"the death of average"

Sabem o que escrevemos, o que prevemos aqui há muitos anos?
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O advento de Mongo, o advento do Estranhistão, o horror cada vez maior que os clientes têm em serem tratados como plankton, como mais um no meio da massa, da mole.
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Lembram-se do que escrevo aqui há muitos anos sobre a miudagem e os fantasmas estatísticos?
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Lembram-se que acredito que as PME podem ter alguma vantagem vantagem face aos Golias que apenas confiam no Big Data e não pensam em cada cliente como um ser único?
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Este vídeo tem alguns segmentos cheios de sumo:

Por exemplo:

"This idea of how you will deliver [Moi ici: Não quero mas vou passar por picuinhas, não é "deliver" é "co-create"] value will be different. And value will be for individuals not for segments.
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The best is the micro-segment.
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You will see the death of average ... and instead you will see an era of YOU"

Só me faz espécie é isto ser preferido pela CEO da IBM uma empresa que tem feito tantas asneiras nos últimos, uma empresa que não encontra nada melhor para o seu dinheiro do que comprar as suas próprias acções.

Cuidado com a média

Há muitos anos que escrevo no blogue e falo nas empresas sobre a miudagem e os fantasmas estatísticos:

"At some point in your company’s growth, someone will utter the most pernicious phrase in business: “The average customer.”
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There is no such thing.
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Not only do average customers not exist, they also don’t matter. It is more valuable to identify the best customers (the ones who spend more and promote your business to other people) and the worst customers (so that you can convert them to promoters or fire them).
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How do you avoid the average trap?
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By continuing to have one-on-one conversations with your customers, even as their numbers grow. Keeping the voice of real customers alive in the business means keeping it in front of managers and executives just as much as front-line employees.
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Aggregated data distilled into averages won’t cut it. [Moi ici: Cuidado com o Big Data] Everyone in the company needs regular, recent customer feedback that includes verbatim comments about individual transactions. And when customers offer their precious time to provide those comments, managers and executives should call them back and close the loop."

Trechos retirados de "Why There Is No Such Thing as an ‘Average Customer’"

Big data, mais um aviso

Mais uma chamada de atenção para o lado negro do Big Data, "Don’t Let Big Data Bury Your Brand".

"Marketers have always had to strike a careful balance between brand building and short-term sales promotion.
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Today that balance is harder to strike than ever because of big data and analytics and the highly targeted promotions they enable. The temptation to neglect brand investments in the pursuit of sure sales is nearly irresistible.
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To protect your brand, make every message do double duty. Use insights from data to make the long-term case for brand investments. Don’t pursue sales offers you can’t defend in brand terms."

"Get out of the building"

"“Big Data” is the phrase du jour — it’s no secret that data can serve as a powerful and practical resource for understanding consumer behavior. But it must be used in the proper context, or else it can distance companies from those they wish to understand.
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A common problem arises when corporate innovation teams over-rely on data to uncover new insights about customers, or understand user behavior on a deeper level. They become seduced by numbers, convinced that statistics reveal indisputable truths about target-market behavior.
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Think of your customers as individuals, not data sets.
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In the early days of developing a new product or service, seek depth over breadth. Move beyond large surveys and customer data sets, and have long, open-ended conversations with 10 current or potential customers about their experiences with your product and competitors’ products.
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Put on your anthropologist hat.
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Here is a human truth: People say one thing, but do another. Because of this, it’s imperative that you observe your customer in the wild, exploring their behavior in the context of their everyday lives.
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Don’t get us wrong — it’s terrific to have big data. It points you in the right direction and helps you hone in on a problem to solve. But to get the texture and nuance that leads to innovation, you need to have direct experiences with the individuals whose problems you’re solving."

