Nonlinear Thinking

Business Models and the Internet of Things

Two topics close to my heart - Business models and the Internet of Things

 

The Social Enterprise of the Future

We have discussed the impact that social media and the channels that have emerged based on social technologies will have on the enterprise previously here and here.  Rob Harles, of Accenture Interactive has a nice article on the social enterprise of the future on CMO.com, including a terrific graphic of what that enterprise might look like.  From the article:

Within five years, “social enterprises” could completely redefine customer value. We will see organizations emerge that will go way beyond polishing their presence on social networks and channels. Instead, they will make social media–the channels, the data, the users, the approach to collaboration–a part of every activity that zooms in on the customer.

The future of social enterprises (see figure, below) will be defined by how these organizations incorporate a real-time stream of predictive insights and personalized messages into their businesses, and how they define customer relationships and experiences by the level of complete digital integration and influence. Social enterprises will notice the redefinition of management roles, with each part of the business responsible for managing, synthesizing, and acting on ongoing torrents of digital information and content received in real time.

 

Additionally, they will depend more on the integrated views of the customer across multiple touch points and channels–such as combining social with physical call centers–to maintain customer happiness, with access to the most up-to-date customer data in real time.

As new technologies and digital strategies need to be developed almost every day, social enterprises will need to constantly adapt to their evolving landscape and anticipate what the social enterprise of the future will look like. This moves away from social strategies that are siloed within the business, focused only on expanding reach and “engagement,” and closer to a landscape where social is everywhere, driving real-time actions tied firmly to measurable business objectives.

If companies get this right, social can increase intimacy and relevance with their customers, which can become the tipping point between buying or not buying and remaining a loyal customer or going elsewhere.

Business Ecosystem Redux

“Business ecosystem” may be a relatively recent entry into our business lexicon but it is, perhaps, not an entirely modern concept.  Confederacies of market participants have allied around delivering comprehensive offerings to markets across epochs.  One could imagine Christopher Columbus, operating in the context of emerging western imperialism and economic competition between European kingdoms bent on establishing trade routes to access raw materials, devising a business ecosystems of sorts – ships, private equity, spice merchants -  to reach the East Indies and gain a foothold in the spice trade.

That those collections of interdependent actors were not identified as a business ecosystem matters little as the basic construct existed within the business, industries and markets of their particular time.  The strategic planning idea of “business ecosystem” is more contemporaneous and could be grouped with all the other management buzzwords of the recent past if its practical application in the science and process of strategy development wasn’t so damned profound.

Technology-focused organizations were among the earliest to understand that the connection and interdependence of all the actors in an industry, or sub-segment of an industry, could provide tremendous insight into market dynamics and uncover potential white space/blue ocean opportunities for their products, services and solutions.  While the concept has remained resonant over the past two decades, its use has seemed to vacillate between being a primary pillar of strategic assessment or languishing on the periphery as new ideas have taken their turn at center stage.  Lately, it seems to be achieving a higher profile and once again assuming, what I consider, its rightful place in the portfolio of core market and strategic planning tools.

The concept was codified in a 1993 Harvard Business Review article by James F. Moore, "Predators and Prey: A New Ecology of Competition".   In that article, Moore cited the anthropological process of coevolution and the biological model of ecosystems to provide context for his definition of business ecosystems.

“To extend a systematic approach to strategy, I suggest that a company be viewed not as a member of a single industry but as part of a business ecosystem that crosses a variety of industries. In a business ecosystem, companies coevolve capabilities around a new innovation: they work cooperatively and competitively to support new products, satisfy customer needs, and eventually incorporate the next round of innovations.”

Moore expanded on the concept in his seminal book, The Death of Competition: Leadership and Strategy in the Age of Business Ecosystems.  In the book, Moore did not suggest that competition was going to vanish.  His thesis was that the old notion of competition, where like-minded competitors match wits in pursuit of a prospect company’s business, was no longer as viable in an increasingly connected world.  As vertically integrated enterprises became less and less common and the extended enterprise business model increasingly took its place, understanding the broader environment in which the business operates became the foundation for holistic strategy development, more interdependent partnering structures and management of assets – human, intellectual, capital and financial – that cross traditional enterprise boundaries.

