Tuesday, August 13, 2019

Smart, fast, innovative and digital

The title of this post is the answer to the question:  what does my business need to look like in the future in order to be successful?  I think that increasingly we can make the assumption that the pace of change will remain about the same, the world and markets we participate in will remain volatile and the increasing effects of the digital transformation will only increase.  Therefore, slow, rigid, dumb companies that cannot evolve quickly, cannot become nimble and can't innovate are already dying a slow death.  I'm looking at you, Sears.

I think most people would agree that the factors I've listed in my post title are conditions for future success, but many might debate the depth of knowledge or engagement that is required to really succeed.  Further, it may be apparent that many of these attributes are desirable, but they may be addressed in a siloed or discrete manner, rather than with the understanding that these aren't discrete or standalone capabilities but are mutually reinforcing, and need to be continuous capabilities.  To compete effectively you can't simply make a one-time digital transformation and rest on that new infrastructure.  Digital will keep changing and your new platform will need to change with it.

The same is true with innovation. Your company might "become" innovative but once it has achieved this milestone it must continue to conduct and perfect its innovation chops.  There are no one time effects in the race to remain relevant.  These aren't throw away lines in a management report or one time showcase projects.  These are the new operating realities.

Digital and Smart

These two factors are a good case in point.  It is entirely possible to be digital - to have a lot of digital, automated processes and good data management and hygiene and to be relatively dumb.  Having a digital framework and good data management does not ensure the ability to act with insight and precision, to become a "smart" organization.  Even in companies that are making the digital transformation today, too much of the data remains uninterpreted and unused, and decisions are made without the benefit of good information and insight.  It's not enough to make a digital transformation, because no one really knows what that means.  It's more important to use digital techniques and tools to become smarter than your competition.

Digital and Fast

Again, two factors that could work together that are at risk of working in opposition.  Digital transformation means creating new processes, managing data more effectively, automating processes which should enable speed and agility, but in many cases simply reinforces the status quo and blocks agility and change.  Ask yourself - does our digital transformation work help us work faster, to become more nimble and agile, or does it simply create barriers to new change?

Being digital should enable a company to work at greater speed, to be able to anticipate course changes and move with agility.  So far many "digital transformations" I've seen do the opposite.

Digital and Innovative

Finally, we reach the culmination of the review.  Being digital does not ensure that your company will become more innovative.  In fact it could mean the exact opposite.  If you are doing digital transformation you are implementing machine learning or artificial intelligence, robotics or IoT.  You are improving your ability to gather, manage and use data.  In other words, your teams are using their engineering brains.  Are you at the same time using your creative brains to imagine new solutions, new ideas and discover new opportunities and problems?  More importantly, is your digital transformation guided by the need for efficiency or the quest for better innovation?

The key word is AND

Future competitive strength will reside in organizations that are smart, fast, digital and innovative.  As the subheading suggests, the key word is "AND".  These capabilities aren't mutually exclusive - they rely on each other for greater success, and can't be one time activities - they must become internal capabilities that are constantly evolving and improving.  When you stop working on one of these, all the rest will suffer.  We have to learn to think differently about our companies, their operating models and internal core competencies and capabilities and prepare them to work in a new way, where digital is a priority, where speed and innovation are paramount and where intelligence and insight guide every action.
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posted by Jeffrey Phillips at 7:08 AM 0 comments

Wednesday, August 07, 2019

Digital transformation marks the demise of product innovation

There comes a time when every phenomenon reaches its zenith, before a long fall or a sudden collapse.  We like to refer to this point in the cycle as the "tipping point" - the point at which we can remain in stasis or the structures will collapse.  We are warned that we are close to the tipping point for global warming, for example, where more carbon dioxide in the atmosphere may result in weather and climate changes that create catastrophic change in the weather, sea levels and other factors.

