Why Redesigns are So Damn Hard

Redesigning social functionality – that is, re-doing a social product already in use by some sort of entrenched audience – is sometimes tougher than designing from scratch. Very often you're fighting against organizational and institutional inertia; legacy issues that determine what's actually possible; entrenched user expectations; nervous stakeholders demanding guarantees; and a little understood, fickle market always on the verge of catastrophic "creative destruction".

But what interests me here, is that in my experience the difficulty of redesigning a product – both the subjective experience of effort and the objective expenditure of time and attention in completing a redesign, start to finish – seems to vary with the product's success, but not in a particularly straightforward manner. That is, how successful the product to be redesigned currently is affects the difficulty of the process in a complex, non-intuitive way. Why?

Well, first of all there are at least three big classes of factors impacting the difficulty of redesigning a site. Some of these are important in designing the site from scratch, too, but the way they interact with the current success of the product when embarking on a redesign is what interests me. The three factors are Market Information, User Entrenchment, and The Organization.

Market Information
When redesigning, we look to the market for clues, approach our users for tests, and effectively try to tease out guidance from the field. Ultimately, we're looking for the formula for design success. But this stuff is incredibly complicated, including such things as the design conventions determining current user expectations; the competitive landscape identifying areas of relevant differentiation; trend dynamics suggesting potential "innovations"; etc. But the most subtly difficult factors are the complex social dynamics of product acceptance. I've written about these before: the hard to discern workings of network effects, informational cascades, and the resultant path dependencies cause enormous confusion among stakeholders, greatly increasing the difficulty of redesigning social functionality. In our misguided search for a simple formula for redesign success, these factors, which decrease the role of product qualities (the stuff of design) in predicting product success, can really lead you astray.

In a nutshell, the externalities inherent in the social web (i.e. we initially evaluate a product based on others' actions and then get the most value from the products that everyone else uses) make predicting success from product qualities almost impossible. Success is usually a matter of context, timing and accidents of the product's acceptance history rather than objective design quality. So, beyond a set of user expectation-defining standards – the competitive baseline, which you should have already identified in the initial design round – market analysis and user research won't help you identify a redesign guaranteed to succeed.

Even worse, up to a certain point, the more relative success you have, the murkier the information derivable from testing users and combing the market becomes. Your variance from the competitive baseline tends to be smaller the more successful you are, and the true drivers of success are rarely clear cut product design issues beyond this competitive baseline. Very few stakeholders understand these subtle dynamics and insist that more market research, testing and "innovation" will crack the "guaranteed success" design code. As a result, redesigns of moderately successful products tend to bog down in obsessive, inconclusive research, the results of which are infinitely and inconsistently interpretable (especially if testing is public). Research is necessary, but will never provide a guarantee.

User Entrenchment
Perceived usability – as opposed to laboratory usability – is more about familiarity than objective human factors metrics. Users invest their time and attention in your product, amassing a sort of practical capital of product-specific know-how. When you start changing things, they view this as effectively theft of a precious resource: their investment in practical capital has been thrown out the window without their explicit blessing.

As anyone who has ever redesigned anything knows, users get angry when they feel they've wasted time and attention; they must reinvest to get back to the same level of practical capital. So, up to the point where nearly everybody's using your product and there's no real alternative (i.e. where the network effect is so strong and the average user's "sunk cost" so great they overcome practically all anger over perceived losses associated with change), redesigns get dicier the greater the success of the product. One consequence of this is that testing redesigns with current users will significantly skew your results toward the negative, regardless of "actual" quality. If these tests are public, you've just created a significant political battle and, thus, headaches.

The Organization
There are two related but distinct sources of organizational inertia. First, people within the organization simply get used to doing things one way and – being human – are reluctant to change. If the product's relatively successful, that felt reluctance can be rationalized by arguing that any redesign is a dangerous and unneeded rocking of the boat that endangers continuing success. Slowdowns, endless discussion, and frequent miscommunications are usually the result.

