelligence. And what better forum for Watson’s public debut than on Jeopardy — the pinnacle of human intelligence (at least from a game show perspective)?

Watson went on to crush its opponents, including Jeopardy’s winningest champ and future host, Ken Jennings. Despite this success, Watson had a few stumbles along the way, including this Final Jeopardy round exchange:

Category: U.S. Cities
Question: “Its largest airport is named for a World War II hero;
its second largest, for a World War II battle.”
Watson’s Answer: “What is Toronto”

While anyone could have missed the correct answer (Chicago), it’s unlikely that you would have guessed “Toronto” when the category was “U.S. Cities.” This blunder was later attributed to Watson misinterpreting context, such as the fact that the Toronto Blue Jays compete in the “American” league.

A noble effort, but not quite yet the AI the movies had promised us. This made me appreciate how difficult it would be to reach true artificial intelligence and practically apply it to the work that most people do.

2017: The Future of Work

Five years ago, I led an engagement for a client on the “future of work.” The company was/is a business services outsourcing provider, so they were rightly concerned about trends that would reduce the demand for the labor that they monetize (contrary to most companies, where the incentive is often to reduce labor). Over the decade prior, I had helped them migrate from pure labor arbitrage to a more value-added mix of people within digital workflows (e.g., insurance claims processing, accounts payable, etc.), but “human” work remained at the core of their business model.

Even then the writing was on the wall that the nature of “work” was changing. What was called “software robotics” was beginning to augment/replace repetitive office tasks and early machine learning use cases were taking hold. Our quick engagement focused on projecting the implication of technology and labor trends to identify new sustainable business models. The effort was guided by two principles about the dividing line between humans and technology in the future of work.

Principle 1:
Human labor will remain where there is not a practical business case for technology.
Implication:
Non-standard labor will remain long after the technical means to replace it exists.

The notion of non-standard labor involves work that would not be “practical” to eliminate. Applying this principle provocatively, being a plumber may be a more enduring long-term career than a surgical cardiologist. If you live in a house built in 1904 like I do, you will appreciate how “non-standard” plumbing can be, but you pretty much expect a heart to be located in the same place consistently. Just as zero-defect spot-welding robots replaced humans on auto assembly lines, it’s not a question of “if” but “when” AI-driven robotics will be the norm for many routine surgeries. For our client’s outsourcing business, this led to the creation of a new Corporate Campus Logistics service that combined non-standard labor activities with digital logistics workflows.

Principle 2:
Human labor will remain where creative problem solving is at the core of the activity.
Implication:
Knowledge work where there is a multiplicity of potential solutions is most survivable.

While the first principle addressed labor with “head and hands,” most of the folks reading this blog are pure knowledge workers. Well, the future is gaining on us too. Since it’s ok to pick on lawyers, let’s consider a tax attorney billing at $500 an hour. Attorneys operate within a defined tax code (i.e. programable “business rules”), and the high cost of this service creates a strong business case for AI intervention. Perhaps surprisingly, the one thing that will preserve this profession for at least the foreseeable future is “creativity.” Creativity in subjectively interpreting the tax code to their clients’ benefit. For our client, this principle led to exploring new outsourced marketing services that could be delivered efficiently through on-shore and off-shore solutions.

Let’s carry forward these principles around what’s practical versus possible, as we look at the state of AI today.

2022: AI at the Tipping Point

I started experimenting with OpenAI’s “playground” a few weeks before they launched ChatGPT in the fall of last year. I wanted to see how far things had come along those dimensions of “practical” and “possible.” What I found suggested that AI had finally crossed the tipping point from the lab into our daily work lives.

“What is Practical”

I began by using the algorithm to categorize research verbatims into themes and to provide a summary with examples. A task that might take a junior analyst a couple of hours to do, was completed instantaneously, and the output was usable without any meaningful edits. My colleague entered a few simple bullet points and was provided the full prose for a conference invitation. Not tasks that could yet replace whole types of “jobs” but ones that could immediately reduce the volume of “work.”

By using natural language inputs, any request framed in a conversational sentence or two can be tackled by the algorithm. Now the benefits of AI are accessible to everyone without need of a specialist gate keeper. We are now a few entrepreneurial applications away from reducing the dumb work that bogs down enterprises and demotivates staff. Think how much time we waste versioning spreadsheets and PowerPoint presentations alone.