Em linha com o que ao longo do tempo aqui tenho escrito sobre os perigos do Big Data:

• Curiosidade do dia (Maio de 2013)
• Big Data (Junho de 2013)
• Big Data, pois (Outubro de 2013)
• Big data e PMEs (Dezembro de 2013)
• Cuidado com o Big Data (Abril de 2014)

Trecho retirado de "Your Customers Aren't Data -- They're People"

Quem vai relacionar-se com as tribos de Mongo?

Uma grande verdade:

"Organizations want customers to have relationships with their brands without the expense of the brands having actual relationships with customers.
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Loyalty for most organizations is a one-way street. The customer is expected to be loyal to the brand. The idea of loyalty to the customer is not even considered.
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Real human relationships take time and effort. To become a good and loyal friend does not happen quickly. But loyalty and caring are powerful human emotions and brands seem to want to have these emotions on the cheap.
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Technology has been used to replace expensive human-to-human, face-to-face relationships, because these relationships are the most expensive of all."

No Estranhistão, planeta cheio de tribos, quem as vai servir?
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As empresas grandes ou as pequenas?
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Qual delas aposta mais na relação?


Trechos retirados de "Relationships are expensive"

O truque é a interacção, a co-criação. Os robots não têm hipótese!

Ontem de manhã, fui agradavelmente surpreendido por um tweet que me mereceu logo uma resposta:

Interessante como a frase vai ao encontro do tema da escola do futuro:

"Information creates more value than inventory and interaction creates more value than information!" (fonte)

Algures li uma afirmação de Kasparov que dizia que um grande mestre perdia sempre contra um supercomputador, mas que um jogador mediano com um computador mediano, juntos batiam sempre o supercomputador.
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Em "The Machines Are Coming" leio:

"Most of what we think of as expertise, knowledge and intuition is being deconstructed and recreated as an algorithmic competency, fueled by big data.
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Machines aren’t used because they perform some tasks that much better than humans, but because, in many cases, they do a “good enough” job while also being cheaper, more predictable and easier to control than quirky, pesky humans. Technology in the workplace is as much about power and control as it is about productivity and efficiency.
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the way technology is being used in many workplaces: to reduce the power of humans, and employers’ dependency on them, whether by replacing, displacing or surveilling them.
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It’s easy to imagine an alternate future where advanced machine capabilities are used to empower more of us, rather than control most of us. There will potentially be more time, resources and freedom to share, but only if we change how we do things. We don’t need to reject or blame technology. This problem is not us versus the machines, but between us, as humans, and how we value one another."

Nós humanos não somos explicáveis por leis newtonianas. Sim, o retalho levava a deles avante ao principio, com os saldos. Agora, nós humanos, torpedeamos o seu sistema, porque aprendemos a dar a volta. Vai ser bonito ver os humanos a aprender e a tomar partido de formas de enganar as máquinas.
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Gente sem paciência estratégica acha que é tudo uma questão de eficiência e poupança. Gente mais inteligente percebe que o truque é a interacção, a co-criação.
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Em "Is Your Job ‘Routine’? If So, It’s Probably Disappearing" leio:

"In the most recent recession, routine jobs collapsed and simply have not recovered, with employment in both cognitive and manual jobs down by more than 5% if the tasks are mostly routine.
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In recessions of the 1960s and 1970s, routine jobs would fall during the recession but quickly snap back. But after the recession in 1990, something changed. Routine jobs fell and, as a share of the population, never recovered. In the recessions in 2001 and in 2007-09 they fell even further. The snapback never occurred, suggesting that many firms began coping with recessions by scrapping tasks that could be automated or more easily outsourced.
For his part, Mr. Siu thinks jobs have been taken away by automation, more than by outsourcing.
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“Many of the routine occupations that were once commonplace have begun to disappear, while others have become obsolete,” they write. “This is because the tasks involved in these occupations, by their nature, are prime candidates to be performed by new technologies.”

Li também "Cheaper Robots, Fewer Workers".

Recordar o destino dos robots da Toyota e das linhas de montagem da Canon na produção, quanto mais na gestão "Why Your Best Managers Soon May Not Be Humans".
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MacGyver ganha sempre ao Sandy!

