Since 2005 startup accelerators have provided cohorts of startups with mentoring, pitch practice and product focus. However, accelerator Demo Days are a combination of the graduation ceremony and pitch contest, with the uncomfortable feel of a swimsuit competition. Other than “I’ll know it when I see it”, there’s no formal way for an investor attending Demo Day to assess project maturity or quantify risks. Other than measuring engineering progress, there’s no standard language to communicate progress.
Corporations running internal incubators face many of the same selection issues as startup investors, plus they must grapple with the issues of integrating new ideas into existing P&L-driven functions or business units.
What’s been missing for everyone is:
a common language for investors to communicate objectives to startups
a language corporate innovation groups can use to communicate to business units and finance
data that investors, accelerators and incubators can use to inform selection
While it doesn’t eliminate great investor judgment, pattern recognition skills and mentoring, we’ve developed an Investment Readiness Level tool that fills in these missing pieces.
Investment Readiness Level (IRL) for Corporations and Investors
The startups in our Lean LaunchPad classes and the NSF I-Corps incubator useLaunchPad Central to collect a continuous stream of data across all the teams. Over 10 weeks each team gets out of the building talking to 100 customers to test their hypotheses across all 9 boxes in the business model canvas.
We track each team’s progress as they test their business model hypotheses. We collect the complete narrative of what they discovered talking to customers as well as aggregate interviews, hypotheses to test, invalidated hypotheses and mentor and instructor engagements. This data gives innovation managers and investors a feel for theevidence and trajectory of the cohort as a whole and a top-level view of each teams progress. The software rolls all the data into an Investment Readiness Level score.
(Take a quick read of the post on the Investment Readiness Level – it’s short. Or watch the video here.)
The Power of the Investment Readiness Level: Different Metrics for Different Industry Segments Recently we ran a Lean LaunchPad for Life Sciences class with 26 teams of clinicians and researchers at UCSF. The teams developed businesses in 4 different areas– therapeutics, diagnostics, medical devices and digital health. To understand the power of this tool, look at how the VC overseeing each market segment modified the Investment Readiness Level so that it reflected metrics relevant to their particular industry.
Medical Devices Allan May of Life Science Angels modified the standard Investment Readiness Level to include metrics that were specific for medical device startups. These included; identification of a compelling clinical need, large enough market, intellectual property, regulatory issues, and reimbursement, and whether there was a plausible exit.
In the pictures below, note that all the thermometers are visual proxies for the more detailed evaluation criteria that lie behind them.
Therapeutics Karl Handelsman of CMEA Capital modified the standard Investment Readiness Level (IRL) for teams developing therapeutics to include identifying clinical problems, and agreeing on a timeline to pre-clinical and clinical data, cost and value of data points, what quality data to deliver to a company, and building a Key Opinion Leader (KOL) network. The heart of the therapeutics IRL also required “Proof of relevance” – was there a path to revenues fully articulated, an operational plan defined. Finally, did the team understand the key therapeutic liabilities, have data proving on-target activity and evidence of a therapeutic effect.
Digital Health For teams developing Digital Health solutions, Abhas Gupta of MDV noted that the Investment Readiness Level was closest to the standard web/mobile/cloud model with the addition of reimbursement and technical validation.
Diagnostics Todd Morrill wanted teams developing Diagnostics to have a reimbursement strategy fully documented, the necessary IP in place, regulation and technical validation (clinical trial) regime understood and described and the cost structure and financing needs well documented.
For their final presentations, each team explained how they tested and validated their business model (value proposition, customer segment, channel, customer relationships, revenue, costs, activities, resources and partners.) But they also scored themselves using the Investment Readiness Level criteria for their market. After the teams reported the results of their self-evaluation, the VC’s then told them how they actually scored. We were fascinated to see that the team scores and the VC scores were almost the same.
The Investment Readiness Level provides a “how are we doing” set of metrics
It also creates a common language and metrics that investors, corporate innovation groups and entrepreneurs can share
It’s flexible enough to be modified for industry-specific business models
It’s part of a much larger suite of tools for those who manage corporate innovation, accelerators and incubators
P.S. if you want to learn more abut the IRL and other tools, we teach a 2-day class for corporate innovation, accelerators and incubators. Info here
If you were forced to rely on only two target audiences to guide all your future design work, I’d strongly recommend using astronauts and toddlers. Fortunately, the connection between them goes beyond the design of their underwear to the nature of perception and expertise, and in what we treat as valid data, and what we choose to ignore as “noise”–the extraneous details, out-of-category input, the anecdotal tidbits. As it turns out, noise is much more valuable for useful design insights than you might think.
