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Why The Heck Can’t We Change Our Product?

Screen Shot 2016-02-08 at 10.48.08 AM

I drove by the fork in the road and went straight.
— Jay-Z (see author’s endnote)

One of the most vexing product challenges is evolving the UX (user experience, and/or user UI) over long periods of time, particular when advancing a successful product with a supportive and passionate community.

If you are early and still traveling the idea maze in search of product-market fit, then most change is good change. Even in the early days of traction, most all changes are positive because they address obvious shortcomings.

Once your product is woven into the fabric of the lives of people (aka customers) then change becomes extraordinarily difficult. Actually that is probably an understatement as change might even become impossible, at least in the eyes of your very best customers.

The arguments are well-worn and well-known. “people don’t like change”…”muscle memory”…”takes more time”…”doesn’t take into account how I use the product”…”these changes are bad”…”makes it harder to doX”…”breaks the fundamental law of Y”…”what about advanced users”…”what about new users”…and so on. If you’re lucky, then the debate stays civil. But the bigger the product and the more ardent the “best” (or most vocal?) customers, well then the more things tilt to the personal and/or emotional.

Just this past week, our feeds were filled with Twitter rumored to make a big change (or even changing from Favorite to Like), Uber changing a logo, and even Apple failing to change enough. It turns out that every UI/UX change is fiercely monitored and debated. All too often this is a stressful and unpleasant experience for product designers and an extremely frustrating experience for the customers closest to the product. Even when changes are incredibly well received, often the initial response is extremely challenging.

For all of the debates, a product that fails to dramatically change is one that will certainly be bypassed by the relentless change in how technology is used.

Yet change, even of a core user experience, is an essential part of the evolution of a product. For all of the debates, a product that fails to dramatically change is one that will certainly be bypassed by the relentless change in how technology is used. We do not often consider the reality that most new products (and services) we enjoy are often quite similar to previously successful products, but with a new user experience.

Consider that the graphical interface for spreadsheets and word processors replaced whole companies built around predominantly similar capabilities in character mode interfaces. The competitive landscape for browsers was framed by having minimal interface. Today’s SaaS tools often lead with capabilities similar to legacy products expressed through consumerized experienced and cloud architecture.

Technology platform disruptions are just that, disruptive, and there’s no reason to think that the user experience should be able to smooth out a transition. There’s every reason to think that trying to make a UX transition go smoothly might be a counter-productive or even a losing strategy.

The biggest risk in product design is assuming a static world view where your winning product will continue to win with the same experience improving along the same path that got you success in the first place.

The reality is that if you are not doing more in your product you are doing less, and doing more will eventually require a redesign and rethinking over time. The corollary is that if you are only doing what you’ve always done, but a little better every time, then as a practical matter you are also doing less relative to always-emerging competitive alternatives.

The biggest risk in product design is assuming a static world view where your winning product will continue to win with the same experience improving incrementally along the same path that got you success in the first place.

There are dozens of amazing books that tell you how to design a great user experience. There are seemingly endless books and posts that are critical of existing user experiences. There are countless mock-ups that say how to do a better job at a redesign or how to fix something that is in beta or already changed (see The Homer). Few and far between, however, are the resources (or people) that guide you through a major change to user experience.

No one tells you that you’ll likely face your most difficult product design choices when your product is incredibly successful but facing existential competitive challenges — competitive challenges that your most engaged customers won’t even care about.

This essay is is presented in the following sections:

  • User Experience Is Empowerment
  • Everyone’s A Critic
  • Pressure To Change
  • 5 Ways To Prepare
  • 5 Approaches To Avoid
  • Reality

User Experience Is Empowerment

At the most basic human level, the mastery of a tool (a user interface or experience) is about empowerment. Being able to command and control a tool feeds a need many of us share to be in control of our environment and work.

Historically we (all) seek to be the master of our “life tools” whether an shovel, a horse, a car, a PC, or the arcane commands of a modern social network. Something magical happens for a product (and company) when it is so compelling that people spend the time and effort required to master it.At that moment, your product becomes an essential part of the lives of customers, customers who come to believe their world view is shared by “everyone”.

Those customers become your very best customers who see your tool as a path to mastering some of the ever more complex aspects of life or work.Those same people also become your harshest critics when you try to change, anything.

A Story

Permit me to share an example of how this empowerment can work, deliberately using an historic example few will remember.

Some time in the mid 1990’s I was a product (program in Microsoft lingo) manager on Office and we were trying to figure out how to transition from a consumer app (yes we used the phrase consumer app back then) to an enterprise platform (that word was new to us). There were many elements to this, but one in particular was the setup and deployment of the Office apps.

As is often the case, customers were ahead of us on the product team when it came to figuring out the most efficient way to copy the Office bits (all 50MB of them) from floppies to a file server to desktops and laptops. Customers had all sorts of things they wanted to do when “installing” Office onto a PC — changing default settings, removing unneeded files like clipart, and even choosing which drive to use for the bits. Many of those could be controlled by the setup program that was itself an app requiring human interaction, save for a few select capabilities. PC admins wanted to automate this process.

As you might imagine, admins cleverly reverse-engineered the setup script file that was used to drive the process. This was a file that did for the comma what LISP did for parentheses. It was a giant text file filled with record after record of setup information and actions, with an absurd number of columns delineated by commas. In fact, and this is a little known embarrassment, the file was so unwieldy that to edit it required a non-Microsoft editor that could handle both the text file length and the line width. Crazy as that was, a very large number of PC admins became experts in how to “deploy” Office by tweaking this SETUP.INF. I should mention, one missing comma or unmatched quote and the whole system went haywire since it was never designed to be used by anyone but the half dozen people at Microsoft who understood the system and were backed by a large number of test engineers.

We believed we had a clever idea to solve a broad range of customization, security, and even engineering challenges which was to replace the fragile text file and third party text editor with a robust database and graphical interface. Admins could then push a customized installation to a PC without being in front of it and the PC could even repair an installation if it somehow got corrupted or munged. We really put a lot of effort into solving this with a modern, thoughtful, and enterprise friendly approach. Consumers would see almost no changes.

Then came the first beta test and what could best be described as a complete disaster. Of course the customers in the beta were precisely the small same set of customers that had figured out how to hack the previous system. We had little understanding that these customers had become heroes within world of PC Admins because they could get a new PC up and running with Office in no time flat. Many had become the “goto person” for Office deployment in an era when that was a big deal. Deploying Office had become a profession.

That should have been success for us on the Office team except we changed the product so much that everything special the admins had mastered had become irrelevant. They had lost their sense of mastery over their environment.

Looked at through another lens, implicit in the change is a devaluation of the acquired knowledge and expertise of these customers.

The pain was felt by our team as well. Our goal was to make things better for admins by replacing the tedious and error prone work with a platform and slick new tools. As an added bonus the new platform greatly improved robustness and reliability and added whole new features such as install on demand. All the admins saw, however, was a big change and subsequent loss of empowerment. Looked at through another lens, implicit in the change is a devaluation of the acquired knowledge and expertise of these customers.

It would have been easy to see how to take their very specific and actionable feedback and roll the changes back to what we had before, or to introduce some bridge technology (or other “solution” discussed below). On the other hand, the competitive forces that drove these choices including web-based and browser-based tools were increasingly real. The technology shift was underway. It was clear if we did not change the product and disrupt the established processes we would have only hastened a potential disruption of our business. The market was clear about the failures of the architecture we had in place.

Everyone’s A Critic

If you ever want to go for a record on the world’s longest comment thread then author a post on user interface suggesting how a product should be improved, fixed, re-done, or just rescued. On the internet, no one knows you’re a dog but everyone is a user interface critic and/or designer. Certainly well-intentioned, each person is genuinely responding to challenges they have with a product. Some of debates over the past few months in Windows circles over the hamburger menu or the discussions around iOS’ 3D touch show the many sides to how this plays out from friends and fans alike. As I type this, Twitter even has a trending hashtag on rumored changes to the product.

Some of my favorite posts have always been the ones where someone takes the time and effort to do a rendering to improve upon an experience I worked on/managed — “this is what it should look like”. The internet and tools make it easy to turn a complex and dynamic system design into a debate about static pixels and an image or two (or twenty). The ensuing debate might be narrowly focused on specific affordances such as “the hamburger menu” or whole themes such as “skeuomorphic versus flat” design.

The presence of renderings or “design alternatives” only add stress and uncertainty to what is already an emotionally charged and highly uncertain process while at the same time creating a sense of authority or even viability. The larger the project the more such uncertainty brings trouble to the design, especially as people pile on saying “why not do that?”. It is worth noting that the internet can also be right in this regard, such as this post on iOS keyboards.

The irony is that you’re far more likely to participate in a UX discussion/debate with people with very different starting and end points than those for whom your design is intended.

There’s quite a challenge in the tech dialogs around UX. First, those that participate in the dialog are on the whole representative of power users and technology elite. More often than not, UX design is seeking to include a broader audience with a wide range of skills or even interest in using more depth functionality.

Second, the techies (to use @waltmossberg’s favorite phrase) often prefer innovations that enable shortcuts or options to existing features they see flaws with rather than doing whole new things. Techies tend to want to fix the shortcomings in what they see, which is also not always aligned with solving either broader usage challenges or even business problems. The irony is that you’re far more likely to participate in a UX discussion/debate with people with very different starting and end points than those for whom your design is intended.

While every person can be a critic (often even for products that they do not routinely use), it is also the case that every UI can become old or at least static and open to criticism. Interfaces age both internally (the team) and externally (the market). Internally, you might hit a wall on where to evolve. Customers fall into routines and usage patterns. Nothing new you do is recognized or used.

Externally, your shiny new experience that replaces some old experience (for doing slightly different or totally unrelated things) will eventually become the type of experience that gets replaced. While some think of this in terms of stylistic trends like transparency or gradients, the truth is there are functional aspects to aging as well such as interacting with touch or gestures, bundling of different feature sets, or macro trends in visual design.

When you put together the large number of critics and the certainty of your experience aging, you’re in for a challenging time to evolve your interface. Whether you have a consumer app or site with a billion users, a commerce site, a productivity tool, or a line of business app the challenges are all the same. While the scale or direct economic impact might differ, to those designers and product managers working the problem the challenges and decisions are the same, and to their customers the frustration is just as real.

Pressure To Change

Changing a user experience should in theory be no more or less difficult than a major re-plumbing or even creating the first experience. Some things make changes more difficult, or perhaps at least more open to direct criticism. With a backend change, the most visible changes might be performance or uptime (to be fair, the debates about change within product engineering are just as contested). With UX changes (additions, subtractions, reworking) everyone seems them through a more complex lens.

Changing something that people have an emotional connection to is difficult. An emotional connection creates expectations or even norms, and the natural human reaction is to defend the status quo and maintain control. The discussions of change rapidly deteriorate to preference, taste, or argument by analogy, or assertion all of which are very difficult to counter when compared to facts, stopwatches, or physics.

In my experience there are several key pressure points that drive change, beyond the most obvious of fixing what is broken. You can accept or reject these and advocate for change yourself or leave room for your competitors to capture the leadership and change. Depending on context wisdom could be found from many perspectives.

Pressure to change confronts a successful and engaging product because of:

  • Evolving use cases
  • Locating new capabilities
  • Discovering features
  • Increasing tolerance of complexity
  • Isolating change leads to complex analysis of benefits
  • Competing products and/or changing expectations

Evolving use cases. You might design your product to solve a specific key scenario, but over time you find a different set of use cases coming to dominate. This in turn might require rethinking the flow through the product or the features that are surfaced. In a sense this can be seen as evolving the product to meet real world usage versus theoretical usage, except it will still be a change. We see this in the amount of UX real estate legacy tools devote to print-based formatting or layout design compared to the next generation of tools that surface collaboration and communication features as primary use cases. The changes in Facebook and Facebook Messenger demonstrate this driver. A relatively minor scenario saw increased usage and strategic value driving a significant, and hotly debated, experience change.