Para reflexão profunda

Em "Your Digital Strategy Shouldn’t Be About Attention" encontrei boas propostas de reflexão, sobretudo conjugadas com o que aqui temos escrito sobre o Big Data:

"attention without relation is like revenue without profit: malinvestment.
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The real question — the one that counts for leaders and institutions today — isn’t “How loyal can we compel, seduce, or trick our customers into being?” It’s: “How loyal are we to our customers? Do we truly care about them?” Not just as targets consumers, or fans. But as people. Human beings. What every institution needs — and what every leader needs to develop — before a “digital strategy” is a human strategy. If you want to matter to people, you must do more than merely win their fickle, fleeting, frenzied attention. You must help them develop into the people they were meant to be. When you do, maybe, just maybe, they’ll reward you. With something greater than their grudging, wearied attention. Their lasting respect, enduring trust, and undying gratitude."

Parar! Reler e, pensar sobre a capacidade das empresas grandes dialogarem, conhecerem e estabelecerem relações com os seus clientes... e as PME?

"What will your “digital strategy” help them become better at? Does it have a point? Skiing, dating, cooking, coding, creating, building? If the answer is no, you don’t have a strategy. You have a vaudeville show."

Depois, aquela imagem de Luke e Yoda:

 O cliente é o herói, não um zombie parvo:

"I mean that when all you do is earn people’s attention, without trying to earn their respect or trust, they can turn on you on a dime.
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Unless you happen to want to spend the rest of your life at war with the people formerly known as your customers. Creating an army of zombie customers is a terrible way to build a great brand."

Sobre a viralidade em vez da relação:

"The holy grail of the digital marketing strategy is “virality.” But the goal of a digital business strategy is connection. One is shallow and fleeting; the other is deep and enduring. Connection means more than just gawping at your “content” when it’s trending. Connection means going beyond the strictures of marketing, and literally forging living, breathing relationships. It requires that you actually empower people to act as advisers, counselors, mentors to your customers … not just plastering your logo on digital billboards, or winning two more Facestagram hearts."

Para finalizar:

"Forget about “building the brand.” Ignore the rules of communication. They were built to sell miraculously mass-made “product” to a stable, secure, sedated middle class forever ascending upwards into the plastic cornucopia of perfect prosperity. .
Instead, focus on giving people what matters most to them — but what they feel cheated of, stymied from, and suffocated by at every turn. Improve their lives. Deliver lasting gains in their quality of life. Don’t just carrot-andstick them into “loyalty.” Be loyal to them. Don’t win their attention — give them your attention. And one tiny interaction at a time, help them live lives richer with meaning, happiness, and purpose. After all, they’re the only people that can help you find something greater, truer, and better than a strategy. A point." 

Selfies, uma mina de informação

Lembram-se das "personas"? (aqui e aqui)
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Lembram-se da “Catherine, Anna, Maria, or Monica”
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Este artigo "Smile! Marketing Firms Are Mining Your Selfies", vem revelar uma realidade super-interessante. As selfies que inundam a internet e as redes sociais são uma mina para a recolha de informação que contextualiza o uso de produtos, por pessoas, em certos locais.

"a new crop of digital marketing companies are searching, scanning, storing and repurposing these images to draw insights for big-brand advertisers.
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Some companies, such as Ditto Labs Inc., use software to scan photos—the image of someone holding a Coca-Cola can, for example—to identify logos, whether the person in the image is smiling, and the scene’s context. The data allow marketers to send targeted ads or conduct market research."

