Tag Archives: problem solving

Problem Solving, Process Improvement, Project Management

Tools for Solving Problems

puzzle

Persistent problems cannot be solved by repeatedly using the same knowledge and insights. Or, as Albert Einstein phrased it, we can’t solve the problems at the same level of thinking with which we created them!

Few decisions have a greater impact on the likelihood of success of an improvement project than the definition of the problem.

Stephen Covey says that the way we see the problem is the
problem.

Dr. Don Wetmore of the Productivity Institute says that a problem well defined is at least 50% solved!

However you choose to look at it, the way we define and communicate the problem the team is expected to solve will greatly influence the speed and efficiency with which a team will complete its work, the
degree of satisfaction between the team and the project sponsor, and the efficacy with which an organization prioritizes and sequences the problems to devote resources to.

So the first key step to problem solving is to define the problem. Four key best practices for doing so are:

  1. Write it down and share it
  2. Quantify the waste it is causing
  3. Be specific about the metric you are using to size the problem
  4. Avoid judgments or opinions about root causes

Once a problem is well defined, it is often best to use classic problem-solving tools to examine current reality from a variety of different angles. This will most often require the use of multiple tools to reveal more advanced insights and solutions, as in many cases no one tool will provide all the answers. These tools can include:

  • Pareto Charts to explore ideas about possible causes
  • Process Mapping to spot and quantify the waste and trace it to the primary cause
  • Cause and Effect Diagramming to stretch beyond initial ideas about possible root causes
  • Histograms to provide new insights into the dynamics of process performance
  • Run Charts to understand current process performance and distinguish between random variation and special causes
  • Scatter Diagrams to clarify the importance of possible causal factors on results measurements
  • Affinity Diagrams to find breakthrough ideas and natural relationships among the data
  • Priority Matrices to consider alternatives and identify the right things to work on
  • Interrelationship Digraphs to visually demonstrate the relationship among factors—causal factors (drivers) vs. symptoms
Continuous Improvement, Problem Solving

Tough Problems v. Tough-to-Implement Solutions

Continuing with our previous post’s theme of problem solving, business leaders often find themselves with these kinds of difficult decisions: significant problems or opportunities versus proposed solutions that cost too much, take too long to implement, or carry adverse unintended consequences of their own.

Here are some examples:

  • A large chemical company had opportunities to increase sales by $60 million if they could expand production capacity, but the capital investments would cost $20-$30 million and would take 18 months to implement.
  • A data processing company received too many complaints about quality but the market and margins would not bear additional costs for ‘QC.’
  • The manufacturing company needed to cut raw material costs without weakening its suppliers.
  • Breakthrough technology that cost too much to be commercially viable.
  •  Centralizing the Purchasing function had reduced responsiveness and efficiency but when it was decentralized, it lacked sufficient controls and access to expertise.

In most problem solving situations, the first idea is the barrier to the second idea. Steve Jobs hit the nail on the head, observing, “When you first start off trying to solve a problem, the first solutions you come up with are very complex, and most people stop there.”

In every example cited above, the people working to solve the problem had stopped at the first idea. Once an idea was developed the attention shifted toward evaluating the return on investment and lining up support rather than improving or replacing the idea with something better, faster, less expensive, or more effective. They stopped too soon!

The best idea is almost always hidden somewhere behind the first idea. In order to arrive at the best idea, you have to keep going. As Steve Jobs observed, “… if you keep going, and live with the problem and peel more layers of the onion off, you can often arrive at some very elegant and simple solutions.”

Continuous Improvement, Problem Solving, Process Improvement

What’s the Problem?

Problem

Few decisions have a greater impact on the likelihood of success of an improvement project than the definition of the problem.

Stephen Covey says that the way we see the problem is the problem.

Albert Einstein warns that we cannot solve problems at the same level of thinking with which we created them.

The way we define and communicate the problem the team is expected to solve will greatly influence the speed and efficiency with which a team will complete its work, the degree of satisfaction between the team and the project sponsor, and the efficacy with which an organization prioritizes and sequences the problems to devote resources to.