Locating new capabilities. As new capabilities are added, most all of the time those features require some UX affordance. Almost never is there room in the existing product for the new feature. In evolving Office, we reached a point where we literally ran out of room on menus and then on toolbars (originally the goal of toolbars was to be a shortcut for things on the menus or dialog boxes, but soon features on toolbars had no counterparts in menus and dialog boxes). This challenge is even more acute in today’s mobile apps that are often “filled” from the very first release. This design challenge can be likened to trying to add a new major appliance to an existing kitchen — there is almost never room to add one until the next major redesign when flows are reconsidered. As a result, when it comes time to add UX for entirely new scenarios your product will change significantly. Recently, LinkedIn chose to invest heavily in content authoring and sharing but the core experience was aimed at jobs and resumes. The new mobile app, which was reviewed positively in many cases, changed the focus substantially to these new scenarios.

Discovering features. It is easy to want common features to be easy to use and new features to be discoverable, but those are increasingly at odds as a product evolves. The first challenge is just in finding the screen real estate for new capabilities as discussed above. More likely, however, is that new capabilities will be subordinate to existing ones in terms of surface area. This leads to affordances such as first-run overlays to explain what all the product might do or what gestures are available, which is itself added complexity (and engineering!). One also sees new capabilities with a disproportionate “front and center” placement in an effort to increase discoverability. Often this results from a “marketing” need to drive awareness of the very features being used in outbound marketing efforts.

Over time, A/B testing or usage data will then drive additional change as features are rotated out to make room for new. This all seems quite natural, but also clearly drives complexity or even confusion. This in turn raises the challenge of even changing a product in the first place. Most Google productivity tools we use experience this challenge. Gmail and Apps are increasingly complex and it is getting more difficult to discover capabilities. Historically Google had Labs features to explore new areas and now even Inbox is a whole new experience for mail.

If you ever doubt the ability for people to tolerate more complexity, then just look at the old version of any famous site, app, or program. You’d be amazed at how sparse it is.

Increasing tolerance of complexity. Everyone loves simplicity and certainly every designer’s goal in creating a system is to maintain the highest level of simplicity while providing the right functionality. Over time there is no way to remain simple as more features are added the ability for someone new to the system to command it necessarily decreases and the usage of the system’s breadth decreases. Nevertheless, people become accustom to this growing complexity. It creates a moat relative to new entrants and a barrier to change. People loved the ironically named Chrome browser when it arrived because it was so clean and simple. Few would argue that level of simplicity remains today, yet the complexity is embraced and there’s little opening for a browser that provides less functionality.

For all the criticisms directed at the complexity of Microsoft Office, few switched away to products that do less simply because they were simpler. If you ever doubt the ability for people to tolerate more complexity, then just look at the old version of any famous site, app, or program. You’d be amazed at how sparse it is. The pressure to reduce and simplify comes from everywhere with technology products, but sometimes a failure to embrace a level of complexity can prevent important and strategic change. The most adaptable part of the entire technology stack is the human being at the very top.

Isolating change leads to complex analysis of benefits. UX experience, new or changed, is almost always viewed in isolation. New UX is viewed relative to the small number of initial capabilities and the ease at which those are done compared to existing solutions (i.e. make a voice call on the original iPhone). Changes to products are viewed through the lens of “deltas” as we see in reviews time and time again — reviews look at the merits of the delta, not the merits of the product overall relative to new scenarios that might be more important and old scenarios that might be less important now (as user needs evolve). When viewed in isolation, change is amplified which then makes change more difficult to execute, absorb, or even accept.

Isolation results in intense levels of discussion among the technologists as alternatives are proposed (after the fact) even for very small changes. More importantly, this dialog amplifies the value of small changes which in the scheme of thing will do nothing to improve the business and everything to prevent larger and more strategic changes from happening. Platforms providing horizontal capabilities to broad audiences are notorious for these debates in isolation. Consider the transition iOS made to a new visual design which is now a distant memory.

Competing products and/or changing expectations. The biggest and most important driver for change are the external market forces of competition. Each of the previous drivers are all within your own world view — these are changes you are driving for products you control with inputs and feedback you can monitor. The competitors you view as strategic are incredibly important inputs relative to the longer term viability of the business.

The fascinating thing is that your best customers are the least likely to be worried about your longer term strategy, especially if they have bet their jobs and are empowered by your product. In fact, they will be just as “dismissive” of competing products or new approaches or solutions as your highly paid sales people that are continuing to close deals or the self-taught expert who can’t wait to join the product team. As a technologist you know that your product will be replaced or superseded by a new product and/or technology. It is just a matter of time.

The most important thing to consider is that it is almost never the case that your direct competitor will serve as motivation for changing expectations. The pressure to change will come from unexpected substitutes or newly crafted combinations of a subset of existing capabilities. Ironically, most all of your inputs will come from people and members of the team/company focused on your direct competitor (and the bigger your presence the more likely this will be).

5 Ways To Prepare

The first rules of product design relative to change are to expect it and to prepare for it. It is common-place to remind ourselves in product design that the enemy of the good is the perfect, but relative to evolving experience the enemy of the good is the past.

Assuming that today’s user experience encompasses the value of your product tomorrow is certain to get you in trouble (just as assuming some specific code or API is the core of your value). A comforting way to approach this is to remind yourself that before your current successful user experience there was a successful experience that was widely used. People gave up that product to learn and use your new and different product.

The following are five ways to prepare your design for a future that will require you to change:

  • Solve the n+1 problem up front
  • Design for the choices you know about
  • Optimize only to a point
  • Decide your app strategy early on
  • Flat is your friend

Solve the n+1 problem up front. One of the most common times a new feature causes UX churn is when you’re adding something you knew about but didn’t have time to engineer. I call this n+1 because across the product there are places where your experience (and code) assumed a finite number of choices and then down the road you find you need one more choice. Commonly this is seen as choices like photo filters, email accounts, team/channels, formatting options, and so on. These changes are recognizable when you go from either no choice to a choice or need to switch from binary/ternary to some list.

The warning signs for this potential change come very early on because you either cut the feature or the feedback is everywhere. It is almost always the case that these are core flows in the experience so designing up front can be a big help. Incidentally, this also holds for engineering and the product architecture where the highest cost additions are often when you need to go back and engineer in a level of indirection to solve for choice where there was no architecture. Some might see this as counter to MVP approaches but nothing comes without a cost.

Design for the choices you know about. As a corollary to above, there is a design approach that says to leave room for the unknown, “just in case”. Such a design often leaves open space in the interface that stares at you like an unused parking spot at the mall. At first this seems practical, but over time this space turns into an obstacle you must work around because nothing ever seems to meet the bar as belonging in the space.

On the other hand, this also serves as a place where everyone on the team is battling to elevate their feature to this valuable “real estate”. Even more challenging, your best fans will have a million ideas for how to fill up this space (and renderings to demonstrate those ideas), and too often that amounts to using it to provide shortcuts to existing functionality. Preparing for what you don’t know by compromising the current does little to postpone the inevitable redesign and does a lot to make the current design suboptimal.

Optimize only to a point. Optimize to a point and recognize that you will change, and assume that the vast majority of input will be focused on areas you were not really expecting (someone on the team probably was expecting but not everyone). In preparing for a future of change one of the most difficult things to do in design is to recognize that where you are at a given point in time for a development cycle is good enough to ship. Stop too soon and the risk of missing is high. Stop too late and the reluctance on the team to change down the road is only increased because of sunk costs and a too much historic baggage.

The most critical rule of thumb in product design is that a product releases “as is” and does not come with all the designs you considered or could consider. When it comes time to disrupt yourself with significant changes, do not underestimate the amount of institutional inertia that will come from a few years of researching and testing every possible alternative to a design. The expression often used, “peacetime generals are always fighting the last war” applies to design and product choices as well.

Decide your app strategy early on. A strategic question facing any broad-based product will be how many mobile apps do you need. In the enterprise if you’re building a full ERP system there’s no way to have a single app, but it could also be very easy to create a sort of app shrapnel and replicate the 1500 legacy web sites that the average large corporation maintains. If your product has either a desktop or web solution and apps are being added, you have to decide early on if your app is a scenario-based companion of the primary/only way you expect people to use a service — you might be considering a mobile capture app to go with a web-based analysis app, or keeping the admin tools on the web to accompany mobile workers in apps.

It is very difficult to switch mindsets down the road so this choice is key. A valuable lesson (in disruption) was learned during the transition from desktop to web. The prevailing broad view that web apps would be supersets of desktop apps proved to be true as many believed, but it just took about three times as long as people thought. If you believe your mobile app is a companion to your site, just be prepared for a large number of customers that only want to access over mobile even if they are not doing so today.

Flat is your friend. Programmers and designers often love hierarchy — hierarchy helps our computer brains to organize and deal with complexity and most techies have no problem navigating hierarchy. Unfortunately most people long ago failed to grasp the Dewey Decimal system and search seems to win out over hierarchical organization in most every instance. Aside from that, the most frustrating changes to experience come when you reorganize a hierarchy (trust me on this one).

Hierarchy is the source of muscle memory and also where much of a sense of mastery comes from. The power users are the people that know where features are hidden or how to drill through panels to find things. Hide and Seek or Concentration are great for the right people, but a poor way to do user experience. A solid approach to avoid a future reorganization is to see how flat you can keep your experience. SEO or A/B testing (or marketing) will always push to keep things above the fold, oddly motivating hierarchy, and not favor scrolling which most everyone understands. The alternative of click/tap to a new place is way more disruptive both today and down the road.

We all wish we could be fully informed about the way we will evolve our product and the way competitors will provide a unique view into the space we are going after. That is never as easy as it could be. The above are just a few ideas to consider if you start from the mindset that once you achieve success you will end up going through a user experience change.

5 Approaches To Avoid

With a successful and deeply used product, when you do make a significant change to your experience the feedback is often swift and clear, and universal praise is exceedingly rare. As a result, the product team discussion will move from expressing frustration to proposing solutions very quickly. Even if you were expecting some pushback, it is never pleasant. At that moment, there is a limited design vocabulary available to make unplanned adjustments, perhaps even more limited than the engineering time you have to execute (assuming that as with most projects you are under pressure to complete all the new stuff).

Similarly, you might anticipate some pushback and are considering a proactive approach with proactive objection handlers or scheduled time for feedback. Regretfully, the solution set is the same since the problem is the change itself, not the way you are changing. The only difference is that the more you engage in defensive engineering efforts the less time you have to get the new work done. More importantly, time spent on salves or bridges only takes away from the existential competitive dynamic that is motivating the need for change.

These potential solutions all arise from the same place, which is that your early adopters, best customers, and front lines sales are all successful with your product and resisting a big change. The resistance is natural — the feeling of empowerment and familiarity. Remember, the reason your are making changes is because your successful product, in your best judgement, is facing an existential threat. This threat is not coming from these early voices, but from the customers you have failed to acquire or are not likely to ever acquire. You are making changes to support future growth not incrementally improving your existing customers.

While the 5 approaches outlined below are typical, they often backfire in predictable ways which is why they should be avoided:

  • Add a new mode
  • Offer customization
  • Solve with a UI level of indirection
  • Downplay the changes
  • Redesign quickly

Add a new mode. Enthusiasts, marketing, and enterprise customers have no problem with change so long as you add an option they can use to get back to the old way of doing things. This feedback can be pretty sneaky. They will say that the option can be hidden and hard to get to because it is really only for power users or admins, or just an objection handler for the sales process. They might even tell you that you can take away the option after some time to adjust. By the way, another variant of this request is to just provide an option to “hide the new stuff”. You see how this is a sneaky ask — eventually there will be something in the new stuff that even these customers will want but without interfering with the existing “old” way. It certainly seems lightweight enough.

The challenge is twofold. First, once you can get back to the old way of doing things then everyone will want to know why that option exists. “Is the new way not good enough?” will be a common refrain. Second, once you have such an option you are designing for two experiences all the time. Everything you add needs to consider the old way and new way of getting to a new product areas. Not only is this super difficult, it is expensive and it takes away from forward-looking strategic needs. In general, modes, whether user-directed or contextual, are a way to postpone making a strategic choice about the future of your product and advertise your own indecisiveness.