I'm going to stipulate that the business cycle and innovation are at a tipping point.  For close to 20 years (dating approximately from when Jobs returned to Apple) we've been living in the product innovation era.  That era I believe is rapidly drawing to a close, and shortly will collapse, because of other factors such as digital transformation.  When the transition occurs, those companies still focusing on discrete product innovation will be left in a difficult place, because the skills they are building and the focus on product innovation will be less important than emerging abilities in digital transformation and in agile, nimble business models.  They will have succeeded in preparing to fight the previous war, as my military friends like to say.

Several converging forces

There are several reasons why we'll see at least a slow decline in product innovation, if not a collapse.  First is corporate, especially executive cynicism.  Innovation hasn't delivered on its promises in many cases.  There are many reasons why, most notably the inability to accept risks and learn from exploration, as well as the fact that most businesses are too locked into their operating models, business models and markets to do more than incremental innovation.

The second reason is that we are reaching the point of feature saturation.  Most companies don't innovate entirely new products.  For the most part they add additional features and capabilities to existing products.  When cars compete on the number of cup holders and TV remotes require a PhD to determine how to use them, we've reached feature saturation.  There's really not much further we can go with many of the existing products.

The third reason for forecasting a rapid demise in product innovation is the emergence of digital transformation.  As data becomes more important and frankly more valuable and scalable than tangible products, companies will shift to digital products or products that produce data.  What they haven't yet realized is the digital transformation will require shifts to their business models and revenue streams.  Digital transformation will require that companies become a lot more agile and nimble, able to adjust their business models and revenue streams as customer demand shifts.

There's a silver lining in that cloud

If this all sounds a bit dire or ominous, take heart.  There is a silver lining for those companies that recognize where we are on the life cycle of the product innovation era, and what's about to unfold.  Digital Transformation holds within it the demise of physical product innovation but contains within it the new opportunities for business model agility and innovation.  Big businesses will simply have to think differently about what their operating structures and models must be.  No longer will they be able to tinker on the edges with new products.  Innovation will move to the very core of the business, to consider what all the new data means, and how to take advantage of the data streams and insights.

Digital transformation can open up an entirely new way of thinking about innovation, but that innovation will focus on what has traditionally been the most resistant to innovation and change - the existing structures and business models.  Companies that realize this and become more flexible, nimble and agile will use digital transformation to innovate how they operate.  Other firms will do some digital transformation but attempt to retain their old business models, and will collapse due to the conflicting goals of old models and new data.

The future is here, just not widely distributed

If this all sounds futuristic, you aren't looking close enough.  Some of what I'm writing about is already here, just not widely distributed.  Airbnb and Uber are examples of what a more nimble, asset-less company might look like.  Time will tell if they are the avatars or just the next iteration on a journey toward a new type of company.  Companies that understand how to use the data that digital transformation creates and create business models, revenue models and operating models based on the data and needs of customers will succeed, and they'll operate in a different fashion, with different structures and different models than companies do today.

It's both a challenge and an opportunity, blending digital transformation and new innovation models.  Are you ready for some real change in big corporations?  Or, will they slowly wither and die as newer, more nimble players demonstrate the ability to use data effectively?

Digital Transformation will also transform Product Innovation, by the way

There is one really ironic twist to all of this.  Just as we are 'ending' an era of product innovation, digital transformation will revive product innovation, mostly by adding new sensors and IoT capabilities to existing products.  If the data is valuable (and it is) companies will want to gather and harvest the data in any way they can, so more products will become smart and connected.  That's one way the product innovation era will be extended, mostly to the benefit of digital transformation and data.

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posted by Jeffrey Phillips at 6:04 AM 0 comments

Friday, August 02, 2019

Challenges when innovating smart, connected devices

I've been struck by the importance of two rapidly converging forces - digital transformation and new product innovation.  As we've discussed, here and elsewhere, ad nauseam, there is increasing demand for new products and services, making stretching the capacity of tenuous innovation processes and teams.  When we add in the new requirement that many of these new products must also be smart and connected, innovation gets a lot more interesting and a lot more difficult.

