Category Archives: Continuous Improvement

“Selling” the Concept of Change

change is good, but never “easy!”

The point has been made, in prior posts, that “change” is not always perceived as being good, and instead tends to promote fear, uncertainty, doubt; and even resentment!

Consider that, in organizations of all types people tend to look with skepticism at new policies and procedures, and look with deep concern at new compensation plans or updated benefits programs. Similarly, in their daily quest for new customers, sales people constantly struggle to overcome buyers’ comfort with the status-quo; and people at all levels regularly cringe at the suggestion that there might be a different or better way to do their jobs!

Yet without change comes stagnation… and potentially worse things too. Current-day examples include Polaroid in instant photography, Blockbuster in video, Xerox in copiers, or the Yellow Pages! Each of these household name enterprises experienced significant declines, or worse, as competitors introduced new and better alternatives.

The cassette tape replaced the eight-track, but was then outdone by the compact disc, which was undercut by MP3 players… and the list can go on.

A Selling Mission…
If we’re to learn from these examples, then we must accept the fact that change — either in the form of innovation, continuous improvement or both — is a critical component of growth and ongoing success. Without innovation and change we run the risk of losing our competitive position or potential obsolescence.

“Whatever made you successful in the past won’t in the future,” said the late Hewlett Packard CEO Lew Platt.

But if people tend to resist change as previously noted, how might managers or business owners best go about getting the team to accept it — to buy in? How can we help people more readily embrace improvement programs, try new protocols, accept new pricing models or generally believe in the up-side of change?

Simply stated, we must sell it.

Just like the sales and marketing experts who create the “new and improved” ad copy, slogans and selling presentations, we must sell the concept of change to our staff members before trying to present or roll-out new policies, procedures, campaigns, programs or plans.

And just like any sales mission, this will require forethought and planning.

We might start by identifying how the team will benefit from a proposed change. What’s in it for them? What are the consequences of not changing? What will it cost? What opportunities might we lose?

What’s the competition doing?

The next step is to determine how to properly position a proposed change. Since we know there is a tendency toward defensiveness, it’s important to make people understand that they are not the problem. In other words, a change in policy or approach need not mean that the team has been doing things the wrong way. Rather, it means the world is changing and we must change too, lest we fall behind.

Finally, once the presentation is made and the new whatever is launched, there must be follow-up reinforcement and assessment. Has everything worked as we’d hoped? Should we modify the new plan? Are there unforeseen consequences? While we don’t want to send a message indicating we’re not resolved to the new program or approach, it is also a good idea to let everyone know we’re fair and open-minded — that at the end of the day we’re all on the same side.

Change may be unsettling, but without it our futures are at risk; and there are clearly ways to minimize the negative effects. It will require effort, planning and, like any selling mission, persistence, as behaviors and attitudes are not easily influenced.

Margaret Thatcher may have summed it up best when saying, “You may have to fight a battle more than once to win it!”

Confirmation Bias – Has it Happened to You?

CONFIRMATION BIAS AT WORK

It has happened to most of us. Has it happened to you?

That is, has there been a time when data supported a decision you knew to be the right one, but for some reason or reasons you did not get the outcome you expected?

Perhaps you find an exciting investment opportunity like the winners you have spotted before, but it yields mediocre or poor results. Or despite your experience and successful track record when judging candidates, a person you just “knew” would be a good fit turns out to be a bad hire.

With experience can come wisdom… but also confirmation bias.

Confirmation bias is the tendency to pursue and embrace information that matches our existing beliefs. We tend to seek out and enjoy people who write or say exactly what we think. We gravitate toward these sources not for information but for confirmation.

Researcher and writer Thomas Gilovich posits the “most likely reason for the excessive influence of confirmatory information is that it is easier to deal with cognitively.” It’s easier to think what we think!

Yet confirmation bias in business can be especially hazardous and costly to highly-experienced and successful individuals. These minds are adept at spotting patterns, learning from experience, scanning the horizon and connecting the dots. If that describes your talents, take a look at this classic puzzle nicely presented by the “The Upshot.”

If you attempted the puzzle, how did you do?

For those who opted out, in this puzzle participants are given a numerical pattern and are asked to determine the underlying rule. The pattern is quite simple, and participants can test their theories as often as they like before specifying the rule. Yet 77% of participants fail to identify the rule because as soon as they find a pattern that supports their theory they conclude it is the correct rule.

In other words, 77% of participants succumb to confirmation bias.

This is a common occurrence in business. When trying to solve problems or make decisions we overwhelmingly look for patterns that support our theories rather than looking for data that would clue us in that we have missed the mark. And with each piece of data that does not refute our theory, we become more confident in our belief.

