Tag Archives: socio-technical

A Robust Approach to Determining Voice of the Customer (VOC)

Image Credit: Doug Buckley of http://hyperactive.to

Image Credit: Doug Buckley of http://hyperactive.to

I got really excited when I discovered Morris Holbrook’s 1996 piece on customer value, and wanted to share it with all of you. From the perspective of philosophy, he puts together a vision of what we should mean by customer value… and a framework for specifying it. The general approach is straightforward:

“Customer Value provides the foundation for all marketing activity…
One can understand a given type of value only by considering its relationship to other types of value.
Thus, we can understand Quality only by comparison with Beauty, Convenience, and Reputation; we can understand Beauty only by comparison with Quality, Fun, and Ecstasy.”

There are MANY dimensions that should be addressed when attempting to characterize the Voice of the Customer (VOC). When interacting with your customers or potential customers, be sure to use surveys or interview techniques that aim to acquire information in all of these areas for a complete assessment of VOC.

The author defines customer value as an “interactive relativistic preference experience”:

  • Interactive – you construct your notion of value through interaction with the object
  • Relativistic – you instinctively do pairwise comparisons (e.g. “I like Company A’s customer service better than Company B’s”)
  • Preference – you make judgments about the value of an object
  • Experience – value is realized at the consumption stage, rather than the purchase stage

Hist typology of customer value is particularly interesting to me:

typology-customer-value

Most of the time, we do a good job at coming up with quality attributes that reflect efficiency and excellence. Some of the time, we consider aesthetics and play. But how often – while designing a product, process, or service – have you really thought about status, esteem, ethics, and spirituality as dimensions of quality?

This requires taking an “other-oriented” approach, as recommended by Holbrook. We’re not used to doing that – but as organizations transform to adjust the age of empathy, it will be necessary.

Holbrook, M. B. (1996) . “Special Session Summary Customer Value C a Framework For Analysis and Research”, in NA – Advances in Consumer Research Volume 23, eds. Kim P. Corfman and John G. Lynch Jr., Provo, UT : Association for Consumer Research, Pages: 138-142. Retrieved from http://www.acrwebsite.org/search/view-conference-proceedings.aspx?Id=7929

What (Really) is a Data Scientist?

Drew Conway's very popular Data Science Venn Diagram. From http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram

Drew Conway’s very popular Data Science Venn Diagram. From http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram

What is a data scientist? What makes for a good (or great!) data scientist? It’s been challenging enough to determine what a data scientist really is (several people have proposed ways to look at this). The Guardian (a UK publication) said, however, that a true data scientist is as “rare as a unicorn”.

I believe that the data scientist “unicorn” is hidden right in front of our faces; the purpose of this post is to help you find it. First, we’ll take a look at some models, and then I’ll present my version of what a data scientist is (and how this person can become “great”).

#1 Drew Conway’s popularData Science Venn Diagram” — created in 2010 — characterizes the data scientist as a person with some combination of skills and expertise in three categories (and preferably, depth in all of them): 1) Hacking, 2) Math and Statistics, and 3) Substantive Expertise (also called “domain knowledge”). 

Later, he added that there was a critical missing element in the diagram: that effective storytelling with data is fundamental. The real value-add, he says, is being able to construct actionable knowledge that facilitates effective decision making. How to get the “actionable” part? Be able to communicate well with the people who have the responsibility and authority to act.

“To me, data plus math and statistics only gets you machine learning, which is great if that is what you are interested in, but not if you are doing data science. Science is about discovery and building knowledge, which requires some motivating questions about the world and hypotheses that can be brought to data and tested with statistical methods. On the flip-side, substantive expertise plus math and statistics knowledge is where most traditional researcher falls. Doctoral level researchers spend most of their time acquiring expertise in these areas, but very little time learning about technology. Part of this is the culture of academia, which does not reward researchers for understanding technology. That said, I have met many young academics and graduate students that are eager to bucking that tradition.”Drew Conway, March 26, 2013

#2 In 2013, Harlan Harris (along with his two colleagues, Sean Patrick Murphy and Marck Vaisman) published a fantastic study where they surveyed approximately 250 professionals who self-identified with the “data science” label. Each person was asked to rank their proficiency in each of 22 skills (for example, Back-End Programming, Machine Learning, and Unstructured Data). Using clustering, they identified four distinct “personality types” among data scientists:

As a manager, you might try to cut corners by hiring all Data Creatives(*). But then, you won’t benefit from the ultra-awareness that theorists provide. They can help you avoid choosing techniques that are inappropriate, if (say) your data violates the assumptions of the methods. This is a big deal! You can generate completely bogus conclusions by using the wrong tool for the job. You would not benefit from the stress relief that the Data Developers will provide to the rest of the data science team. You would not benefit from the deep domain knowledge that the Data Businessperson can provide… that critical tacit and explicit knowledge that can save you from making a potentially disastrous decision.

Although most analysts and researchers who do screw up very innocently screw up their analyses by stumbling into misuses of statistical techniques, some unscrupulous folks might mislead other on purpose; although an extreme case, see I Fooled Millions Into Thinking Chocolate Helps Weight Loss.

Their complete results are available as a 30-page report (available in print or on Kindle).

#3 The Guardian is, in my opinion, a little more rooted in realistic expectations:

“The data scientist’s skills – advanced analytics, data integration, software development, creativity, good communications skills and business acumen – often already exist in an organisation. Just not in a single person… likely to be spread over different roles, such as statisticians, bio-chemists, programmers, computer scientists and business analysts. And they’re easier to find and hire than data scientists.”

They cite British Airways as an exemplar:

“[British Airways] believes that data scientists are more effective and bring more value to the business when they work within teams. Innovation has usually been found to occur within team environments where there are multiple skills, rather than because someone working in isolation has a brilliant idea, as often portrayed in TV dramas.”

Their position is you can’t get all those skills in one person, so don’t look for it. Just yesterday I realized that if I learn one new amazing thing in R every single day of my life, by the time I die, I will probably be an expert in about 2% of the package (assuming it’s still around).

#4 Others have chimed in on this question and provided outlines of skill sets, such as:

  • Six Qualities of a Great Data Scientist: statistical thinking, technical acumen, multi-modal communication skills, curiosity, creativity, grit
  • The Udacity blog: basic tools (R, Python), software engineering, statistics, machine learning, multivariate calculus, linear algebra, data munging, data visualization and communication, and the ultimately nebulous “thinking like a data scientist”
  • IBM: “part analyst, part artist” skilled in “computer science and applications, modeling, statistics, analytics and math… [and] strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge.”
  • SAS: “a new breed of analytical data expert who have the technical skills to solve complex problems – and the curiosity to explore what problems need to be solved. They’re part mathematician, part computer scientist and part trend-spotter.” (Doesn’t that sound exciting?)
  • DataJobs.Com: well, these guys just took Drew Conway’s Venn diagram and relabeled it.

#5 My Answer to “What is a Data Scientist?”:  A data scientist is a sociotechnical boundary spanner who helps convert data and information into actionable knowledge.

Based on all of the perspectives above, I’d like to add that the data scientist must have an awareness of the context of the problems being solved: social, cultural, economic, political, and technological. Who are the stakeholders? What’s important to them? How are they likely to respond to the actions we take in response to the new knowledge data science brings our way? What’s best for everyone involved so that we can achieve sustainability and the effective use of our resources? And what’s with the word “helps” in the definition above? This is intended to reflect that in my opinion, a single person can’t address the needs of a complex data science challenge. We need each other to be “great” at it.

A data scientist is someone who can effectively span the boundaries between

1) understanding social+ context, 

2) correctly selecting and applying techniques from math and statistics,

3) leveraging hacking skills wherever necessary,

4) applying domain knowledge, and

5) creating compelling and actionable stories and connections that help decision-makers achieve their goals. This person has a depth of knowledge and technical expertise in at least one of these five areas, and a high level of familiarity with each of the other areas (commensurate with Harris’ T-model). They are able to work productively within a small team whose deep skills span all five areas.

It’s data-driven decision making embedded in a rich social, cultural, economic, political, and technological context… where the challenges may be complex, and the stakes (and ultimately, the benefits) may be high. 


(*) Disclosure: I am a Data Creative!