Para os fãs do Big Data

"There is no higher praise these days than being data-driven. A person who is data-driven is free of bias, and cuts through arguments with a sword of truth. No longer do we need to fumble through life. The answers will come. We will know how to respond, just what to do. We will let the data tell us!
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as we enter the Age of Big Data, the Age of the Internet, and the like, is that we are also entering an Age of the Axiomatic.
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To be axiomatic, at its best, is to be deductive, but at its worst, it is to assume that a system is consistent and complete.
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Axioms work well in the realm of pure numbers and physics, but they are often superficially applied to biology, and especially so when applied to the social sciences.
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Exactly the point we assume the data of a system to be both consistent and complete. This is when axiomatic logic at its most naïve and dangerous.
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This dangerous kind of axiomatic logic is pronounced when we assume that a user is a collection of “data points” with a consistent or complete identity."

E:

"“alterity,” or otherness—the possibility of being totally blindsided by new facts, to achieve an experience that was before entirely foreign." 

Trecho retirado de "Love Is Not Algorithmic"

"fantasmas estatísticos e a miudagem potenciada em grande"

Muitas empresas, em especial as PMEs, porque se consideram demasiado pequenas, o que é verdade, e porque têm poucos recursos, o que também é verdade, olham para o mercado como algo que não podem influenciar, olham para o mercado como uma realidade dada, como uma constante na equação do seu sucesso.
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Fez este mês de Agosto dez anos que, sem o saber na altura, comecei a pôr em causa esse posicionamento mental pessoal, ao desenvolver um trabalho numa PME em que nos armamos em modeladores do mercado. Se um mercado resulta da actuação de actores que trocam ou partilham serviços, relações, símbolos, normas, aspirações, ... talvez seja possível pôr o mercado, pôr a paisagem competitiva ou parte dela, a dançar a um ritmo e com um estilo que seja o mais adequado para a nossa empresa em particular.
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Ontem, no Twitter, alguém escreveu:

"O banco alimentar é provavelmente umas das formas mais ineficientes de ajudar pessoas"

Não tenho informação suficiente quer para corroborar, quer para contestar esta afirmação. Contudo, o primeiro pensamento que me veio à cabeça quando a li foi qualquer coisa como:

"Mas para aquela pessoa concreta X, fez toda a diferença do mundo" 

Fiz este desvio por causa da capacidade de modelar o mercado ao jeito da nossa PME. Quando se fala em modelar o mercado, há empresários que tomam a ideia por absurda pois pensam logo numa alteração com escala, para alterar as estatísticas gerais do sector onde actuam. Uma PME não precisa de mudar o mercado, essa entidade estatística geral, basta-lhe alterar o mercado onde actua, cliente a cliente, relação a relação, troca a troca, interacção a interacção.
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Esta cascata de pensamentos foi gerada pela leitura de "Why Small Businesses Actually Have the Big-Data Advantage". Uma leitura que me fez recordar:

• "Big data"
• "Big Data e PMEs"
• "Cuidado com o big data" 

Sim, a história dos fantasmas estatísticos e a miudagem potenciada em grande:

Acerca da criação do futuro

"Smarter machines will reduce the number of traditional management jobs in the second machine age and force a change in both the practice and philosophy of management for the millennials poised to become the next generation of managers.
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managers must become entrepreneurial again: Number-crunching computers will replace number-crunching managers.
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Perhaps the transition from owner–entrepreneurs to professional managers was inevitable in an era driven by physical labor and scale economies [Moi ici: O que ficou para trás, o modelo do século XX]. However, returning to modern times and looking ahead, a focus on “the numbers” means management will increasingly be subsumed by computers. Future managers will need to use their creativity to challenge the constraints to both commercial success and social welfare.
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Instead of simply testing hypotheses, management must create the future. The future can’t be created (or even uncovered) by simply examining the past, even with the massive computer power employed in “big data” analyses. The strategic answer can’t be found in the numbers, not even in that central tool of the MBA: the net present value calculation. At the same time, managers can’t run a company based on a set of untested hypotheses: The right business strategy requires creativity and analysis.
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“There’s nothing so practical as a good theory.” Computers can analyze massive quantities of data and discover patterns by drawing on inferential statistics. But even big data computers don’t form the hypotheses needed to develop new strategies designed to break existing constraints and create new business models. Accordingly, managers who seek to break constraints and embrace a hypothesis-driven approach will not face extinction but will instead create the future.
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The millennials have grown up in the earliest days of the second machine age. Although they are aware of the massive quantity of information now available, they understand that new business models aren’t discovered through a historical pool of big data but are instead invented through a process of management that starts with hypotheses, which are tested with data. Big data will allow them to test far more hypotheses, far more cheaply. But data—or the machines that collect it—won’t in itself create the innovative business models of the future, especially those that seek to balance commercial and social goals."