First, the astronauts. One little-known quirk of the Apollo moon landings was the difficulty the astronauts had judging distances on the Moon. The most dramatic example of this problem occurred in 1971 during Apollo 14, when Alan Shepard and Edgar Mitchell were tasked with examining the 1,000-foot-wide Cone Crater after landing their spacecraft less than a mile away. After a long, exhausting uphill walk in their awkward space suits, they just couldn’t identify the rim of the crater. Finally, perplexed, frustrated, and with the oxygen levels in their suits running low, they were forced to turn back. Forty years later, high-resolution images from new lunar satellites showed they had indeed come close–the trail of their footprints, still perfectly preserved in the soil, stop less than 100 feet from the rim of the crater. A huge, 1,000-foot-wide crater, and they couldn’t tell they were practically right on top of it. Why?
It should have been easy for them, right? These guys were trained as Navy test pilots; landing jets on aircraft carriers requires some expertise in distance judgment. They also had detailed plans and maps for their mission and had the support of an entire team of engineers on Earth. But their expertise was actually part of the core problem. The data their minds were trying to process was too good. All of the “noise” essential to creating the patterns their minds needed to process the data accurately was missing. And patterns are the key to human perception, especially for experts.
Consider everything that was missing up there. First, there’s no air on the Moon, so there’s no atmospheric haze, either. Eyes that grew up on Earth expect more distant objects to appear lighter in color and have softer edges than closer things. Yet everything on the Moon looks tack-sharp, regardless of distance. Second, the lack of trees, telephone poles, and other familiar objects left no reference points for comparison. Third, since the Moon is much smaller than the Earth, the horizon is closer, thus ruining another reliable benchmark. Finally, the odd combination of harsh, brilliant sunshine with a pitch-black sky created cognitive dissonance, causing the brain to doubt the validity of everything it saw.
Ironically, that kind of truthful, distortion-free data is usually what experience designers want to have as input for their decision-making, no matter what they’re trying to do. We tend to believe that complex systems are the tidy, linear sum of the individual variables that create them. But despite the pristine environment of the Moon, the Apollo astronauts were repeatedly baffled when it came to simple distance and size perceptions, even after each team came back from the Moon and told the next team to be aware of it.
Meanwhile, the toddlers I mentioned earlier provide a corresponding example of the power of patterns in perception. When my first child was about 4, we came across a wonderful series of picture books called Look-Alikes, created by the late Joan Steiner. Each book has a collection of staged photographs of miniature everyday scenes like railway stations, city skylines, and amusement parks created entirely from common, found objects (see some examples here). Without any special adornment, a drink thermos masquerades as a locomotive, scissors become a ferris wheel, and even a hand grenade makes for a very convincing pot-belly stove. The entire game is to un-see the familiarity of the scene, and identify all the common objects ludicrously pretending to be something other than what they are. There’s no trick photography involved, but you can look at each picture for hours and not “see” everything that’s right there in front of you. You know it’s a trick, but you keep falling for it over and over.
The really amazing part is that the toddler, a true novice with only a few years’ experience in seeing, completely understands the scenes she’s looking at, even though every individual piece of “data” she’s looking at is a deliberate lie. Yet the pattern of data that creates the scene is “perfect.” We already know what those scenes are supposed to look like before we even see the book’s version of them, so we unconsciously project that pattern onto what we’re looking at, even to the point of constantly rejecting the contrary data our eyes are showing us. There is in fact no amusement park in the photograph I called an amusement park. But I see it anyway.
In data-processing parlance, the signal-to-noise ratio of the moonscape was perfect (actually, infinitely high), and zero for Look-Alikes pages (the whole joke is that there really was no signal there in the first place). Yet a toddler can read the noisy scene perfectly, and the seasoned test pilots were baffled by the noiseless scene. How can this be?
The lesson is that patterns drive perception more so than the integrity of the data that create the patterns. We perceive our way through life; we don’t think our way through it. Thinking is what we do after we realize that our perception has failed us somehow. But because pattern recognition is so powerfully efficient, it’s our default state. The thinking part? Not so much.
This just might be why online grocery shopping has yet to really take off. The average large U.S. supermarket offers about 50,000 SKUs, yet a weekly grocery shopper can easily get a complete trip done in about 30 minutes. We certainly don’t feel like we’re making 50,000 yes/no decisions to make that trip, but in effect we actually do. Put that same huge selection online, and all of those decisions are indeed conscious. Even though grocery shopping is a repetitive, list-based task, the in-store noise of all those products that aren’t on your list give you essential cues to finding the ones that are, and in reminding you of those that were not on your list but you still need. That’s even before you get to the detail level, where all the other sensory cues tell you which bunch of bananas is just right for you. So despite all the extra effort and hassle involved in going to the store in person, it still works better because of, not in spite of, the patterns of extraneous noise you have to process to get the job done.