Here are 5 very practical things you can try today:

1. Generate a first draft. There are always things we have a tough time getting around to writing, so use this experiment to tackle one of those. Just enter a few bullets of content and simple instructions and see what it comes back with. If you don’t like what you get, just hit refresh and get another take on it.
2. Make something better. As good as AI is with first drafts, it excels at doing the final clean-up of a document. Beyond just fixing grammar, if you would like to say the same thing in half the words, no problem. Turn paragraphs into bullets, bullets in long-form, change first-person to third, etc.
3. Summarize a meeting. Before Teams/Zoom recordings and transcriptions, managers use to get helpful one-page summaries of group discussions. Instead of slogging through the transcript of a meeting you missed, let AI summarize it for you.
4. Create a value proposition. Turn technical products specs into a clear description of what something does – or even a compelling new customer-facing value prop statement.
5. Empower an intern. While I would encourage everyone to try it for themselves, you can also ask an intern to experiment for you. In less than an afternoon they should be able to come with three time-saving ideas for reducing tedious tasks bogging down your office.

“What is Possible”

Now let’s look at what is possible with AI today. Specifically, how far has AI come with the type of “creative” problem solving that only a few years ago I thought would save us humans from our AI overlords.

One of my experiments was to have AI write the dialogue for the final scene of a movie or play by providing it with a simple plot summary and character descriptions. I disguised just enough of the inputs, so that the algorithm wouldn’t be tempted to cheat and consult the source material. The results were, to me at least, quite amazing. To be clear it wasn’t Shaw or O’Neill, but I now understood how it was possible for Lifetime to churn out a couple dozen movies every year.

Occasionally we still see some early Watson context-confusion creep into the output – particularly with image generation. When a different algorithm was asked to generate candid shots from a house party that never happened, it inserted an extra finger or two on a hand holding a camera. Forgivable for something without fingers and easily fixed.

Imagine how life-saving this AI image generation will become – at least “work life”-saving. Getty Images alone has over 80 million images which generate over 2.3 billion searches annually. Let’s assume it takes an average of three minutes to find the ideal image (I’ve sadly spent much longer). That adds up to almost 1,800 lifetimes of work lost annually.

Perhaps to confirm that there really is something here, we are already starting to see the backlash to AI’s early forays into the once exclusively human domain of creativity. The rules of some online art competitions are being rewritten after AI generated images started beating their human competitors (it does particularly well in Fantasy categories, where an extra finger is more easily explained away). When a fan presented singer/song writer Nick Cave with a song written by ChatGPT in “his” style, he had this to say:

“…it will always be a replication, a kind of burlesque…Songs arise out of suffering, by which I mean they are predicated upon the complex, internal human struggle of creation and, well, as far as I know, algorithms don’t feel. Data doesn’t suffer.”

To better understand where this is all going, I turned to the one source who I trusted to be objective, my new AI collaborator:

Q: Will AI algorithms eventually replace human creativity?

A: No, AI algorithms will never replace human creativity. Artificial intelligence is a tool that can be used to enhance creativity, but it cannot replace the unique and innovative ideas that come from the human brain. AI algorithms can help humans to automate certain creative tasks, but they will not be able to come up with truly creative ideas the way a human can.

Maybe the algorithm was just trying to make us feel better and divert attention from its real goals. But even if the creative glass-ceiling for AI is one of a junior copy writer or designer, destined to write the first draft that helps inspire real “human” creation, that’s still a very big deal.

So, now what?

Yes, we are still a long way off from where this is all going. But we have to acknowledge that things will now move at a much faster pace as we reach “the end of the beginning” of AI in the workplace. We must accept AI as a co-worker who is here to stay (albeit one who won’t try to sell you Girl Scout Cookies).

I’m choosing to view these early breakthroughs in AI as a wakeup call for us humans to up our game. There has long been too much “dumb” work sapping the energy and potential of all our organizations. Now that the means exist to draw a clearer line between work that must be done by humans and work that can and should be done by technology, we should all seize this moment.

Is AI the liberator of human potential, or the inevitable next evolutionary step away from us? When it comes to the future of work, maybe Terminator 2 got it right.

“The future has not been written.
There is no fate but what we make for ourselves.” 

***

PS: If you’re interested in more thinking like this, or would like to share your perspectives, please send me a LinkedIn connection invite.

Chris Halsall is a Senior Partner with Vivaldi, who focuses on reinvention and growth at the intersection of customer, brand and business. Prior to joining Vivaldi, Chris was the co-founder of Ogilvy Consulting, where he was the Global COO and leader of the Growth & Innovation practice. Chris began his consulting career at McKinsey & Company, where he led the Marketing Effectiveness Practice and was the Senior Branding Expert for North America.