Trechos retirados de "Management in the Second Machine Age"

Cuidado com o Big Data

Como se pode ver no histórico deste blogue, desconfio muito do poder do "big data", por isso, recomendo vivamente a leitura de "Big Data: Are we making a big mistake?":

"while big data promise much to scientists, entrepreneurs and governments, they are doomed to disappoint us if we ignore some very familiar statistical lessons.
“There are a lot of small data problems that occur in big data,” says Spiegelhalter. “They don’t disappear because you’ve got lots of the stuff. They get worse.”"

"- Please! Go ahead punk, make my day"

"Here’s a simple rule for the second machine age we’re in now: as the amount of data goes up, the importance of human judgment should go down."

Apetece dizer aos grandes:

- Please! Go ahead punk, make my day.

Nunca me esqueço de MacGyver vs... Sandy. Também recordo "Passou-lhe completamente ao lado ... no fim MacGyver vence a Sandy".
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Quando os grandes derem o poder de decisão às máquinas, vão ficar ainda mais previsíveis, ainda mais obsoletos. Entretanto, os outros vão poder apostar no factor humano, no inesperado, na paixão... na insurgência.

"invest time in listening to your customers"

Nem de propósito, bem na linha da parte II do antropologista que entra num bar:

"Founders need a way to make great design become automatic, and there’s only one way I’ve found to do that reliably: invest time in listening to your customers.
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You’ve probably heard this advice a hundred times before. Whether you call it “user research” or “customer development” or just “getting out of the building”, we all know that hearing directly from customers is one of the fastest ways to learn and improve our products. But when I ask founders how long it’s been since they’ve watched a real customer (not a family member) use their product, they usually look embarrassed and admit they haven’t tested anything in months.
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It’s so much fun to make things that it’s often hard to stop and listen.
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No one expects customers to design the product for you. That’d be way too easy! But customers can absolutely tell you their goals and frustrations. Customers can show you what they like or dislike about products and you can watch when they get stuck or confused. So if customers say they want faster horses, what you should hear is that getting around is too slow. It’s the team’s job to take all that raw input and build products to delight customers."

Trecho retirado de "Braden Kowitz: Why You Should Listen to the Customer"

Um antropologista entra num bar... (parte II)

Parte I.
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Lembro-me do posicionamento que a marca Volvo tinha há uns anos no meu referencial. Imagino que a sede de crescimento a todo o custo terá sido um dos factores que os impulsionou a construírem SUVs e, assim, diluírem aquilo que a marca representava e a quem se dirigia.
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O artigo referido na parte I, "An Anthropologist Walks Into a Bar" de Christian Madsbjerg e Mikkel Rasmussen, tem um relato que me fascinou, e que mostra como é possível uma alternativa de crescimento, não alargando o âmbito da oferta, mas aprofundando a relação com os clientes e aprofundando a percepção de qual é a experiência vivida.
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O artigo descreve o percurso da Coloplast, líder no sector da colostomia. Qual era o desafio?