This exercise shows how people tend to work at proving their theories right, instead of robustly testing the theories to prove them wrong. Once we have seen enough supporting evidence to confirm we are right, it is far more natural for us to fully embrace our premise or idea.

For instance, maybe we are tasked with determining why a certain work process is not being done well. Is the work done less well by inexperienced employees, or when the machine is overdue for maintenance, or when the materials have a certain characteristic?

We could test all three of these ideas with data. But our natural confirmation bias makes us far more likely to look for evidence that the idea we favor is correct than to look for ways it may be mistaken. So, we start testing the idea we think is most likely and as soon as we find enough evidence to support it, we risk diving into the solution and excluding the other possibilities; and we could very well be headed down a path of action that is sub-optimum for our organization.

In our next post we’ll take a closer look at examples of confirmation bias in the workplace and steps that can be taken to avoid it.

Conventional Wisdom & Utilization

As you are most likely aware, “utilization” is a measure of the actual number of units produced divided by the number possible when machines and people work at full capacity.

Conventional wisdom says that the best way to maximize profits is to encourage every department within an organization to achieve 100% utilization. Like so much of conventional wisdom, this has a ring of truth to it; and it has the added beauty of simplicity. We can evaluate and reward each department independently of one another, and if everyone is given incentives to get as close as possible to 100% utilization, then the company will surely be maximally profitable.

But this premise will fail us in the real world… a world riddled with variation.

For example, let’s say a company has three operations:
• Glass Blowing
• Filament Insertion
• Cap & Wrap

Utilization of the 3 departments is 50% in Glass Blowing, 100% in Filament Insertion, and 80% in Cap & Wrap. So where do you focus your improvement efforts? The natural conclusion is that you would focus on increasing utilization in Glass Blowing: either by increasing production (which would simply increase the inventory of bulbs waiting for insertion) or by decreasing capacity.

But if you look at the throughput of the process as a whole, you see that Filament Insertion is the bottleneck. At 100% utilization, they are unable to produce enough to keep the next operation, Cap & Wrap, fully utilized. Furthermore, Glass Blowing, despite the lousy utilization numbers, is already piling up inventories of bulbs waiting for filaments. The utilization numbers suggest that Filament Insertion is the last area needing improvement, but to improve the process flow, it must be the first area to improve.

If the world were perfectly predictable, we could reduce the capacity in Glass Blowing and Cap & Wrap to exactly match Filament Insertion to achieve 100% utilization. But if we did so in ‘Murphy’s world,’ any variation in glass blowing production — such as machine downtime, absenteeism, yield deterioration, material availability or quality issues — will not only impact Glass Blowing utilization numbers, but the bottleneck — Filament Insertion —will also be idle! Production opportunity lost at the bottleneck is lost forever. Instead of trying to optimize individual operations, identify the bottleneck and make sure there is enough capacity in the feeder operations to ensure that any disruptions do not impact the utilization of the bottleneck capacity. Instead of aiming to maximize utilization at each operation, as conventional wisdom would have us do, we must find and eliminate waste at the ‘bottleneck’ or ‘rate-limiting’ step in order to increase profitability.

Does Your Organization Have a Strategic Internal Communication Plan?

Missing Link in Communication?

In a previous post we identified five ways to enhance the success of Continuous Improvement (CI) within an organization, with “communication” being one of the keys.

Consider that, even if a team applies the CI methodology to great success but no one hears about it, the goal of making CI a cultural way of doing business will not catch on.

However, facilitating consistent and open internal communication is one of the many things in life that might be simple, but not necessarily easy.

For example, Bruce Bolger, Co-Founder of the International Center for Enterprise Engagement, shared an interesting observation recently when he said, “Most organizations put far more effort into communicating with customers than with employees.”

We’ve found Mr. Bolger’s comments to be accurate. In many cases, customer communication is the higher priority, thus making it easy to put internal communications on the back burner. In other instances, the “silo” approach to operations tends to result in haphazard internal communication.

To gain the best results from its CI as well as its Engagement effort, an organization must connect these initiatives, along with internal communications, to a strategic and systematic approach.

5 Ways to Enhance CI Success

Our previous post summarized three of the most common reasons why CI efforts fail. Today’s focus is on how to avoid those pitfalls and increase the likelihood of success.

Generally speaking, in order to ensure on-going success, an organization must make sure that its measurement systems, rewards, recognition, and communication systems support CI. But more than that, one must make sure that management behavior itself supports CI.