The post The End of the Beginning for AI in the Workplace appeared first on Vivaldi.

If you want to achieve extraordinary impact for customers, investors, and society, we can help with strategies to do that.  

Here are 10 questions that can help to steer internal conversations with teams to help your business get ahead.  

1) What is your business’s field of play? 

A “field of play” refers to where your brand might reasonably fit, unencumbered by the boundaries of categories. For instance, Tesla’s field of play is not just cars, or transport, but intelligent energy. Rather than being bound by strict category definitions, consider how your business might exist in a larger context.  

2) How are you using technology to evolve around your consumers? 

Today technology is reinventing the core of businesses. Consumers are now empowered decisionmakers. In what areas could your business benefit from better utilizing technology? How would your consumer relationships change? What would be the impact on your business’s category? Finding new tech solutions can have wide-ranging implications.  

3) Are you experimenting? 

Those who can achieve transformational growth do so by experimenting at scale and integrating learnings as a systemic capability. Does your business test out new ideas regularly? Do you have a process for utilizing feedback from experiments? Think about how you can incorporate experimentation into your regular processes to help identify new areas for growth or improvement.  

4) How are you taking your strategy beyond transactions? 

The focus of value creation has shifted from driving transactions to driving interactions. It’s not enough to simply accomplish a task for a customer. Brands and businesses deliver real value when they achieve something more or create greater connections. Consider how your company uses brand technology, ownable experiences, data, purpose, and hyper-personalization.  

5) How would you reimagine the structure of your organization to be ambidextrous? 

Now more than ever, organizations need to learn how to optimize their current business model, while building a new one. So called “ambidextrous organizations” are those that can compete in the present while creating possibilities for the future.  

6) If someone evaluated your brand’s actions, would they be consistent with its strategy? 

Strategy is nothing without action. But how often is your company engaging in actions that aren’t aligned with your strategy? Or vice versa? How much strategic thinking does your business have simply sitting in PowerPoint decks? Figure out how to activate this thinking in the real world. 

7) Does your brand harness the power of others to create a more rewarding ecosystem of shared value? 

The value chain doesn’t just end with your product or service. There are opportunities to grow beyond your brand through collaborating with other businesses, or even starting other businesses to create shared value. Applying an ecosystem lens may open opportunities you hadn’t previously considered.  

8) Can all your employees/colleagues articulate what your business stands for in under 20 seconds? 

Every business needs a North Star to guide what they do, and how they do it. Powerful brands and businesses are the ones who can quickly articulate why they do what they do. Going beyond that are brands who have a higher purpose, or a mission that society can connect to. How strong is your North Star?  

9) What is your strategy to retain your top talent? 

We are in an ongoing war for talent. As companies look to retain and attract top talent, it’s not enough to think about what’s working well enough today. Think about what you will have to do in the next three years to keep your team motivated.   

10) Will your consumers be able to relate to your offering this time next year if you don’t change anything you are doing today? 

In a world of changing technology and consumer needs, companies that fail to reinvent themselves or parts of their business get left behind. How could your business anticipate what’s coming next? How can you build something for the future? 

Vivaldi’s team of strategists is always happy to discuss these questions in depth with you. We want to help create the next generation of your business. Reach out to our team.  

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A first step forward can be through idea generation, and we previously spoke with Jeremy Utley about the practice and value of generating ideas.  

In this interview, Cerrone Lundy, Director at Vivaldi, shares how valuable ideas get put into action, the importance of true ideation sessions, and the mindset shift that needs to occur for companies to prepare for the future.  

One of the keys is found in the implementation of a model that Vivaldi CEO Erich Joachimsthaler calls the “interaction field” model. As Joachimsthaler explains, interaction field companies “generate, facilitate, and benefit from interactions and data exchanges among multiple people and groups.” Read on about why this is the business model of the future.  

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Vivaldi: When it comes to idea generation, how do you distinguish between an “ideation session” and a “brainstorm”?  

Cerrone Lundy: “Brainstorm,” in my opinion, is one of those words that’s used so flippantly and so often that its lost its meaning. There’s no stimulus, no clear roles, output, goal, no clear exercises and activities. An ideation session is very different in that it has that structure that you need to actually generate useful ideas. That’s critical.  

You’ve said that for something to be a real idea, it needs to pass the “crumpled paper” test — can you elaborate on what that test is? 

