PDCA

What Happened to My Linear World 1

I grew up in the manufacturing world. I think I might have learned how to weld before I learned how to walk. I ended up putting myself through college along with help from the G.I. bill as a welder and later moved into industrial drafting. I even built process equipment. I loved process mapping; value stream mapping and flow diagrams. I eventually moved into the sales and marketing area and fell in love once again with sales funnels, marketing funnels, customer journey mapping and later workflows. I was a process guy through and through.

Reinforcing all this, I think I purchase the first version of Microsoft Project. Not sure it was the first, but it came on (2) 5¼” floppy discs. My projects were always lined up on a Gantt charts. These projects were well defined, well scoped, and we delivered on time, on budget and at high quality.

Linear Thinking

I was first introduced to Lean through Peter Senge and The Fifth Discipline but for the life of me could not understand what Senge was thinking with all those loops. I eventually move into Six Sigma, later Lean Six Sigma and later Lean. I was still primarily a process thinker, but those loops still bothered me.

As time moved forward, I saw the world changing around me. Those end to end linear processes that I understood so well and could map out have started getting shorter and shorter. I started justifying doing the work using the analogy that it was the planning that was important more so than the plan itself. However, reality was that the world had more influence on what I was doing, and I had less control. My planning became more frequent and less conclusive, I discovered I was no longer living in a linear world.

What should I do?

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How Many Good Ideas are Lost because of a Poor Plan? 0

I feel like we spend a great deal of time re-naming or re-packing different processes and methodologies. Half of our arguments between these methods do little to improve either process. It is a shame because most have a lot to learn from the other. I can hardly think it will change; we have been doing it for centuries. Countries, religions and organizations have splinted apart and depending on if you’re looking at the glass half-empty or half-full; this evolvement could be called growth in some circles and in other circles, well let’s not name it.

In the broad scope of change efforts, there seems to be a new method developed daily. We could argue that it is needed in today’s world because of the ever growing complexity that is somehow being solved or attempting to be solved by big data. You would think big data would minimize complexity, but that is another blog post in itself.

Change is difficult. I always wonder why we complicate the process with untested processes. Why not use a process that works, so that your failure to change will be the result of the change not the process. Do I make sense? I learned this message in project management, and I apologize because I no longer remember where I heard this, but it went something like this, “How many good ideas are lost because of a poor plan”. I tried to Google it, but Obama Care was the first 80 million results. No kidding, try it.

The secret to having a chance in your change effort is to start with a plan that works. Lean, of course, in its most basic sense is nothing more than a change management system. Even as an avid follower of Lean, I still rely on another change formula that is well structured and has stood the test of time. It is very project-centered, well-scripted and flexible enough to be used in a variety of ways. It is John Kotter’s 8-Step Process for Change introduced in Leading Change. I wrote about how I use it in the blog post The Missing Link in Continuous Improvement SALES (Not What You Think).

As I have taken the time the last several years to spend more time with this method, I have become much more reliant upon in my everyday work. I use over and over again to assist companies internally and even more so externally in developing product platforms. I have included a shortened version of the mind map that I use and is not even a bad way of setting up a Trello board for a change effort. Let me know your thoughts?

Kotters 8 Step Change ProcessPDF Download of Mind Map

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The Customer Knowledge Map 0

This is not a Marketing Funnel

We are in love with our mapping processes from Value Stream Mapping, Process Mapping and Customer Journey Mapping. My problem with most mapping processes is that we are making a prediction about how our customer is going to act. After we make this prediction, we determine the reactionary steps that we take to satisfy this prediction. We are driving towards a decision, resolving issues and concerns. We are trying to solve the problem from the inside-out. We think we can control things and shape the outcome. I think by the time we are done we have invested so much in what we think a customer should do that well, we better make them do it!

I view knowledge mapping as a process of iterative steps that both sides are acquiring knowledge from each other. I have found The Knowledge Vee to be useful in transferring the knowledge-creation activities or thoughts to PDCA. Overlaying PDCA on the Knowledge Vee correlates to what must occur when viewing PDCA as a knowledge creating methodology (Blog Post: The Transfer of Knowledge in PDCA).

However knowledge is a continuous process where new knowledge contributes or modifies new concepts, forming new principles and theories. Or in a graphic way create the start of another Knowledge Vee or PDCA cycle. As a result, we have a “Parade of Vees” to illustrate this process. This is how we learn over time.

Parade of Knowledge Vees

What is remarkable about viewing The Knowledge Vee and PDCA is the resemblance it has to the WV Model of Continuous Improvement that I was introduced in the book Four Practical Revolutions in Management : Systems for Creating Unique Organizational Capabilityclip_image001 by Shoji Shiba and David Walden. This book is the most comprehensive book on continuous improvement that I have found. The WV Model introduces EDCA-PDCA –SDCA, an excerpt follows:

WV Model

Improvements are derived from the use of a scientific approach (and tools) and a structure for team or individual effort. A scientific approach considers a variety of possible solutions until the best—not just the most obvious—is identified factually. Structuring a team’s efforts facilitates the participation of all members, eliciting information from even the more reticent of them. Having made a first step at improvement using these methods, the methods can be repeated to get continuous improvements.

