7 Tips for Working from Home

Thanks to the Corona Virus, many people are suddenly forced to work from home.  Here are some tips to make that transition smoother.

Four Lean Six Sigma Principles That Strengthen Your Digital Transformation

Digital Transformation is a major element of strategy for many businesses. But according to studies done by Forbes and McKinsey, most digital transformations are failing. There are many reasons for the failures - some are cultural, some are related to technology, and some are resource based.  Regardless of the underlying reasons, a company with a strong Lean and/or Six Sigma program can leverage this program to improve the success of their digital transformation.

Digital Transformation Challenges

According to the Forbes and McKinsey research, the primary reasons for digital transformation failure are cultural. And just to be clear, the reason was “corporate” culture. Issues included top-down decision-making, inappropriate organizational structure alignment, lack of senior management support, and a poor understanding of digital trends and approaches. But the issues were not only cultural. There were also problems with poor process definition and control, and a lack of data and use of data management techniques. Of course, there were also challenges such as finding the right talent, acquiring the technical infrastructure – or finding the right partner to augment the infrastructure, and funding the projects to include the training of the workforce. What is clear is that digital transformation challenges are not limited by the technology. They are limited by the organizational capabilities and resources.

Lean Six Sigma Characteristics

Fortunately, Lean Six Sigma can assist to overcome these challenges. Let’s review the characteristics of Lean and Six Sigma. These methodologies, which are often combined, are problem solving approaches to drive continuous improvement. Lean emphasizes the process flow and knowledge of why the process slows down or is less than 100% effective in delivering exactly what the customer wants. The ultimate goal of Lean is to eliminate waste. Six Sigma relies on a structured problem-solving process that is grounded on data associated with the problem, process and products being studied. The problem is defined from the customer perspective with data. The problem is analyzed statistically using data. A solution is implemented, and data is again used to demonstrate it works and the situation is improved. The ultimate goal of Six Sigma is to eliminate variation and problems. In both cases, you are likely to have a trained cadre of individuals who are accustomed to using a structured process for driving customer-focused continuous improvement that relies on data. If incorporated into the digital transformation approach, these will be a tremendous advantage.

Let’s look at four principles of Lean Six Sigma that can accelerate and support your digital transformation:

Principle One: Understand Your Processes

A common approach for achieving digital transformation is to automate manual processes or even better, to replace them with technology-based systems that can perform the same functions in a fraction of the time and with a fraction of the resources. The Lean Value Stream Map and data boxes for each business process are an excellent method for documenting the existing processes to then either automate them or replace them with a system that has equivalent functionality. A problem that has often occurred when doing digital transformation is that everyone has a different idea of what the digitally transformed system should do. The Lean analysis removes that uncertainty. In addition, a Six Sigma project to find and fix problems in the existing process before it is digitally transformed will help to ensure that the new process does not start off with a fatal flaw. The process knowledge gained with Lean and Six Sigma will accelerate your ability to transform.

Principle 2: Rely on Data

Digital business systems use digital data – lots of data. When implementing a digital transformation, an organization often finds that through the use of the Internet of Things and digital portals for their customers, they are creating massive amounts of real-time data. In addition, the data mining of unstructured databases creates even more data and information. The organization can quickly reach data overload and not know how to prioritize and use the data that is generated. This creates confusion for the organization trying to implement the digital transformation.  Lean and Six Sigma establish disciplines for using data to make day-to-day business and process management decisions. The data box found at each step in a Lean Value Stream Map is a great vehicle for aggregating the data and setting warning flags if the data shows the process or product is unsatisfactory. The final phase of Six Sigma, the Control phase, encourages the establishment of statistical process control charts to track process or product performance with real-time data. The use of these disciplines prepares the organization to establish and manage the business operations with data and analytics. When this has become standard practice, it is easy to use more advanced digital tools of a digital transformation to maintain that discipline.

Principle 3: Use Problem Solving Methodology

The third way in which Lean and Six Sigma can improve a digital transformation initiative is to institutionalize a problem solving methodology and continuous improvement mindset. When undergoing a transformation, there will inevitably be some unexpected situations that have a detrimental effect on business performance and customer satisfaction. If these situations are not quickly and effectively resolved, they can derail the entire transformation as both customers and employees reject the new digital processes and products. Lean and Six Sigma provide a structured method to confidently identify the root causes of problems using numeric and statistical tools. They also provide a baseline of performance against which solutions can be evaluated to ensure they have the desired effects. While everyone knows that problems happen, when there is confidence and trust in the methods used to resolve the problem, the organization maintains the momentum that will sustain them through the transformation. Without a trusted methodology, the organization often flips and flops around, trying to decide if the issue is a problem and what should be done about it. This only creates delays and confusion along with extra costs and loss of customers. Over the years, Lean and Six Sigma have established a proven track record of problem solving and continuous improvement.