(**)Quality professionals (like Six Sigma Black Belts) have been doing this for decades. How can we enhance, expand, and leverage our skills to address the growing need for data scientists?

ASQ Asks: What Can We Do to Encourage STEM? I Say: STEAM

zome-2In his March 2015 post, ASQ CEO Paul Borawski asks “What can we do to encourage the next generation of STEM (Science, Technology, Engineering, and Math) professionals?” My answer will be short today because I’ve been actively working on that for the past several months with a senior capstone project team (Cassidy Moellers, Dylan Chance, and Robert Spinoza) at James Madison University – we’re getting ready to finalize the project in the next couple of weeks, and submit an academic paper to the STEAM Journal about how you can use art to catalyze interest and engagement in STEM. [Postscript: Check out our published paper in the STEAM Journal — Radziwill, N. M., Benton, M. C., & Moellers, C. (2015). From STEM to STEAM: Reframing what it means to learn. The STEAM Journal2(1), 3.]

So much innovation in STEM is fueled by imagination and exploration, and in my opinion, we don’t communicate that very well to younger people. A great gateway drug for this purpose is art. There’s even a movement underway to expand out vision of STEM, and more tightly and more essentially integrate aesthetics, form, design, and fun into what we do via STEAM (Science, Technology, Engineering, Art, and Math).

STEAM doesn’t advocate just doing the arts alongside more traditional science and engineering. It actually requires that we look towards how we can use STEAM to create meaning for ourselves and our communities. In other words, it can help us get our mind off of science and engineering to understand and control the world around us – and focus more on how beautiful and intriguing things are that we can learn in those domains.

The picture above is the interactive zonohedral dome (or “zome”) that our students created specifically to engage others in the fun of integrated science and engineering. Here’s how they summarize their project:

As our communities expand rapidly, both physically and digitally, we can lose our sense of connection and togetherness. Interactive and participatory art interventions cultivate community by provoking engagement in unexpected areas. In this project, the prototype for an interactive zonohedral dome (or “zome”) was constructed as a proof of concept for an art intervention to engage students in collaborative STEM (Science, Technology, Engineering, and Math ) learning, by creating feelings of connection with the technology and with each other. Consequently, it demonstrates the values of the STEAM (Science, Technology, Engineering, Art, and Math) movement in education. Design elements (and an assessment approach) were selected based on a comprehensive literature review which focused on the aspects of engagement that would boost participants’ interest in and proficiency with STEM subjects.
 
A zome is a structure that supports itself solely due to its geometry. No nails or glue are used in the construction. The interactive nature of the structure emerges from sensors that detect occupancy, with music and lights automatically responding to the pattern of people entering and leaving the zome. Many technologies were combined to create this experience, including SketchUp (to design the components), Makerbot Replicator II (to build the structure), Arduino (to detect occupancy via phototransistors), LightShowPi (to generate Fast Fourier transforms of music files and control the frequency and amplitude of audio communicated via LEDs), and RaspberryPi (a microcomputer to run LightShowPi and translate the signals from the Arduino to play audio at pre-designated decibel levels). 
We’ll post a video of the zome in action very soon. It’s so fun to look at, and play with… and what better way to learn programming than to make a structure respond to the presence and motion of the people around it?

Change vs. Transformation: What’s the Difference?

Image Credit: Doug Buckley of http://hyperactive.to

Transformation involves changing your frame of reference. Image Credit: Doug Buckley of http://hyperactive.to

Last week, on the Lean Six Sigma Worldwide discussion group, Gaurav Navula (CEO of Perky Pat India) asked us to reflect on the difference between change and transformation. Change management was a major thrust in the 1990’s and early 2000’s, but you don’t hear as much about it anymore. Today, the tools of change management (making the business case, aligning strategy with tactics, engaging stakeholders, instituting goal-directed training and education programs, etc.) have faded into the everyday landscape of management. Leaders seem to be focused more on “surviving and thriving” in the midst of rapid and disruptive innovation, which enhances the importance of transformation.

But what’s the difference? Just a couple months ago, Ron Ashkenas (on the Harvard Business Review blog) asserted that we don’t know the difference: “We really do know how to execute discrete changes. What we know much less about is how to engineer a transformation.”