We will use the WV to explain the concepts relating to an improvement as a problem-solving process. The WV model is not a prescription for making specific improvements; it is too abstract for that. Rather, it is an aid to understanding and remembering generally used stages of quality improvement and quality maintenance. It also conveys the idea of moving systematically back and forth between abstract
thought and empirical data during the process of solving a problem. Like all models, it is an abstraction and idealization, useful for figuring out where you are and where you need to go next.

The WV model depicts the overall form of problem solving as alternation between thought (ruminating, planning, and analyzing) and experience (getting information from the real world, e.g., through interviews, experiments, or numerical measurements). The path between these two levels over time forms the shape of a W and then a V; hence, the name WV.

For instance, you sense a problem and then collect data on where it might be; choose a specific improvement activity and then collect data on exactly what is wrong; plan a solution and then collect data to be sure it works; and then standardize on the new solution.

The WV model reminds you not to skip directly from sensing problem to standardizing solution—for example, from “sales are down” to “reorganize the company.”

I am not trying to put the Knowledge Vee into the same framework as the WV Model but instead trying to show the similarities on how continuous improvement cycle relates to a knowledge building cycle. It is this method the Parade of Vees, the Parade of Improvement, the Parade of Knowledge Creation that suits the co-creation process in today’s business environment and in particular the sales and marketing process. It is not a sales funnel or a marketing funnel that are manipulative and steers the customer down a certain path. Instead, it is a learning process that both teacher and learner are willing participants to build upon each others efforts. .

Can a set of Vees replace a Funnel?

Can a set of Vees replace a Customer Journey Map?

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Can Lean lead to Better Intuition? 0

One of the most difficult things to teach people is intuition. Even when you say, “How to become more intuitive?” it seems to have this mystical sound to it. In Gary Klein’s book, The Power of Intuition: How to Use Your Gut Feelings to Make Better Decisions at Work, he discusses the ability to recognize patterns as an integral part of intuition. He says,

Once we recognize a pattern; we gain a sense of the situation. We know what cues are going to be important and need to be monitored. We know what types of goals we should be able to be accomplish. We have a sense of what to expect next. And the patterns include routines for responding — action scripts. If we see a situation as typical then we can recognize the typical ways to react. That’s how we have hunches about what is really going on, and what we should do about it.

Intuition is the way we translate our experiences into judgments and decisions. It’s the ability to make decisions by using patterns to recognize what’s going on in a situation and to recognize the typical action script with which to react. Once experienced intuitive decision makers see the pattern, any decision they have to make is obvious.

Klein shows a similar figure to outline how the action script affects the situation.

Intuition Model

As Klein points out, it is through action and developing a variety of action scripts to pull from the more intuitive, you will become. I liken it very much to a PDCA cycle in Lean. We form a hypothesis (Plan), carry out an action (Do), study (check) what we did, and make our adjustments (act). If we do this often and in small increments we could make the case that we would develop more intuitive skills.

What Klein later discussed is that the action script actually has a deeper component which we use to assess our actions through a mental simulation or painting a scenario of a process from an existing mental model. In simpler terms, we develop from past experiences a sense of what to do. I relate this process to another Lean term, catch-ball. In this version of catch-ball, it is not done with others but internally within our own mind. We envision a process, tying it to current patterns and react accordingly.

I have always thought of Lean, first and foremost, as being a knowledge building tool. Or, do I only have a hammer and everything is looking like a nail?

Become a Learning Organization through Relentless Reflection

Marketing with PDCA

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Business901 Podcast of the Year 0

Each year, I end my podcast year recognizing the podcast that Business901 listeners and I believe offered the most memorable experience.  In the 2013 podcast of the year, I interviewed Dr. Joyce Orsini, a professor of Fordham University and president of the W. Edwards Deming Institute and Kevin Cahill, the Executive Director of the Institute. Dr. Orsini has also recently authored the book, The Essential Deming: Leadership Principles from the Father of Quality and Kevin is the grandson of Dr. Deming.

Transcription and PDF Download

Deming Group

Podcast: Dr. W. Edwards Deming: Still making a difference in 2013

Transcription and PDF Download

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Monitoring & Evaluating your Outcomes 0

Are you  plugged into your customer?

When we look at continuous improvement efforts, we determine what we need to change to create a better process. We emphasize the change needed. Certainly there is a degree of “Check” in our hypothesis and experiments but seldom is that the emphasis of our work. Often, we concentrate on doing an experiment and making it work. We are accustomed having a product, a service, a website that we can monitor and acquire metrics. With a new product, we may use Lean StartupTM thinking in validating product (service)/market fit. We prototype, we try, Build-Measure-Learn or that PDCA stuff of “Check” and “Adapt”.  plugged-in

The difficulty taking product development or operational thinking to sales and marketing is that it assumes you have control of the prospect. There is a difference between customer validation versus selling. There is a difference in the perception of what waste is in operations versus selling. There is a difference in developing a service versus selling. Lean Startup, Service Design, Design Thinking and Lean (whatever noun you choose) can be difficult applying directly to sales and marketing.