Next, as much as I hate calling simple regularities or covariances "laws" for comic effect (Moore's Law, Metcalfe's Law, etc.), Conway's Law, or something like it, seems to be pretty prevalent. In 1968, Melvin Conway observed that organizations produce products that mirror their structure or at least their internal communication patterns. He was referring specifically to the development of intercommunicating software systems produced by different design teams existing in some sort of institutional, social or communication structure. His claim is that this structure will manifest itself in the design of the interfaces between the systems.

Conway thought this was inevitable, which is way too strong by my lights. But stretching the idea a bit, some products, particularly websites, often mirror the structures of the organizations that created them. Furthermore, it seems to go the other way as well. Sometimes the organization and product have co-evolved in such a way that they're truly intermingled or even identified in many stakeholder's minds. Stakeholders view the product as a direct manifestation of the organization, and any change to the former necessarily impacts the latter.

Whatever the underlying mechanisms that generate this feeling, the upshot is that redesigning a product often has organizational implications, at least in terms of many stakeholders' perceptions of the project. Tampering with the product is often perceived as tampering with roles, responsibilities, and the delicately negotiated distribution of power within the organization. Understandably, this can lead to a significant amount of internal resistance, particularly when the product has been relatively successful and actual power and prestige have accumulated. The resulting inertia and sometimes downright sabotage can lead to massive struggles and delays.

These factors interact with the current success of the product (and with each other) to impact the difficulty of redesigning the product. Drawing from my highly subjective experience designing, redesigning, and "researching" social functionality, the situation seems to look something like this:


On the x axis is increasing success and on the y axis, increasing difficulty of redesigning the product. Some of the more interesting areas have been called out with letters. I'll discuss them briefly.

Why is a more difficult than b? After all, nobody's using the product, so redesign should be really easy. At this level of market failure, if you're asked to do a redesign, you should consider it carefully: this product should be completely abandoned and a different product built. But if you have to do a redesign, the whole organization probably understands and embraces the need to change and analyzing the market may help you identify appropriate conventions, standards and design directions. However, you are re-starting from a hole with little prospect of success (remember the importance of network externalities). Your potential users have already invested somewhere else (this a redesign… you had an initial chance and blew it. At this point your users have invested elsewhere and people burned earlier won't come back.). Finally, you have absolutely no user data on which to base your redesign recommendations and no prospect of launching then optimizing, bootstrapping your way to a successful design. After all, there's not enough activity to get a picture of where it's failing or succeeding; analyzing the market will suggest directions, but you can't really put it out there and optimize on the fly as no one's using your product.

As success modestly improves to b, the ease of redesign increases dramatically. At this point, your stakeholders are still ready for change. Analyzing the market could probably still help with design standards, conventions and trends. But now you have some data on what might work and what definitely won't. You have real users that you can gently test against, but not so many that changes will be met with a loud protest. You also have at least a foothold, which, with luck could be turned into something more by doing everything you can to generate an informational cascade through targeted design differentiation and smart positioning/marketing.

But things get progressively tougher from b to c. You're probably nearing the conventional designs as you're at least competitive at this level of success, so analyzing the market too much could lead to frustration and confusion among your stakeholders. Selling designs internally becomes more difficult as the product's modest success has been enough to spread a bit of influence and power throughout the organization. But, there are enough users to make switching costs to another product at least non-negligible to many users. However, the User Entrenchment process begins to become an issue at this point, as you've enough success for your users to have begun internalizing the system.