Our Partners in Improvement groups identified the following five best practices for making an enterprise-level CI effort more successful:

  1. Top Management Support: Senior-level leadership must visibly support CI efforts. It’s best if management meets with the teams and individuals regularly for the specific purpose of seeing how the improvement project is going and what can he or she do to support the effort and speed progress.
  2. Team Training: During our Partners discussions it was agreed that nearly everyone in the company needs some basic training. But team leaders need to be very well trained, so that they can ensure that the team follows the methodology, asks the right questions, gathers the right data, and stays on trac. It was also noted that team leaders should be very carefully chosen.
  3. Diligent Upfront Work: Project planning, even before the launch, as critical to success. This involves defining the right charter, problem statement, scope, time frame, and team.
  4. Once an enterprise-level CI plan is launched, the first principle is that nothing succeeds like success. Starting out with carefully selected projects staffed with highly qualified people is a good way to promote that success. Giving the earlier projects careful guidance and support (as referenced in bullet #1 above) is another best practice that increases the likelihood of some early wins. Making “speed to success” a priority should also be part of the plan.
  5. Communication is the next most important thing. If a team applies the CI methodology to great success but no one hears about it, the goal of making CI a cultural way of doing business will not catch on. In other words, “advertising” is important! Intranet, newsletters, presentations, story boards, discussions at staff meetings and formal recognition programs are all ways to communicate success and make sure that everyone learns from successful experiences.

3 Reasons Continuous Improvement Efforts Fail

Why Projects Fail…

During one of our Partners In Improvement forums it was noted that in approximately 80% of the cases organizations embark on a path of Continuous Improvement, they abandon the effort prematurely.

The reason? No results.

The Partners went on to the discuss “why” so many CI efforts fail to succeed, and agreed that the following three causes are among the most common:

  1. Lack of buy-in from both managers and participants derails many improvement efforts. Management support is required to free up the resources to work on improvement, without which meetings tend to get pushed out and progress slows. The slower the effort moves, the more likely it becomes that priorities will change, or new opportunities or problems arise that decrease available resources further. When projects fail to produce good results, buy-in deteriorates rapidly. Unless serious intervention counters this adverse reinforcing loop, subsequent efforts become less and less likely to succeed.
  2. Lack of data when defining a project is another common reason for failure. Without data the waste is not adequately quantified, thus increasing the likelihood of working on the wrong things and the likelihood that priorities will shift before the project is complete — leading to no results and subsequent lack of buy-in.
  3. Along similar lines, poor decisions about scope can cause stalls and frustration during implementation and can ultimately result in failure to achieve goals. If the project tackles too much at once, progress will be slow; and if the team substitutes opinions for facts/data about the problem and possible solutions in an effort to accelerate pace, they are likely to make a number of wrong turns — once again slowing progress and bringing the effort to an unsuccessful conclusion.

Fortunately there are some straightforward ways to avoid these three common pitfalls, which we will summarize in our next post.

All About Run Charts

Run Charts are simple line graphs of data plotted over time. They are used to better-understand the performance of a process, as they help people distinguish between random variation and special causes, or to track information and predict trends or patterns.

A run chart can also reveal whether a process is stable by looking for a consistent central tendency, variation and randomness of pattern.

One of the most common CI tools, a run chart is easy to interpret and does not require tedious calculations or special software to produce.

Sample Run Chart

How to create a run chart:

    1. Identify the question that the run chart will answer and obtain data that will answer the question over a specified period of time. For example, if you were looking at how long it takes to complete a task, you will make note of the time taken (in minutes) to complete it over a specified period of time.
    2. Gather data, generally collect at least 10 data points to detect meaningful patterns.
    3. Create a graph with vertical line (y axis) and a horizontal line (x axis).
    4. On the vertical line (y axis), draw the scale related to the variable you are measuring. In our example, this would include the complete range of observations measuring time-to-completion
    5. On the horizontal line (x axis), draw the time or sequence scale.
    6. Plot the data, calculate the median and include into the graph.
    7. Interpret the chart. Four simple rules can be used to distinguish between random and non-random variations:
      1. Shift – 6 consecutive points above or below the median
      2. Trend – 5+ consecutive points going up or down
      3. Too many/too few runs – too few or too many crossings of the median line
      4. Astronomical data point – a data point that is clearly different from all others (often a judgement call)

Learning & Development: 3 Key Best Practices

We are often asked about how organizations can optimize the value of their Learning & Development programs, with many C-level leaders looking for ways to increase training-related behavioral change as well as their return on investment.

A recent VitalSmarts webinar addressed this subject quite nicely, and shared several perspectives that are well-aligned with ours. For as long as the recording might be available, you can listen to the webinar here.

Alternatively, here’s a brief summary:

First and foremost, the webinar’s over-arching premise is that Learning & Development must become a strategic partner of the C-suite in order to bring about improvement and real behavioral change. In addition, there must also be a C-level commitment to consistent L&D programming. As the presenters said several times, “Training, or L&D, must be treated as a process rather than an event.”

In case anyone needed convincing, some thought-provoking statistics were then shared.