By the way, technology enthusiasts love modes because modality (I suppose dating back to VI) implies hierarchy, control, choice, and a priori knowledge of where your are heading in the product that most people don’t have. Almost all choice and modality is ultimately ignored by customers and when the product magically switches modes, there is almost always a level of frustration that comes from the unexpected behavior changes (even think of the cleverness of having views defined by portrait or landscape which tend to be confusing in practice).

Offer customization. Customization permits you to make big changes with three mitigations.

First, you can allow people to customize your functionality one setting at a time until it returns to where it was. Often this is how a product evolves as it tries to automate previously multi-step processes. For example, if you used to manually turn off the lights at home via some IoT app but then add machine learning to guess, the first time the lights are wrong the answer will be to disable the new automation (AutoCorrect in Word was like this). You need to get something right or handle it gracefully when you’re wrong, but turning it off means it will never be successful.

Second, customization is often used to rearrange the user interface to get it back to where it was before when it was good Maybe you took away a share button to use the one provided by the OS or maybe you added a few tabs to the top level UI, well then just a switch to move things around.

Third, customization can be used for when you want to add something and the team can’t even decide whether it is a good idea or not so you add your own way to turn it off or hide it. All of these have the same downstream problems with setting a risky precedent that can’t be maintained (i.e. everything new comes with a way to change it) and adding combinatorics that can’t be managed (the testing matrix).

Making up your mind is the best approach. Longer term, the disruptive innovation will come from when the new product subsumes your product and at that time customizing how your product works will prove to be extraordinarily low-level, almost like a debugger. Think this will never happen, then look at all the options in Office that we totally sweated over. Again, technologists love customizations so you are almost certain to get positive feedback and strong encouragement to providing customization.

Solve with a UI level of indirection. The hamburger, Tools|Options, right click, sub-menus, and more are all ways of adding things without adding things or hiding things you add but don’t want to add. There’s no magic answer to where to squeeze all the things you need in a design into a (very) finite space, but for sure if you find yourself putting something new behind a level of indirection then think twice.

Once you think you can get away with “change” by putting it behind a level of indirection then you might as well not do it. Sometimes this type of approach takes place in enterprise products where you are responding to a competitive dynamic but you don’t agree with the competitor or the competitor’s approach is at odds with your overall design. The theory is to add the checkbox but not break your overall model or experience. Only you can judge whether you are seeking credit with reviewers and analysts or actual humans but be careful thinking that you have solved the problem and not just created a future problem.

The discoverability of your work hidden behind a level of indirection is minimal so always ask if you’re doing the work for customers or to make yourself feel like you’re addressing a business or customer need.

Downplay the changes. If you go through the work to understand why you are going to make a big change, then design and engineer a change, the very worst strategy is to downplay the effort when it comes time to communicate what you did.

If you make a big change and talk about it like it is a little change then many will wonder if you are confused and/or lack empathy. The challenge is that this one is the easiest of all responses since it is simply a different tone or wording in a post describing what is changing. You choose the right screen shots or feature names and things can look more familiar. When customers who were expecting the same or incremental see what you’ve done this tends to increase the backlash and the internet loves a good dose of corporate “wool over the eyes of customers”.

Since significant strategic challenges are driving this change, backing off is a worst of all worlds reaction — you send the message to the market that you’re fighting the last war, thus not engaged in the future, and customers come to expect that as well.

Redesign quickly. If how you communicate the change is the short term response, then the medium term response is to quickly redesign what you just spent a lot of time designing. How quickly can you back out the most egregious changes? How can you undo things with as little engineering work as possible? What if you just added a couple of old things back front and center? These are all things that will be rapidly floated within the team.

The most fascinating aspect of this response is that this is what the internet will do for you, both quickly and broadly. The reason is that once a new design is put forth, incremental changes to that design along the lines of “do this instead” will be offered by the community that is empowered by your product. There will almost certainly be good ideas amongst all of these, and even more likely they will be alternatives you considered (we never really learned why Apple so steadfastly refused to highlight the shift state on the iOS keyboard but it is impossible to believe this was not discussed).

Design and engineering are difficult and we all know that the likelihood of mistakes increases with the pace of reactionary change.


As this post keeps saying, the reason it is so painful and frustrating to change user experience is because right at the moment that your product has successfully reached the point of being empowering and critical to the jobs and lives of your customers it is also facing the most existential competitive and marketplace challenges.

The reality is you have to respond to the marketplace. You can choose to continue to iterate on the same path with the same customers. In the technology world that is, with as high a certainty as you can count, focused on the shrinking market. Disruption is real and it so far it is proving to be much more of a law than a theory.

Is the time to change right? Is the design you chose the right one? Are you focused on the right strategic competitors? The other reality of technology change is that most often the forces that keep a product and company from transitioning from one generation to the next are not an understanding or ability to debate these choices, but the ability to execute across product, engineering, marketing, and sales.

The really good news about all of this is that if you can create the product change and go-to-market execution, the reality is that short-term memory is a real thing, especially in a growing market. If you can make changes that secure new customers and grow or that your typical customers can adjust to without “incident” then there’s a really good chance that memory will be short term.

Those customers that chose to stick with character interfaces or would not move off a web app, got left behind by graphical and mobile users. This happens with every technology platform shift and happens within every category. Growth is the friend of change and if you’re not growing you are by definition shrinking.

I’d like to add one last reality for everyone who both made it this far and is out there critiquing new designs for products they use and love. The people working on products you love are on average as good as you, as thoughtful as you, and as informed as you. They are all open to feedback and good two-way discussion. Treat them the way you would like to be treated in the same situation.

Steven Sinofsky (@stevesi)

Author’s note. I’ve never used a music lyric quote and don’t mean to steal Ben’s intro, but this quote from this song has special meaning to me in this particular situation.

This post originally appeared on Medium.

Written by Steven Sinofsky

February 8, 2016 at 12:00 pm

5 Ways to Compete With [Big] Incumbents

Japan, Jiu-Jitsu-KämpferIn The Stack Fallacy: Why Big Companies Keep Failing Anshu Sharma writes about how difficult it is for a [big] company to move up the stack to adjacent businesses/product categories by building on their successful base. If you are competing against one or more incumbents, even if you believe they will ultimately fail because of this fallacy, it is still an incredibly challenging competitive situation. Using some typical weaknesses as your competitive strengths can increase your potential for success when being the next part of the stack a big company takes on.

In a competitive environment, often a “checklist” battle dominates. This is especially true if you are competing with an enterprise incumbent. There are many ways to compete with a company that has more resources, existing customers, and access to broad communications channels. You can be systematic in product choices and communication approaches and increase the overall competitive approach.

You can think of these as the Jiu-Jitsu of the Stack Fallacy — using the reasons competitors can fail as your strengths:

  • Avoid a “tie is a win”
  • Land between offerings or orgs
  • Know about strategy tax
  • Build out depth
  • Create a job-defining solution

This post is mostly from an enterprise competitive perspective, but the consumer and hardware dynamics are very much the same. While some of this might seem a bit cynical, that is only the case if you think about one side of this battle being better than another — in practice this is much more about a culture, context, and operational model than a value judgment.

Avoid a “tie is a win”

The first reaction of an incumbent (after ignoring then insulting the competition) is to build out some response, almost always piggy-backed on an existing product in an effort to score a “tie” with reviews and product experts (in the enterprise this means places like Gartner). The favorite tool is the “partner” or “services” approach, followed by a quick and dirty integration or add-in. Almost never do you see first party engineering work to compete with you, at least not for 12–24 months following “first sighting”.

Their basic idea is to clear the customer objection to missing some feature and then “get back to work”. In enterprise incumbent-speak, “a tie is a win”.

The best way to compete with this behavior is to go head to head with the idea that a checkbox or add-in does away with the need for your service and worse such an implementation approach will almost always be insufficient over time and hamstrung by the need for integration.

Don’t worry about your competitor pointing out the high cost of your solution or the burden of something new being brought into the enterprise. Both of those will become your strengths over time as we will see.

Land between offerings or orgs

The incumbent’s org chart is almost always the strongest ally of a new competitor. The first step is to understand not only where your competitor is building out a response, but the other product groups that are studying your product and getting “worried”. Keep in mind that big companies have a lot of people that can analyze and create worry about potentially competitive products.

You can bet, for example, that if you have any sort of messaging, data storage, data analysis, API, or visualization and compete with the likes of Oracle, Salesforce, Tableau, or other big company that several groups are going to start thinking about how to incorporate your product in their competitive dialog.

You can almost declare success when you hear from your customers that your product has come up in multiple briefings from a single company. Perhaps the biggest loss in a large company is when a Rep loses a deal to a competitor and news of that travels very fast and drives tactical solutions equally fast — tactical because they are often not coordinated across organizations.

When you find yourself in this position, two things work in your favor. First, there’s a good chance you will soon find yourself competing with two “tie is a win” solutions , one from each org— white papers talking about partners who can “fill in the gaps” or add-ins that “do everything you need”, for example. No P&L or organization wants to lose a deal over a competitor.

Second, you will have time to continue to build out depth because the organizations will begin the process of a coordinated response. This just takes a long time.

The best thing that can happen at this point is if you have a product that competes with two larger companies. At that situation you can bet that you are the thing those companies care the least about and what they care the most about is each other. You might find yourself effectively landing between many organizations then and that spot in the middle is your whitespace for product design and development — go for it!

Know about strategy tax

Once an organization grows and becomes successful, one of the key things it needs to do is define a reason for the whole to be greater than the sum of the parts. The standard way incumbents do this is to have some sort of connection, go-to-market, feature, or common thread that runs through all the offerings. This defines the company strategy and the reason why a given product or service is better when it comes from a particular company (and also the reasoning behind a company being in multiple businesses).

In practice, the internal view of these efforts quickly becomes known as astrategy tax. From a competitive perspective these efforts are like gifts in that they make it clear how to compete. For example, your product might have integrated photos but your competitor needs to point customers to another app to deal with photos. Your product might be supported by channel partners but your competitor will only sell direct (or vice versa). This can go to an API level, particularly if you compete with a platform provider who is strategically wedded to a specific platform API.

A classic example for me was the Sony Memory Stick. If you were making any device that used removable storage then you were clearly going to use CF or SD. But there was Sony, marching forcefully onward with Memory Stick. It was superior. It had encryption. It had higher capacity (in theory). At one point after a trade show I left thinking they are going to add Memory Sticks to televisions and phones, and sure enough they did. What an awesome opening if you needed to compete with a Sony product.

A strategy tax can be like a boat anchor for a competitor. Even when a competitor tries to break out of the format, it will likely be half-hearted. Any time you can use that constraint to your advantage you’ll have a unique opportunity.

Build out depth

The enemy of “tie is a win” is product depth. Nothing frustrates an incumbent more than an increasingly deep feature set. Your job is to find the right place to add depth and to push the incumbent beyond what can be done by bolting capabilities into an existing product via add-ins, partners, or third parties.

Depth is your strength because your competitor is focused a checkbox or a tie, figuring out the internal organization dynamics of a response, or strategizing how to break from the corporate strategy. While you might be out-resourced you are also maniacally focused on delivering on a company-defining scenario or approach.

The best approach to building out depth is to remain focused on the core scenario you brought to market in the first place. For example, if you are doing data visualization then you want to have the richest and most varied visualizations. If you have an API then your API should expose more capabilities and your use of the API should show off more opportunities for developers.

There’s a tendency to believe that you need to build out a solution that is broad and to do that early on. The challenge here is that this takes you into the incumbent’s turf where you need to build not only your product but the existing product as well. So early on, push the depth of your service and become extremely good at that — so good that your competitor simply can’t keep up by using superficial means to compete. This example from Slackcrossed my feed today and shows the depth one can go to when there is a clear focus on doing what you do better than anyone else.

Your goal is to expand the checkbox and to move your one line of the checkbox to several lines. This is how you change the “tie is a win” dynamic — with depth and ultimately defining a whole category, rather than one item.

Create a job-defining solution

When building a new product and company, one of the most significant signs of success is when your product becomes so important it is literally someone’s job. Once you become a job then you are in an incredible feedback loop that makes your product better; you have an opportunity to land and expand to other parts of a big company; and you have an advocate who has bet a career on your product.