Principle 4: Establish Culture of Customer Preeminence

The fourth way in which Lean and Six Sigma will assist in a digital transformation is by keeping the organization’s focus on the customer experience and customer impact. It is very easy when implementing process and technology changes to become internally focused. After all, that is what you are changing. Yet in digital industries, the customer has increased power and the customer experience is often the most important factor in determining market share. An internal focus can lead to disastrous business performance. Both Lean and Six Sigma (when implemented correctly) will start and finish their analysis with the customer experience. Lean tracks the critical customer KPIs through the process with its data boxes. The As-Is Value Stream Map quantifies the customer experience. The To-Be Value Stream Map demonstrates the customer impact of the process change. Six Sigma starts with a problem definition that is based upon what is a customer-defined Critical to Quality (CTQ) characteristic.  And a Six Sigma project does not end until the project team can demonstrate that the CTQ is meeting customer expectations and is under control. By using every customer complaint as the starting point for the next Six Sigma project, the customer experience is maintained as the most significant aspect of the business operations throughout the digital transformation.

Summary

Your organization may have been using Lean and Six Sigma for years. In fact, you may have felt that you got all the benefit you could from these approaches and you then moved onto other business initiatives. But don’t abandon these when undergoing digital transformation. The principles of these methods are excellent enablers of your digital transformation and are essential elements for resolving the speed bumps you are sure to encounter. A cadre of trained and experienced Lean Six Sigma Black Belts and Green Belts are a critical element of your organization’s successful digital transformation.

IoT and Product Development

People have been developing products for thousands of years.  The general process is well understood:  1) Identify a need, 2) Imagine a product concept that could address that need, 3) Create a prototype of the product, 4) Test it and refine it until it works satisfactorily, 5) Produce, market, and sell it to your customers.  There are numerous product development methodologies that are tailored to specific companies or industries, but they follow this same pattern.  The Internet of Things (IoT) will transform each of those steps.

Let me define what I mean by IoT.  I am using it in its broad context.  The IoT is a network of devices, sensors, actuators, computers, displays, and any other physical device you can imagine that can communicate on a network.  That means it either creates, distributes, displays or reacts to data on the network.  And the network could be hard-wired or wireless.

So, let’s consider what the IoT will mean to product development.

Identifying a Need

The IoT will reduce the guesswork when it comes to identifying a customer need.  First, many current products have little or no IoT presence, but they could.  So, an obvious new product development is to add IoT capability to existing products.  Then with the IoT information, look for defects, inefficiencies and other problems with existing products and processes.  These are the next obvious candidates for new products.

Imagine a Product Concept

The characteristics of the concept will be affected by the IoT.  The developers will need to consider the use of the product and all the ways that meaningful data could be generated and used, both within the product and remotely.  The communication capability of the product can dramatically expand its ability to access data and coordinate its actions with other nearby products and systems.  The product will no longer be an isolated and autonomous system. Now the concept is an integrated system with significantly enhanced capabilities.

Create a Prototype

Now the IoT moves from not just the product and product idea, but into the actual product development process.  With IoT technology, the developers can connect to 3D printers to create prototype parts in a fraction of the time that was required formerly.  In addition, since much of the product functionality is likely to be based upon the software applications and both onboard and remote processing, changes to functionality can be prototyped with changes to a few lines of code.  This will also shorten the time it takes to create a prototype. 

Many of us who have been through multiple development projects know that you seldom get everything right with the first prototype.  So you build a second or third until you achieve the performance that is desired.  This often creates delays, overruns, and eventually cutting corners elsewhere in the project.  But again, with the IoT and the 3D printing and nightly downloads of new software, many prototypes can be quickly created and the lessons from one can be incorporated into the next and so on.  Implementing the development best practice of iterative design and fast failure.

Refine and Test It

Now let’s consider how the IoT will impact the detailed product design definition, process development and verification testing processes.  Both the new product IoT capability and the IoT capabilities of the test equipment and manufacturing process equipment will be used.  The product IoT will provide data throughout testing to establish a performance database.  And with an extensive use of sensors in the product and the communication capability of IoT, this will be rich source of data for “tweaking” performance and fully characterizing the product characteristics.  Add to this, the IoT capability of the test equipment being used and the designers and developers will have immediate access to extensive data that will both uncover hidden design flaws and then demonstrate acceptable performance. 

But the even bigger benefit is likely to be based upon the IoT capability of the manufacturing process equipment – both in-house and at suppliers.  Manufacturing process development is often costly.  This is especially true do to the ongoing changes when the doing concurrent engineering – that is development the product and process concurrently.  Yet this concurrent approach is used because an even greater cost to the business is the delay in product launch that results from doing the manufacturing process development sequentially after the product development is finished.  The IoT simplifies the change process with manufacturing equipment and at suppliers by electronically communicating design changes.  In addition, the IoT provides real-time process data so manufacturing process issues – both in-house and at suppliers – are identified quickly, reducing the time needed to qualify the production process.  

Produce, Market, and Sell

The IoT will also improve our ability to product and market the new product.  Let’s talk about production first.  The IoT that is in the production equipment will enable the application of predictive maintenance algorithms that will reduce unplanned down-time and smooth production flow.  In addition, the IoT sensors on the manufacturing equipment will enable a higher degree of real-time statistical process control that will decrease defects and improve overall product quality.  And to the extent that a product is customized for each customer order, the IoT capability of the product will allow the manufacturing process to install the unique software and configuration just prior to packaging and shipping the product.  This will also serve to smooth out manufacturing flow and reduce scrap and rework.