What does it take to create not just a new product, but a new product that is smart and connected?  Certainly it takes more than simply gluing a sensor to an existing device.  If only it were that simple.  Let's think about what it takes to create smart and connected new devices by considering the simply air filter.  Yes, 3M has released a smart and connected air filter.  As I noted in a previous post, capital equipment (tractors as an example) have been smart and connected for years, but when the concept jumps to consumables like air filters, literally any device can be smart and connected, and that changes everything.

Smart AND connected

First, let's talk about our language.  There are a number of what I'd call "smart" products that capture data or respond to surroundings.  These devices can analyze the environment and turn on or off or take a specific action.  They are somewhat "smart" in that they operate in a way that responds to commands or to the environment.  But many of these aren't necessarily connected to the internet or other systems.

Smart and connected requires that the product include senors and other IoT capability AND share that information with the consumer and with the manufacturer or distributor through the internet.  When the data is shared beyond the household, the smart and connected device becomes the basis for a new potential revenue and business relationship.

What's more important, the product or the data

Using 3M's air filter as an example, we can begin to see that the end product will become the razor and the data created and shared will become the razor blades, only in reverse.  The air filter's value to 3M in terms of revenue and profit is marginal, but the value of the data gathered, managed, analyzed and repackaged is much higher.  As the data is shared, and aggregated from other sources and combined with other geographic, demographic or psychographic data it creates insights for new products and new services and can be packaged and sold to others.  This in turn offers the potential for new business models, new recurring relationships with consumers that the company can control and monitor and new product development based on insights from the data.

Emerging impact on customer experience

A smart connected filter also means that 3M can create and leverage new customer experiences.  Previously if I acquired an air filter I did so based on availability and cost, since the filters were mostly commodities.  If I acquire the 3M smart filter and download the app and have a good experience learning about my usage and in the reordering process, I may "lock in" to 3M's products and even a recurring revenue stream if the customer experience is good.  For a product where traditionally customer experience wasn't important, suddenly secondary issues like customer experience with reordering or the applications or data presentation matters.

Managing and harvesting data

There are so many considerations when transitioning a traditionally "dumb" product to a smart, connected product.  I've noted the challenges with customer experience just above.  Another is the nature and volume of data that will be generated, and the importance of gaining insight and value from that data.  While many of these products may not generate a lot of data, the aggregate data generated will be significant.  Imagine that 3M sells hundreds of thousands of air filters in a year and each is connected and shares even just a few bits of data every day.  That data provides a baseline about product usage.  But when consumers sign in to 3M's app more data becomes available - the customer's location, purchase preferences, reordering models and so forth, for every home that has a smart device.  With that data 3M can then merge their data with more data about location, geography, neighborhood incomes and other data to get a full picture of the client profile, usage, buying patterns and other data to use to improve products, offer new incentives or advertising or package and sell the data.

Transition from dumb to smart and connected

So, far from a simple transition, there are significant shifts when moving to a smart, connected device.  Beyond simply adding a sensor and connectivity, which are not simple but are probably the easier activities, companies will have to consider the data generated and how to obtain value, the enhanced customer interaction and experience and the potential impact to existing business relationships and business models.

If you find that this is more complex than you first imagined, you are right.  My team can help think through this with a framework we've built that considers many of these components to a successful smart, connected device as part of innovation and new product development.  Contact us if you'd like to learn more. 