To account for the role of noise within the essential skill of pattern recognition, we need to remind ourselves how complex seemingly simple tasks really are. Visually reading a scene, whether it’s a moonscape, a children’s book illustration, a grocery store, or a redesigned website, is an inherently complex task. Whenever people are faced with complexity (i.e., all day, every day), they use pattern recognition to identify, decipher, and understand what’s going on instantly, instead of examining each component individually. The catch is that all of the valuable consumer thought processes we want to address–understanding, passion, persuasion, the decision to act–are complex.
However, the research we use to help us design for these situations usually tries to dismantle this complexity. It also assumes a user who is actually paying attention, undistracted, in a clean and quiet environment (such as a market research facility), and cares deeply about the topic. Then we “clean” the data we collect, in an attempt to remove the noise. And getting rid of noise destroys the patterns that enable people to navigate those complex functions. So we wind up relying on an approach that does a poor job of modeling the system we’re trying to influence.
The challenge is to overcome the seemingly paradoxical notion that paying attention to factors completely outside our topic of interest actually improves our understanding of that topic. Doing so requires acknowledging that our target audience may not care as much about something as we do, even if that topic represents our entire livelihood. It requires a broader definition of the boundaries of what that topic is, and including the often chaotic context that surrounds it in the real world. It also requires a more than casual comfort level with ambiguity: Truly understanding complex systems involves recognizing how unpredictable, and often counterintuitive, they really are.
This is why ethnographic research is so popular with all kinds of designers. The rich context ethnographies offer is full of useful noise; the improvising people do to actually use a product, the ancillary details that surround it, and the unexpected motivations a consumer might bring to its use. These are all easier to access via a qualitative, on-location approach than they are via a set of quantitative crosstabs or sitting behind a mirror watching a focus group. It’s also a powerful human-to-human interface, in which the designer uses his innate pattern-recognition capability to analyze patterns in user behavior.
What often gets overlooked is the role noise can and should play in quantitative research. Most designers’ avoid quantitative research because of the clinically dry nature of the charts it produces, and the often false sense of authority that statistically projectable data can wield. However, only quantitative research can reveal the kind of perceptual patterns that are invisible to qualitative methods, and the results needn’t be dry at all. The solution is to appropriately introduce the right kind of noise to quantitative research, to deliberately drop in the necessary telephone poles, trees, and haze that allows those higher-level perceptual patterns to be seen and interpreted.
How audio dithering works.
Fortunately, there’s already a model for this. When analog music is digitally recorded, some of the higher highs and lower lows are lost in the conversion. Through a process called dithering, audio engineers can add randomized audio noise to the digital signal. Strangely enough, even though the added noise has nothing to do with the original music, adding it actually improves the perceived quality of the digital audio file. The noise fills in the gaps left by the analog-to-digital conversion, essentially tricking your ear into hearing a more natural-sounding sound. The dithered audio really isn’t more accurate, it just sounds better, which is more important than accuracy. Returning to our opening examples, the moonscape was in dire need of dithering, while the Look-Alikes scenes were already heavily dithered. And the real world in general is heavily dithered.
So, for quantitative research aimed at guiding the design process, the trick is to value meaning above accuracy. Meaning can be gleaned via the noise you can add to the quantitative research process by including metrics outside the direct realm of your topic area. It means considering what else is adjacent to that topic area, acknowledging the importance of respondent indifference as well as their preferences, and recognizing what kind of potentially irrational motivations are behind the respondents’ approach to the topic, or the research itself.
At Method, we’ve developed a technique for observing these perceptual patterns in quantitative data by using perceptions of brands far afield of the category we’re designing for. Essentially, it’s a dithering technique for brand perceptions. This technique often displays an uncanny knack for generating those hiding-in-plain-sight aha moments that drive really useful insights. There are doubtless many other approaches you can employ once you make the leap that acknowledges the usefulness of noise in your analysis.
But no matter what format of research you use in your design development process (including no formal research at all), there are some guidelines you can follow to allow the right amount of useful noise to seep into your field of view, so that your final product does not wind up being missed on the moonscape of the marketplace:
• A LITTLE HUMILITY WORKS WONDERS.
Recognizing that you’re not the center of your target audience’s universe allows you to understand how you fit in. Be sure to take honest stock of just where your target audience places your topic area on their list of priorities.
• STEP BACK FAR ENOUGH TO ALLOW PATTERNS TO EMERGE.
No matter what metrics you’re using, consider looking several levels above them–or next to them–to identify patterns that are impossible to see when you’re too close to the subject.
• GAUGE THE LEVEL OF EXPERTISE OF YOUR TARGET AUDIENCE.