The IoT can also enhance the marketing of the new product.  Of course, one obvious element of marketing is to promote the IoT capability of the product and the advantages for the customer.  In addition, through IoT interfaces, the marketing and sales personnel will know product availability.  Further, they can take a customer’s unique order information and communicate it right to operations in order to have a custom configured product.  Finally, the sales person, or even the customer, can track the production and delivery status of the product to know when it is coming and to be prepared for its arrival. 

IoT is not just a buzzword or fad.  It is transforming companies and industries.  It will also transform the product development process.  

The Value in Non-Value Added Activities

With the wide-spread acceptance of Lean Manufacturing and Lean Enterprise principles, the term “non-value added activities” has come into the business lexicon.  These are the activities that an organization performs that do not directly contribute to the generation of customer value.  Within the context of manufacturing, these activities are categorized as one of these types of waste.

• Over-production, ahead of demand – wasted effort.
• Waiting for the next process step – wasted time.
• Unnecessary transport of product or goods – wasted effort.
• Over-processing of product due to poor process design – wasted effort.
• Inventories greater than necessary – wasted cost.
• Unnecessary movement of employees (looking for tools, paperwork, help, etc.) – wasted effort.
• Producing defective parts – wasted time, cost, and effort.

The Lean Value Stream Map categorized all of the activities in a business process into either value-added steps or non-value-added steps.  Even the value-added steps are further analysed and the time spent conducting that step is divided into value-added time and non-value-added time.

Implementing Lean has led to improvements in productivity and cycle time.  This has often transformed an operation; improving both customer satisfaction and profitability.  But sometimes, implementing Lean has not resulted in dramatic improvements for the business. 

Of course there are the Lean implementation failures, which seem to occur at least 50% of the time.  These are often due to poor management commitment and understanding, inadequate training, and the difficulty of culture change.  But I would like to discuss a different type of failure.  This is the failure to see improved customer satisfaction and the increase in sales and profitability after a “successful” Lean implementation.

This condition occurs when the company misunderstands the elements of value from a customer perspective.  Yes, there is value in the efficacy of the product.  The customer wants it to work to the expected level of fidelity and be reliable and durable enough to continue working through the expected life.  The Lean manufacturing definition of value-added activities will cover these elements of value. 

But many customers also want other aspects of value that are not directly tied to product performance.  These include brand affinity, ease of doing business, and a sense of personal engagement with the company. 

Let me give you an example.  Many companies have “Leaned” their customer service and help desk functions.  Now when a customer calls the company with a question or complaint, they are routed into an endless series of “push this number” and “select this number” until they finally are placed on a lengthy hold, waiting to talk to a live body.  Often that live body can’t answer any questions, but can only read from a script.  So while the company thinks it has “Leaned” customer service by eliminating non-value-added effort, the customer feels abandoned, belittled and unwanted.  Activities the company categorized as non-value-added because they did not support the manufacture of product, were activities that were very important to the customer.  The result is a customer who experiences a reduction in value, not an improvement in service.

An internal, product-centric view of “value” can lead a company to remove activities and functions that are important to overall customer satisfaction and that build a strong relationship with the customer.  A Lean initiative needs to start with a true understanding of what the customer values.  This should not be determined by the design engineers, manufacturing managers, or even the Lean consultants.  This needs to be determined through voice of the customer analysis. 

In many industries today, the new competitive advantage is creating and establishing a personal relationship between the company and the customer.  “Leaning” these customer interaction processes can destroy competitive advantage.  Strong positive relationships take time and numerous positive interactions.  Lean processes that minimize and eliminate interactions are eliminating value-added activities – even though the activities may have nothing to do with the product.

So let me propose, as an adjunct to the list of activities used in Lean analysis to define a waste, a list of activities that define value-add.

• Activities that directly answer specific customer questions.
• Activities that provide special privileges and offers to existing customers.
• Activities that measure customer engagement and satisfaction with the company and its products and services.
• Activities in the company’s operations that create or add to the functionality of products or services.
• Activities that build customer confidence in the company’s brands, products and services.

I’m not suggesting that a company should abandon Lean or ignore the attributes of waste.  I am suggesting that a company should embrace the attributes of value.  Prepare a value stream map for the attributes of value and ensure that these value-adding processes are operating smoothly.

Practical Idealism

Those two words are normally considered opposites.  I’ve heard for years that “idealists” aren’t “practical.”   “Practical” is grounded in reality.  “Idealism” is wishful thinking that can’t be achieved.  But by the same token, “idealists” challenge us to improve and go beyond our current performance, whereas “practical” approaches are stuck in the current paradigm.   If we could put them together, practical idealism could lead to an innovative approach that is transformational. 

This isn’t just hypothetical.  There is a real-life example right now in the sports world of what happens when practical idealism is implemented.  Have you heard of the University of Connecticut (UCONN) women’s basketball team?  Here are a few facts about them:

• They just won their fourth straight national title – no women’s basketball team has ever done that.
• They have won 75 straight games – all by double figures.
• Their average margin of victory this season (including the NCAA tournament) was 39 points.
• The program has a 100% graduation rate and over 80% of the players have a GPA of 3.0 or higher.
• Their coach has won more national titles (11) than any other coach in college basketball – men or women.

Now this type of dominance does not mean that the sport of women’s college basketball is in decline or immature. The caliber of the competition and the quality of the players has been improving for years. There are tremendous women athletes in this sport. And between all of the other teams that play women’s college basketball, there is fierce competition. In my opinion, women’s college basketball exemplifies better team play than men’s college basketball – which is dominated by individual play. It is a tough, competitive, athletic sport. 