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posted by Jeffrey Phillips at 7:21 AM 0 comments

Wednesday, July 31, 2019

The conflict between digital transformation and speed

Just one more post about the importance of speed and agility and I'll leave this tired trope alone.  It took over 50 years for a reasonable majority of US households to obtain landline telephone service.  It took less than 10 years for a majority of households to obtain cellphone services and less than a handful of years for a majority of households to access and use Facebook.  There are a few points to make about that progression:

  • The initial investments were huge - putting wires up all over America, especially when many people still lived in rural areas, and the costs and benefits of a home phone were tenuous.
  • As people became convinced that home phones were valuable, cell phones emerged and again the cost/benefit was relatively uncertain when anyone could drop a quarter into a neighborhood pay phone.  When the phones started offering other features and immediate convenience became paramount, cell phones really accelerated.
  • Facebook and other platforms are built on the previous two ideas - ubiquitous connectivity through a global backbone and often wireless connectivity based on smart phones.  Building on these or other platforms, one can get to the market much more quickly and efficiently for digital products.
These ideas matter because we are increasingly acquiring digital products and exchanging information, even when we are acquiring or using physical products.  Thus, the idea that "digital transformation" is vital almost goes without saying.  What few people are talking about is the conflict between being "digital" and acting at speed.

Mutually reinforcing or at conflict?

The supporters and especially the vendors who are backing "digital transformation" want you to believe that you can work at speed only through digital transformation, and for the most part they are right.  But what they aren't telling you is there is no final destination for digital transformation.  It isn't a place on the map, but a journey that once started never reaches a destination.  Once you create fully digital business processes you'll need to collect and manage the data and obtain insight from the data to put back into your business.  Analyzing and understanding the data generated is just as important (if not more so) than simply automating and digitizing the processes.  Yet analyzing and understanding the meaning of the data is more difficult and more time consuming.

So good digital processes and insights CAN offer more speed to insight, speed to product and speed to market.  But only if your systems and processes are tuned to digital work, and only if you can manage the data generated.  But as only close observer of the IT revolution knows, once on the treadmill, you can never get off and it only goes faster.

Plus, there is a "dark side" to technology and the IT that supports it.  Any architecture that makes you efficient, able to process more data or make more decisions, often also makes your processes and decision making more structured and more rigid.  ERP has proven this time and again, helping organizations work more efficiently but often locking them into older operating models and processes.

Will digital transformation be an accelerator or an inhibitor?

The reasonable answer to the question above is:  yes.  Initially, digital transformation will accelerate business operations.  Of course many companies are just beginning this journey, and are learning how to make sense of the data they generate and obtain new insights.  Once they begin to fully engage the benefits of digital transformation, will these mechanisms and processes become enablers or barriers to future changes in business models?  If history is any guide, we can project that digital transformation will become first an enabler, and then potentially a barrier to agility and speed.

That's because any new implementation is first a disruptor and then becomes the norm, to be coddled and protected.  Plus, an additional challenge is that the more data is created and the more valuable it becomes, the more important it is to manage and analyze the data, creating a vicious cycle.  One wonders at the amount of data that will be generated in the next few years and how much of it will be actively and successfully analyzed and interpreted.

Speed and agility will be paramount

One other item - no matter how important the data becomes, moving with agility, decisiveness and speed will always win.  The ability to preempt competitors and customers with attractive and viable solutions, getting there first with the best product and accruing as much market share as possible, will be the deciding differentiator.  So no matter how much data you can accumulate and analyze, if it becomes analysis paralysis, slowing and diverting your company from working at speed, digital transformation won't be helpful.

The question companies should be asking themselves in the face of digital transformation messaging is:  how does this digital transformation help me make better decisions faster, and move at better and more decisive speed than my competitors and customers?  If you can't answer that question definitively, reframe your digital transformation activities and projects.  Notice I did not say "stop" those projects, because you should be experimenting now.  But these projects must help you get smarter and faster simultaneously.  Getting smarter without getting faster is second or third place.  Getting faster without getting smarter is suicide.
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posted by Jeffrey Phillips at 7:42 AM 0 comments