From c the difficulty quickly rises with success, slowing to a peak at d. This is the zone of incredible difficulty for a redesign; throughout this region all of the factors are potentially against you. Unless you're just adding hot new functionality pioneered by a competitor, culling the market for tips will be largely fruitless. You're most likely conventional – if not the leader – at this level of success, so most of the factors determining further success are those frustrating, inconsistently interpretable, and highly contingent social dynamics. Thus prolonged research and analysis in this situation actually pays little – and often costs much in terms of focus, morale and transactions. But most organizations in this range still get hung up searching the field and bugging their users in an obsessive search for a magic design formula when they should just be looking for suggestive trends to fuel experimentation. But you have to remember, users in this range become ever more entrenched, so the "right" changes are both difficult to identify and nearly impossible to justify through testing or interviews. Users want what they know now, not what they will want later, so at high levels of entrenchment asking them to evaluate a change (as opposed to just testing lab usability) often confuses the issue or leads to the agonizing death of bold new designs. Finally, organizationally, great success can make people scared to change for fear of losing it (people are, after all, far more risk averse than gain hungry). The organization has "rigidified." Success has pumped prestige and power into it's structure, creating significant vested interests in maintaining status quo. Projects in this range can quickly become nightmares.

At d, however, things turn around a little. Though it's never as easy as it is when you've poor to moderate success, the network effect is so strong, that the specter of losing position is largely mooted. That effectively removes the rationalization for status quo from within the organization and greatly mitigates the sting of negative test results from entrenched users. Also, at this point, you lead the market and most of the tips you're looking for are in terms of competitive and trend analysis, not the elusive success guaranteeing design formula. You largely co-determine the conventions defining the completive baseline along with other highly successful players. Thus, redesign at this point becomes slightly easier, but there's still there's a lot of reluctance from those who might fear loss of position and entrenched users will definitely make a lot of noise, which is never pleasant.

Redesigns are necessary to stay competitive. But along with the excitement and product / organizational rejuvenation they generate, they can also be headaches for the designers involved. Hopefully I've managed to shed some light on why and how. As I said, all of this stems form my subjective observation that redesign difficulty seems somehow oddly related to product success. Whether or not your experience of the relation between the two mirrors mine, I hope you'll at least agree that there's some relationship and that it's impacted by the factors I've suggested.

Trendsetters, Hipsters and Regular Joes: value curves and cultural trends

Luis Bettencourt suggests that trend setting and following can be thought of as a game that offers maximal benefit for those who partake of a successful trend as early as possible, ride it to its height and then bail before it loses momentum and crashes. But different people are likely to engage trends (and cultural artifacts in general) at different points in the trend’s life cycle and for different reasons. Some people self-consciously seek out novelty; others monitor the culture for the most promising up and coming trends; and still others simply follow the majority’s lead. It’s as if “communities” are comprised of sub-populations that differ in the way they evaluate trends relative to their uptake by the larger population.

Of course there are a large number of cultural factors (consumption/cultural capital; salient norms; symbolic capital and esteem; etc.) other than their fellow agents' behavior that impact people's evaluation of a trend. But for this post we want to hold those things steady and look at how the general uptake of a trend within a population impacts the trend’s attractiveness to three distinct sub-populations: trendsetters, hipsters and regular joes.

All in all it’s a system characterized by mutual interdependence, with agent’s evaluations of whether or not to join a trend strongly influenced by others’ opinions and expectations as evidenced by their actions (this includes the so-called trendsetters). With trends, it’s generally believed that the more others partake, the more valuable it is – up to a point – for the average agent to partake. For example, most people wouldn’t want to be the first person to introduce a fashion, but are willing to rock it once a significant (but not overwhelming) number of relevant others have. We can illustrate this idea with the following graph.


As the population partaking increases from 0 to n the value of partaking moves from negative to positive at point a. This is the so-called tipping point. From there it climbs until point b where saturation devalues the trend. To keep things simple, we’ll pretend that the trend eventually collapses and disappears or else becomes part of the cultural fabric – a presupposition – like wearing clothes in public in most Western cultures. In both of these cases, we’ll just say that the valuation tends to 0 as uptake approaches n. (Actually, there are several distinct possibilities for a trend’s life after point b, but those will be investigated in another post.)