New products have a magic opportunity to become job-defining. That’s because they enter a customer to solve a specific problem and if that gets solved then you have an advocate but also a hero within the company. Pretty soon everyone is asking that person how they get their job done so much better or more efficiently and your product spreads.

The amazing thing about this dynamic is that it often goes unnoticed because rarely are you replacing entirely something that is already in use, but simply augmenting the tools already in place. In other words, the incumbent simply goes about their business thinking that your product just complements their existing business.

This obviously sounds like a big leap to accomplish, but it speaks to the product management decisions and how you view both the product and customer. With enterprise products it is almost always a two step process. First you solve the specific user’s problem and then you solve the problems the IT team has in using the product as part of a business process (i.e. authentication, encryption, mobile, management).

This works particularly well because your incumbent’s product has already achieved this milestone, and it is their product that (a) is not working and (b) is almost certainly some other function’s job software. It is another way of landing in the whitespace of the organization. Your competitor’s job is not looking for more to do, especially not someone else’s job, so you have some clear road ahead.

The challenge of existing winners breaking into new or adjacent businesses is real and difficult. Very rarely does this happen. The inherent obstacles, both technically and culturally, new products have specific entry points to compete.

Steven Sinofsky (@stevesi)

This post originally appeared on Medium.

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Written by Steven Sinofsky

January 29, 2016 at 9:44 am

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Startups aren’t features (of products or companies)

Checklist with pen isolated on whiteCompanies often pay very close attention to new products from startups as they launched and ponder their impact on their scale, mainstream work. Almost all of the time the competitive risk was deemed minimal. Then one day the impact is significant.

In fact up until such a point most pundits and observers likely said that the startup will get overrun or crushed by a big company in the adjacent space. By this time it is often too late for the incumbent and what was a product challenge now looks like an opportunity to take on the challenges of venture integration.

Why is this dynamic so often repeated? Why does the advantage tilt to startups when it comes to innovation, particularly innovation that disrupts the traditional category definition or go to market of a product?

Much of the challenge described here is rooted in how we discuss technology disruption. Incumbents are faced with “disruption” on a daily basis and from all constituencies. To a great degree as an incumbent the sky is always falling. For every product that truly disrupts there are likely hundreds of products, technologies, marketing campaigns, pricing strategies and more that some were certain would be last straw for an incumbent.

Because statistically new ideas are not likely to disrupt and new companies are likely to fail, incumbents become experts at defining away the challenges and risks posed by a new entrant into the market. Incumbents view the risk of wild swings in strategy or execution as much higher risk than odds of a 1 in 100 chance a new technology upending the near term business. Factoring in any reasonable timeline and the incumbent has every incentive to side with statistics.

To answer “why startups aren’t features” this post looks at the three elements of a startup that competes with an incumbent: incumbent’s reaction, challenges faced by the incumbent, and the advantages of the startup.


When a startup enters a space thought (by the incumbent or conventional wisdom) to be occupied by an incumbent there are series of reasonably predictable reactions that take place. The more entrenched the incumbent the more reasoned and bullet proof the logic appears to be. Remember, most technologies fail to take hold and most startups don’t grow into significant competitors. I’ve personally reacted to this situation as both a startup and as the incumbent.

Doesn’t solve a problem customers have. The first reaction is to just declare a product as not solving a customer problem. This is sort of the ultimate “in the bubble” reaction because the reality is that the incumbent’s existing customers almost certainly don’t have the specific problem being solved because they too live in the very same context. In a world where enterprises were comfortable sending PPT/PDFs over dedicated lines to replicated file servers, web technologies didn’t solve a problem anyone had (this is a real example I experienced in evangelizing web technology).

Just a feature. The first reaction to most startups is that whatever is being done is a feature of an existing product. Perhaps the most famous of all of these was Steve Jobs declaring Dropbox to be “a feature not a product”. Across the spectrum from enterprise to consumer this reaction is routine. Every major communication service, for example, enabled the exchange of photos (AIM, Messenger, MMS, Facebook, and more). Yet, from Instagram to Snapchat some incredibly innovative and valuable startups have been created that to some do nothing more than slight variations in sharing photos. In collaboration, email, app development, storage and more enterprise startups continue to innovate in ways that solve problems in uniquely valuable ways all while incumbents feel like they “already do that”. So while something might be a feature of an existing product, it is almost certainly not a feature exactly like one in an existing product or likely to become one.

Only a month’s work. One asset incumbents have is an existing engineering infrastructure and user experience. So when a new “feature” becomes interesting in the marketplace and discussions turn to “getting something done” the conclusion is usually that the work is about a month. Often this is based on estimate for how much effort the startup put into the work. However, the incumbent has all sorts of constraints that turn that month into many months: globalization, code reviews, security audits, training customer support, developing marketing plans, enterprise customer roadmaps, not to mention all the coordination and scheduling adjustments. On top of all of that, we all know that it is far easier to add a new feature to a new code base than to add something to a large and complex code base. So rarely is something a month’s work in reality.


One thing worth doing as a startup (or as a customer of an incumbent) is considering why the challenges continue even if the incumbent spins up an effort to compete.

Just one feature. If you take at face value that the startup is doing just a feature then it is almost certainly the case that it will be packaged and communicated as such. The feature will get implemented as an add-on, an extra click or checkbox, and communicated to customers as part of the existing materials. In other words, the feature is an objection handler.

Takes a long time to integrate. At the enterprise level, the most critical part of any new feature or innovation is how it integrates with existing efforts. In that regard, the early feedback about the execution will always push for more integration with existing solutions. This will slow down the release of the efforts and tend to pile on more and more engineering work that is outside the domain of what the competitor is doing.

Doesn’t fit with broad value proposition. The other side of “just one feature” is that the go to market execution sees the new feature as somehow conflicting with the existing value proposition. This means that while people seem to be seeing great value in a solution the very existence of the solution runs counter to the core value proposition of the existing products. If you think about all those photo sharing applications, the whole idea was to collect all your photos, enable you to later share them or order prints or mugs. Along comes disappearing photos and that doesn’t fit at all with what you do. At the enterprise level, consider how the enterprise world was all about compliance and containing information while faced with file sharing that is all about beyond the firewall. Faced with reconciling these positioning elements, the incumbent will choose to sell against the startup’s scenario rather than embrace it.


Startups also have some advantages in this dynamic that are readily exploitable. Most of the time when a new idea is taking hold one can see how the startup is maximizing the value they bring along one of these dimensions.

Depth versus breadth. Because the incumbent often views something new as a feature of an existing product, the startup has an opportunity to innovate much more deeply in the space. In any scenario becomes interesting, the flywheel of innovation that comes from usage creates many opportunities to improve the scenario. So while the early days might look like a feature, a startup is committed to the full depth of a scenario and only that scenario. They don’t have any pressure to maintain something that already exists or spend energy elsewhere. In a world where customers want the app to offer a full stack solution or expect a tool to complete the scenario without integrating something else, this turns out to be a huge advantage.

Single release effort. The startup is focused on one line of development. There’s no coordination, no schedules to align, no longer term marketing plans to reconcile and so on. Incumbents will often try to change plans but more often than not the reactions are in whitepapers (for enterprise) or beta releases (for consumer). While it might seem obvious, this is where the clarity, focus, and scale of the startup can be most advantageous.

Clear and recognizable value proposition/identity. The biggest challenge incumbents face when adding a new capability to their product/product line is where to put it so it will get noticed. There’s already enormous surface area in the product, the marketing, and also in the business/pricing. Even the basics of telling customers that you’ve done something new is difficult and calling attention to a specific feature it often ends up as a supporting point on the third pillar. Ironically, those arguing to compete more directly are often faced with internal pressures that amount to “don’t validate the competitor that much”. This means even if the feature exists in the incumbent’s product, it is probably really difficult to know that and equally difficult to find. The startup perspective is that the company comes to stand for the entire end-to-end scenario and over time when customers’ needs turn to that feature or scenario, there is total clarity in where to get the app or service.

Even with all of these challenges, this dynamic continues: initially dismissing startup products, later attempting to build what they do, and in general difficulty in reacting to inherent advantages of a startup. One needs to look long and hard for a story where an incumbent organically competed and won against a startup in a category or feature area.

Secret Weapon

More often than not the new categories of products come about because there is a change in the computing landscape at a fundamental level. This change can be the business model, for example the change to software as a service. It could also be the architecture, such as a move to cloud. There could also be a discontinuity in the core computing platform, such as the switch to graphical interface, the web, or mobile.

There’s a more subtle change which is when an underlying technology change is simply too difficult for incumbents to do in an additive fashion. The best way to think about this is if an incumbent has products in many spaces but a new product arises that contains a little bit of two of the incumbent’s products. In order to effectively compete, the incumbent first must go through a process of deciding which team takes the lead in competing. Then they must address innovator’s dilemma challenges and allocate resources in this new area. Then they must execute both the technology plans and go to market plans. While all of this is happening, the startup unburdened by any of these races ahead creating a more robust and full featured solution.

At first this might seem a bit crazy. As you think about it though, modern software is almost always a combination of widely reused elements: messaging, communicating, editing, rendering, photos, identity, storage, API / customization, payments, markets, and so on. Most new products represent bundles or mash-ups of these ingredients. The secret sauce is the precise choice of elements and of course the execution. Few startups choose to compete head-on with existing products. As we know, the next big thing is not a reimplementation of the current big thing.

The secret weapon in startups competing with large scale incumbents is to create a product that spans the engineering organization, takes a counter-intuitive architectural approach, or lands in the middle of the different elements of a go to market strategy. While it might sound like a master plan to do this on purpose, it is amazing how often entrepreneurs simply see the need for new products as a blending of existing solutions, a revisiting of legacy architectural assumptions, and/or emphasis on different parts of the solution.

—Steven Sinofsky (@stevesi)

Written by Steven Sinofsky

November 17, 2014 at 12:00 pm

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Apps: Shrapnel v. Bloatware

imageMuch is being said lately about the trend to unbundle capabilities for the web and apps. Is this a new trend, a pendulum, or another stage in the evolution of providing software solutions for work and life? Are we going to learn what some would say are lessons from a past generation of software and avoid bloatware? Perhaps we will relive some of the experiences from that era and our phones and tablets will be littered with app shrapnel as our PCs once were?

My own personal experience in product choices is marked by a near constant tension over not just bundle v. unbundle from a product perspective, but also from a business perspective. Whether on development tools, Office, Windows, or internet services I’ve experienced the unbundle <> bundle dynamic. I’ve bundled, unbundled, and had the “internal” debates about what to do when, what went well or not. If you’re interested in an early debate about bundling Office you can see the Harvard case study on the choice of “best of breed v. suite” in Finding the Suite Spot ($).

The Pendulum

This HBR article does a good job of bringing forth some of the history and describing the challenges of positioning unbundle/bundle as both a binary choice and a pendulum or Krebs-like cycle of resource conservation. Marc Andreessen does a great job in these two tweetstorms of detailing the bundle/unbundle cycle on the internet and the computer history we both grew up with (http://tweetstorm.io/user/pmarca/481554165454209027 and http://tweetstorm.io/user/pmarca/481739410895941632).

There’s one maxim in business that drives so much of the back and forth or pendulum behavior we tend to see, which is that most strategies have a complementary approach (vertical v. horizontal, direct v. indirect, integrate v. distinct, first v. third-party, product org v. discipline org, quantitative v. qualitative performance evaluation, hack v. plan, etc.) So in business depending on your roots or your history, and most importantly the context you find yourself, you are going down a path of one of more of these attributes.

Over time your competition tends to pick you apart the other way or ways. Equally likely, your ecosystem builds up around you innovating in parts where you are weaker, gaining strength, and showing off new approaches to product or market. Certainly, if you’re a new company entering an established market you will not just copy the approach of the incumbent which is why new products seem to be at the other end of one of these spectrums.