An important consideration here is that, for a business operating in a world of constant change, what you do is not as important as how your capabilities relate to what others are doing.  In this accelerating business environment, strategy-making involves having an awareness of the big picture and finding ways to play a role in it.  For some, the rise of ecosystems thinking is an opportunity to create powerful new competitive advantage.

There is a real “the whole is greater than the sum of the parts” idea at work here.  Many ecosystems are created to pursue objectives that would be beyond the effective scope and capabilities of any of the individual ecosystem members.  Also important to recognize and incorporate in ecosystem thinking is that business ecosystems emerge, operate and evolve over time.  Key to achieving some level of success and stasis is that all members of the ecosystem either evolve or are replaced so that the ecosystem continues to deliver the value proposition(s) it was founded upon.

In the connected economy, the value of interdependent relationships – partnerships, alliances, collaborations – continues to grow and ecosystems thinking provides a discipline and framework for understanding where active and latent opportunities reside.  Identifying and delivering the value proposition that addresses those opportunities can be done more effectively, efficiently and expeditiously when understanding and leveraging the power of the business ecosystem in which the enterprise finds itself.

Ecosystem thinking is also about leverage.  As the enterprise better understands its role in its business ecosystem, they can more effectively integrate their operations with those of partners/allies and have more influence on how partner assets are deployed and employed to deliver a more robust solution to a broader customer base.

A recent report by Deloitte highlighted the impact business ecosystems might have as they become more recognized and utilized.

The rise of business ecosystems is fundamentally altering the key success factors for leading organizations, forcing them to think and act very differently regarding their strategies, business models, leadership, core capabilities, value creation and capture systems, and organizational models.

If you have not read The Death of Competition, I encourage you to seek it out as it remains as resonant and contemporary today as when it was first published.

Big Data and the Science of Storytelling

Big data, and the analytics that make sense of the exponentially growing volumes of it, seem to be top-of-mind across the business landscape and increasingly central to both strategic and tactical decision making today.  In certain realms, marketing comes immediately to mind, it possesses the potential to become the central unifying force that moves the practice further from art and closer to science.  But, with big data has come big challenges in using the data for practical and impactful purposes.

That is why telling stories built upon data and analytics will become the critical manner for articulating the value buried deep in the lines and columns of huge stores of data. Narrative has been foundational for communication since words were first spoken.  It is the way to simplify and make sense of complexity in our lives, our businesses and our world.

Storytelling is central to the human experience.  As humans, we are wired to understand the connection between cause and effect via stories.  We think in narratives all day long.  Whatever our physical world may look like and however we choose to move through it, it is the narratives we create and pass along that bind us and the places we inhabit in a level of coherence that enables progress toward goals, actions and results.  Of course, this is not new.  What is a more recent element of the story making and telling process is the ability to incorporate the immense amounts of data that we can now generate and aggregate into a data-driven narrative through the use of analytics.

Data tells you what’s happening. Stories tell you why it matters.

This is where “the rubber meets the road” in the world of big data.  Data is inert until animated by the mathematical models that transform it into elements of insight that can be woven into a narrative that makes the complex simple and the overwhelming into something digestible and understandable.  With a data-driven story, hundreds of millions of rows can be distilled into a unique story. By following that narrative, it’s much easier to understand what’s going on beneath the surface. The data and corresponding analysis can tell you what’s happening, but you need a story to articulate the importance and the potential impact, allowing you to make decisions that are more targeted and supported.

But, storytelling is about more than simply understanding and articulating one’s world, though that is critically important.  Stories that incorporate data and analytics can be catalysts for change, driven by the insights and actions that result from “crunching the numbers”.  The impact of big data can be extraordinary with the potential to influence much of the way things will be done in the future but that requires moving out of the realm of the quants.  Telling the stories, with data and analytics, can communicate the who, what, how, when and where of the business, creating context for making strategic and tactical decision, both big and small.  To tell a great story with data and analytics, data scientists must begin to think like storytellers.