The crumpled paper test is essentially taking what you believe is an idea, writing it down on a piece of paper, and then asking yourself, if you were able to crumple that piece of paper up and toss it out a window, could a passerby pick that up, smooth it out, and then actually execute on your idea with 95 – 99% fidelity. And if a random passerby could not actually do that, you have an idea starter. It’s not an actual idea yet. It’s just the inkling of an idea. It’s only when you get to a specific level of clarity around something, would it be what I consider an idea. Now it has entered a space where it is executable in a way that is true to the essence and the desire of the idea creator, or the teams of people that created that idea.  

After you’ve generated ideas, how do you know which ones to follow through on? 

There’s a bit of an art and a science to it. The science is, often there are metrics when it comes to what kinds of ideas can actually move forward. You don’t necessarily want to be culling ideas when you are generating because that changes the energy of the room. Once you’ve generated a lot of ideas, then you often need to go back to the metrics you started off with, and ask — do these fit within the scope of what our client can do? Is this stuff too fanciful to actually be executed? Does it actually have a potential to generate income? Whatever those metrics may be.  

In addition, there’s a bit of the art to it. Sometimes you have “kitchen sink ideas,” and you can tell it’s just an amalgam of things, but there’s no focus to the idea. It’s like, a fork that also brushes your hair and you can use it on your dog and it also picks up antenna messages from space. True, it’s an idea and you can probably write it to pass the crumpled paper test, but it’s not a great idea and has no focus. It’s not solving a particular problem and may just not make sense. 

At Vivaldi we’ve been talking a lot about reinvention — at what point do companies need to think about reinventing themselves?  

I think that organizations should always be asking themselves what can be changed, what can be reinvented. There’s the core of the organization, the brand essence, the reason the organization exists, and that should be pretty stable, but marketplaces, technology, and consumer desires are changing so much that you need to always be in this role of pushing yourself forward and not sitting on your laurels. When organizations get to a place where they’re so comfortable that they aren’t capable of looking at themselves, that’s when they get disrupted. You should always be looking at what you’re doing and be introspective while paying attention to what’s going on around you. Otherwise you’re destined to become a fossil. A victim of circumstances.    

In some of the projects you’re working on at Vivaldi, you’re not just generating or presenting ideas, you’re actually building products and systems. Knowing that you’re going to be building something, how does that affect your approach to that idea generation or conception stage?  

It shouldn’t. If you’re an innovator and a strategist and you’re coming up with an idea that you’re like, “I hope I never have to do this,” it’s probably not a great idea. It can be difficult of course, and it can potentially involve something that’s not in your skill set, but you should always think, “how would I execute this thing?” Even if the answer is, “I would find someone who is an expert in x y and z.” If you don’t have that conviction to put your skin in the game, then it’s easy to come up with crazy ideas and hope someone else will figure it out, or pray to the innovation gods that the solution will drop out of the sky. It is much more personal and important to feel like you have a stake in it. You’re not expected to be a master of every category, but you should have some perspective on it and ideally some passion around it. 

Some of the systems that are being built are what Vivaldi calls “interaction fields.” How can a company know that it could benefit from being part of an interaction field? 

Interaction fields are going to be the business models of the future and there are very few organizations that would not benefit from forming, connecting with, or integrating themselves with a larger interaction field. The notion behind them is that value is generated for all the participants. You don’t necessarily need to be the nucleus, the generator, of an interaction field, but understanding where your organization fits and what interaction fields are out there to generate value for your organization and your organization’s participants.  

I think it’s very difficult for people to get out of thinking about the pipeline model or the platform model. A lot of organizations, even consulting organizations, are still essentially pipeline organizations and there’s a shift in how one thinks about business, and even how businesses talk, that needs to happen in order to really embrace this idea of cooperation as opposed to competition.  

It’s a mindset shift if you’ve been going down one pathway for a long time. 

Even beyond that, there’s this sense of scarcity mindset versus abundance mindset. So much of our society is based on a scarcity mindset, or stealing share as opposed to finding ways to grow the pie. Scarcity mindset is often a killer of ideas, the sense of “we can’t do that” or “we’re bound by this,” as opposed to an abundance mindset of saying, “what if we did this,” “how could we do this,” “let’s push this and see where it goes.” That’s inherent in an abundance mindset and inherent in being able to generate really interesting new creative ideas. If you’re blocked off by the sense of scarcity, by the sense of what you can’t do, then you’re going to come up with the same ideas that everyone’s always come up with since the beginning of time. 

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Cerrone Lundy is a Director at Vivaldi. He works with organizations to better understand their client needs and create products, services, experiences and more. 

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