In sales and marketing, and when most organizations apply Lean to sales and marketing, the tendency is to get into a mapping exercise very quickly, sometimes before developing a User Persona ,Outcome Based Mapping versus a Marketing Funnel. What I have found about most mapping exercises is that the emphasis is on ridding ourselves of waste and thereby drawing conclusions, (Mapping Expectations of Customer Behavior), about the future and how we are going to proceed with our plan of action. We develop SMART goals with defined targets. One of my favorites, we are going to increase revenue by 10% this year. That dictum is echoed every year and though a mighty goal, seldom do we have evidence in supporting exactly how we intend to accomplish it.

In Outcome-Based Mapping, we focus on outcomes, not impact. We do not look at increasing revenue by 10% that is the impact we want to make. In outcome-based thinking, we look at what actions or behaviors we need to change to accomplish our vision. This seems like a fine line or a slippery slope that I am traversing, but the secret sauce is not how we are going to do it. Nor is it any of the other secrets that Rudolph Kipling has so simply and wonderfully expressed to us, The Kipling Growth Strategy Map. It is not, in Lean terms, finding root cause of the problem. It may be not even in the Appreciative Inquiry sense of Root Cause of Success (though I lean this direction, sorry for the pun). What Outcome-Based Mapping brings to the table is the emphasis on Monitoring and Evaluation.

Why are Monitoring and Evaluation so important? In the same token, a map provides directions but it is not a roadmap. Sales is not going from point A to Point B and following this direct path. Sales and marketing compares more to air travel where there is a constant monitoring and evaluation but the plane is never on a direct path towards the destination. The elements of wind and other weather conditions and other flights determine our path. We are in control of adjusting because of a very good Check and Adjust process (Side Note: As good as airlines are in the air, you wonder why they are so poor on the ground).

In the Outcome-Based Mapping that I have done, I have found it difficult to focus organizations on the monitoring and evaluation. Once the outcome challenges are addressed, progress markets identified, strategies and actions developed, we are off to the races. If you review most Six Sigma, Lean and Marketing books, you will find the shortest chapters consistently about the monitoring and evaluation practices. You will find books about pre-event planning, getting the right people on board and the meetings or Kaizen Events to do this, but the monitoring and evaluation is one chapter in any of these and half the size of the others.

We have plenty of measurements and data. That is what Big Data all about. However, how much of this data can only be used in transactional selling processes? As Dan Pink said, To Sell Is Human. The Monitoring and Evaluations I am talking about is the change in behaviors that we address in the Outcome-Based Mapping process, The Expect to See, Like to See and Love to see Columns. It is about developing and sustaining a process.

Outcome-Based Mapping

Seldom do we address how WE understand our customers. We are always looking to have a call to action, move someone down the pipeline. However, are we addressing and adapting to reach common agreement and become a better fit with our customers. Our monitoring and evaluations should focus more on ourselves and our actions than trying to move a customer to the next stage of the pipeline. We should be consistently trying to improve the experience we offer at this stage. This is not about fixing problem. It is about going deeper and gaining a better appreciation of our customers’ needs and wants. Are we actively monitoring and evaluating how we are increasing customer knowledge? Are you  plugged in to you customer?

Book reference: Outcome Mapping: Building Learning and Reflection into Development Programs

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Do Analytics provide the Power to Predict? 1

ERIC SIEGEL, PhD, 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. His new book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die was called by Tom Peter’s, “the most readable big data book I’ve come across, By far, great vignettes and stories.“ This quote was pulled off Twitter and not from the book.

An excerpt from next weeks podcast:

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?Predictive Analytics

Eric: 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 premised 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 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.

Joe: In the sales and marketing world, we’re always furnishing forecasting for operations, can predictive analytics improve our sales forecast?

Eric: Sales forecasts are a tough thing. It’s going to depend on factors that are way outside of your knowledge. It has to do with the overall world. What’s happening in the economic climate etcetera, sort of macro scale factors. What predictive analytics is good at is ranking all the consumers relative to one another. Who is relatively more or less likely to exhibit behavior. As far as how many are going to buy, that’s prone to go up and down in ways that we’re all susceptible – we’re all going for a ride in the rollercoaster that’s known as the economy, so there’s a difference between macro level forecasting. On the other hand, as far as the core technology, there are ways in which making millions of per person or per consumer or per enterprise client if it’s B-to-B rolling all of those millions of predictions up. In B-to-B maybe more like thousands, but rolling all of them up for macro level forecasts, there are technical ways to do that in which it can help, but in general there’s no sure fire solution to the difficulty of forecasting.

Predictive Analytics book description: This rich, entertaining primer by former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of predictive analytics, showing how predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime-fighting, and boosts sales.