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Levels of Abstraction, Levels of Completeness 0

Musicians, Architects, and Systems Thinkers seem to have a similar thread woven through them. When you think about Frank Lloyd Wright, Dr. W. Edwards Deming, Peter Drucker and many others had musical composition in their background.

Next weeks, Podcast guest Jim Kalbach, is a Principal UX Designer with Citrix Online and an active speaker, writer, and instructor on business design, user experience, and information architecture. In preparation for the interview, I read his blogs at experiencinginformation.com and got lost in the multiple layers of information I found. Read an excerpt from the podcast and discover an interesting similarity and Jim’s taking on systems architecture and music composition.

Joe: I found it interesting that you have a Master’s degree in Music and Composition.

Jim: Yes, that’s what I studied initially. I have a very musical family. Both my parents are musicians, and I’ve always played instruments and been around music in more than just a passive entertainment kind of way. I was always active in making music and organizing events and concerts and things. So I studied music as an undergrad and went on to graduate school to get a degree in Music Theory and Composition, which means that I’m not a really good performer although I have a formal degree in that. I realized there’s not much of a career there so I got a second Master’s degree in Library Science, which at that time put me in contact with the web and programming – a little bit of HTML. And that was kind of my introduction into web design and digital design.

Joe: Well it seems that architectures, systems thinking goes well with music composition. Deming was a composer, Drucker and even Frank Lloyd Wright; I think their parents were music composers. What do you think that connection is?

Jim: That’s a really interesting question. I’ve always wanted to do more with that. Again it’s one of those things that’s my life experience. So those two things in my mind aren’t separate. I think if you break it down you can make comparisons. Particularly when you talk about music composition, you can talk about levels of abstraction at which you create a solution. In music composition, we talk about form. The form of music is, for people who don’t understand it, very kind of abstract and nontangible topic. But that’s where a lot of it begins. How is my piece going to begin and take shape in the middle and then come to the conclusion? Those kinds of questions, but also then how you layer up towards the surface from there, as well. You have these levels of abstraction, levels of completeness in music composition. So when coming up a digital solution whatever it might be, a product interface, or even a strategy, my experience as a composer I think does help me approach problem solving at multiple levels at the same time. So thinking about an abstract problem in terms of “what’s the form of this?” and then moving up to the surface from there. I think there are probably some other comparisons, but I’ve never really broken it down. That’s probably a talk that I need to work up for some conference at some time.

Jim:  Interestingly enough I’ve made some other comparisons between music and just collaboration in general but particularly design collaboration. That is a creative type of collaboration in teams, in companies, projects that we work on and particularly around jazz. I played and listened to a lot of jazz although I studies kind of classical composition. There are actually a couple books on this topic. There’s one in 1996 I believe from a man named John Kao called “Jamming,” and another one more recently by Frank Barrett called “Yes to the Mess.” In both of those books they use jazz as a larger metaphor for an alternative way of companies, businesses, and leaders, and teams even, how to think and collaborate because when you think about it a jazz improvisation and how a group on stage can improvise and look at all those dynamics and dimensions going on, I think it’s a valuable lesson for us particularly in this day and age. We have to rethink businesses, how we work.

Jim: The hierarchical command and control type of leadership isn’t working anymore. So what do we do? Jazz improvisation can provide a metaphor for us. Jeff Gothelf, who wrote the Lean UX book is close to me here in New Jersey where I am, and he and I are going to be giving a talk where we’re actually going to play on stage – Jeff plays keyboards. We’re actually going to play with a little jazz group that we put together. We’re going to play some music and then talk about exactly what I just mentioned. That is what are the dynamics of a jazz group and how can we use that as a larger metaphor for teams to work together better. That’s at the RE:DESIGN Conference on April 28 and 29 in Brooklyn. If you search for just redesign on Google, you don’t find it but if you search in RE:DESIGN in Brooklyn, you might find that conference on Google. We’re going to be speaking on Tuesday, April 29.