"Sensemaking starts with learning to think of a problem as a phenomenon—that is, to see it in terms of human experience. (Moi ici: O fundamental é a experiência) This conceptual shift requires companies to stop looking at the market, the product, and the customer from their own perspective and examine the customer’s perspective instead. (Moi ici: O fundamental é olhar para o mundo sob a perspectiva do cliente, ou dos pivôs do ecossistema da procura)
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Thus, Coloplast recast the question “How do we capture new sources of growth?” as “What is the experience of living with ostomy?” (Moi ici: Esta pergunta muda completamente o foco, a orientação da pesquisa. Em vez de apontar para o alargamento da oferta, começa pelo ponto de chegada, pela vida do cliente) Its managers knew a lot about customer metrics—who bought how much of which products when, and so forth. But they realized they knew less about their customers’ worlds. What was it like to be an ostomy patient? How did it afect your self-image? Your social life? What was a good day, or a bad day? The company’s product development and marketing strategies had been driven by two assumptions about customers and their needs: that within two years of leaving the hospital, people had their ostomy care under control and were living essentially normal lives; and that product innovation should focus largely on improving the various features of an ostomy bag, one by one."

O que fez a equipa de antropólogos ao serviço da Coloplast? Foi para o terreno observar os clientes no seu habitat natural, foi conversar com eles, foi viver com eles. Sem ideias pré-concebidas, sem hipóteses explicativas. A equipa registou um conjunto de recortes em primeira-mão da vida dos clientes : narrativas; fotos; confissões; ...

"This eye-opening feed can be tremendously inspiring for business leaders used to thinking about their customers as abstractions—as segments, need states, or consumption occasions.
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In addition, the researchers spent a day with stoma-care nurses (Moi ici: Ter em atenção o ecossistema da procura) in order to understand the way they choose products for their patients, how they prepare patients for discharge, and their concerns about patients’ ability to manage at home."

Esta metodologia foi a que seguimos, por exemplo, num projecto de 2011. Visitamos cerca de 20 equipas, falamos com mais de 70 pessoas distribuídas por várias zonas do país. Recolhemos as suas reacções, transformámos-las em pequenas frases e construímos um modelo causal:

Depois de reconhecido o fenómeno, o passo seguinte é procurar padrões para identificar causas-raiz que têm de ser eliminadas... ou percebidas, no caso da Coloplast

"The key to uncovering patterns is to find root causes—in this case, the fundamental explanations
for patients’ and nurses’ behavior. The process is like peeling an onion. The outer layer contains directly observable facts, such as how often patients change their bags and what inconveniences they experience while doing so. The next layer contains the habits and practices informing patients’ behavior and choices. And fnally there is the center—the underlying causes of those habits and practices."

E o que é mais interessante no diálogo com os actores na cadeia da procura é o conseguir perceber a ilusão que a estatística esconde:

"As it repeatedly returned to the phenomenon—what is the experience of living with a stoma?—Coloplast started to understand the efects of diferences between care in a clinical setting and care at home. (Moi ici: A importância do contexto)
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Indeed, Coloplast realized that the problem it believed it had largely solved—leakage—in fact remained a formidable, life-altering challenge.
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The pattern recognition process revealed that the complaints had dropped of not because the problem was solved but because people had radically adapted their lifestyles to avoid the risk of accidents, accepting that their new lives were, in the words of one patient, “probably as good as it gets.”"

E assim, perceber uma realidade importante que muitos gestores desconhecem:

“There is no perfect product, because there is no perfect patient” (Moi ici: Generalizando, já existe mais gente fora da caixa do que dentro da caixa... sim, o Estranhistão está em todo o lado) and “It’s a good product, but it’s not right for everyone.”
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Stoma patients’ bodies are all so diferent that no single solution exists. The main challenge wasn’t the type of stoma a patient had—it was the type of body a patient had. That might seem an obvious point, but Coloplast’s innovation process had blinded management and R&D engineers alike to the possibility. Just as individuals can sufer from confrmation bias (a refexive seeking of only information that supports an existing position), so can entire organizations.
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This was a major problem—and, incredibly, no one in the billion-dollar industry had addressed it. It immediately became clear that Coloplast needed to categorize body types and create products designed specifically for each one."