How familiar is your target audience with your subject? Are they experts or novices, and how are you defining that? Generally, the higher the level of expertise, the higher the dependence on pattern recognition. Novices carefully and slowly compare details; experts read patterns quickly and act decisively.
• CHECK THE DATA DUMPSTER BEFORE EMPTYING.
No matter where your data comes from, think about what has been omitted. Was that distracting noise that was tossed, or crucial context?
By taking a look at the entire picture–instead of isolating a single data point–you open up opportunities for understanding the motivations, reasons, and outlying factors that impact data. Contrary to popular practice of stripping out noise, noise is in fact critical to the generation of deep insights that allow us to design better and more effective brands, products, and services.
The burgeoning Latin American digital media market represents an amazing opportunity for content creators. Representing more than 7% of global Internet users, Latin America is home to emerging markets, Brazil and Argentina, where 79% and 28% of the population consumes content on the Web, respectively — a combined population of more than 100 million. If you add Mexico to the list, where 30% of the country’s 112 million people use the Internet, the list grows to 130 million Internet users.
In Latin America, Facebook accounted for 25% of all time spent online and social networking in general accounted for nearly 30% of online minutes at the end of the year, an increase of 9.5% over the past year. In addition to social media usage, online video consumption increased more than 10% across Brazil, Mexico, Argentina and Chile, and online retail visits increased 30%. The number of searches in 2011 increased 38% to more than 21 billion and, with an average of 173 searches per searcher, Latin America leads the globe in search frequency.
The U.S. Hispanic market represents an equally important demographic. More than 33 million Hispanics were online in September of last year, representing 15% of the U.S. online market, a demographic that is growing three times faster than the general market online. Eighty percent of online Hispanics use a search engine each month and 80% of online Hispanics visit Facebook each month.
Content creators must focus on the Latin American and U.S. Hispanic markets in order to maximize overall content viewership and engagement. Reaching English-speaking content consumers in the U.S. and south of the border has never been more important and will only become more important in the coming years. Moreover, creating and distributing Spanish-language content in the U.S. and Latin America is an equally important objective.
Understanding and working within these communities will enable brands and publishers to attract a portion of the world that will dominate digital content consumption in the coming years. The creation of relevant content and finding partners to help distribute that content must be among your top priorities.
With all of this in mind, Outbrain is honored to have been named the Top Digital Media Innovator in the Latin World at the 2012 Latin American Advertising and Media Awards at the Portada Hispanic Media Conference. The award honors companies in Latin America, the United States Hispanic market and Spain for excellence in media and digital advertising. We are particularly humbled to have been nominated alongside the following innovators:
Hunt Mobile Ads
Jumba Mobile Network
Premier Retail Networks México
Terra Live Music
“So much of the Portada Conference focused on the power of storytelling and producing great content,” said Erik Cima, VP of Hispanic Markets at Outbrain. “Winning this award is satisfying because we’re playing a part in helping the Hispanic and Latin American markets surface and distribute that great content.”
Book review: “Thinking, fast and slow” by Daniel Kahneman
Thinking, Fast and Slow
By Daniel Kahneman
Farrar, Straus and Giroux (October 25, 2011)
I am always on the lookout for ways to improve my scientific thinking. That’s why I have an interest in the areas of sociology concerned with decision making in groups and how the individual is influenced by this. And this is also why I have an interest in cognitive biases – intuitive judgments that we make without even noticing; judgments which are just fine most of the time but can be scientifically fallacious. Daniel Kahneman’s book “Thinking, fast and slow” is an excellent introduction to the topic.
Kahneman, winner of the Nobel Price for Economics in 2002, focuses mostly on his own work, but that covers a lot of ground. He starts with distinguishing between two different modes in which we make decisions, a fast and intuitive one, and a slow, more deliberate one. Then he explains how fast intuitions lead us astray in certain circumstances.
The human brain does not make very accurate statistical computations without deliberate effort. But often we don’t make such an effort. Instead, we use shortcuts. We substitute questions, extrapolate from available memories, and try to construct plausible and coherent stories. We tend to underestimate uncertainty, are influenced by the way questions are framed, and our intuition is skewed by irrelevant details.
Kahneman quotes and summarizes a large amount of studies that have been performed, in most cases with sample questions. He offers explanations for the results when available, and also points out where the limits of present understanding are. In the later parts of the book he elaborates on the relevance of these findings about the way humans make decision for economics. While I had previously come across a big part of the studies that he summarizes in the early chapters, the relation to economics had not been very clear to me, and I found this part enlightening. I now understand my problems trying to tell economists that humans do have inconsistent preferences.