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How Many Scenarios are Correct? 0

I prefer using scenario type thinking in my work versus plotting these maps. I think creating a scenario; a story is much more useful and memorable to all concerned parties. I have always believed in the power of three. A few of these outlines are below:

Pre-Purchase Purchase After Purchase
Expect to See Like to See Love to See
Worst Case Most Likely Best Case
Short Term Intermediate Long Term

 

I can go on, but you get the idea. You take the description that you can explain best and determine the other stories around it. You will not always choose a middle ground to start. You start where you can tell the best story. The trick is to tell the story with enough definable content that you can distinguish the difference.

In re-reading Scenario Planning: Managing for the Future the other day, it may have caused me to differ on this thinking. In the book,  they ask the question, How Many Scenarios?

An excerpt from the book:

Shell had experimented with four, three and two scenarios for strategic planning.

What it had found was that:

  • Four scenarios encourage divergent thinking and are useful for creating vision
  • Three scenarios lead to the expectation that one is “the forecast”‘
  • Two scenarios allowed two very distinct (not necessarily “low” or “bad* vs “good” or “high”) to be developed.

This approach is very different from the baseline, high, low” approach, in that it concentrates on creating credible, but different, worlds for each scenario.

I struggle with this concept for every scenario, but it certainly has some value. As I think about the four scenarios, it certainly stops me from classifying and being more open and as they say encourage divergent thinking. Three is certainly limiting.

However, three scenarios can also serve a purpose when we move away from the strict sense of the word scenario and use it in a way to forecast. Painting other scenarios around a forecast is entirely acceptable if that is our intent.

What are some of your thoughts? Should we even consider 2 scenarios? Is there a time that we would never use 2, 3 or 4? Is there a perfect number?

How would you re-phrase one of the rows of three to four in the table above?

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Measure the Journey not the Destination 1

In most of my sales and marketing work, I try to use only three different measurements to guide it. I have found that though we can create more these pieces to the measurement puzzle can cover a lot of ground without complicating things. The three different pieces are performance measures, impact measures and outcome measures.

Performance measures are about the work you did. They are composed of a number and a unit of measure. The number will give us how much and the unit will be the meaning of the what.

Examples:

  1. Number of people visited
  2. Number of outgoing calls
  3. Number of mailings
  4. Response time on calls

Impact measures are about how the audience responded. They are also composed of a number and a unit of measure. The number will give us how much and the unit will be the meaning of the what.

Examples:

  1. Number of people attended
  2. Number of website visits
  3. Number of messages returned.
  4. Number of product requests

These types of measures can be fairly simple, and most of us are familiar with them. Performance is what we do; impacts are what we hope for, but the third measurement of outcomes is much more difficult. They actually rests in the middle of this equation.

Performance = Outcome = Impact

For our performance to be effective, we require a change in someone or something. That difference is the result of our work or the outcome of it. Impacts are eventual outcomes. They are not the journey, they are the destination. If we intend to measure outcomes, there must be a way for us to measure change. Just because we make 100 calls does not mean we will get 10 people to attend our event. Outcomes give us the ongoing measurement on how we are achieving or not achieving the desired impact.

I use an approach called BACKS measure developed by Lucy Knight and mentioned in the book The Nonprofit Outcomes Toolbox: A Complete Guide to Program Effectiveness, Performance Measurement, and Results. We evaluate our outputs based on how the BACKS are improved. The acronym BACKS stands for Behavior, Attitudes, Conditions, Knowledge, and Status.

BACKS and the Description of Condition

  • Behavior: Repeated patterns of action
  • Attitude: The way you think and feel about someone or something
  • Measures: The state of a person, organization or a thing
  • Condition:
    • In Crisis Experience – The worst negative effects of behavior
    • Vulnerable – Worst behavior has been temporarily suspended
    • Stable – No longer teetering but could slip back without assistance
    • Safe – Job has been done and is performing satisfactorily
    • Thriving – Ideal condition
  • Knowledge: Amount of new information retained
  • Status: Change in social condition or standing

These are all very subjective. I usually describe the present condition or what I expect to see and then what I would like to see followed by what I would love to see. Using this outcome approach or a BACKS measurement allows for us to have a discussion about the present versus using lagging indicators. If interested to see how this works review the blog posts, The BACKS Approach to Building an Eco-System and Outcome-Based Persona.