Um antropologista entra num bar... (parte I)

Um artigo cheio de exemplos e mensagens para as empresas. Na HBR de Março de 2014, "An Anthropologist Walks Into a Bar" de Christian Madsbjerg e Mikkel Rasmussen.
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Antes de mais já sabem do papel que reservo aos antropologistas no mundo das empresas (recordar, por exemplo: aqui, aqui e aqui).
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O artigo começa com o caso de uma empresa produtora de cerveja que estava insatisfeita com a evolução das vendas nos bares. Por que é que as vendas não crescem? Um grupo de antropologistas foi enviado para os bares, para estudar o que se passava...
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Resultado, a percepção de que os bares não são todos iguais, por isso:

"Instead of bombarding them with one-size-fits-all promotional materials, it began customizing items for different types of bars and bar owners. It trained its salespeople to understand each bar owner better and invented a tool to help owners organize sales campaigns. It created in-workplace “academies” to train waitstaf about its brands and won over female servers by providing taxi service for employees who worked late. After two years BeerCo’s pub and bar sales rebounded"

Ehehe, algo que poderiam ter aprendido neste blogue!
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Outro ponto importante, em sintonia com este blogue, a opinião sobre o Big Data:

"According to a recent global study of 1,500 CEOs conducted by IBM, ... The research also reveals that CEOs see a lack of customer insight as their biggest deficit in managing complexity. They prioritize gaining customer insight far above other decision-related tasks and rank “customer obsession” as the most critical leadership trait.
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Accordingly, many companies are turning to customer research that is powered by big data and analytics. Although that approach can provide astonishingly detailed pictures of some aspects of their markets, the pictures are far from complete and are often misleading. It may be possible to predict a customer’s next mouse click or purchase, but no amount of quantitative data can tell you why she made that click or purchase. Without that insight, companies cannot close the complexity gap.
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In the rush to reduce consumers to strings of ones and zeros, marketers and strategists are losing sight of the human element. Consumers are people, after all. They’re often irrational, and they’re sometimes driven by motives that are opaque even to themselves. Yet most marketers cling to assumptions about their customers’ behavior that have been shaped by their organizational culture, the biases of the firm’s managers, and, increasingly, the vast but imperfect data stream fowing in."

Outra preocupação deste blogue, a concentração na experiência do cliente, em vez dos atributos da oferta:

"At the core of sensemaking lies the practice of phenomenology: the study of how people experience life. Management science can tell Starbucks, for example, how many cups of cofee its customers will drink in a day; phenomenology reveals how those customers perceive the cofee experience."

Continua.

A escolha dos pivôs (parte III)

Parte I e parte II.
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O que fazer depois de identificados e seleccionados os pivôs do ecossistema da procura que interessa à nossa empresa?
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Não é novidade aqui no blogue; contudo, como santos da casa não fazem milagres e, a galinha da vizinha é melhor que a minha, voltemos a Simons e ao seu segundo passo:

"Once you’ve determined who your primary customer is, the next step is to identify which product and service attributes the customer values. [Moi ici: Aqui no blogue já estamos noutra, produtos e serviços são artifícios para gerar a experiência, para produzir um resultado na vida do cliente. Isso é o que realmente conta] Within the same market and industry, different primary customers may value different things: Some demand the lowest possible price, others want a dedicated service relationship, and still others are looking for the best technology or brand or other specific attribute. To complicate matters, customers often don’t know exactly what it is they value.
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Let’s take the easy part first. Assume you have already chosen the best primary customer and have a good working idea of what the customer wants.
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Such data can help you fine-tune a product or a website’s functionality to better meet your customer’s known needs. They’re unlikely, though, to help you identify what your customers want but aren’t getting. For that, you need to actually ask them. Smart companies set up systematic dialogues with their primary customers. [Moi ici: Por isso, cuidado com o Big Data]
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you should set up processes for identifying products or services that customers may not know they need.
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Most companies assume that their products and services meet the needs of their customers. But surprisingly few actually test this assumption. So ask yourself, What are the processes we use to make sure that we truly understand what our customers value and that we can deliver value better than our competitors do?"