Friday, July 26, 2019

Don't break the rules - become flexible and agile

I've read yet another good and insightful piece on success in digital transformation, which relies on an unfortunate metaphor - one about "breaking the rules".  I've been around consulting just long enough to have "broken the rules" in the business process re-engineering wave, the ERP wave, the CRM wave, the Six Sigma wave, the innovation wave and now the digital transformation wave.  Each one of these relatively significant changes in how business operates had experts writing about "breaking the rules".  In fact by now, if you've lived through several of these management phenomenon you should be a rule-breaker in chief.  But all of this rule breaking begs a few questions:
  • Who is setting these 'rules'
  • Where are they written down
  • How might we restructure or rethink the rules
  • Are these rules really just the embodiment of culture, past thinking and lethargy
  • What are the "new rules" about how we should structure and manage companies for maximum efficiency
I think this idea of rule breaking is inarticulate and often just a lazy trope.  Rather, what we should be working on is changing not "the rules" but how we think about business, how business operates, and how we best engage customers and their needs.

The Rules

If we are going to talk about "the rules" of business, most management gurus think there are only a few, and those are very flexible.  My favorite set of rules was put forward by Peter Drucker, who said a business had only two imperatives:  marketing and innovation.  He felt everything else were costs.  If we were naive enough to ask any business executive about "the rules" of their business, they'd likely chuckle.  There aren't any rule books, except what regulatory bodies produce.  Businesses form their own, mostly intangible "rules" based on past history, profit guidelines and management experience.  These are then supported by managers who want consistency, low risk and low variability.  The rules - such as they are - are unwritten, informal and based on maintaining existing capabilities and processes.

Breaking the Rules

Since every major management phenomenon over the last 30 years (BPR, Six Sigma, ERP, Innovation, Digital transformation) starts by arguing we need to "break all the rules", we clearly need to take a long, hard look at how businesses operate, and how the internal, informal thinking is created and propagated, because every new advance seems to require that we break the rules and start afresh.

Or, perhaps what we really need to do is to create organizations that are more nimble, more agile, much more dynamic and capable of evolving as new thinking evolves and as customers and markets evolve.  In other words, it's not the rules that need rethinking - it's how we organize, structure, compensate, incentivize the organization and how deeply we engage with existing and future customers

Not rules but engagement

Rules are restrictive and binding, they keep ideas, people and processes in line.  They create fixed ways of thinking and lead businesses down blind alleys, because allegiance to the 'rules' becomes more important that seeing what's actually happening and reacting to the emerging changes in the worst case or working proactively to adapt to operational and market changes in the best case. 

The experts who tell you to "break the rules" are suggesting that we should remake a business and then conform to a new set of rules that apply to the latest emerging phenomenon.  If the new phenomenon is "digital", then we must all become digital, and quickly lock in this operating model.  This only leads to new, definitive operating models and rules.  Instead we need to break this cycle and create organizations that are much more adaptable, flexible, fungible and that can evolve and adapt quickly as markets, competitors and customers evolve and new capabilities or threats emerge.

Less efficient but less dramatic

The challenge with a more flexible and dynamic organization is that it will be by definition less efficient and perhaps less profitable than a more 'rules' driven, efficient but inflexible model.  Investing in adaptability means more training, more consistent change over time, better systems and communication.  However, a more flexible and adaptable business model will be more engaged with customers, much more able to change as new thinking and new models emerge.  A more flexible and adaptable business won't have to periodically "break all the rules" and adapt - or appear to adapt - the latest management thinking.  Flexible and agile models will simply incorporate the best parts of new thinking and new engagement models on the fly.

Periodic drama or constant evolution

So the real question is - do you prefer periods of steady state operation periodically interrupted by the drama of adopting new management thinking or a constant evolution based on more agile and flexible business models?  Many of the operating models we see today are structured for a time when change was slower and less dramatic. They are built for a time when there was less change and more certainty.  They are increasingly unprepared for a more dynamic market and more fickle customer base.  These older models that require constant rule breaking are living relics of a past which simply haven't recognized they are anachronisms soon to become living fossils.