But I think we do know how to engineer a transformation, and we can use this recipe. I’ll explain more towards the end of this post, but it acknowledges the relationship between larger-scale changes and transformation: that change is required for transformation, and all transformation involves change, but not all change is transformational. This is based on the idea that all observable changes come with “shifts in state” – from the quality management perspective, you can think of these as observed changes in system performance (cost savings, more efficient or effective use of time, increasing throughput, enhancing return on investment).

transformation

What this says is: transformation is what you get when you adjust the frame of reference that you observe the world with, and then add to that new perspective the product of all the shifts in state that have occurred as a result of incremental changes. I say “when you adjust the reference frame,” but that’s somewhat misleading. Usually there is some sort of transformational experience… an “a-ha” moment or event… where the scales fall from your eyes and you see the world in a completely different way. The shift in reference frame always involves relationships: either your relationship to other people or other groups, or your relationship to yourself and how you see yourself, or maybe both. 

“My sense is that there’s an underlying semantic problem, stemming from confusion between what constitutes “change” versus “transformation.” Many managers don’t realize that the two are not the same. And while we’ve actually come a long way in learning how to manage change, we continue to struggle with transformation.” — Ron Ashkenas, HBR blog

Here are some of the qualitative descriptions that have been offered to further articulate the differences between change and transformation. Notice that they do not conflict with the expression for transformation above.

Change:

  • Finite initiatives which may or may not be cross-cutting (HBR)
  • Desire to improve the past directs what we do (Mohanty)
  • Makes the system better (Mohanty)
  • Any time an organization asks its people or systems to stop, start, or execute in a new way a process, behavior or location of performanc (Holtz)
  • Making setups in different format within the given system to achieve improvements in performance (Bob Matthew)
  • Incremental (Anand)

Transformation:

  • A portfolio of open-ended initiatives which are necessarily cross-cutting (HBR)
  • The future directs your actions and only the limits of imagination and courage constrain possibilities (Mohanty)
  • Makes a better system (Mohanty)
  • The base of transformational is the word “formation” – the stuff things are made of or the structure – that needs to change for the change to be transformational. (du Plessis)
  • Encompasses bigger, more radical shifts (Holtz)
  • Makes a total change of system, procedure and a total mindset to get a better transparency and communication within the process owners including the customers. (Bob Matthew)
  • Should be informed by strategy (Kshirsagar)
  • Transformation is not a preference; it’s a necessity as a result of resistance to change. (Aydin)
  • Major; result of many changes (Anand)

Think about the last time you experienced a transformative change, perhaps even in your personal life. For example, think of a time when you were able to truly and completely forgive someone for some way they had wronged you. There were certainly a collection of changes in state that occurred — prior to, during, and after the forgiveness experience. But as a result, didn’t you also come to see the world in a completely different way? Your frame of reference with respect to that person… and probably, other people you have relationships with… also shifted.

Quality as a Cultural Vision: My Week in Japan

japan-treesIn his July post, ASQ CEO Bill Troy reflects on the immense value of an ultra-clear organizational vision. After a trip to Sweden, where he attended a quality conference organized by the European Organization for Quality (EOQ), he was struck by IKEA’s starkly elegant focus on its customers’ needs, and Volvo’s BHAGgy(*) goal that no one will be seriously injured or killed in a new Volvo by 2020.

This past June, I went to Japan for the first time. It wasn’t a work trip, so I didn’t visit any companies or do any plant tours. I didn’t intend to learn anything about quality, despite the obvious opportunities. And quite frankly, I wasn’t really sure I would enjoy Japan, or feel comfortable in that country, despite my profession’s obvious ties to that country’s insights and contributions to knowledge!

Why? Well, two reasons. The first is that I have some deep-seated emotional issues associated with Japan. It’s kind of like that time I was 16 and decided to experiment with too much vodka and Great Bluedini Kool-Aid. It was not a good idea. And I’ve never been able to eat or drink anything blue (or even drink Kool-Aid) since — that’s over 20 years completely inoculated to Kool-Aid, all because of a negative emotional association. I kind of had the same thing with Japan, prior to this summer.