Decision science has been around for decades but computing power, communication speeds and smart technologies have driven the need for better analytic tools.  Big data is big and getting bigger and our methods and means of analysis have become faster, finer and more robust and that creates both opportunity and threat for the enterprise.  Extract insights from the data and craft a story that resonates with key constituencies and you create competitive advantage.  Bore them with spreadsheets and charts and you just may find yourself out of business.

Big data and analytics have now entered the realm of must have for the enterprise to realize the greatest success.  Storytelling has always been thus.  The combination has the potential to change the way we do everything. But the holy grail has to be the story; the story that communicates what is happening in the business and what can and needs to be done to address the challenges and exploit the opportunities that the analysis uncovers.

Perhaps most importantly, though, stories motivate action. And in today’s world of information overload, it’s crucial to be able to make informed, actionable decisions based on all of your data. 

By using analytics to create a compelling story, big data can become the transformational force that it’s promise has suggested it can be.

 

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The Shrinking Lifecycle of Business Models

McKinsey & Company continues to publish some solid thinking on innovation and the evolution of business models.  While I have long argued that business models are much more ephemeral owing to the continuing impact of digital technologies, I do think the article reinforces that thinking while providing a simplified approach to reframing one’s thinking about business models.  From the article, Disrupting beliefs: A new approach to business-model innovation 

Let’s face it: business models are less durable than they used to be. The basic rules of the game for creating and capturing economic value were once fixed in place for years, even decades, as companies tried to execute the same business models better than their competitors did. But now, business models are subject to rapid displacement, disruption, and, in extreme cases, outright destruction.

Every industry is built around long-standing, often implicit, beliefs about how to make money.  These governing beliefs reflect widely shared notions about customer preferences, the role of technology, regulation, cost drivers, and the basis of competition and differentiation. They are often considered inviolable—until someone comes along to violate them.

 

Surprising Stats Regarding the Internet of Things

CMO.com publishes a weekly column, "Mind Blowing Stats"  that collects disparate and sometimes arcane data points about a specific topic.  A recent edition of the column highlighted the great traction and movement forward that IoT is achieving though most people, and companies, don't recognize how fast the technology is being embraced.  From the column:

1. In 2008, there were already more "things" connected to the Internet than people. By 2020, the amount of Internet-connected things will reach 50 billion, with $19 trillion in profits and cost savings coming from IoT over the next decade.

2. Connected homes will be a huge part of the Internet of Things. By 2019, companies will ship 1.9 billion connected home devices, bringing in about $490 billion in revenue. Google and Samsung are already ahead of the pack. Google bought smart thermostat maker Nest Labs last year for $3.2 billion, and Samsung purchased connected home company SmartThings for $200 million.

3. Right now, most IoT smart devices aren't in your home or phone; they are in factories, businesses and health care. By 2025, the total global worth of IoT technology could be as much as $6.2 trillion--most of that value coming from devices in health care ($2.5 trillion) and manufacturing ($2.3 trillion).

4. Only 0.06% of things that could be connected to the Internet currently are, which means 10 billion things out of the 1.5 trillion that exist globally are currently connected.

5. By 2020, it’s estimated that 90% of cars will be connected to the Internet as compared to 10% in 2012.

6. The connected kitchen will contribute at least 15% savings in the food and beverage industry by 2020.

7. By equipping street lights with sensors and connecting them to the network, cities can dim lights to save energy, only bringing them to full capacity when the sensors detect motion. This can reduce energy costs by 70% to 80%.

8. GE estimates that convergence of machines, data, and analytics will become a $200 billion global industry over the next three years.

9. More than two-thirds of consumers plan to buy connected technology for their homes by 2019, and nearly half say the same for wearable technology. Smart thermostats are expected to have 43% adoption in the next five years.

10. In 2008, Proteus Digital Health created a pill with a tiny sensor inside of it. The sensor transmits data about when a patient takes his medication and pairs with a wearable device to inform family members if it's not taken at the right time.

11. A whopping 94% of all businesses have seen a return on their IoT investments.

12. Wearables will becomes a $6 billion market by 2016, with 171 million devices sold, up from $2 billion in 2011 and just 14 million devices sold.