Then as you get in trouble you look around and try to figure out what to do. There’s a good chance the organization will double down on the approach that has always worked—after all as Christensen says, that is the natural energy force in an organization. That happens until a big moment of change (a major competitive success, leadership change, etc.) and then you change approaches. More often than not, your choice is to do the thing you weren’t doing before. If you’re around in the workforce long enough, you start to see things as a series of these evolutionary steps.

This is business, context is everything. There’s never a right answer in absolute, only a right answer given the context.

The moments of change, of breaking the cycle or swinging back the other way, are the moments that unleash significant improvements in the work, the product, or the workplace.

History and Customers

As consumers we adopt new technologies without realizing or thinking about whether they are bundled or unbundled, and our choices and selections for one or other are highly dependent on the context at the time. There are times when bundling is essential to the distribution of technology, just as there are times when unbundling brings with it more choice, flexibility, and opportunity. Obviously the same holds for businesses buying products, only businesses have purchasing power that can make bundled things appear unbundled or vice versa.
It is worth considering a few tech examples:

  • Autos began with minimal electronics, followed by optional electronics, then increasingly elaborate integrated electronics and many now think that smartphones will be the best device for in-car electronics/apps (for example the BMW i series).
  • LinkedIn began as a network for professionals to list their credentials and connect to others professionally. Recently it has bundled more and more content-based functionality.
  • Mobile telephony used to have distinct local, long distance, text and then data plans, which have now been bundled into all-you-can-consume multi-device plans.
  • Word processing used to have optional spell-checking and mail merge which was then bundled into single products which were then subsequently bundled into suites and also now bundle cloud services. Similarly, financial spreadsheets, data analysis, and charting were previously distinct efforts that are now bundled. Today we are seeing new tools that have different feature sets and approaches, representing some unbundling and some bundling.
  • Operating systems were once highly hardware dependent, then abstracted from hardware but with optional graphical interfaces, followed by a period of bundling of OS+Graphics, followed by a bundling of OS, graphical interface, and hardware in a single package. Today with services we’re seeing different combinations of bundling and unbundling innovations.
  • Microprocessors have been on a fairly continuous bundling effort relative to peripherals, graphics, and even storage.
  • Modern smartphones are a wonder of bundling, first at the hardware level (SoC packaging) followed by hardware+software, then through all the devices that were previously distinct (GPS, still camera, video camera, pedometer, game controller, USB storage, and more).

There are countless examples depending on what level in the full consumer offering is being considered (i.e. product, price, place, promotion). Considering just these examples, one can easily see the positives and potential pitfalls of any of these.

Yet in looking these examples and others, one can make a few observations about how customers and teams approach bundling choices for products and services:

  • People like distinct products when exploring new capabilities and product teams like building single purpose tools early in product lifecycle, out of both focus and necessity/resources.
  • People like it when their favorite product adds features that previously required a separate product, especially when their favorite product is growing in usage. Product teams love to add more features to existing products when those features map to obvious needs.
  • People have some threshold for when an integrated product turns into an overwhelming product, but that “line in the sand” is impossible to define a priori and depends a great deal on how products are evolving around your product. Mobile phone plans today are great, but many are very unhappy with Cable TV bundles.
  • Competition can come from a bundle that you were previously not considering **or** competition can come from unbundling the product you make.
  • Product managers often reach a point where they can no longer solve the problem of adding new features while seeing them get used and also getting credit for innovating.
  • Macro factors can radically alter your own views of what could/should be bundled. If your business does not have a software component and your competitors add one, attempting to bundle that functionality could be quite challenging (technically, organizationally). If the platform you target (autos, spectrum, screens) undergoes a major change in capability then so too does your view of bundling or unbundling.

These examples and observations make one thing perfectly clear: whether to bundle or unbundle features depends a great deal on context and customer scenarios and so the choices require a great deal of product management thought. The path to bundle or unbundle is not linear, predictable, or reactionary but a genuine opportunity and need for solid product thought.

Strategic questions

On the one hand, considering whether to bundle or unbundle innovations might just be “do what we can that is differentiated”. In practice there are some key strategy questions that come up time and time again when talking to product folks.

  • Discoverability. The most critical strategic question to bundle or unbundle is whether the new work will be discoverable by intended customers. In a new product, the early waves of innovative features often make sense bundled. Over time, just responding to customers means you’ll be bundling in new capabilities (whether organic or competitive).
  • Usability. When faced with a new feature or business approach, the usability of this approach is a key factor in your choice. If you’re unable to develop a user experience that permits successful execution of the desired outcome, then it doesn’t really matter whether your bundled or unbundled.
  • Depth. When making the choice to bundle or unbundle you have to think through how much you plan on innovating in the spaces. If you’re setting yourself up for a long-term head to head on depth versus believing you are “checking a box” you have different choices. Incumbents often view the best path to fending off a disruptive unbundled feature as adding a checkbox to compete (to avoid the trauma of a major change in approach). Marketing often has an urgency that drives a need for market response and that can be represented as an unbundled “add-on that no one cares about” or “a checkbox that can be communicated” — that might sound cynical until you’ve been through a sales cycle losing out to a “feature as a product”.
  • Business economics. If you charge directly for your product or service (or freemium), then there will be a strong incentive to bundle more and more into your existing offering. Sales will generally prefer to add more features at the current price. Marketing will potentially advocate for a new pricing level to increase revenue. If you choose to unbundle and develop a new product, side-by-side or companion, then you’ll need to consider what your attach rate might be. A bundled solution essentially sees a 100% attach rate to your existing product whereas a whole new product brings with it the need to generate demand and subsequent purchase or usage. An advertising-based service will see increased surface area for an unbundled solution but will also dilute usage. A web-based service allows for cross-linking and easy connection between two different properties, but apps will require separate downloads and minimal cross-app connections.
  • Usage economics. It might sound strange separating out business from usage, since especially in a SaaS world they are the same thing. In practice, if you’re revenue is tied to usage directly (page views, transactions, etc.) then your design needs to factor in how you measure and drive usage of the features, bundled or unbundled. If you’re economics are not tied directly to usage you will have more strategic latitude to consider how your offering plays out bundled v. unbundled (assuming your boss lets you keep working on something no one uses).

Product management approach

Should you add that new feature or capability to your existing product or should you create a new destination (app, site)? Should you break out a feature because unbundling is the new normal or will that just break everything? Those are the core questions any PM faces as a product grows.

One tip: do not claim that one approach (bundle v. unbundle) is good for users and the other approach is only good for business. In other words, bundle v. unbundle cannot be distilled down to pro-user or anti-user, or more importantly marketing v. product. The best product people know that context is everything and that positioning a choice as A against B is counter productive—everyone is on the same team and has the same broad goals. As difficult as it is, working through these questions with as much dialog as possible and as much “walk in the other’s shoes” is absolutely critical.

There are many natural forces at play that will drive one way or another.

For example, most organic product development will tend to expand the existing product as it builds on the infrastructure and momentum already present.

Most new acquisitions will tend towards acquiring unbundled solutions, aka competition, though in the enterprise space one can expect significant calls to integrate even disparate technologies.

Part of being a good PM is to step back and go through a thoughtful process about whether to bundle or unbundle new capabilities. The following are some design choices.

  • Advertising new features in proportion to expected usage. There’s a general view to advertise a new feature in the UX in an excessively prominent manner. You want people to know you fixed or added a feature. At the unbundle extreme this means a whole new app and a trend to shrapnel. In the bundle extreme this means a big UX to drive you to a new thing. The most critical choice is really making sure that you are designing the access to the feature to be in relative proportion to how much you expect your customer base to use something.
  • Plan for “n+1” in all experience choices. As you make the choice to bundle or unbundle, know ahead of time that this will not be the first place you make this choice. If you’re adding a new app today then chances are that will become the way you solve things down the road. If you’re adding new UX access to a feature then plan on more depth in that feature or more peer features. Is the choice you are making scalable for the growth in creativity and innovation you expect?
  • Integrate or connect in one direction, not both. If you bundle or unbundle there will be a relentless push to promote the connection between elements of the product or service. Demo flows, top-level UX, even deep linking between apps. At some extreme if you bundle n items, it might not be unrealistic to go down a path where every n is connected to every other n-1 and vice versa. This is incredibly common in line of business apps/modules.
  • Bundle and innovate, don’t bundle and deprecate. If you make a choice to bundle a capability into your mainline effort, do not bundle it to make it go away. Bundle it and think of it as just as important as other things you do. This dynamic appears when your competition does something you don’t like so you hope to have a checkbox and make the competitor go away. This never happens.
  • Designing for good enough leaves you open to disruption. Closely related to deprecating while bundling is the idea that a “tie is a win”. Once you’re established you often think that you can continue to win against a competitor with an integrated implementation that is “good enough”. That might work in short-term marketing but over time, if the area is important you’ll lose.
  • Expect hardware to be relentlessly bundled. If you connect to hardware in any way, then you’ll be faced with a relentless march towards bundling. Hardware naturally bundles because of the economics of manufacturing, the surplus of transistors, and the need to reduce power and surface area. Never bet on hardware or peripherals staying unbundled for long.
  • Expanding software depth is easy, but breadth often adds more value. Engineers and product managers love to round out features, add more depth, more customization, and more incremental improvements. This is where the customer feedback loop is really clear. In terms of growing the business and attracting new customers, expansion in breadth is almost always a better approach so long as you “bundle” features that seem natural. Over indexing on depth, particularly early in a product life-cycle leaves you open to a competitor that does you plus other valuable things, no matter how much you think you’re unbundling approach is cleaner and simpler.
  • Defined categories do not remain defined for long. In enterprise products the “category” or “magic quadrant” is everything. In practice, these very definitions are always in transition. Be in the lookout for being redefined by an action of bundling or unbundling.
  • Assume sales and marketing will prefer new capability to be bundled, or maybe not. Finally to highlight how contextual this is, there is no default as to how outbound efforts will prefer you approach the problem. It is not necessarily the opposite of what you are doing or the same as a competitor. For example, if your sales force economics are such that they are strongly connected to a single product and sales motion, it will be clear that bundling will be preferred no matter what a competitor is up to. At an extreme, even an unbundled feature will be used as a closer or a discount, particularly in the enterprise. Conversely, even if your competition is highly bundled, you’re own outbound efforts might be structured such that unbundling is a competitive and sales win. You just never know. Most importantly, the first reaction isn’t the way to base your approach—spend the time to engage and debate.

To bundle or unbundle is a complex question that goes beyond the simplistic view that minimal design makes for good products. Take the time to engage broadly across the team, organization, and to project forward where you want to be as these are some of the most critical design choices you will make.

–Steven Sinofsky @stevesi


Written by Steven Sinofsky

June 28, 2014 at 3:00 pm

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The Price Is Right: For Early-Stage SaaS Companies, It Needs To Be

TPIRWordmarkNothing is more critical to a software-as-a-service (SaaS) business than pricing strategy. Pricing is the moment of truth for a new product … and doubly so when it is a company’s first product. But far more often than not, I’ve observed new startups leaving “money on the table” when it comes to pricing enterprise products. I’ve seen founders say their product saves hundreds of thousands of dollars — yet their product is priced as if it’s only saving thousands of dollars.

One reason for this is assuming the need to price and program similarly to competitive products. With a potentially disruptive product, however, falling into the trap of pricing like a legacy competitor not only leaves money on the table — but it could fail to surface your differentiation. Said another way, your product is your price and how you price your product reflects value from the buyer perspective as well as what your company believes is valuable. SaaS products also have the advantage that they are priced not just for the service they offer, but for the potential of saving massive capex/opex spent directly by the customer.

From your business perspective, SaaS products have a level of stickiness that would be the envy of the packaged-and on-premise software generation.

Since the uncertainty and social science aspects of pricing can be uncomfortable, especially for technical founders, here is a framework — from the perspective of a product manager — to consider when pricing new SaaS products. The product manager role is critical in SaaS because the ability to fine-tune the monetization of the product is closely tied to its features and implementation. The product needs to be designed with such flexibility in mind when it comes to making features available, prioritizing features, or even just choosing where to spend engineering time.

Just remember that “business isn’t physics”, as Bill Gurley notes in his excellent post on some of the metrics here. Andreessen Horowitz also has a detailed primer on understanding SaaS valuations as great background for pricing discussions. Because pricing is math, there’s a tendency to create the spreadsheet model and assume it will all work. But there’s also a ton of psychology that comes into play: beyond math, pricing involves judgment, vision, and flexibility.