Yet UCONN performs at a level that is far above everyone else.  Why is that? Practical idealism. 

UCONN’s coach, Geno Auriemma, sets idealistic goals for the team and each individual.  Their goal as a team is not to be competitive, but rather to be dominant.  And their measure of performance is not only against the other team, it is against their previous performance.  The team is always striving to get even better.  But Auriemma also focuses on personal goals for each of his players.  That is why they have a 100% graduation rate and such high GPAs.  Any coach who lists these yearly goals for his team is an idealist:

1. Go undefeated.
2. Win the national championship.
3. Beat opponents by an average of 40 points.
4. Team members have a 3.0 or higher GPA.     

What makes UCONN different is that they have established a practical approach for achieving these idealistic goals.  The UCONN women’s basketball team works as hard as any college team in the nation.  Their practices are tough and exhausting.  They work on basic skills and on teamwork.  They are constantly seeking to improve.  Every turnover, every missed shot, every lost rebound from the previous game is scrutinized to understand what happened and prevent that from occurring again.   While the Auriemma shows genuine care and concern for each player, he also challenges and pushes them to be their best.  He refuses to accept complacency or mediocrity from any player in any aspect of her game.

 

Granted, UCONN is able to recruit from among the best high school women basketball players. But there is lots of talent to go around in women’s college basketball today. UCONN is only able to recruit 12 players for scholarships. They have talented team members, but so do many other programs. And UCONN does not limit their schedule to playing “powder puff” teams. In the final rankings of women’s college basketball for the 2015-2016 season, UCONN was number one and they played six of the remaining nine (beating all of them by double digits).    

Early this year, Auriemma quoted Julius Caesar as the team was preparing for a game, “Vini, Vidi, Vici” – we came, we saw, we conquered.  The attributes of dominance that were the hallmark of the Roman Legions 2,000 years ago were used to inspire his team this year.  “We came.”  They will go anywhere and play anybody.  In fact, they try to schedule the best teams in the nation.  “We saw.”  They study their opponents and prepare for them.  Some of the teams are bigger, some are great shooters, some play tenacious defense.   Doesn’t matter.  UCONN negates their strength, often by besting them at their own game.   “We conquered.”  UCONN teams hustle.  They are always working hard.  They dominate many aspect of the game.  And even when the “second string” enters the game – often early in the second half – they continue to dominate. 

So what are the lessons of “practical idealism” we can learn from UCONN?  

• First, it is OK to be idealistic. Set big goals – seemingly impossible goals. 
• Second, recruit talented people. Find the best people available and embed them into your team.
• Third, work hard at the basics. There should be excellence in everything you do. Don’t accept mediocrity on any level.
• Fourth, study your competition to understand their strengths and weaknesses. Then work to be as good or better than they are at their strengths and exploit their weaknesses.
• Fifth, continuously improve. Set the standard of performance and then exceed your own standard.
• Sixth, coach and encourage your people fulfill their personal goals and to be successful in all walks of life.

The UCONN story is inspiring.  Oh, and it is also excellent basketball.

VUCA Product Development

In most companies, developing new products is a critical component of strategy.  Many companies are finding this to be more and more difficult as their environment increases in VUCA.  The acronym VUCA stands for Volatility, Uncertainty, Complexity, and Ambiguity.  This acronym was created and gained recognition in the strategic planning circles of the US military during the past 15 years.  A body of knowledge is being developed around leadership in the VUCA world, with numerous articles and books published in the past few years.

Bob Johansen has proposed a leadership response to the VUCA environment which he titles VUCA Prime.  According to Johansen, volatility is countered by vision, uncertainty is countered by understanding, complexity is countered by clarity, and ambiguity is countered by agility. Let’s take a look at each of the elements of VUCA and VUCA Prime as they apply to product development.

Volatility

Volatile is defined as changeable – and often with an explosive or fleeting connotation.  Volatile situations are full of surprises.  Vision is the recommended leadership response.  Developing and articulating a clear vision will assist an organization through the volatility be reducing the disorientation that occurs when a volatile situation unfolds.  Even though there is rapid changes happening all around, the vision and direction stay constant; providing a basis for decision-making and action.

Product development involving innovative new technology, or a marketplace that is fast developing with new customers and competitors, can often be volatile.  The vision that is needed for the product development team is a clear product line strategy.  The strategy that has identified target markets and the characteristics of new products will guide the product development team through the technology, design, and business trade-offs that must be made when volatility strikes.  Without a clear product line strategy, the product development team often stalls as they start chasing options and waiting for decisions from stakeholders.

Uncertainty

Uncertain is defined as the state of being unpredictable and indeterminate.  There are numerous significant unknowns in the business situation.  The environment is novel to the point that past experience cannot be used as the measure for what should be done now.   However, in an uncertain environment, there are facts that could be discovered.   The recommended response to uncertainty is understanding.  This requires investigation, fact-finding, and analysis.  Rather than responding in a dogmatic manner using outdated principles, the response is to slow down and learn what is actually happening. 