What will be more interesting is to see how newer business decide to structure themselves, the operating models they adopt and the corresponding agility and flexibility of newer models.  For some, there may be a little bit less profitability and efficiency but much greater adaptability and far less periodic drama as new thinking emerges or new demands unfold.  Isn't that what we ultimately want - implementing the best thinking and engaging customers in the best way possible, as quickly and efficiently as possible?
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posted by Jeffrey Phillips at 5:34 AM 0 comments

Thursday, July 18, 2019

Smart and connected devices change everything

In my last post I wrote about a big transition in innovation that will occur in the near future - when the tipping point is reached and most innovation is focused on smart, connected devices as opposed to dumb products.  Currently, most of the innovation that is created is focused on new software applications or on new physical products, but with little integration between them.  In the near future, we'll see a convergence to the point where smart, connected devices become the norm.

What powers these smart, connected devices?  Sensors and IoT capabilities, which can gather data or receive data, along with some basic intelligence on the device.  Given Moore's law we can assume that systems on a chip become exceptionally inexpensive, and the last major hurdles to lots and lots of smart connected devices are power and connectivity.  Connectivity will get solved as 5G rolls out - in the meantime connectivity will be provided by WiFi or other means.  Once really low power chips are ubiquitous or chips can be passively powered, every device can be a smart connected device.

Forget IoT?

The headline suggests that I think we should forget IoT, the ubiquitous internet of things.  I think we should forget that because IoT is a feature and a platform that will provide capabilities that we have yet to consider, but we should focus more on the opportunities and benefits that IoT capabilities and ubiquitous connectivity provide.  As 5G and IoT capabilities unfold, and low power or smart power comes into existence, almost any device can become smart and connected, sharing data with an advertiser, a data collection company, the manufacturer, all of the above, or some other company.  This is when we enter the era of Really Big Data (RBD).

People today talk about Big data - data lakes, data estates and so on.  What happens when the majority of the devices you own - and I'm not talking about iPhones or PCs that are meant to process information but your average consumer device - has the capability to publish data?  Suddenly millions of everyday salt shakers, plastic tumblers, yard ornaments and more are recording and publishing data.  We are only a few years from this reality.  When this happens, we'll see that the data generated by these devices, collected and harvested and analyzed, is far more valuable than the devices themselves.

Smart, connected and free

We'll need to innovate in a market where many low cost devices are smart, connected and may need to be free, where the revenue is recouped in gathering, aggregating and monetizing the data streams.  This of course changes the entire business model.  We'll have to innovate our business models to account for a shift from a one time purchase to a range of revenue recognition models, and most companies that today rely on shipping metal or plastic for a revenue stream will need to become companies that make money from the data they generate or the ads or other means of monetizing data.  In other words, every company, regardless of what they make, becomes a data company.

Innovation shifts to the intangible

In this outcome, innovation is no longer the responsibility of the R&D team.  Innovation is the responsibility of the strategic team, the business teams and the data scientists, because the physical features of the product are much less interesting than the data that can be generated and how the data and relationship with the customer is monetized.

In other words, the way you innovate will change, who innovates will change, and the outcomes you generate will change.  Oh, and at least a portion of your business model and revenue recognition models will change, and you'll either need to become much, much better at managing and monetizing data or create relationships with partner companies that can do this for you. 
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posted by Jeffrey Phillips at 4:48 AM 0 comments

Monday, July 15, 2019

Learning to innovate in the IoT Age

Lately, many commentators are given to sweeping claims about seismic change.  We are either in the 3rd or the 4th industrial revolution, depending on the commentator.  It can be hard to keep up.  However, where there is smoke there is often fire.  These commentators are correct in the sense that we are entering a time where the Internet of Things (IoT) and the data generated by billions of IoT devices will create radically new opportunities for innovation.  In one sense that fact is a good thing - it means innovation takes on an entirely new life.  In another sense it is a difficult thing - because so many companies haven't mastered the basics of innovating yet, before the deluge of data changes everything.  Innovation is about to get a lot more interesting, and I think a lot more complex.