That’s fine for the average cultural consumer, the regular joe, but what about people we would consider trendsetters? These people self-consciously value things few others do. Does their value curve look like this? Well, if we expressly confine n to their reference group – the people from whom they directly seek esteem and acceptance – then, yes. However, if we say n is some largish portion of the people in the trendsetter’s wider community, then, no. Trendsetters – or at least the cultural connoisseur and contrarian varieties – tend to value certain trends (and cultural artifacts generally, like bands, fashions, etc.) because they aren’t widely appreciated within their community (though they must be at least understandable within their reference group). Though many other cultural variables (consumption capital, cultural capital, etc.) come into play, the snotty urban movie store employee likes that movie you’ve never heard of partly because you’ve never heard of it.

So, those are two extremes, the regular joes and the trendsetters. The regular joes tend to hold off on positive evaluation until the expectation of general participation is high. Trendsetters on the other hand evaluate trends by more reference-group focused cultural standards (which we’ll ignore here) along with the trend’s uptake among the general public. For the little cultural caricature we’re doodling, we can say they’re pretty much opposed. As trend uptake moves toward the tipping point – point a in the graph above – it decreases in value for the trendsetter, ultimately becoming negative.

But there’s a third group worth looking at. I call this group the hipsters, but they aren’t exactly the tight-jeaned crew we associate with that word today. Some elements of the contemporary version, however, are descended from the more general hipster I’m considering here.

Hipsters aren’t trendsetters because they’re interested in finding only the winning trends. But they’re not regular joes either because they want to join prior to general uptake; they highly value joining before the tipping point. They want some of the cultural novelty, or attendant symbolic capital, of partaking of something others don’t currently but may soon value. But they also want that symbolic capital to extend beyond the trendsetter’s tightly focused reference group into the more general population. That is, they want the esteem that can be gotten from truthfully saying “I was into that before it was cool.” However, they also value novelty enough to bail on trends prior to their peak and subsequent collapse. So they value trends highest around the tipping point, but devaluation sets in shortly thereafter.

Anyway, putting all three idealized types together gives us the following graph.


The trendsetter disvalues the new and under-represented trend much less than the hipster and the regular joe, thus he starts from a point much closer to neutrality (of course, he could start from neutral or even positive). It also takes a much smaller portion of the population partaking (a couple of fellow trendsetters) for the trendsetter to positively evaluate the trend.

As the new thing catches on among the trendsetters, it approaches point a. At this point the hipsters, who have been monitoring the culture for up and coming trends, take note and the trend moves from negative to positive for them. This is a tipping point for the hipsters and it marks the beginning of devaluation for the trendsetter.

Absolute devaluation for the trendsetter occurs at point b, the tipping point for the regular joes and the point of highest value for the hipsters. The trend has nothing to offer the trendsetters anymore as it has now been officially accepted by the mainstream. The hipsters act as a bridge between the miniscule number of trendsetters and bulk of the population. Indeed, they are probably the ones that bring trends at the cultural periphery into the mainstream, giving them enough exposure to decrease their disvalue to the regular joes.

Moving from b to c, the trendsetter’s value curve declines while the regular joe’s peaks. The hipster, however, has had steadily diminishing value since the peak at b. Around c, it goes negative and only returns to neutrality as the trend is in absolute decline/disappearance on approach to n. In future posts I’ll look at a more complete model of the possibilities after c.

The most interesting thing about this model is that it paints a relatively intuitive picture of how three groups of cultural consumers/producers value trends relative to each other’s valuations. And if we squint a little, it meshes relatively well with Duncan Watts’s [pdf] contention that the most important element in a viral model isn’t necessarily the Influentials (here, the trendsetters, who are looked to by others as harbingers of hot new trends), but rather the connected subgroup of folks with low switching and adoption costs (here, the hipsters, who pick up and amplify trends that become highly valued among the trendsetters). Hipsters are seeking a broader display of cultural capital and the accumulation of symbolic capital or esteem in general and thus seek out potentially successful trends, joining early and switching often. To that end, they bring trends into the mainstream and give them enough exposure to potentially tip the regular joe’s. Without them, the trend might be noticed but not generally valued.