Within the product development environment for innovative new products; there is normally uncertainty with respect to customer needs, product performance, and market response.  There are two approaches being used to create understanding within product development methodologies.  One approach is to do extensive upfront analysis using tools such as the Quality Function Deployment.  The other approach is to create a series of rapid prototypes of a minimally viable product to get “real-world” experience and feedback.  I have used both approaches and there are pros and cons for each.  The key takeaway for this discussion is that there is work that must be done to gain understanding.  And that work needs to be built into the development project plan.

Complexity

Complex is defined as intricate, often complicated, interconnected parts, processes, or organizations.  With complexity comes options and opportunities.  Some of these options and opportunities are very favourable and some are disastrous.  Navigating through the complexity requires numerous decisions.  The recommended response to complexity is clarity.  Clarity exposes the decision points and the options.  Clarity will also often provide a framework for understanding the implications of decisions.  Clarity exposes pathways through the complexity.

Product development of new innovative products will often involve complexity on several levels.  If the product is a system, there will be multiple components, possibly hardware and software, that must all work together.  And research shows that system integration and test is one of the most likely areas of a product development project to overrun both time and money.  In addition, there is often organizational complexity.  Marketing is developing requirements, engineering is creating designs, quality is establishing test and inspection methodologies, operations is setting up manufacturing and logistics processes and facilities, IT is bringing new databases online and possibly new systems for support.  All of these functions must work together and a change in one cascades through all the rest.  Establishing a stage-gate product development methodology with defined practices and decisions points will go a long way to creating clarity in product development.

Ambiguity

Ambiguous is defined as obscure, indistinct, and with numerous possible interpretations.  Unlike our definition for uncertain where facts are available but are not yet known; in an ambiguous environment there is normally no “right” or “wrong” answer.  Instead the answer is always, “it depends.”  The recommended response to ambiguity is agility.  This means that as the fluid situation continues to change, the decisions are revised and updated frequently.   Nothing is ever final; it is just the “current state,” with the expectation that change will soon be required.

In the global marketplace, industries are separating into those that are ambiguous and those that are rigid.  The highly regulated industries have a tendency to be very rigid and those that are not regulated are often ambiguous.  But regardless of the industry, the product development environment is ambiguous.  It follows that an ambiguous end market will create an ambiguous product development process.  As the target for product definition and performance is constantly changing, whatever product is developed will immediately need an upgrade or replacement product.   But even in rigid end markets, development is ambiguous.  The regulatory environment is often different in different countries or areas, and these regulations are frequently changing.  In addition, the regulatory agencies interpretations of regulations are often inconsistent.   Regardless of the industry, a rapid pulsing process is needed to determine the current state of the market and industry environment.  This must be coupled with a robust change management process for product development.   Finally, the product development metrics must be focused on business success or failure of the product, not on time and budget targets for the project.

If you are involved in product development today, you are probably experiencing VUCA.  You may reminisce about the “good old days” when things were calm and simple.  But don’t expect those days to return.  Instead embrace an approach to have vision, understanding, clarity and agility.

Learning Lessons from Lessons Learned

They go by many names including: Lessons Learned Sessions, After Action Reviews, Post-mortems, Post Project Evaluation, Learn and Grow, and Project Retrospective.  These sessions are the time when the project leader and project team look back over the project, or at least a portion of it, and attempt to learn from their experiences.  It is a practice that is called for in many project management methodologies, yet often neglected.  

When I ask people why they haven’t done one, I get many different reasons.  “Everyone is busy on other projects now.” ‘Why bother, we won’t change anything.” “Most of the team at the end of the project is different from the beginning team.  They didn’t participate in many of the decisions.”   In fact, often these are backwards looking, blame-focused sessions.  When that occurs, it is an indicator that the organization and project teams don’t understand how to use these sessions.

I would like to discuss five elements of effective reviews.  These are the purpose, the timing, the participants, the questions asked, and the follow-up.

Purpose

The purpose of these sessions is continuous improvement.  These are not meant to be final project reports or a history of what happened.  They are intended to improve the planning and execution of the current and future projects.  One of the implications of this purpose is that anything can be discussed.  There are no “sacred cows.”  Don’t avoid subjects because it many hurt someone’s feelings or it makes them uncomfortable.  The goal is to improve performance.  If we ignore some aspect of performance, it will not improve. 

Timing

A mistake often made when doing project reviews is that the review occurs long after the project is over and the review then considers the entire project.  A much better approach is to do a quick review after each phase or milestone with the project team so that they can immediately take action to improve the remainder of the project.  This type of review doesn’t need to be an all-day offsite meeting with formal facilitators and reports.  It can be a pizza lunch with post-it notes on a white board.

Let’s consider for a moment one of the best models of how to conduct one of these sessions, and that is the US Army’s After Action Review format.  First, note that it is not an “After War Review” with Monday morning quarterbacks looking back over years of history and trying to find the big lessons of the war.  It is a review that is immediately conducted following an action or event.  Everyone from the team is still there.  The events are fresh in everyone’s mind, and because it is focused on what the team just did; many of the recommendations are immediately actionable by the team.

Participants

This gets us to the participants in the review.  I recommend that it is the team, the whole team, and nothing but the team.  Well, you may want to have someone from the PMO or another project leader to help take notes and facilitate.  This is especially true if there were some leadership problems and the team might be uncomfortable discussing this in a meeting being run by the project leader.  There is no need for senior management in this meeting.  Their presence is likely to repress the conversation.  It is appropriate for the project leader to provide a summary of the results to senior management and the PMO.  But the discussion is likely to be much more open and honest if the meeting is just the team members.