Acerca do contacto humano

Ai o futuro é Mongo? Ai o futuro é a personalização?
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OK!
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Então, os Golias deste mundo, munidos da tecnologia e do Big Data vão tentar conquistar o mercado dessa forma.
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Qual o truque dos Davids?
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O contacto humano!
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Reflectir sobre "Nest and Google’s Customer Service Problem"

"Google just bought entry into the home automation market. It could be very exciting, not just for Google, but for all its customers and potential customers. But in the absence of superior customer-service capabilities, their purchase is worthless."

Como é que a sua empresa trata o feedback dos seus clientes?

Big data e PMEs

A leitura de "Is There Hope for Small Firms, the Have-Nots in the World of Big Data?" fez-me recordar uma conversa desta semana numa micro-empresa.
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A empresa teve a sua primeira fase da auditoria de concessão, para a certificação do seu sistema de gestão da qualidade. Nessa auditoria, o auditor apresentou como oportunidade de melhoria a contabilização, como indicador isolado, da facturação devida aos novos clientes. Comentei com a empresa que achava a sugestão interessante, resposta do responsável da Qualidade:

- Qual a vantagem em termos práticos? Os gerentes conhecem todos os clientes, falam com todos eles, sabem perfeitamente quem rende e quem não rende.

E, a partir desta resposta regresso ao artigo referido inicialmente. Quando leio casos sobre a implementação do Balanced Scorecard nos Estados Unidos é comum verificar que são projectos em que a implementação dura mais de um ano porque há que alinhar várias unidades de negócio dispersas por um ou mais continentes. Os decisores nas empresas grandes estão tão longe do contacto directo com os clientes que precisam do Big Data para tentar obter pistas sobre o que se está a passar. Até que ponto é que o Big Data será assim tão relevante para as PMEs que lidam directamente com os seus clientes? Quantas pessoas medeiam entre um cliente e um gerente?

Big data, pois!

Como eu aprecio estas histórias, sobretudo agora que leio tanto sobre os amanhãs que cantam baseados no big-data

"Imagine that you are a subject in the following experiment, conducted by pioneering behavioral economist Richard Thaler and his colleagues. You are told that you are in charge of managing the endowment portfolio of a small college and investing it in a simulated fi nancial market.
The market consists entirely of just two mutual funds, A and B, and you start with a hundred shares that you must allocate between the two. You can put all of your shares into A, all of them into B, or some into A and the rest into B. You will be running the portfolio for twenty-five simulated years. Every so often, you will be informed of how each fund has performed, and thus whether your shares have gone up or down in value, and you will then have the opportunity to change how your shares are allocated. At the end of the simulation, you will be paid an amount that is proportional to how well your shares have performed, so you have an incentive to do as well as you can. Before the game begins, however, you have to choose how often you would like to receive the feedback and have the chance to change your allocations: every month, every year, or every fi ve years (of simulated time).
The correct answer seems obvious: Give us information, and let us use that information, as often as possible! Thaler’s group tested whether this intuitive answer is right— not by giving people the choice, but by randomly assigning them to receive feedback monthly, yearly, or every five years. Most people initially tried a 50/50 allocation between the funds since they knew nothing about which might be better. As they got information about the per for mance of the funds, they shifted their allocations. Since the simulated length of the experiment was twenty five years, the subjects in the five- year condition got feedback and could change their allocations only a few times, compared with hundreds of times for the subjects in the monthly condition. By the end of the experiment, subjects who only got perfor mance information once every five years earned more than twice as much as those who got monthly feedback.
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How could having sixty times as many pieces of information and opportunities to adjust their portfolios have caused the monthly- feedback investors to do worse than the five-year ones?"

Trecho retirado de "the invisible gorilla - And Other Ways Our Intuitions Deceive Us" de Christopher Chabris e Daniel Simons.