If innovation today is like playing chess, innovation in the IoT age will be like playing three dimensional chess against several opponents simultaneously.  Companies that have mastered innovation today (and there are few that are really good at innovation now) will face much more complexity in innovating in the future.  Companies that have avoided innovation or who have fiddled around the edges are about to encounter a much more difficult task.

What makes innovating in the IoT Age challenging?

Until a few years ago, the vast majority of products were "dumb" products.  That is, they weren't connected to the internet or communication channels and did not create or publish data.  Your average physical product exists in a space outside of the internet and neither collects, generates or receives data.  As IoT devices and capabilities expand, this is going to change, and when it changes it changes everything.

Take for example my favorite insulated cup that I drink my breakfast beverage from every day.  It does not have sensors or IoT capability.  But if once it does, and if it connects to the internet to share data about my location, my beverage or other data about my life and experience, a number of things change in the creation and use of the cup, and the ability to obtain value from the cup after the purchase.

First, consider the creation of the cup.  Mass production of the insulated cup is simple without a sensor, but becomes a bit more complex by adding sensors, since the sensor must also have power or receive power from the environment, must gather data and share that data with the manufacturer through communication channels like Bluetooth or WiFi.  Simply designing and manufacturing the cup becomes more interesting, but that's the easy part.

Next, think about the business model implications of a connected cup.  One could imagine the ability to sell the cup with the sensor at full price, allowing the customer to determine if or when the sensors are turned on or connected to the internet.  Alternatively, one could imagine a business model in which the cup is provided at cost or perhaps even for free to consumers in return for full access to all the data generated.  In other words, there are many possible business models and consumer relationships possible where as in the past there were few.

Next, consider all of the data.  There are thousands or perhaps millions of insulated cups.  If all join the internet and share data, all of that data must be capture and managed.  We could go into a rather interesting discourse on what happens when millions of different products, each of which are acquired by millions of customers, all generate data every day.  The sheer volume of data generated by even a few IoT devices in your home is difficult to imagine, and also carries exceptional value.  AI and Machine Learning will be vital in many cases to parse out this data and combine it with other data to create new insights, recommend new offers, suggest new features.  However, most companies aren't ready to manage all the data, much less create value or insight from all that data.

So what's this got to do with innovation?

Today innovation is easy.  We understand customer needs or "jobs to be done" for a product or service and build a relatively simple, typically dumb product to meet those needs.  Since the product is dumb, we don't worry too much about business models, revenue models, data and data management, customer experience and other considerations.  Innovation today is primarily focused on getting the product's features - primarily physical features - right and getting the product to market on time.

As IoT enabled products become an increasing reality, innovators have to consider a much larger scope.  They may need to consider different revenue models or business models.  They may need to consider how data is captured, exchanged, and even monetized.  They may need to think about how data may enhance or detract from a customer experience.  They may need to consider how to augment their product with readily available third party data.  In other words, innovators will be forced to think through a number of alternatives and possibilities that just aren't on their radar today, and more importantly all of these considerations are intertwined.  For example, if you capture data, could that have an impact on the cost of the product?  The customer usage and experience of the product?  Will the data have value that can be monetized? 

Learning or relearning how to innovate

All of these factors and more are why I say that every firm will need to rethink how they innovate, and most will need to gain a much broader understanding of what innovation is, and what the product, service, business model and ecosystem considerations are for their products today, and more importantly in the future.

What innovation teams used to worry about were primarily physical features inherent to the product.  In the near future these issues will still remain top of mind, but will compete with issues and challenges related to data capture and exchange, business model and revenue model options, customer service and customer experience considerations and likely the need to involve third parties to provide data, data exchange, support or service for a connected device.  And all of that must be considered in the front end, a place that many companies haven't invested enough in up till now.

The companies that have mastered innovation will need to expand the definition and scale.  Those that have not mastered simple product innovation are about to be faced with a much more daunting challenge.  I'll address some of the factors that companies must consider when innovating in an IoT Age in a subsequent post.
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posted by Jeffrey Phillips at 7:48 AM 0 comments