Questions

The agenda for the meeting is very simple.  What is going right and what is going wrong.  The team may want to vent a little if there are problems or celebrate if things are going well.  Let them release a little emotion, but then focus them on these questions:

• What is going well that we want to continue?
• What is not going well that we need to change?
• What should we do differently as part of the change?
• What recommendations do you want to make to the organization to pass onto other teams?

Follow-up

Well, as you can see from the questions, we anticipate that we will want to make changes.  It is possible that the team may say that everything is going great and nothing should change.  When that is the case, the team should be making a recommendation to the organization so other teams can copy their result.  However, most of the time there will be some changes.  By conducting the review with the current project team, they can also decide what they will change – starting tomorrow.  I like to get very specific when I discuss the changes.  I go around the room and ask each person what they personally will be doing differently.  Doing this in the room among the team members will improve personal accountability among the team members.

Turning these reviews into forward looking change events instead of backward looking blame events will make them productive.  They really will drive continuous improvement.  

Kaizen, Lean, Six Sigma - What's the Difference?

Kaizen, Lean, and Six Sigma are all business improvement approaches.  They can be thought of as three different tools in the business leader’s toolbox.  It is important to understand the focus and purpose of each.  Using the wrong tool will not fix the problem, and it may make things worse.  As an illustration, if I have three tools: a hammer, a screwdriver, and a wrench; I must use the correct tool to accomplish my goal.  I must use a hammer to drive a nail; a screwdriver will not do the job.  However, if I need to remove the cover of a light fixture from the ceiling, I will want to use a screwdriver.

Kazien

Kaizen can be summarized as, “Fix the next problem.”  Kaizen is a team-based problem solving technique.  Kaizen puts focus on a problem to understand it and solve it – then on to the next for continuous improvement.  A Kaizen project is normally requires only a few days to complete.  The Kaizen team is usually dedicated to fixing the problem during those few days. 

The Kaizen team employs data collection techniques and uses basic problem solving tools to understand the root cause(s).  They then create a solution (within the boundaries and constraints given them by management – such as budget or time) and an implementation plan for the solution.  Often the Kaizen team is empowered by management to immediately implement their solution. 

Kaizen works very well with problems that have a singular root cause, or to improve new and emerging business processes that have “low hanging fruit.”  Kaizen is not as effective at solving complex system problems or transforming an entire business operation. 

Lean

Lean can be summarized as, “Eliminate waste from the flow.” Lean is a process analysis problem solving technique.  Lean focuses on mapping a business process flow and identifying all areas of waste – time waste, cost waste, and wasted activity. 

A Lean analysis for a process normally takes one week to one month, (depending upon the nature of the process).  Once the analysis is completed and solution options identified, the implementation of change can take several days to several months, depending upon whether facility or system changes are needed.  Lean will consider all aspects of how a process is performed, from the process controls, operator training, facilities and systems used, and the process measurements.  Often the team conducting the Lean project is the same individuals with day-to-day management responsibility for the process.  They will lead the change implementation. 

Lean works very well for improving business processes that have a continuous or regular flow.  Lean is not as effective for processes that are only occasionally performed or for problems that have suddenly emerged.

Six Sigma

Six Sigma can be summarized as, “Remove variation.”  Six Sigma is a process control problem solving technique.  Six Sigma focuses on measuring the outputs from a process, aligning those outputs with customer expectations, and then controlling the process so that the outputs stay aligned.  Six Sigma uses a structured five phase project management approach: Define, Measure, Analyze, Improve, and Control.  Six Sigma establishes a permanent management control system to ensure the process maintains a minimal amount of variation in process output. 

A six sigma analysis will normally start with several weeks of data collection, once the real-time data collection system is established.  The data will undergo statistical analysis to understand all sources of variation so that they can be either eliminated or controlled.  This often takes weeks or months to complete the analysis and testing of hypotheses.  The new control system is then implemented and used for day-to-day management of the process by process operators and managers.  Because of the extensive use of statistical analysis, often a Six Sigma team will include several people with process knowledge and several people who are Six Sigma Black Belts or Green Belts.  The solution will often require a change in management control processes and procedures and usually requires changes or upgrades to various business systems. 

Six Sigma works very well with complex business systems that have known performance goals.  Six Sigma is not as effective with processes that have changing requirements.  Also, Six Sigma is a cultural change for management and employees since all process control decisions are data-driven rather than using intuition.  Management no longer is providing direct process supervision, but is acting more as a coach, facilitator, and strategic decision maker.   Operators are now responsible for making the day-to-day decisions required to achieve desired process performance.  This culture change can take a long time.