How do you solve an unsolvable problem? Bound it.

In a new business, it’s easy to spend money, but the combination of a new product and the unknown cost of acquiring customers leads to an “unsolvable” problem. One approach is to take lean/iterative methods and apply them to finding the right pricing fit. This post is about a framework to arrive at such early prices, which will change. (This is very different from what happens in an existing company with existing customers, where you really only get one shot at pricing something right).

The business side of SaaS involves a complex array of variables such as customer lifetime value (LTV), customer/subscriber acquisition cost (CAC), average revenue per user (ARPU), cost of goods sold (COGS), and churn; as well as pricing models such as freemium, tiered, and time based. Then, depending on whether you’re targeting consumers or enterprises, there are very different sales models that influence your pricing approach (for example, business products invite complexity, especially when dealing with purchasing managers). Similarly, the product side of SaaS is a complex set of equations related to usage patterns, scenarios, and variable costs of a large number of resources.

The most critical costs are related to customer acquisition and sales/marketing expense — which can appear to erase any potential for profit by traditional accounting measures — so the key to early-stage SaaS businesses is to focus on understanding customer acquisition costs relative to the estimated long term value of a customer. Since we don’t know how much it will cost to acquire a customer yet, we will just have to move forward assuming some budget (along with some allocation for margin in the ultimate price relative to this long term value). This post focuses on the pricing models relative to product and features and assumes a higher level view of customer acquisition costs and long term value.

One way to approach this is to establish upper and lower bounds on pricing:

A lower bound for your pricing

The lower bound represents your costs to serve a customer your product. One common example is the basic costs of spinning up the IaaS/PaaS elements of what you do — creating accounts, allocating minimal resources, other infrastructure, and then subsequent usage.

It might be convenient to think of this lower bound as what you could offer for “free” to some customers. You might make some assumptions about the use of variable resources such as compute, egress, storage, etc. in order to arrive at this lower bound. (Note, since this is a product-centric view these bounds are absent the allocation for fixed and variable costs outside the product/technology, so do not not include opex, S&M, etc.)

It is important to understand this bound across the full breadth of your product. While you might initially view some features as “premium”, you also want to assume that over time capabilities will migrate from advanced to essential and you will fill in new features at the top. I think it is a good exercise to consider the full product as a base case initially.

An upper bound for your pricing

The upper bound represents your costs to serve a “depth” user: in this case, the customer using the parts of your product that drive ongoing costs to scale (for example, this customer is using increasingly more bandwidth, storage, or compute). Now this is where you can look at what you offer relative to your competition, and want to understand if you have scale attributes that are better/worse/same. By knowing this you can begin to separate out variables for your model.

Presumably in developing your product, you created a unique architectural approach relative to existing competitors. Do you scale better for more tenants, use storage more effectively, or maybe your mobile app is more efficient at bandwidth? The importance of knowing your own strengths and weaknesses will inform what variables to use in your pricing.

You can also think of your upper bound as a competitive foil — the stronger you are on some attribute, the more you should use this attribute to differentiate your offering. This might allow you to charge more for capabilities that are just too expensive for your competition.

These are the core attributes for pricing

When you’re pricing a new offering, it is worth understanding where your product is today relative to a core set of potential pricing attributes.

Whether it is Bronze/Silver/Gold, Free/Select/Premium, Trial/Select/Premium, or Individual/Business/Enterprise, the norm for SaaS is to offer a “3xN” matrix of 3 pricing plans and N attributes — as inthese examples. The more mature a SaaS product, the more rows and columns its matrix has. (One SaaS product I researched had five top-level features organized into an array of 27 price points based on combinations of the three to five of the features and number of users.)

A broad range of SaaS products can be considered across the following core service attributes:


If your product lends itself to dividing the features themselves — such as import/export, visualization, view/edit, or connectivity to other products — into good-better-best then differentiating price points here might work. In a freemium model, dividing must-have features among free v. paid users can be a customer-hostile way to differentiate or optimize pricing, so beware.

The reason to hesitate on this dimension is because customers understand that you’re basically just inhibiting access to code that is already there and hence being draconian. Another reason to be cautious with this model is that as usage of the product deepens over time, paid features will tend to get pulled into lower-priced tiers — which means you need to fill in new features/prices with every release or update. As easy as it is to communicate general-use features in pricing tiers, there’s a level of distaste with this approach for many customers.


One of the most common approaches to differentiating a SaaS product designed for business is to separate out the IT-focused features as a pricing attribute. These could be features for security, audit, identity integration, domain names, sharing, control, management, etc. Businesses understand what it is like to both value and pay for these features.

Commonly this approach is used to rectify a product that has become viral within an enterprise, so be careful about how you approach an enterprise with pricing here. Otherwise you might come across as an arsonist-firefighter who is offering to contain the very situation you knowingly created.

Scale in consumption

Another broadly used SaaS pricing attribute is storage consumption (even for products for which storage is not a primary attribute): It’s easy to measure, easy to articulate, and is relatively expensive. The benefit of using storage is that people “get it” to some degree. It also gets cheaper faster than people can consume it (and in most scenarios customers need to be doing something fairly extreme to consume vast amounts of storage). At the same time, the platform companies have been steadily increasing free storage or ultra-low priced storage as a base, no-frills service so simply using storage as a one-dimensional offering might not work. With a new SaaS product, be sure to consider ways to avoid basing costs on storage given challenges.

One novel approach seen recently is using third-party storage and letting the customer establish a paying relationship such that storage is not part of the pricing of your product, since that way you do not serve as a pure pass-through for a visibly priced third-party element of your product. There are many novel attributes in modern software that can be used as consumption variables; one relatively new one is to use depth consumption of APIs/calls as a price tiering structure. (Box, where I’m an advisor, recently announced pricing for Box APIs as an example.) Developer-oriented products work especially well for consumption pricing because developers understand the product architecture and what can drive costs, even if those costs are variable with usage.

Scale in consumers

SaaS products used by small teams, cross-organizations, or that just scale with more members collaborating/sharing/using are almost always priced by number of unique users (and subsequent integration with organization-based directories). Pricing this variable is straightforward and over time you will see distribution of engagement and resource usage that will further let you refine the discrete price points.

Because most products priced this way also want to encourage more users/usage, carefully consider where you put the first step or two. But large-scale customers like this approach because it allows for predictable pricing on a metric they understand: number of employees/users. In general, you can think of this as per-seat pricing but can also apply to device end-points, servers/CPUs, VMs, etc.

Segmenting your customers

Every product is used by different customer segments — whether measured by size of organization, industry segment, geography, or type of individual within an organization. Common pricing tier labels here include “government”, “non-profit”, “academic”, “healthcare”, “small business”, and so on.

As a product matures, you will almost certainly either label or expand your pricing tiers to account for this. Before you jump into this level of differentiation, however, you want to gain more data on usage — are you seeing customers across some set of segments, and are they using the product differently? More importantly, do you see a path to develop differentiation that allows you to target and sustain these segments (or are you just optimizing revenue along these lines)? Some products are designed only for specific segments like education, which allows you to further refine within them: e.g., public, private, post-secondary, etc.

But one customer segment that is almost always special is the engaged technical user. These folks can push a product through an organization when required, or develop custom solutions on your platform that either deliver or enhance the value of your work.

Developers are key in this regard. For any platform-oriented product, it is worth considering how you offer developers the ability to experiment with and use the full product in a development environment at a very low price. One way to accomplish this is to separate out usage-as-development versus usage-as-production, and price accordingly.

* * *

As a new offering with any established competitors, pricing will be the easiest point of attack. And if you are a disruptive product, you want to have the deepest possible understanding of the value you are bringing to the table so you can maximize the initial pricing model. So the most important suggestion for pricing I have here is to wait until the last possible moment to price and announce.

Even for enterprise products, things like round-numbers, 9′s, and discounts all matter. Do keep in mind that discounting will be substantial in enterprise products with direct sales and 50% or more off “list” price is not uncommon (and often required). That’s not an excuse to bloat the price, but it is important for purchasing managers and for empowering your salesforce that you enable a level of customization — and know what variables you are using to do so.

Some say that you can never change or raise your prices once you’re out of the gate. Always keep in mind that once you have customers, price changes or product composition relative to price are never viewed as positive changes, even if you think for some customers you are lowering the price. And when you do change your prices, always offer existing customers time to adapt and grandfather them in (at least). Finally, remember to engineer a product framework that can support pricing flexibility.

Create the model, use the model, but don’t let the model do your thinking. Price carefully!

–Steven Sinofsky (@stevesi)

This post originally appeared on TechCrunch.

Written by Steven Sinofsky

May 16, 2014 at 11:00 am

If at first you don’t succeed: disrupting incumbents in the enterprise

rocky-movie-on-stepsI was talking with a founder/CEO of an enterprise startup about what it is like to disrupt a sizable incumbent. In the case we were talking about the disrupting technology was losing traction and the incumbent was regaining control of the situation, back off their heels, and generally felt like they had fended off the “attack” on a core business. This causes a lot of consternation at the disrupting startup as deals aren’t won, reviews and analyst reports swing the wrong way, and folks start to question the direction. If there really is a product/market fit, then hold on and persevere because almost always the disruption is still going to happen. Let’s look at why.

Incumbent Reacting

The most important thing to realize about a large successful company reacting to a disruptive market entry is that every element of the company just wants to return to “normal” as quickly as possible. It is that simple.

Every action about being disrupted is dictated by a desire to avoid changing things and to maintain the status quo.

If the disruption is a product feature, the motion is figuring out how to tell customers the feature isn’t that important (best case) or how to quickly add something along the lines of the feature and move on (worst case). If the disruption is a pricing change then every effort is about how to “manage customers” without actually changing the price. If the disruption is a new and seemingly important adjacent product, then the actions focus on how to point out that such a product isn’t really necessary. Across the spectrum of potential activities, it is why the early competitive responses are often dismissive or outwardly ignore the challenger. Aside from the normal desire to avoid validating a new market entry by commenting, it takes a lot of time for a large enterprise to go through the work to formulate a response and gain consensus. Therefore an articulate way of changing very little has a lot of appeal.

Status quo is the ultimate goal of the incumbent.

Once a disruptive product gains enough traction that a more robust response is required, the course of action is almost always one that is designed to reduce changes to plans, minimize effort overall, and to do just enough to “tie”. Why is that? Because in a big company “versus” a small company, enterprise customers tend to see “a tie as a win to the incumbent”. Customers have similar views about having their infrastructure disrupted and wish to minimize change, so goals are aligned. The idea of being able to check off that a given scenario is handled by what you already own makes things much easier.

Keep in mind that in any organization, large or small, everyone is at or beyond capacity. There’s no bench, no free cycles. So any change in immediate work necessarily means something isn’t going to get done. In a large organization these challenges are multiplied by scale. People worry about their performance reviews; managers worry about the commitments to other groups; sales people worry about quarterly quotas. All of these worries are extremely difficult to mitigate because they cross layers of managers and functions.

As much as a large team or leader would like to “focus” or “wave a wand” to get folks to see the importance of a crisis, the reality of doing so is itself a massive change effort that takes a lot of time.