My second reason for resisting Japan is more legitimate. I’ve worked with Japanese colleagues in the past, and it’s always been subtly disturbing. I always got the distinct sense of a lack of authenticity, and authenticity has always been a really important value of mine. I found that my Japanese colleagues could be very nice to my face, but then later, I’d realize that they completely disagreed with me (or in fact, disliked me completely). I didn’t like the (real or perceived) dichotomy. It made me nervous. If I can’t know you authentically, how can I work with you?

After spending a week in Japan, I’m not so bothered by this “lack of authenticity”. Even acknowledging this shift in my feelings is very surprising to me.

Being in Japan is an amazing, refreshing experience. Each person clearly has a sense of duty. Everyone I encountered was very respectful, genuinely interested in not bothering other people, and genuinely interested in providing a high level of service quality. There was no question about it: if you were in a service role, you were going to provide high quality. If you were responsible for providing products: they were going to be of high quality, regardless of how much you had paid for the privilege.

It would be shameful if you did not provide high quality.

This just seems to be part of their culture. I’m not advocating the threat of shame, or the threat of being ostracized by your community if you don’t meet their expectations — but there’s something very nice about having a socially-enforced baseline of high expectations. This  cultural vision, socialized into everyone since childhood, ensures that the entire country routinely meets high standards for quality just because how could it be any other way?

In fact, the cultural vision related to quality in Japan is so clear, I’m sure no one can even see it.

 

(*)BHAG = “Big Hairy Audacious Goal” or alternatively, a really crazy-out-there stretch goal, conceptualized and popularized by Collins and Porras (1994).

What #BIF9 and Burning Man Taught Me About Transformation – Part II (via Deming!)

brc-phone

Even the phones at Burning Man tell you that you’re in Black Rock City, NV

In Part I, I described some observations from my experiences at BIF and Burning Man, and alluded to the notion that I might have uncovered a very simple “secret sauce” they share. Here are the observations:

  • Both communities consist of active and engaged participants who could be considered “innovation junkies”. Whereas the BIF crowd focuses on more traditional organizational and social innovation, the Burning Man crowd spans the extremes of experiential innovation (through art, technology, interactions with other people, or even just figuring out how to navigate life in the Black Rock Desert).
  • “Random Collisions of Unusual Suspects” (#RCUS) is the norm in both environments. First, the “unusual suspects” seem to be attracted to opportunities to be inspired and get their brains re-wired; second, the participants in both environments seem predisposed to the notion that serendipity is working on their behalf — and they let it happen.
  • People at both BIF and Burning Man tend towards non-judgment, seeking to appreciate and learn from their differences (rather than to resist, deny, or challenge those differences).

The common thread is that both environments have something magical designed into them, and this is the secret sauce: the push to drive out fear. Many of the BIF storytellers have been through Campbell’s Hero’s Journey and make themselves vulnerable so that the audience can vicariously (and often emotionally!) experience their transformation; at Burning Man, you’re stripped of your usual identity and thus unburdened from the fear you might carry as a result of having developed that identity over so many years.

When quality guru W. Edwards Deming formulated his 14 Points decades ago – principles for managers to transform business effectiveness – he expressed that the purpose of the points was to enable everyone to work with joy. One of the points (my favorite one, in fact) is to drive out fear so that everyone may work effectively.

If you are to fully embrace innovation, there is no room for fear! You must work towards fully being yourself, to push your own boundaries, and by extension, to push the boundaries of others, and to push the boundaries of traditional and accepted ways of doing things (“business models”). You are encouraged to own your own story, to TELL your own story, and to connect with others to help them identify with their own stories – and chase away the fear of being authentic, of being able to contribute to your greatest potential.

Why do we hold back? Why are we fearful? (I do it too, all the time.)

  • I am afraid you won’t accept me. I am afraid you won’t like me.
  • I am afraid you will disagree with my choices or decisions, and struggle with me or reject me as a result.
  • I’m afraid you won’t think I’m smart enough, good enough, worthy enough.
  • I am afraid that if you know who I really am, it might have consequences for my health or well-being (e.g. I could lose job, my reputation, my standing within the organization or community).
  • I’m afraid that what I’m trying to do – or be – just won’t work.

 

FEAR **IS** THE BOX.


To think “out of the box,” you must be living out of the box, and it’s an ongoing (and lifelong) process to do that.