The Bottom Line is I Hate Jargon: why hated language is inescapable

Everybody says they hate jargon, but everybody uses it. How can jargon be so hated yet so prevalent? It’s clearly more than just a personal shortcoming of your annoying co-workers. It’s more likely that jargon is a symptom of sociability and thus we’re all susceptible to it. Looking closely, there seem to be at least three types of irritating jargon (each with its own jargon-like name!):

Fluffy Neologisms (FuNs): Often a “verbized” noun or a verb phrase shortened to one word, e.g. conversate for have a conversation. Frequently an active sounding, metaphorical stock phrase for something simple, e.g. circle back for get back to you and take it offline for talk after the meeting. FuNs are most often emergent (bottom-up).

Pernicious Euphemisms (PEus): These are classic business speak, e.g. calling criticisms opportunities. The purpose is to mask some harsh reality, neutralize something negative or insinuate desired behavior (e.g. employees must be passionate – i.e. work-obsessed, myopic, ass-kissers – as opposed to just good at their jobs). PEus tend to be institutionally imposed (top-down).

Exclusionary Technicalities (ETs): These are jargon in the traditional sense of “words or expressions that are used by a particular profession or group and are difficult for others to understand”, e.g. AJAX interface or MVC Architecture. They’re domain specific “technical” terms intended to ease in-group communication. ETs can be either institutionally imposed (by e.g. standards bodies) or emergent (from e.g. open source developers).

We tend not to think of legitimate uses of ETs as jargon in the pejorative sense (unless you are particularly insecure). After all, these words have a technical rationale. What gets us miffed is inappropriate use by the tech guy in an effort to maintain his wizard status. So, for ETs it’s intention that matters. A lame, illegitimate use can turn an ET into a PEu and open the user up to justified criticism. Indeed, many words that end up as PEus probably started out as ETs in management science.

FuNs, though, seem inexcusable to most people. They probably stem from middle-management aping the “management science” consultants they caught the PEus from. And that’s part of my point: jargon is catching. It’s not simply some aggravating sign of your boss’s personality disorder. Rather, it’s a symptom of sociability which we all display; it's an equilibrium in a social market like a fad or a trend. Of course, there is the pretension to hate, but generally before the pretension there was the desire to communicate something in a codified way.

The net net on jargon...

Typically, we’re aggravated by jargon in one of the following three ways.

1. We consider it pretentious when the user is too obviously attempting to wring cultural or social profit from what should be a purely instrumental linguistic exchange.

2. We’re exasperated when some overused phrase, which has been nearly drained of significance by loose use, is unreflectively trotted out. This sort of hackneyed jargon is often used more as a combination filler/badge than as a thoughtful addition to the discourse, serving no purpose in the conversation other than a noise our type tends to make in situations like this one.

3. Worst of all, we’re infuriated when someone mixes 1) and 2), using hackneyed jargon pretentiously.

But if you look at these from the other direction – from the jargon user’s perspective – you can see how the user could derive value from using jargon. After all, people don’t use jargon in order to be negatively viewed by others; presented with socially informed options, they have made a choice, albeit a non-deliberative one. When we have questions about a choice, look to the expected value of the options for some answers.

Let’s start with the most straightforward example: legitimate uses of Exclusionary Technicalities (ETs). You can see how these are valuable: they are agreed upon domain specific names for objects, phenomena, etc. If we want to speak efficiently and non-circuitously when discussing these things with our peers, we should use the jargon. The more people who use the term for the intended thing, the more valuable the term becomes in the field and the more value it holds for a potential adopter. After a certain percentage of your peers start using the jargon it behooves you to climb aboard. We call this a network effect: the more folks using the jargon, the more valuable it becomes. Network effects can lead to cascades (where everyone sees the value of adopting the jargon as greater than not adopting) and suddenly the jargon is everywhere.