The book introduces a lot of terminology, and at the end of each chapter the reader finds a few examples for how to use them in everyday situations. “He likes the project, so he thinks its costs are low and its benefits are high. Nice example of the affect heuristic.” “We are making an additional investment because we not want to admit failure. This is an instance of the sunk-cost fallacy.” Initially, I found these examples somewhat awkward. But awkward or not, they serve very well for the purpose of putting the terminology in context.
The book is well written, reads smoothly, is well organized, and thoroughly referenced. As a bonus, the appendix contains reprints of Kahneman’s two most influential papers that contain somewhat more details than the summary in the text. He narrates along the story of his own research projects and how they came into being which I found a little tiresome after he elaborated on the third dramatic insight that he had about his own cognitive bias. Or maybe I’m just jealous because a Nobel Prize winning insight in theoretical physics isn’t going to come by that way.
I have found this book very useful in my effort to understand myself and the world around me. I have only two complaints. One is that despite all the talk about the relevance of proper statistics, Kahneman does not mention the statistical significance of any of the results that he talks about. Now, this is all research which started two or three decades ago, so I have little doubt that the effects he talks about are indeed meanwhile well established, and, hey, he got a Nobel Prize after all. Yet, if it wasn’t for that I’d have to consider the possibility that some of these effects will vanish as statistical artifacts. Second, he does not at any time actually explain to the reader the basics of probability theory and Bayesian inference, though he uses it repeatedly. This, unfortunately, limits the usefulness of the book dramatically if you don’t already know how to compute probabilities. It is particularly bad when he gives a terribly vague explanation of correlation. Really, the book would have been so much better if it had at least an appendix with some of the relevant definitions and equations.
That having been said, if you know a little about statistics you will probably find, like I did, that you’ve learned to avoid at least some of the cognitive biases that deal with explicit ratios and percentages, and different ways to frame these questions. I’ve also found that when it comes to risks and losses my tolerance apparently does not agree with that of the majority of participants in the studies he quotes. Not sure why that is. Either way, whether or not you are subject to any specific bias that Kahneman writes about, the frequency by which they appear make them relevant to understand the way human society works, and they also offer a way to improve our decision making.
In summary, it’s a well-written and thoroughly useful book that is interesting for everybody with an interest in human decision-making and its shortcomings. I’d give this book four out of five stars.
Below are some passages that I marked that gave me something to think. This will give you a flavor what the book is about.
“A reliable way of making people believe in falsehoods is frequent repetition because familiarity is not easily distinguished from truth.”
“[T]he confidence that people experience is determined by the coherence of the story they manage to construct from available information. It is the consistency of the information that matters for a good story, not its completeness.”
“The world in our heads is not a precise replica of reality; our expectations about the frequency of events are distorted by the prevalence and emotional intensity of the messages to which we are exposed.”
“It is useful to remember […] that neglecting valid stereotypes inevitably results in suboptimal judgments. Resistance to stereotyping is a laudable moral position, but the simplistic idea that the resistance is cost-less is wrong.”
“A general limitation of the human mind is its imperfect ability to reconstruct past states of knowledge, or beliefs that have changed. Once you adopt a new view of the world (or any part of it), you immediately lose much of your ability to recall what you used to believe before your mind changed.”
“I have always believed that scientific research is another domain where a form of optimism is essential to success: I have yet to meet a successful scientist who lacks the ability to exaggerate the importance of what he or she is doing, and I believe that someone who lacks a delusional sense of significance will wilt in the fact of repeated experiences of multiple small failures and rare successes, the fate of most researchers.”
“The brains s of humans and other animals contain a mechanism that is designed to give priority to bad news.”
“Loss aversion is a powerful conservative force that favors minimal changes from the status quo in the lives of both institutions and individuals.”
“When it comes to rare probabilities, our mind is not designed to get things quite right. For the residents of a planet that maybe exposed to events no one has yet experienced, this is not good news.”
“We tend to make decisions as problems arise, even when we are specifically instructed to consider them jointly. We have neither the inclination not the mental resources to enforce consistency on our preferences, and our preferences are not magically set to be coherent, as they are in the rational-agent model.”
“The sunk-cost fallacy keeps people for too long in poor jobs, unhappy marriages, und unpromising research projects. I have often observed young scientists struggling to salvage a doomed project when they would be better advised to drop it and start a new one.”
“Although Humans are not irrational, they often need help to make more accurate judgments and better decisions, and in some cases policies and institutions can provide that help.”
En nuestro entorno y quehacer como empresarios hay una constante que aparece una y otra vez, esta constante es como debe ser la propuesta. Nos referimos a la propuesta de servicio o a la propuesta de producto.
Muchos de nosotros como empresarios definimos un producto o servicio y creemos que lo que sigue es comercializarlo para lo cual están las áreas de mercadotecnia y ventas.