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How Visual is Your Storytelling? 1

EkatrinaHow well do you understand the pandemonium towards visuality? A new book,The Power of Visual Storytelling: How to Use Visuals, Videos, and Social Media to Market Your Brand by Ekaterina Walter, is a great introduction to this subject. The book offers a viewpoint from the 20K level all the way down to pixels without missing a beat.

Ekatrina is a passionate marketer, who writes and speaks on topics of leadership, business innovation, and digital revolution and also authored Think Like Zuck.

 

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Constructing Teams starts with Standard Work 0

When I use the SALES SDCA approach in Lean Marketing, I emphasize the use of sales and marketing teams. It is one of the underlying principles that are needed. A few basic team development structures need to be identified at the very beginning of the project.

I discuss Leans around the three processes of SDCA, PDCA, EDCA. First, we must address everyone’s standard work. If we do not, there is limited work that can get accomplished and seldom can a team come together to accomplish the other work of PDCA and EDCA.

The amount of Standard Work that each person has differs from organization to organization and from person to person but we all have some. My thoughts about Standard Work:

  • Standard Work should only encompass part of your time.
  • Every person wants some form of standard work. Most enjoy doing tasks that they are comfortable with and it gives them a sense of accomplishment when completed.
  • Standard Work is what provides line of sight for your team. It enables support and provides opportunity for managers to serve you.
  • Standardizing your work makes it easier for customers to go deeper into your organization for knowledge sharing. This provides a flood of new ideas for innovation and co-creation opportunities. More importantly, it secures a vendor-customer relationship or partnership that is difficult for others to replicate.
  • Standard Work does not need to be boring, remember Zappos.

I have been a longtime fan and practitioner of Franklin Covey’s, The 4 Disciplines of Execution. In 4DEx, they use the term the “Whirlwind” in the same manner as I think about Standard Work. As they describe operating outside the whirlwind (SDCA) think of that as PDCA or EDCA depending on if you are looking for incremental or breakthrough type improvement.

People can be participating on one type of team, two or all three teams. Even though it is hard to imagine that there would not be both SDCA and PDCA in everyone’s job, there may not be EDCA. Or, it may only be on an infrequent basis. What I encourage though is that the time spent is clearly defined with emphasis on handling one hour of EDCA a week as there is thirty hours of SDCA. It should be a very fluid process. I am not trying to split hairs about time just trying to reinforce a point that is described in the video above from Franklin Covey.

One of the key considerations in developing a team is to determine the objective of the cycle. Is it primarily problem resolution, creativity, or tactical execution? Team structure needs to be considered as well as the participants. You will find a variety of structures will work for you, but the typical model is one of a business team that has a team leader, and all others are on equal footing. Many times the team leader is really just a participant but has the administrative work as an added responsibility.

Think about the kind of team needed: Tactical execution(SDCA), Problem Resolution (PDCA), and Creativity (EDCA). Separate the sessions so people know which hat they are wearing when. Without this process, you may have creative teams working on tactical execution or on the other hand a problem-solving team working on a creative solution.

Once you’ve identified the team’s broadest objective—problem resolution, creativity, or tactical execution—then you set up a team structure that emphasizes the characteristic that is most important for that kind of team. For a problem-resolution team, you emphasize trust for a creativity team, autonomy, and for a tactical-execution team, clarity. Listed below is an outline identifying the team structure needed for Standard Work (adapted from Teamwork and the Rapid Development books):

SDCA: Tactical-Execution Team

  1. Objective: Focuses on carrying out a well-defined plan.
  2. Dominant Feature: Clarity
  3. Sales Process Example: Upgrade to an existing product
  4. Process emphasis: Highly focused task with clear roles
  5. Lifecycle Models: Waterfall, design to schedule, spiral, staged delivery
  6. Team Members: Loyal, committed, action-orientated, sense of urgency, responsiveness
  7. Team Models: Business team, feature team, SWAT

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A DFSS Expert’s View of TRIZ 2

Dr. Kai Yang is a Professor in the department of Industrial and Manufacturing, Wayne State University. His areas of expertise include Six Sigma, statistical methods in quality and reliability engineering, Lean product development, Lean healthcare, and engineering design methodologies.