This means that the actions taken often follow a known pattern:

  • Campaign. The first thing that takes place is a campaign of words and positioning. The checklist of features, the benefits of the existing product, the breadth of features of the incumbent compared to the new product, and so on. If the new product is cheaper, then the focus turns to value. Almost always the campaign emphasizes the depth, breadth, reliability, and comfort of the incumbent’s offer. A campaign might also be quite negative and focus on a fear, compatibility with existing infrastructure, or conventional wisdom weakness of a disruptor, or the might introduce a pretty big leap of repositioning of the incumbent product. A good example of this is how on-premises server products have competed with SaaS by highlighting the lack of flexibility or potential security issues around the cloud. This approach is quick to wind up and easy to wind down. Once it starts to work you roll it out all over the world and execute. Once the deals are won back then the small tiger team that created the campaign goes back to articulating the product as originally intended, aka normal.
  • Partnership. Quite often there can be a competitive response of best practices or a third-party tool/add-on that appears to provide some similar functionality. The basic idea is to use someone else to offer the benefit articulated by a disruptive product. Early in the SaaS competition, the on-premises companies were somewhat quick to partner with “hosting” companies who would simply build out a dedicated rack of servers and run the traditional software “as a service”. This repotting plants approach to SaaS has the benefit that once the immediate crisis is mitigated, either the need to actually offer and support the partnership ends or the company just becomes committed to this new sales channel for existing products. Again, everything else continues as it was.
  • Special effort. Every once in a while the pressure is so great internally to compete that the engineering team signs up for a “one off” product change or special feature. Because the engineering team was already booked, a special effort is often something carefully negotiated and minimized in scope and effort. Engineering minimizes it internally to avoid messing up dependencies and other features. Sales will be specific in what they expect the result to do because while the commitment is being made they will likely begin to articulate this to red-hot customer situations. At the extreme, it is not uncommon for the engineering team to suggest to the sales organization that a consultant or third-party can use some form of extensibility in the product to implement something that looks like the missing work. The implications of doing enterprise work in a way that minimizes impact is that, well, the impact is minimized. Without the proper architecture or an implementation at the right level in the stack, the effort ultimately looks incomplete or like a one-off. Almost all the on-premise products attempting to morph into cloud products exhibit this in the form of features that used to be there simply not being available in the “SaaS version”. With enough wins, it is almost likely that the special effort feature doesn’t ever get used. Again, the customer is just as likely to be happy with the status quo.

All of these typical responses have the attribute that they can be ignored by the vast majority of resources on a business. Almost no one has to change what they are doing while the business is responding to a disruptive force. Large incumbents love when they can fend off competitors with minimal change.

Large incumbents love when they can fend off competitors with minimal change.

Once the initial wave of competitive wins settles in and the disruptive products lose, there is much rejoicing. The teams just get back to what they were doing and declare victory. Since most of the team didn’t change anything, folks just assume that this was just another competitor with inferior products, technology, approaches that their superior product fended off. Existing customers are happy. All is good.

Or is it?

Disruptor Persevering

This is exactly where the biggest opportunity exists for a disruptive market entry. The level of complacency that settles into an incumbent after the first round of victories is astounding. There’s essentially a reinforcing feedback loop because there was little or no dip in revenue (in fact if revenue was growing before then it still is), product usage is still there, customers go back to asking for features the same as they were before, sales people are making quota, and so on. Things went back to normal for the incumbent.

In fact, just about every disruption happens this way–the first round or first approaches don’t quite take hold.

Why is this?

  • Product readiness can improve. Obviously the most common is that the disruptive product simply isn’t ready. The feature set, scale, enterprise controls, or other attributes are deficient. A well-run new product will have done extensive early customer work knowing what is missing and will balance launching with these deficiencies and with the ability to continue to develop the product. In a startup environment, a single company rarely gets a second shot with customers so calibrating readiness is critical. Relative to the broader category of disruption, the harsh reality is that if the disruptor’s idea or approach is the right one but the entry into the market was premature, the learning will apply to the next entry. That’s why the opportunity for disruption is still there. It is why time to market is not always the advantage and being able to apply learning from failures (your own or another entry) can be so valuable.
  • Missing ingredient gets added. Often a disruptive product makes a forward-looking bet on some level of enterprise infrastructure or capability as a requirement for the new product to take hold. The incumbent latches on to this missing ingredient and uses it to create an overall state of lack of readiness. If there’s one thing that disruptors know, it is not to bet against Moore’s law. If your product takes more compute, more storage, or more bandwidth, these are most definitely short-term issues. Obviously there’s no room for sloppy work, but by and large time is on your side. So much of the disruption around mobile computing was slowed down by the enterprise issues around managing budgets and allocation of “mobile phones”.  Companies did not see it as likely that even better phones would become essential for life outside of work and overwhelm the managed phone process. Similarly, the lack of high-speed mobile networks was seen as a barrier, but all the while the telcos are spending billions to build them out.
  • Conventional wisdom will change. One of the most fragile elements of change are the mindsets of those that need to change. This is even more true in enterprise computing. In a world where the average tenure of a CIO is constantly under pressure, where budgets are always viewed with skepticism, and where the immediate needs far exceed resources and time, making the wrong choice can be very costly. Thus the conventional wisdom plays an important part in the timeline for a disruption taking hold. From the PC to the GUI to client/server, to the web, to the cloud, to acceptance of open source each of these went through a period where conventional wisdom was that these were inappropriate for the enterprise. Then one day we all wake up to a world where the approach is required for the enterprise. The new products that are forward-looking and weather the negatives wishing to maintain the status quo get richly rewarded when the conventional wisdom changes.
  • Legacy products can’t change. Ultimately the best reason to persevere is because the technology products you’re disrupting simply aren’t going to be suited to the new world (new approach, new scenarios, new technologies). When you re-imagine how something should be, you have an inherent advantage. The very foundation of technology disruption continues to point out that incumbents with the most to lose have the biggest challenges leading through generational changes. Many say the enterprise software world, broadly speaking, is testing these challenges today.

All of these are why disruption has the characteristic of seeming to take a much longer time to take hold than expected, but when it does take hold it happens very rapidly. One day a product is ready for primetime. One day a missing ingredient is ubiquitous. One day conventional wisdom just changes. And legacy products really struggle to change enough (sometimes in business or sometimes in technology) to be “all in” players in the new world.

Of course all this hinges on an idea plus execution of a disruptive idea. All the academic theory and role-playing in the world cannot offer wisdom on knowing if you’re on to something. That’s where the team and entrepreneur’s intuition, perseverance, and adaptability to new data are the most valuable assets.

The opportunity and ability to disrupt the enterprise takes patience and more often than not several attempts, by one or more players learning and adjusting the overall approach. The intrinsic strengths of the incumbent means that new products can usually be defended against for a short time. At the same time the organization and operation of a large and successful company also means that there is near certainty that a subsequent wave of disruption will be stronger, better, and more likely to take hold simply because of the desire for the incumbent to get back to “normal”.

–Steven Sinofsky (@stevesi)

Written by Steven Sinofsky

January 18, 2014 at 9:00 am

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The Four Stages of Disruption

iexpectyoutodiemrbondInnovation and disruption are the hallmarks of the technology world, and hardly a moment passes when we are not thinking, doing, or talking about these topics. While I was speaking with some entrepreneurs recently on the topic, the question kept coming up: “If we’re so aware of disruption, then why do successful products (or companies) keep getting disrupted?”

Good question, and here’s how I think about answering it.

As far back as 1962, Everett Rogers began his groundbreaking work defining the process and diffusion of innovation. Rogers defined the spread of innovation in the stages of knowledge, persuasion, decision, implementation and confirmation.

Those powerful concepts, however, do not fully describe disruptive technologies and products, and the impact on the existing technology base or companies that built it. Disruption is a critical element of the evolution of technology — from the positive and negative aspects of disruption a typical pattern emerges, as new technologies come to market and subsequently take hold.

A central question to disruption is whether it is inevitable or preventable. History would tend toward inevitable, but an engineer’s optimism might describe the disruption that a new technology can bring more as a problem to be solved.

Four Stages of Disruption

For incumbents, the stages of innovation for a technology product that ultimately disrupt follow a pattern that is fairly well known. While that doesn’t grant us the predictive powers to know whether an innovation will ultimately disrupt, we can use a model to understand what design choices to prioritize, and when. In other words, the pattern is likely necessary, but not sufficient to fend off disruption. Value exists in identifying the response and emotions surrounding each stage of the innovation pattern, because, as with disruption itself, the actions/reactions of incumbents and innovators play important roles in how parties progress through innovation. In some ways, the response and emotions to undergoing disruption are analogous to the classic stages of grieving.

Rather than the five stages of grief, we can describe four stages that comprise theinnovation pattern for technology products: Disruption of incumbent; rapid and linear evolution; appealing convergence; and complete reimagination. Any product line or technology can be placed in this sequence at a given time.

The pattern of disruption can be thought of as follows, keeping in mind that at any given time for any given category, different products and companies are likely at different stages relative to some local “end point” of innovation.


Stage One: Disruption of Incumbent

moment of disruption is where the conversation about disruption often begins, even though determining that moment is entirely hindsight. (For example, when did BlackBerry get disrupted by the iPhone, film by digital imaging or bookstores by Amazon?) A new technology, product or service is available, and it seems to some to be a limited, but different, replacement for some existing, widely used and satisfactory solution. Most everyone is familiar with this stage of innovation. In fact, it could be argued that most are so familiar with this aspect that collectively our industry cries “disruption” far more often than is actually the case.

From a product development perspective, choosing whether a technology is disruptive at a potential moment is key. If you are making a new product, then you’re “betting the business” on a new technology — and doing so will be counterintuitive to many around you. If you have already built a business around a successful existing product, then your “bet the business” choice is whether or not to redirect efforts to a new technology. While difficult to prove, most would generally assert that new technologies that are subsequently disruptive are bet on by new companies first. The very nature of disruption is such that existing enterprises see more downside risk in betting the company than they see upside return in a new technology. This is the innovator’s dilemma.

The incumbent’s reactions to potential technology disruptions are practically cliche. New technologies are inferior. New products do not do all the things existing products do, or are inefficient. New services fail to address existing needs as well as what is already in place. Disruption can seem more expensive because the technologies have not yet scaled, or can seem cheaper because they simply do less. Of course, the new products are usually viewed as minimalist or as toys, and often unrelated to the core business. Additionally, business-model disruption has similar analogues relative to margins, channels, partners, revenue approaches and more.

The primary incumbent reaction during this stage is to essentially ignore the product or technology — not every individual in an organization, but the organization as a whole often enters this state of denial. One of the historical realities of disruption is uncovering the “told you so” evidence, which is always there, because no matter what happens, someone always said it would. The larger the organization, the more individuals probably sent mail or had potential early-stage work that could have avoided disruption, at least in their views (see “Disruption and Woulda, Coulda, Shoulda” and the case of BlackBerry). One of the key roles of a company is to make choices, and choosing change to a more risky course versus defense of the current approaches are the very choices that hamstring an organization.

There are dozens of examples of disruptive technologies and products. And the reactions (or inactions) of incumbents are legendary. One example that illustrates this point would be the introduction of the “PC as a server.” This has all of the hallmarks of disruption. The first customers to begin to use PCs as servers — for application workloads such as file sharing, or early client/server development — ran into incredible challenges relative to the mini/mainframe computing model. While new PCs were far more flexible and less expensive, they lacked the reliability, horsepower and tooling to supplant existing models. Those in the mini/mainframe world could remain comfortable observing the lack of those traits, almost dismissing PC servers as not “real servers,” while they continued on their path further distancing themselves from the capabilities of PC servers, refining their products and businesses for a growing base of customers. PCs as servers were simply toys.

At the same time, PC servers began to evolve and demonstrate richer models for application development (rich client front-ends), lower cost and scalable databases, and better economics for new application development. With the rapidly increasing demand for computing solutions to business problems, this wave of PC servers fit the bill. Soon the number of new applications written in this new way began to dwarf development on “real servers,” and the once-important servers became legacy relative to PC-based servers for those making the bet or shift. PC servers would soon begin to transition from disruption to broad adoption, but first the value proposition needed to be completed.

Stage Two: Rapid Linear Evolution

Once an innovative product or technology begins rapid adoption, the focus becomes “filling out” the product. In this stage, the product creators are still disruptors, innovating along the trajectory they set for themselves, with a strong focus on early-adopter customers, themselves disruptors. The disruptors are following their vision. The incumbents continue along their existing and successful trajectory, unknowingly sealing their fate.

This stage is critically important to understand from a product-development perspective. As a disruptive force, new products bring to the table a new way of looking at things — a counterculture, a revolution, an insurgency. The heroic efforts to bring a product or service to market (and the associated business models) leave a lot of room left to improve, often referred to as “low-hanging fruit.” The path from where one is today to the next six, 12, 18 months is well understood. You draw from the cutting-room floor of ideas that got you to where you are. Moving forward might even mean fixing or redoing some of the earlier decisions made with less information, or out of urgency.