La verdad es que todos comenzamos haciendo una propuesta con lo que tenemos o lo que creemos que debe de ser, esto no es un mal inicio. Es más, es el mejor inicio que hay, solo que este debe estar enriquecido por un halo de duda. A lo que me refiero es, lo que hemos mandado al mercado es una propuesta y como tal puede ser bien solamente recibida, bien recibida o incluso puede ser rechazada. Si concebimos que lo que hicimos fue una propuesta y que estamos reconociendo lo que la gente o el mercado quiere, entonces podremos mejorar o cambiar nuestra propuesta. Y es justo ahí donde muchos nos atoramos. Creemos que lo que proponemos es lo adecuado y que solo debe ser mercadeado o vendido adecuadamente, pero eso no es del todo cierto.
Efectivamente, mercadotecnia nos ayudará muchísimo. Sus técnicas y procesos facilitarán la manera en que nos comunicamos con la gente pero siempre necesitará contar con la clara identidad de la empresa. Si esta identidad tiene oportunidades no atendidas, mercadotecnia y ventas se verán limitadas en sus capacidades para entregar un mensaje claro, contundente y con la fuerza necesaria no solo para entregar, sino para que la gente lo pida.
Les comparto, hacer una propuesta necesita incluir una palabra: “Valor”. Necesitamos hacer una propuesta de valor. En la cual está implícito un beneficio para la persona o entidad que va a usar o consumir el producto o servicio. Así es, nuestra propuesta debe beneficiar a alguien y por supuesto a nosotros también.
En este diálogo que existe entre lo que ofrecemos y entregamos, con quien recibe y usa, es donde muchos perdemos camino o dejamos de ver con claridad hacia dónde vamos. Creemos que si cambiamos nuestra propuesta, dejaremos de beneficiarnos, dejaremos de ser quiénes somos, perderemos nuestra identidad, la razón de ser. Yo les comparto que esto no es así.
La razón es que antes que nada, nuestras empresas y nosotros somos entes sociales y funcionamos en sistemas de convivencia. Nuestro intercambio es eso, un sistema en el que participan diferentes actores o elementos y todos construyen una experiencia que sucede.
Todos vivimos la empresa y sus productos. Al manejar un carro, no solo consideramos la marca, sentimos los asientos, olemos el interior del carro, escuchamos el motor, vemos los accesorios y tocamos las vestiduras, los asientos y el volante; al manejar, escuchamos el sonido de todo el carro en tránsito. En fin, es un sistema que vivimos con la marca y el modelo, sabemos que la identidad y su propuesta es la que nos gusta.
Es por está razón que nuestra propuesta y nuestra identidad están estrechamente relacionadas, necesitan reconocerse en un sistema en el que ante todo hay intercambios. Intercambios de productos y servicios por dinero, pero también hay emociones, relaciones, vivencias, espacios… Es un conjunto de elementos que debe tomarse en cuenta para reconocer con mayor claridad: quiénes somos, cómo participamos, cómo somos percibidos y lo mejor, cómo nos concebimos.
Es un sistema que está vivo y que puede moldearse o cambiarse en el momento que sea necesario.
Esta dinámica de vivencias le sucede tanto a la gran empresa como al micro empresario. Todos participamos y contribuimos en estos sistemas. Todos podemos cambiar y transformarnos para tener una mejor relación con nuestro entorno, para ser más competentes, si así lo queremos ver.
Podemos ser y tener la identidad que decidamos, para hacer la mejor propuesta al mercado. Una propuesta de valor que nos beneficia a todos.
Si reflexionamos sobre nuestra identidad como empresa y recordamos que la identidad se vive y sucede, entonces podemos relacionarla con el cómo queremos que esto suceda. Yo tomo como principio las características que definen ser competente y éstas son:
“Parecer ser, ser y actitud”
Todos conocemos empresas que podríamos colocar en esta definición. Es más, por ella tomamos muchas decisiones para relacionarnos con ella. Nuestras decisiones van desde el coche que usamos, el lugar en el que vivimos, el grupo con el que convivimos, etc. Como personas nos sucede exactamente igual. Convivimos en el sistema y llegamos a acuerdos o principios que nos guían para actuar.
La identidad de una empresa está estrechamente relacionada con su propuesta y es por ésta que podemos ver con claridad si nos propone un beneficio.
A todos nos ha pasado que hemos sentido desconfianza sobre un artículo, un servicio o una persona. Hay algo que no nos gusta. La respuesta está en cómo nos sucede ese contacto, cómo identificamos si nos conviene o no. La razón atrás es que el sistema está actuando y el conjunto de elementos que están participando no entregan un mensaje coherente y congruente. Sencillamente hay algo fuera de lugar. Y no digo que algo esté mal, digo que hay algo fuera de lugar, algo que desentona y que muy posiblemente necesite ajustarse.