Comparison

Kaizen	Lean	Six Sigma
Cross functional team	Process management team	Team with process knowledge and statistical expertise
2 -5 days	2 weeks to 2 months	3 – 6 months
Find and fix a problem with clear root cause(s)	Improve process flow – time, cost, and quality	Control process output to consistently meet customer expectation
Typical Tools: data collection, brainstorming, root cause analysis, basic quality tools	Typical tools: value stream mapping, data collection, process analysis tools, Kanban, value-added time	Typical tools: data collection, process capability analysis, statistical hypotheses testing, Gage R&R, DOE, control charts
Limitation: Has difficulty addressing complex problem	Limitation: Requires a consistently used stable process	Limitation: requires expert knowledge and culture change

Synergy

These approaches can be used simultaneously and in concert with each other.  A few example scenarios are described below.  These are for illustration only; your business conditions may not precisely fit these:

• A new operation is having many problems at startup.  I would start with Kaizen projects to solve any “Crisis” problems and begin to establish some predictable performance.  Once the big problems are resolved, I would follow with implementing Lean to remove waste and inefficiency from the process.  This will improve cycle time, cost and quality.  I would then implement Six Sigma to establish a control system to manage the process.
• An existing operation is undergoing a major upgrade for new products or systems.  I would start with Lean.  Map the old and new processes to understand and communicate the changes.  As the new process is introduced, I would assign Kaizen teams to resolve unexpected problems that arise.  Once the new process is stable, I would implement Six Sigma to establish a control system to manage the process.
• An existing stable process does not meet industry benchmarks for cost or quality.  I would start with Six Sigma to ensure the process is aligned on customer value and then determine the issues within the process.  If issues are due to singular root causes, I would use Kaizen teams to solve those problems.  If the issues are due to systemic problems with organizational processes, I would use Lean to understand and improve the process.  (If issues are due to complex business and system interactions that are inherently unstable, I would not use either of these techniques but would rely on a Design of Experiments analysis.)

Business conditions should be used to determine an approach that is best suited for achieving your goals and objectives. 

Innovation Across Industries

Innovation occurring in one industry can migrate across industries.  In fact an innovation in one industry that is considered an incremental change can be disruptive when it migrates.

This month is National Pizza Month in North America.  In honor of that, let’s examine innovation across industries by considering the case of the pizza printer. 

3-D Printing

The concept of 3-dimensional printing has been around for years.  I first worked with a stereolithography (SLA) printer in the mid 1990s.  This equipment would “print” a 3-dimensional object out of plastic resin.  This was done by creating literally thousands of “slices” of the object that were so thin that they were essentially a 2-dimensional slice through the product.  The SLA equipment then “printed” each slice, stacked them on top of each other and bonded them together. The result was the 3-dimensional object.  

To do this the SLA printer would analyse a 3-D CAD model of an object and create “slices” of the object.  Most SLA equipment then used a photo-sensitive resin and a UV laser to “print” each slice.  The resin would be in a big bath and the laser would print or sketch the pattern for that slice of the product.  The resin would react to the laser by solidifying in the shape that was sketched by the laser.  Once that layer cured, the object was lowered in the bath by a few millimeters and the next layer was printed on top of the first.  The object essentially grew downward into the resin bath.

Over the years other approaches to 3-D printing were developed.  Innovation led to new materials being used that had different material properties of strength, flexibility, and appearance.  New processes were developed that would work with even more materials than just photo-sensitive resins.  The size of the equipment changed allowing bigger objects or very tiny objects with tight tolerances.  Also, the price of the equipment came down as technical efficiencies and user/operator interfaces were improved. 

Today, almost all R&D centers have 3-D printing capability and some manufacturing operations are using these in their standard processes.  Changes and improvement in the technology and equipment are seen as incremental innovation, not breakthrough or disruptive innovation. 

3-D Food Printing

So now let’s migrate the technology to another industry – that of food preparation.  In the R&D and manufacturing worlds, there are 3-D printers using all kinds of material.  What if those materials were pizza dough, pizza sauce and cheese?  You would have a 3-D printer that could print a pizza ready to put into the oven. 

And the added capability of the printer technology is that you could print the pizza in whatever shape you want.  So you could print pizza that were the shape of your team’s logo for a Saturday afternoon party with friends to watch the big game.  Or you could print a pizza that looked like your kid’s favorite TV or movie character for their birthday party.  The options are literally endless.

You might think I am talking science fiction but the technology is here today.  NASA has sponsored 3-D food printing development for astronauts.

In fact, we don’t have to stop at pizza.  There are many other foods that could be printed.  The food printer demonstrated at the Consumer Electronics Show in 2015 and shown in this video could also make cookies and candies.  Why not one to make pasta, pastries, breakfast cereals, chips and crackers?  




If it is processed food, a 3-D food printer can be created to process it into fantastic shapes.  The other benefit of the 3-D food printer is that it can print-on-demand.  Whenever you want it, just give it the design and in a few minutes you have a pizza ready for the oven.  In fact, a logical innovation extension will be for an oven attachment so that the pizza is printed and baked by the same machine.

Innovation Migration

So how do we look for other opportunities for innovation migration?  A key technique is to rephrase what you are trying to do into very generic terms and then investigate how that type of activity is done in other industries. Let’s look at the food printer as an example.

When making a pizza you start with the pizza dough, add sauce, add cheese, add toppings and that bake it in a pizza oven.  A more generic way of saying that is that a pizza is several different materials that are layered on top of each other and then processed.

The second key is to be scanning and reviewing the products, processes, and materials in other industries to find similarities.  You want to intentionally place yourself “outside the box” of your industry to find the similarities and assess whether they can be adapted to your industry and business context.