People legitimately using ETs tend to value communication; the jargon’s value to them is in speaking the language their peers speak. The “value function” is stable, producing a value that rises rapidly to a plateau and maintains high value for a long time provided there are no relevant shocks (say, new standards rendering the old ones obsolete). We call this a monotonic externality. The value function tends to go in one direction, up, until the plateau. It doesn’t suddenly reverse with changes in use of the term.

Illegitimate uses of ETs, however, are a slightly different story. For example, I hear of a technology that’s getting a lot of buzz in the tech blogs and that I’m sure all of my clients will want soon. I drop the new jargon in meetings, making myself more attractive to the client. Of course, all other strategists are doing the same thing. The ET, which solidified it’s value in the tech world enough to be noticed in our non-tech world, is clearly of value to a lot of smart people. So, we assume its value without doing any sort of true evaluation. Many other people do the same thing. Next thing you know, everybody’s talking about and asking for AJAX interfaces, or MVC Platforms, yet very few know just what these are. These ETs have become jargon in the bad sense. Now we’re in an Informational Cascade: given a certain number of visible and presumptively knowledgeable adopters, people stop evaluating and go straight to adopting. The more the jargon’s exposed by adopters, the faster it’s adopted by others.

However, informational cascades are very unstable. Once someone actually does stop and try to figure out what’s being talked about, the cascade can be very quickly shattered. Ideas that spread like wildfire can die out just as fast. The jargon then becomes an embarrassment... what was the big freakin’ deal about “Web 2.0”? Then a backlash can set in.

PEus and FuNs are the prime examples of this sort of success followed by backlash. Despite their differences, they tend to follow the same general cycle: acceptance and use followed by derision and annoyance.

This “value function” that increases rapidly creating a cascade and then crashes just as rapidly after a certain point seems to be what’s called a non-monotonic externality. That is, the value of adopting becomes negative after a certain level of adoption within your group; after a certain level of saturation it becomes uncool, embarrassing or simply over-inflated like a linguistic bubble in a socio-cultural market. A value curve like this looks just like a fad or fashion curve.

In this case, the value function is pretty interesting. There’s an element of “network externality” in that jargon serves as shorthand in recurring situations and it’s assortative, defining your in-group. For these reasons, it behooves you to adopt if others in your group are. But then there’s also an element of informational cascade in that we value adoption simply because others are doing it. It’s about unreflective conformity and social learning. So it’s coordinating to a large extent. Still the curve suggests that difference is significant. That is, the value function delivers disvalue given a certain saturation. But our experience with offices is that negative feelings don’t set in until much later than most fads. Often, an office has to be lousy with a particular bit of jargon before we start to hate it.

Everyone’s “value function” is different, of course. Some get annoyed very easily (“misfits”) and others never really get annoyed (“team players”). Also, whether we evaluate jargon negatively or not is very contextual. I could listen two techies spewing jargon at each other all day and not care, but if one of them scares a client with a string of acronyms, I could really get annoyed.

Basically, the big moral is that we all tend to use jargon and it’s not a personal shortcoming. Rather it’s the result of very common social market conditions. Social markets are noted for each actor’s actions being partly determined by the actions of others. Dynamics like this lead to equilibria, but because of things like the fragility of informational cascades and non-monotonic externalities, they are fragile equilibria. We start to disvalue jargon that was once valued (even if non-deliberatively) for, among other reasons, the desire to feel distinct. We don’t like to feel conformist, while at the same time we clearly value a certain amount of conformity (viz. network effects and informational cascades). That’s just the nature of a non-monotonic value curve; the fact that something’s being used by our peers is reason enough to start doing it, but after a certain level of saturation we start to disvalue what we once valued (we can think of slang in similar terms, though the value curve is usually much shorter, thus it’s much more fragile or fickle). So, the conformity arises, but is rebelled against after a certain level of saturation.