Parecer ser, ser y actitud no son características que se dan por creación espontánea, son expresiones de la empresa. La empresa, sus empresarios y colaboradores construyen de manera cotidiana esta identidad.
La identidad por eso no se puede inventar o colocarse, la identidad es una expresión única de cada empresa.
Como dice el dicho: “La mona aunque se vista de seda, mona se queda”, y la empresa no es ajena a este dicho.
Un buen ejemplo del manejo común de la identidad es la de crear un logotipo. Un logotipo puede servir para identificar a la empresa, para que la ubiquen solamente. Pero no llegará a ser una identidad hasta que contenga y represente a ese sistema dinámico que es la empresa. Un logotipo se transformará en identidad hecha marca al contener esa expresión cultural de empresa.
Una identidad puede tener diferentes propuestas, entendiendo propuesta de servicio o producto durante el tiempo. Además es la manera en que interactúa con su entorno. Una identidad es un proceso que nunca termina, que trasciende en el tiempo y contribuye a la construcción de una cultura.
Una identidad implica poder ofrecer un servicio desde el interior de su razón de ser. -Por quien somos, proponemos y resolvemos para tu beneficio, para el beneficio de todos-.
Tener una identidad con una propuesta clara parece sencillo y sí lo es. Lo único que se requiere es disposición para reconocer que participamos en un sistema. En el cual tenemos características únicas por las que hacemos y ofrecemos un producto o servicio. Lo hacemos con una propuesta que corresponde a nosotros, gracias al proceso de reflexión constante, continuo y estructurado que hacemos. Tener identidad y una propuesta significa que hemos diseñado quiénes somos y cómo nos relacionamos.
El secreto está en el diseño. La palabra clave es: “Diseñamos”. Diseñar no es otra cosa que recrear un proceso de reflexión que nos permite cuestionarnos el por qué hacemos lo que hacemos, cómo lo hacemos, para quién lo hacemos, qué esperamos y qué esperan de nuestro producto o servicio. Diseñar no es embellecer, no es acomodar para que se vea bien. Diseñar implica observar, reconocer, crear ideas, hipótesis, probar y experimentar.
Diseñar nos invita a instalar un proceso continuo de reflexión, capaz de alimentar a la empresa y expresarse en todas las áreas, incluyendo la manera en que se entregan o se brindan servicios. Identidad y propuesta requieren ser definidos por diseñadores. Si eres empresario, este es el momento de comenzar a diseñar tu empresa, sus productos y servicios. Con ello podrás contar con una de los capitales más grandes que una empresa puede tener: el ser querida, deseada o admirada.
Podrás lograr con tu empresa ser la razón por la que muchas personas conducen sus vidas, ser un contribuyente de valores y riqueza en la sociedad. Con tu aportación, la sociedad entera te retribuirá con lealtad y con sentido de pertenencia. La gente adentro y afuera de la empresa se sentirá orgullosa de pertenecer a ella, a tu empresa.
Ahora sí, si en tus planes está darle identidad a tu empresa y crear una propuesta, acompáñate de los diseñadores adecuados como lo son los consultores de la comisión de Consultores de Coparmex en Querétaro. Más de uno podrá acompañarte, pero sobre todo, podrás liberarte de los mitos que te detienen.
Si decides contratar a un diseñador para crear una imagen que te identifique, cuida que no sea solo un embellecedor o creador de disfraces. Con él o sin él, saldrá a relucir la verdadera identidad de quién eres y cómo es tu empresa.
D.G. Federico Hernández RuizSocio fundador y Consultor en Identidad estratégica en asimetagraf y representante para la CGTFL en México de Duraznos, Nectarinas y Ciruelas California
Como consultor se destaca en la creación de sistemas de identidad especializado en productos de consumos. Su trayectoria cuenta con más de 20 años de experiencia y ha colabora desde grandes transnacionales hasta pequeñas y micro empresas. Algunas de éstas son: Kellogg’s, Heinz, La Perla, Grupo Pando, entre otros.
Actualmente representa a la California Grape and Tree Fruit League “CGTFL” para la promoción de duraznos, nectarinas y ciruelas California en México. https://www.facebook.com/CaliforniaDNC
1. BITE THE BULLET: LEARN HOW CODING AND WEB ANALYTICS WORK.
“Learn how to code a web application, learn how to print a design you’re designing for print, and not be limited to renderings and mock-ups. By learning ‘how to build’ a few things happen: You learn what it takes to build things, and can therefore better empathize with and appreciate those who are expert builders. You extend the potential influence of design. You can kick-start a building process, learn about the challenges your design decisions impose on the building process, and otherwise iterate on design throughout the building process.”