I have not yet achieved healthy fearlessness as my steady state – I’m still awaiting bursts of my own personal transformation.  According to Ignite.me:

Joseph Campbell talked about the ‘Hero’s Journey’ whereby the hero is beckoned to enter an unfamiliar world.  When the hero enters this world, they are met with challenges, hurdles, and eventually a seemingly insurmountable confrontation which is achieved by using skills they picked up along the journey.  By overcoming this obstacle, the hero attains new self-knowledge which they can bring back to their people in the ‘ordinary land’ as their gift to the world.

Common themes of ancient mystery traditions are secrecy, death of the ego, participating with archetypal reality, and a rebirth of a new self.  The Eleusinian Mysteries took place over almost 2000 years and were shrouded in mystery from the uninitiated. Shamanic initiation often comes with the shaman being psychologically and experientially deconstructed and put back together.  Some tribal societies had rites of passage where children are ripped away from the bosom of the mother and left in the bush to learn how to become a warrior.  Rites of passage are transformational experiences where the old you is transformed into a new YOU.  That’s where we want to take you, and we create the container for that transformation.

What that means is that you may come as a journalist, or a chef, or a bike messenger, or a computer programmer but for the duration of our journey, you may choose to leave that behind to lose yourself in the present in workshops, dance, yoga, and celebration.  Transformation is disruptive and disorienting and actually occurs when past beliefs are shattered, habits are broken, and futures are rewritten.

By temporarily suspending fear, you create the space for transformation – the space for new experiences to redefine what you know and feel about yourself, and your interactions with other people and the world around you.

But this concept has been around for thousands of years… more on that tomorrow.

Peripheral Visioning

doug-jan-d

Image Credit: Doug Buckley of http://hyperactive.to

Somehow, some way, over the course of too many years growing up staring into a computer screen — my eyesight became much-less-than-perfect.

Only I didn’t know it. I thought everyone lived in a slightly hazy, cloudy world, where all the colors naturally blended into postmodern mosaics of distant trees and mountains. It was never a problem for me until the day about ten years ago that I was headed east on I-64 into Charlottesville, and coming over the hill into town, struggled to identify what that giant number on the speed limit sign was. I squinted, closed one eye at a time, and figured that the number was probably 55… so I slowed down. Then I realized:

They probably make those speed limit signs big enough for anyone to see.

I got scared, and drove straight to the walk-in eyeglass clinic, where I explained my predicament. They quickly made room in their schedule for an emergency appointment. Usually afterwards, they make you wait 24 hours to pick up your new glasses, but with my 20/400 vision, they wouldn’t let me leave without them. Fortunately, my eyesight could be corrected to almost 20/20, which was nice. I walked out of the store with my new glasses on — and into an amazing, sparkly new world! The trees all had individual leaves on them!! Cars were so shiny! I could read license plates — from MY driver’s seat!

But immediately, I recognized how I’d managed to drive for all those years with bad vision!

Because I couldn’t really see what was ahead of me, I just focused my vision off and to the right side of the road, on the ground. I kept the road and the cars in my peripheral vision, so I could easily sense where they were, and make accommodations. If I tried to look straight ahead, I got frustrated quickly, emotionally wrapped around my own axle, because I couldn’t see any of the detail… and ultimately, that state of being wasn’t safe for driving. I couldn’t focus on what I was worried about, or I’d be a danger on the road.

Not long after that, I realized how effective a strategy this was in my work — because there’s so much change and uncertainty, it’s impossible to look directly ahead of you and see clearly. And that can be scary and unsettling! My solution was: if there was some big goal I was trying to achieve, the best way to reduce my angst and qualm my (sometimes very subtle) emotional stranglehold on myself — was to focus on something else. Something just as important, maybe even something that contributed to the main goal, but something I was not quite so emotionally wrangled by!

I starting calling this my “peripheral visioning” technique. It actually helped me achieve my primary goals – because by consciously setting my primary goal to the side, and focusing on something related to it (or maybe in support of it), I was still making progress but I wasn’t experiencing as much stress. And as a result, I was more open to the serendipity and the chance encounters – with people and with information – that helped me make progress on the primary goal!

Set an intention, get your ducks in a row, and then get out of your own way by focusing on something else!

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