13. Currently, 7% of consumers own a wearable IoT device, and 4% of consumers own an in-home IoT device. Nearly two-thirds of consumers plan to buy an in-home device in the next five years, and wearable technology ownership will double by 2015—increasing from 7% in 2014 to 14% by 2015. By 2016, wearable technology is expected to double again and reach a total of 28% adoption rate.

14. Among wearable technology devices, wearable fitness applications and technology stand to see the most growth in the short term, with 13% of consumers planning to purchase within the next year and a total of 33% looking to adopt in the next five years. Smartwatches are the second most popular wearable device, with 5% planning to purchase in the next year and a total of 23% planning to adopt in the next five years.

15. Although the mass adoption of connected technology is likely in the long term, the majority of consumers (87%) haven’t heard of the term “The Internet of Things.”

 

The True Internet of Things

A recent article in the Deloitte Review by Tom Davenport and John Lucker provided some much needed context around the quickly expanding conversations on the Internet of Things (IoT).  Having written about the IoT often over the past 15 years, I have witnessed the term be applied too often to the mechanics of machine-to-machine (M2M) communications with less thought given to the broader impact of all those devices connecting and sharing information and data.  While we are still trying to get our hands around Big Data and ensure that we realize all the value we can derive from that aggregation and analysis, IoT will almost certainly create more data, often in much greater detail, than what many have imagined big data will comprise.  For Davenport and Lucker, the real imperative in IoT is to focus on the integration, analysis, value-add, and action processes around IoT data.  To that end, they define IoT as much more than M2M .

The “Internet of Things” (IoT) is often described as a collection of connected sensors, but it is actually a much more complex concept. It involves not only the connection and integration of devices that monitor the physical world—temperature, pressure, altitude, motion, proximity to something else, biometrics, sound, images, and so forth—but also the aggregation, relationship, and analysis of the information those devices create in order to take action on the situation, and the business and technology changes required to use the data and analyses.

Davenport and Lucker propose a hierarchy of sophistication when leveraging all the data and information created by an IoT ecosystem.

Local Sensing

At this local level of the IoT, the activity tracker is typically connected to one or a few other devices for simple actions and data gathering.

Data Integration

Integration of the data is necessary for analytics and control to take place.  At the moment, this is the most challenging area of the IoT.

The Analytics of Things

Much of the benefit of the Internet of Things lies in our ability to leverage the (useful) data we collect with it.

Cognitive Action

This is the business problem that the IoT is solving for your company or its customers.

The Landscape for the Internet of Things

The growth in Internet of things will far exceed that of other connected devices. By 2020, the emergence of mass-market smart phones, phablets, and tablets, combined with a mature PC market, will result in an installed base of about 7.3 billion units, used by an expected human population of 7.7 billion.  In contrast, the Internet of things will expand at a much faster rate, resulting in an installed base of about 26 billion units at that time. Installed base is the key metric here because it drives the value of service revenue, and it aggregates communications bandwidth and data center activity.

Source: Gartner Inc.

"This is a Generic Brand Video" Video

Funny and disquieting on multiple levels, this is a creative evocation of  Kendra Eash's brilliant advertising takedown, "This Is a Generic Brand Video," originally published by McSweeney's.  Stock video provider Dissolve has taken the text of Eash's screed and set it to actual stock video clips.

From Adweek:

The results, narrated by Dallas McClain, are outstanding. You've seen all of this footage in ads from major brands. It's everywhere. And it's great that a stock video house would so gleefully celebrate the soul-sucking manipulations for which its offerings are generally used.

Watch below, and have an epiphany on how you can continue to make marketing, and brand building, more credible going forward.

 

 

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The Growth of the Internet of Things (IoT)

Cisco continues to be among the vanguard of enterprises that are embracing the emerging Internet of Things (IoT).  John Chambers, CEO of Cisco, recently delivered another speech on the concept and the bottom line, from Cisco’s viewpoint, is that the IoT is going to be a $19 trillion profit market in the next few years. That includes $2.9 trillion for manufacturing alone. Internet of Things is becoming the backbone (at least in rhetoric) of Cisco's overall business strategy, and Chambers pointed in that direction once again, stressing that Cisco's IoT game plan combines the company's cloud strategy with data analytics, mobile, collaboration, and most important of all, security.