So in our pizza example, when you look across industries, you quickly find that the 3-D printers today will often have several different materials that are applied in layers to create a basic object and that object is then further processed in order to make it stable and fit for use.  The similarities in function are obvious; it is just changing the materials and the nature of the processing. 

When the product or process migrates from one industry to another, it will often bring new advantages and capabilities with it.  In the case of pizza printing these are ability to print-on-demand and printing different shapes.

Try this exercise in your industry – describe what you do as generically as possible and then look in companion industries for products and processes that do that same generic function.  You may have a disruptive innovation on your hands in no time at all.

A Definition of Customer Value?

There is a business axiom, “You can’t manage what you can’t measure.”  Managers need to know if their decisions are having the desired effect.  Otherwise, they are flying blind.  This means they need data, and the closer that data can be to real-time, the better.  Otherwise, they are making business decisions based upon hopes and fears.

A concept gaining traction is to manage and maximize Customer Value within the offered products and services.  By providing a high level of Customer Value, customers will be more successful.  This increased success by customers will then lead to loyal customers and increased customer demand.   Everyone wins. This concept makes good business sense, but it has a weakness.  That is the measure of Customer Value.    

The weakness starts with the precise definition of Customer Value.  It remains murky.  There are numerous perspectives on the definition of Customer Value.  I have been conducting a non-scientific survey on the definition of Customer Value with executives and managers from a number of companies in the USA (that means I have talked with them about this over lunch). I have found that the practical definition for the measure of Customer Value is often based upon the individual’s functional discipline.  For instance:

Finance: Uses cost and price as surrogates for value – the ration of the money a customer pays for the product or service divided by the cost to create and deliver the product or service is the measure of Customer Value. But this is an internal measure that does not consider how the customer uses the product.  The actual value to the customer is unknown.

Operations: Focuses on internal efficiency measures – especially those associated with manufacturing cycle time and quality.  They measure Customer Value use measures such as on-time delivery and P_pk or an equivalent quality measure.  But these are also internal measures that do not consider how the customer uses the product.  Again the actual value to the customer is unknown.   

Research & Development: Sees value in features and technology that are “presumed” to be of benefit to the customer.  Essentially “more” of whatever features is being considered is presumed to have value.  They measure Customer Value in terms of product benchmark comparisons. But often these measures are not correlated with customer applications that increase customer success.  Some of these measures may be irrelevant, or even worse, may detract from actual Customer Value.

Marketing: Focuses on brand awareness and brand affinity. They see products as commodities and the Customer Value is based upon the confidence that the customer has in the product brand.  Brand positioning in the minds of the customers is the primary driver of value.  But this approach ignores the internal cost and effort required to develop and sustain the image associated with the brand.  And to the customer, the brand is a promise.  If the actual product or service does not live up to the promise, the value of the brand is lost and may actually become a strong negative value in the mind of the customer.     

Sales: Focuses on customer behavior in the market and infers Customer Value based upon that behavior.  Measures include market price, market share, customer retention and customer conversion.  But these are lagging measures.  This information reflects the result of the customer’s actions.  Managers can’t proactively manage from these measures; they can only manage reactively.   

Each function’s perspective is limited and out of balance, yet each function has something important to contribute to a comprehensive solution. For something to be valuable, it must provide some type of benefit.   The Operations and Research and Development perspectives definitely provide some insight on the potential benefits of the product or service.  And if something is valuable, there is presumed to be some price or valuation of that value.  Finance and Sales are attempting to capture that perspective.  However, Marketing rightly acknowledges that until a real customer is aware of the benefits and the price and has confidence in both, an expression of Customer Value is presumptuous. 

If all of those can be combined into a comprehensive set of measures, then the managers can begin to make the trade-offs between maximizing the Customer Value and minimizing internal costs.  They can proactively manage the business to select a specific Customer Value level that is aligned with their product line strategy and then becomes a business target.  The managers will then optimize the business processes and systems to deliver that value in an efficient and effective manner.

An obvious challenge when creating the comprehensive set of measures is that many of these attributes are customer attributes, not company attributes.  It is highly unlikely that a customer will be able to set up a measurement system inside their customer’s operations or that the customers will voluntarily agree to setup the measurement systems and provide data to their suppliers. A company must then infer these measures based upon a customer’s actions, or non-actions.  To do this, a company must focus on customer relationship management and apply metrics to customer actions and activities.

Measure Customer Relationship

So the first step in measuring customer value is to measure the customer relationship.  What is the frequency of interaction?  What types of interactions are occurring? What levels in each organization are involved in these interactions?  Is there a pattern of interactions that represent those customers who place a high Customer Value on our products and services?  Is there a pattern of interactions that represent those customers who place a low Customer Value on our products and services? Is this interaction data available real-time, or near real-time? What is the customer saying about this relationship on social media and industry forums?  Are we capturing all of the interactions between the company and customer, at all levels and with all interaction media?

There are some efforts to begin to understand customer interactions and measure them.  The Customer Experience movement is a step in the right direction.  The proliferation of “big data” applications makes this collection of information much more practical.  One organization that I am familiar with, Religence, has proposed an interaction management framework that I think holds lots of promise.  This is an area and technology that is rapidly maturing.

The addition of this interaction metric with the existing internal cost, price, and efficiency metrics should provide the comprehensive set of measures needed to proactively manage Customer Value.