–Randy J. Hunt, Creative Director at Etsy
“The day that I started sitting in on meetings with the CEO and talked about things such as conversion metrics and the lifetime of a customer as it relates to our product, it definitely changed the way I think about what I was working on and how I solve certain problems.”
–Josh Brewer, designer at Twitter
2. NEVER UNDERESTIMATE HOW IMPORTANT DESIGNERS ARE TO BUSINESSES…
“We’ve definitely crossed over a threshold in the startup world, where it’s an assumption that it’s a good idea to pay attention to design from the very beginning. But there’s still a big gap in understanding what that means and how to find designers who can contribute in a meaningful way to the early stage of product design. We have a responsibility as designers to step up to the plate here. We’re invited to the table now–we need to bring something to it.”
–Wilson Miner, designer at Facebook
3. …BUT DON’T ALLOW THAT TO DAMAGE YOUR FOCUS.
“If you want to be the best UX designer in the world, then concentrate on that. Don’t let your ego and your thirst for experience distract you into thinking your opinion needs to be heard at the same level as your cofounder’s on all topic, such as hiring, copywriting, product scheduling, business relationships, etc. Steve Jobs and Mark Zuckerberg are a poison in this regard.”
–Ben Pieratt, cofounder of Svpply
4. KEEP A SIDE PROJECT–THEY CLEAR THE COBWEBS OUT.
“I worked as an art director at The New York Times, but I always worked on side projects to maintain my sanity. Something I try to instill in the students and young designers whom I meet is this idea of doing a side project. No matter how small, it is always important. I think when you go to the corporation, and when you’re entry level and just starting out, a lot is asked of you, and you can lose yourself and get washed up in it.”
–Peter Buchanan-Smith, founder of Best Made
5. READ EVERYTHING. A DIVERSE MEDIA DIET WILL LEAD TO RANDOM SPARKS OF INSPIRATION.
“Droog is invariably witty and socially on point. Fine artists would probably be the other inspiration category. I also really appreciate reading about the experiences and approaches of other businesspeople. One column I love is the Corner Office series in The New York Times. There’s also a collected book—The Corner Office: Indispensable and Unexpected Lessons from CEOs on How to Lead and Succeed. Reality TV is my friend. I mean, where else would you hear a Real Housewife of Atlanta say, ‘Irony is so ironic?’ ”
–Jen Bilik, founder of Knock Knock
6. A PROTOTYPE IS WORTH A THOUSAND WORDS.
“No matter how well you visualize, until you see that first hyper-real rendering of the product or the prototype, it’s just an idea—it sits around, and it gestates in your head, but it doesn’t become tangible until you make it real…IDEO’s Tom Hulme said, ‘Talk – Action = Shit.’ I don’t know how many times I’ve sat in meetings where people just talk, talk, talk and show renderings that just don’t sell the idea until they put this physical thing on the table.”
–Scott Wilson, founder of MINIMAL
7. MOST IMPORTANTLY, CONTINUE TO THINK WITH THE UNFETTERED IMAGINATION OF A STUDENT. THE ROLE OF A DESIGNER IS TO RETHINK HOW THE WORLD WORKS.
“We’re offering a $95 product for something that is typically sold at $500, and that question automatically is well, ‘Why?’ And ‘How?’ The why is because we personally experienced the effects of overpriced glasses, and we want to change the world. We want to transfer billions of dollars from these big multinational corporations to normal people. The how is that we’re able to design the frames ourselves and produce them under our own brand. We’ve made relationships with the suppliers that make the hinges and the screws, and then custom-acetate and assemble the frames, and cut and etch the lenses so we’re able to bypass the middleman by having those direct-to-supplier relationships, and by filling orders online, we have direct-to-consumer relationships.”
–Neil Blumenthal, cofounder of Warby Parker
“The Internet startup world’s convention of thinking is that you need to solve problems in a scalable way. You need to solve problems with lines of code, and the Internet allows you to do that. The same line of code can touch one user or 10,000 users. But, as soon as we started to do things that didn’t scale, everything started to click…We traveled to New York City; we talked to hosts; we did unofficial ethnographic research. We observed people using Airbnb. We experienced all of the pain points firsthand it for ourselves…We came back to our roots and applied the industrial design process to the Internet—merging customer feedback with our obsession for good design. Once we did that, everything clicked, and we began making money rapidly.”
–Joe Gebbia, cofounder of Airbnb
Buy Kern and Burn: Conversations with Designer Entrepreneurs for $30here.
[Illustration: Joe Gebbia and Warby Parker, Kelly Rakowski/Co.Design]
Original article: http://www.fastcodesign.com/1673079/from-facebook-to-warby-parker-7-tips-from-leading-design-entrepreneurs?partner=newsletter