Related Podcast and Transcript: Six Sigma’s Voice of Customer

Joe Dager: I also noticed in your product development process that you spend quite a bit of time talking about TRIZ.

Kai Yang:  Well, TRIZ basically is a way to try to improve the creativity of your product development process. Supposedly the TRIZ is you try to condense the inventive principle to a small number of principles. People learn; they can really improve their creativity by learning existing knowledge. Some of the companies are very, very successful at it, as far as I know. Samsung is now is a leading company in electronics. Even now, they still contract TRIZ experts in large numbers working for a couple of years in their headquarters to help them to improve product development. For Samsung, it’s definitely a useful tool. It’s increased their competitiveness. I think that now you hear about more Samsung than Sony Company. So I talk to their product development, some top people. They think that TRIZ really helped them a lot. However, now that every company has the same experience, some use TRIZ and don’t get out a lot. I think this is a tool we need to customize to your own practice. So, it can do wonders, it just needs to be applied correctly.

Joe Dager: I think you’re probably right there, because I always found TRIZ kind of cumbersome. Yet, I’m thinking what you’re saying is that you customize it, and maybe one company will only use a third of it, or half of it, or something like that.

Kai Yang:  I’m thinking about a few things important in TRIZ. One is simplify customize. The other is you have to go with good information searching the IP. So, for example, when people apply TRIZ, one of the common problems they face is, ‘Well I can plug in what the contradiction is, what the problem is. I can find out what principle may be useful for me. But, still, this principle is a general principle. I’m still not able to figure out a particular solution for my design problem.’ So, that is one of the common things.

I found out if people are given relevant information about similar patents, how the people designing similar products resolve this type of problem, if they’re flooded with good examples. They are able to take it. I think that is also one of the reasons Samsung did well in using TRIZ. Only learning it does not make it work. You have to flood it with good information.

Related Podcast and Transcript: Six Sigma’s Voice of Customer

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Can Numbers be Creative, Can Numbers be Imaginative? 0

Author, ERIC SIEGEL, PhD, is the founder of Predictive Analytics World and Executive Editor of the Predictive Analytics Times. Eric makes the how and why of predictive analytics understandable and captivating.

Joe: When we look at this, data certainly plays a part but people would refute the fact that data can tell the future. I always use this Einstein quote "Logic will get you from A to B, but imagination will take you everywhere.” Can numbers be creative, can numbers be imaginative?

Related Podcast and Transcription: Predicting with Analytics


Eric Siegel: That’s a great question; I would say yes because as I’ve mentioned earlier – the core method here is predictive modeling, academically known as machine learning. It is literally looking at data, the history of many transactions of how things turn out in the past in order to learn how to predict under new circumstances for a consumer who has a new profile and new history of behavior that’s never been seen before and to robustly be able to apply what’s been learned. That is you’ve actually not just discovered a pattern that shows up in this particular data set, but that actually holds in general. There is an art to that; it is amazing kinds of things that come out of it; it can’t be visualized ultimately by human thought process because computers can do things in a multidimensional way. It’s all about finding that model that looks at all the different factors about an individual, both demographic and behavioral, and consider them together in concert to come up with the best prediction for that individual. The means; the mechanism to do that is the model is the thing that predicts is the thing that’s learned or output from the predictive modeling process.

I would say yes, there’s definitely creativity, I devoted a chapter to how amazing the results ended up being as far as the IBM Watson computer that learns from Jeopardy, the TV quiz show Jeopardy, questions and how to answer new ones – that’s an amazing story. However, unlike that story, usually it’s not about accuracy, so you premise your question just now by saying, “some people say you can’t really predict very well,” the fact is in general, especially with human behavior and the weather for that matter; there’s a real limit to how far ahead and in what way we can accurately predict. It turns out that the use of this technology on all of these different operations and getting value from it does not hinge on the accuracy. Predicting better than guessing, often significantly better than guessing, is what makes the difference and what provides value in running mass operations more effective.


Related Podcast and Transcription: Predicting with Analytics

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