For example, only 7% of Learning & Development leaders measure the bottom-line effectiveness of their training programs. Possibly more troubling, only about 10% of all Learning & Development executives have met with the C-suite; and only a few align their training plans with the organization’s strategic plan.

In addition, only 35% of the US workforce receives any training at all! And even then, the average is three days of training per year.

Finally, without effective reinforcement and ongoing development, only 14%-15% of the information shared in training “sessions” is applied in the workplace. Instead, people most often do nothing differently or make a few changes for a while and then revert back to whatever they were doing in the past. Clearly this enormous “gap” represents significant waste, which was referred to as “learning scrap.”

Next Steps: 3 Best Practices
For those determined to improve the value and effectiveness of their Learning & Development programs, that is to increase learning transfer and reduce learning scrap, three best practices were suggested:

  1. Define the role and purpose of Learning & Development within the organization. To begin this process, the first couple of questions might be, “What would translate to a breakout year for L&D?” “This training will be a success when… (complete the sentence”?”
  2. Build the Learning & Development platform on defined and agreed-to business outcomes. It was pointed-out that most L&D managers plan their programming on what they “hope people will learn.” But the real focus should instead be on “what people will do differently as a result.”
  3. Recognize that L&D is a process, not an event. The process must include ongoing measurement and support to ensure the business outcomes are achieved. This means coaching, reinforcement, and accountability on multiple levels:
    • C-level must be committed and allocate resources for appropriate levels of learning as well as for reinforcement and ability coaching
    • L&D leaders must align with business outcomes, and move the “finish line” of their training to include an achievement phase.
    • Front line managers must provide reinforcement and support
    • People at all levels are accountable for applying what they’ve learned and related behavioral change

All About Pareto Charts

The Pareto Chart

Simply stated, a Pareto chart is a bar graph that represents problems or opportunities in order of descending magnitude or frequency.

Considered one of the seven key quality and improvement tools, it is named after Vilfredo Pareto, an Italian engineer, sociologist, economist, political scientist, and philosopher. He made several important contributions to economics, particularly in the study of income distribution. He is most well-known for his observation that 80% of the land in Italy was owned by about 20% of the population – now referenced as the “Pareto Principle” or “80/20” rule.

Pareto charts are used for a number of purposes, such as to analyze the frequency of defects in a process, to look at causes in a process, to figure out what the most significant problem in a process is, or to communicate data with others.

Here are seven simple steps for creating a Pareto chart:

  1. Decide what categories you will use to group items
  2. Decide what measurement is appropriate. Common measurements are frequency, quantity, cost and time.
  3. Decide what period of time the Pareto chart will cover: One work cycle? One full day? A week?
  4. Collect the data, recording the category each time, or assemble data that already exist.
  5. Subtotal the measurements for each category.
  6. Determine the appropriate scale for the measurements you have collected. The maximum value will be the largest subtotal from step 5. (If you will do optional steps 8 and 9 below, the maximum value will be the sum of all subtotals from step 5.) Mark the scale on the left side of the chart.
  7. Construct and label bars for each category. Place the tallest at the far left, then the next tallest to its right and so on. If there are many categories with small measurements, they can be grouped as “other.”

All About Fishbone Diagrams

An Ishikawa or fishbone diagram is a visualization tool for categorizing the potential causes of a problem in order to identify its root causes. These diagrams are particularly useful in brainstorming sessions as they help people to focus their conversation.

The technique is named after Dr. Kaoru Ishikawa, a Japanese quality control expert, who invented it to help employees avoid solutions that merely address the symptoms of a much larger problem. The approach begins by stating the problem, and then requires people to identify at least four overall causes or categories that contributed to the problem. Once categories are selected, the team must brainstorm around each cause to further break-down how or why the effect took place.

Because the design of the diagram looks much like a skeleton of a fish, it is commonly referred to as a fishbone diagram.

Common uses of the fishbone diagram range from product design and quality defect prevention to identifying potential factors causing an overall effect or process failure. Each factor or cause for imperfection is a source of variation.

After brainstorming all the possible causes for a problem, users go on to rate the potential causes according to their level of importance and diagram a hierarchy.

Simple Implementation

Fishbone diagrams are typically worked right to left, with each large “bone” of the fish branching out to include smaller bones containing more detail.

  • Create a head, which lists the problem or issue to be studied.
  • Create a backbone for the fish (straight line which leads to the head).
  • Identify at least four “causes” or categories that contribute to the problem. Major categories often include: equipment or supply factors, environmental factors, rules/policy/procedure factors, and people/staff factors. Connect these four causes with arrows to the spine. These will create the first bones of the fish.
  • Brainstorm around each “cause” to document those things that contributed to the cause. Use the 5 Whys or another questioning process such as the 4P’s (Policies, Procedures, People and Plant) to keep the conversation focused.
  • Continue breaking down each cause until the root causes have been identified.