Generally, your business approach follows the initial plan, as well, and has analogous elements of insurgency. Innovation proceeds rapidly in this point. Your focus is on the adopters of your product — your fellow disruptors (disrupting within their context). You are adding features critical to completing the scenario you set out to develop.

To the incumbent leaders, you look like you are digging in your heels for a losing battle. In their view, your vector points in the wrong direction, and you’re throwing good money after bad. This only further reinforces the view of disruptors that they are heading in the right direction. The previous generals are fighting the last war, and the disruptors have opened up a new front. And yet, the traction in the disruptor camp becomes undeniable. The incumbent begins to mount a response. That response is somewhere between dismissive and negative, and focuses on comparing the products by using the existing criteria established by the incumbent. The net effect of this effort is to validate the insurgency.

Stage Three: Appealing Convergence

As the market redefinition proceeds, the category of a new product starts to undergo a subtle redefinition. No longer is it enough to do new things well; the market begins to call for the replacement of the incumbent technology with the new technology. In this stage, the entire market begins to “wake up” to the capabilities of the new product.

As the disruptive product rapidly evolves, the initial vision becomes relatively complete (realizing that nothing is ever finished, but the scenarios overall start to fill in). The treadmill of rapidly evolving features begins to feel somewhat incremental, and relatively known to the team. The business starts to feel saturated. Overall, the early adopters are now a maturing group, and a sense of stability develops.

Looking broadly at the landscape, it is clear that the next battleground is to go after the incumbent customers who have not made the move. In other words, once you’ve conquered the greenfield you created, you check your rearview mirror and look to pick up the broad base of customers who did not see your product as market-ready or scenario-complete. To accomplish this, you look differently at your own product and see what is missing relative to the competition you just left in the dust. You begin to realize that all those things your competitor had that you don’t may not be such bad ideas after all. Maybe those folks you disrupted knew something, and had some insights that your market category could benefit from putting to work.

In looking at many disruptive technologies and disruptors, the pattern of looking back to move forward is typical. One can almost think of this as a natural maturing; you promise never to do some of the things your parents did, until one day you find yourself thinking, “Oh my, I’ve become my parents.” The reason that products are destined to converge along these lines is simply practical engineering. Even when technologies are disrupted, the older technologies evolved for a reason, and those reasons are often still valid. The disruptors have the advantage of looking at those problems and solving them in their newly defined context, which can often lead to improved solutions (easier to deploy, cheaper, etc.) At the same time, there is also a risk of second-system syndrome that must be carefully monitored. It is not uncommon for the renegade disruptors, fresh off the success they have been seeing, to come to believe in broader theories of unification or architecture and simply try to get too much done, or to lose the elegance of the newly defined solution.

Stage Four: Complete Reimagination

The last stage of technology disruption is when a category or technology is reimagined from the ground up. While one can consider this just another disruption, it is a unique stage in this taxonomy because of the responses from both the legacy incumbent and the disruptor.

Reimagining a technology or product is a return to first principles. It is about looking at the underlying assumptions and essentially rethinking all of them at once. What does it mean to capture an image,provide transportationshare computationsearch the Web, and more? The reimagined technology often has little resemblance to the legacy, and often has the appearance of even making the previous disruptive technology appear to be legacy. The melding of old and new into a completely different solution often creates whole new categories of products and services, built upon a base of technology that appears completely different.

To those who have been through the first disruption, their knowledge or reference frame seems dated. There is also a feeling of being unable to keep up. The words are known, but the specifics seem like rocket science. Where there was comfort in the convergence of ideas, the newly reimagined world seems like a whole new generation, and so much more than a competitor.

In software, one way to think of this is generational. The disruptors studied the incumbents in university, and then went on to use that knowledge to build a better mousetrap. Those in university while the new mousetrap was being built benefited from learning from both a legacy and new perspective, thus seeing again how to disrupt. It is often this fortuitous timing that defines generations in technologies.

Reimagining is important because the breakthroughs so clearly subsume all that came before. What characterizes a reimagination most is that it renders the criteria used to evaluate the previous products irrelevant. Often there are orders of magnitude difference in cost, performance, reliability, service and features. Things are just wildly better. That’s why some have referred to this as the innovator’s curse. There’s no time to bask in the glory of the previous success, as there’s a disruptor following right up on your heels.

A recent example is cloud computing. Cloud computing is a reimagination ofboth the mini/mainframe and PC-server models. By some accounts, it is a hybrid of those two, taking the commodity hardware of the PC world and the thin client/data center view of the mainframe world. One would really have to squint in order to claim it is just that, however, as the fundamental innovation in cloud computing delivers entirely new scale, reliability and flexibility, at a cost that upends both of those models. Literally every assumption of the mainframe and client/server computing was revisited, intentionally or not, in building modern cloud systems.

For the previous incumbent, it is too late. There’s no way to sprinkle some reimagination on your product. The logical path, and the one most frequently taken, is to “mine the installed base,” and work hard to keep those customers happy and minimize the mass defections from your product. The question then becomes one of building an entirely new product that meets these new criteria, but from within the existing enterprise. The number of times this has been successfully accomplished is diminishingly small, but there will always be exceptions to the rule.

For the previous disruptor and new leader, there is a decision point that is almost unexpected. One might consider the drastic — simply learn from what you previously did, and essentially abandon your work and start over using what you learned. Or you could be more incremental, and get straight to the convergence stage with the latest technologies. It feels like the ground is moving beneath you. Can you converge rapidly, perhaps revisiting more assumptions, and show more flexibility to abandon some things while doing new things? Will your product architecture and technologies sustain this type of rethinking? Your customer base is relatively new, and was just feeling pretty good about winning, so the pressure to keep winning will be high. Will you do more than try to recast your work in this new light?

The relentless march of technology change comes faster than you think.

So What Can You Do?

Some sincerely believe that products, and thus companies, disrupt and then are doomed to be disrupted. Like a Starship captain when the shields are down, you simply tell all hands to brace themselves, and then see what’s left after the attack. Business and product development, however, are social sciences. There are no laws of nature, and nothing is certain to happen. There are patterns, which can be helpful signposts, or can blind you to potential actions. This is what makes the technology industry, and the changes technology bring to other industries, so exciting and interesting.

The following table summarizes the stages of disruption and the typical actions and reactions at each stage:

Stage Disruptor Incumbent
 Disruption      of    Incumbent Introduces new product with a distinct point of view, knowing  it does not solve all the needs of the entire existing market, but advances the state of the art in technology and/or business. New product or service is not relevant to existing customers or market, a.k.a. “deny.”
 Rapid linear  evolution Proceeds to rapidly add features/capabilities, filling out the value proposition after initial traction with select early adopters. Begins to compare full-featured product to new product and show deficiencies, a.k.a. “validate.”
 Appealing  Convergence Sees opportunity to acquire broader customer base by appealing to slow movers. Sees limitations of own new product and learns from what was done in the past, reflected in a new way. Potential risk is being leapfrogged by even newer technologies and business models as focus   turns to “installed base” of incumbent. Considers cramming some element of disruptive features to existing product line to sufficiently demonstrate attention to future trends while minimizing interruption of existing customers, a.k.a. “compete.” Potential risk is failing to see the true value or capabilities of disruptive products relative to the limitations of existing products.
 Complete  Reimagining Approaches a decision point because new entrants to the market can benefit from all your product has demonstrated, without embracing the legacy customers as done previously. Embrace legacy market more, or keep pushing forward? Arguably too late to respond, and begins to define the new product as part of a new market, and existing product part of a larger, existing market, a.k.a. “retreat.”

Considering these stages and reactions, there are really two key decision points to be tuned-in to:

When you’re the incumbent, your key decision is to choose carefully what you view as disruptive or not. It is to the benefit of every competitor to claim they are disrupting your products and business. Creating this sort of chaos is something that causes untold consternation in a large organization. Unfortunately, there are no magic answers for the incumbent.

The business team needs to develop a keen understanding of the dynamics of competitive offerings, and know when a new model can offer more to customers and partners in a different way. More importantly, it must avoid an excess attachment to today’s measures of success.

The technology and product team needs to maintain a clinical detachment from the existing body of work to evaluate if something new is better, while also avoiding the more common technology trap of being attracted to the next shiny object.

When you’re the disruptor, your key decision point is really when and if to embrace convergence. Once you make the choices — in terms of business model or product offering — to embrace the point of view of the incumbent, you stand to gain from the bridge to the existing base of customers.

Alternatively, you create the potential to lose big to the next disruptor who takes the best of what you offer and leapfrogs the convergence stage with a truly reimagined product. By bridging to the legacy, you also run the risk of focusing your business and product plans on the customers least likely to keep pushing you forward, or those least likely to be aggressive and growing organizations. You run the risk of looking backward more than forward.

For everyone, timing is everything. We often look at disruption in hindsight, and choose disruptive moments based on product availability (or lack thereof). In practice, products require time to conceive, iterate and execute, and different companies will work on these at different paces. Apple famously talked about the 10-year project that was the iPhone, with many gaps, and while the iPad appears a quick successor, it, too, was part of that odyssey. Sometimes a new product appears to be a response to a new entry, but in reality it was under development for perhaps the same amount of time as another entry.

There are many examples of this path to disruption in technology businesses. While many seem “classic” today, the players at the time more often than not exhibited the actions and reactions described here.

As a social science, business does not lend itself to provable operational rules. As appealing as disruption theory might be, the context and actions of many parties create unique circumstances each and every time. There is no guarantee that new technologies and products will disrupt incumbents, just as there is no certainty that existing companies must be disrupted. Instead, product leaders look to patterns, and model their choices in an effort to create a new path.

Stages of Disruption In Practice

Digital imaging. Mobile imaging reimagined a category that disrupted film (always available, low-quality versus film), while converging on the historic form factors and usage of film cameras. In parallel, there is a wave of reimagination of digital imaging taking place that fundamentally changes imaging using light field technology, setting the stage for a potential leapfrog scenario.

  • Retail purchasing. Web retailers disrupted physical retailers with selection, convenience, community, etc., ultimatelyconverging on many elements of traditional retailers (physical retail presence, logistics, house brands).
  • Travel booking. Online travel booking is disrupting travel agents, then converging on historic models of aggregation and package deals.
  • Portable music. From the Sony Walkman as a disruptor to the iPod and MP3 players, to mobile phones subsuming this functionality, and now to streaming playback, portable music has seen the disruptors get disrupted and incumbents seemingly stopped in their tracks over several generations. The change in scenarios enabled by changing technology infrastructure (increased storage, increased bandwidth, mobile bandwidth and more) have made this a very dynamic space.
  • Urban transport. Ride sharing, car sharing, and more disruptive traditional ownership of vehicles or taxi services are in the process of converging models (such as Uber adding UberX.
  • Productivity. Tools such as Quip, Box, Haiku Deck, Lucidchart, and more are being pulled by customers beyond early adopters to be compatible with existing tools and usage patterns. In practice, these tools are currently iterating very rapidly along their self-defined disruptive path. Some might suggest that previous disruptors in the space (OpenOffice, Zoho, perhaps even Google Docs) chose to converge with the existing market too soon, as a strategic misstep.
  • Movie viewing. Netflix and others, as part of cord-cutting, with disruptive, low-priced, all-you-can-consume on-demand plans and producing their own content. Previous disruptors such as HBO are working to provide streaming and similar services, while constrained by existing business models and relationships.
  • Messaging/communications apps. SMS, which many consider disruptive to 2000-era IM, is being challenged by much richer interactions that disrupt the business models of carrier SMS and feature sets afforded by SMS.
  • Network infrastructure. Software-defined networking and cloud computing are reimagining the category of networking infrastructure, with incumbent players attempting to benefit from these shifts in the needs of customers. Incumbents at different levels are looking to adopt the model, while some providers see it as fundamentally questioning their assumptions.

— Steven Sinofsky (@stevesi). This story originally appeared on Recode.

Written by Steven Sinofsky

January 7, 2014 at 9:00 pm

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