Consider these different approaches to defining the same problematic situation:

  • Order fulfillment is too slow and is costing us a lot of business.
  • Our lost sale rate has increased from an average of 125 per month over the previous six quarters to 190 per month this quarter.
  • Our Order-to-Delivery timeline has increased to 60 days due to a bottleneck in packaging.
  • Profits are down.
  • Sales has missed their target for the past three months.
  • Packaging is too slow due to old equipment.
  • Order-to-Delivery time from the Mid-western plant in Q3 increased by 15 days over the same quarter prior year, and was cited as the cause of 42 lost sales in Q3 impacting revenue by $270,000 in the quarter.

Some of these are statements of fact, while others are judgments. Some are very broad, and others are very specific. They may ALL be valid observations about the same situation, yet the problem-solving efforts they would guide would differ greatly in urgency, efficiency, and efficacy.

Developing a good problem statement at the start will help you define and lead an improvement project that most efficiently arrives at better results.

Four Practices That Lead to Better Results
A good problem statement is not rocket-science, but simply requires some solid pre-work, thoughtful consideration & discussion, and the restraint to avoid speculating before the analysis. If you follow the four basic guidelines for problem definition, you will greatly improve the chances the right problem will get solved for good.

  1. Write It Down. If the problem is not written, shared, and discussed, all participants will feel comfortable that everyone is on the same page about the problem they are trying to solve. Such will not be the case, and the blissful ignorance about their different expectations will eventually give way to a combination of bewilderment, conflict, frustration, disappointment, and a great deal of inefficiency.

    Organizations can avoid the problem-solving frustration and rework by surfacing right up front any different views of the problem they are trying to solve. The best way to surface and discuss any differences is to write it down and discuss it with all participants, to ensure it is well understood and agreed to. In addition to getting everyone on the same page, only a written problem-statement can be tested against the next three qualities necessary to effective problem-solving teams.
  2. Include a Quantification of the Waste the Problem is Causing. Yes, this means you have done some pre-work, because no problem statement is as effective as it should be if it does not indicate why we care.

    Quantifying the waste makes certain that the organization does not invest scarce resources on something that will not have a significant impact. Every organization has more opportunities for improvement than capacity to execute on the improvements.

    Quantifying the waste also helps elicit the urgency and support that the project merits. A problem statement that is “…costing the organization $18,000 each week in excess charges” will receive more urgency than a problem “…costing the organization $800 a week.” And problems for which no discernable and measurable impact can be found probably should not receive much urgency at all. Quantifying the waste in the problem statement helps an organization make sure that they are working on first things first.

    The statement of impact best fits at the end of the problem statement but identifying and quantifying the waste should come at the start of the problem definition process. If we cannot reasonably measure the impact a problem is having on an organization, we cannot reasonably prioritize the effort.
  3. Be specific about the metric you are using to size the problem. Malcom Forbes once observed that “It’s so much easier to suggest solutions when you don’t know too much about the problem.” The rub is that you will have a hard time determining if your solutions are effective.

    To avoid this pitfall, your problem statement should incorporate the measurement you expect to move the needle on, the current baseline for that metric, and both the time and the place that your baseline measurement was taken.
    • The metric: If order-to-delivery timeframe is our problem, the problem statement should be a factual statement of order-to-delivery times. Maybe order-to-delivery times have deteriorated or maybe they have always led to lost orders. Either way, a recent measurement of order-to-delivery times must be part of the problem statement if this is the problem you intend to solve.

      For example: “order-to-delivery times have grown to 6 weeks and was cited as the reason for 25 lost orders last month.” A description such as “too long” is too general, but teams may be tempted to substitute this judgment instead of a metric because a recent measurement is hard to get.

      Bear in mind that if the problem is too hard to measure up front, chances are it will be too hard to measure later on when the team needs to evaluate the efficacy of the solution. Even if the team can gather measurements later, they will have no baseline with which to compare the new results.
    • Timeframe: When have you observed the problem? Is your metric from last week, last month, last quarter, or last year?
    • Scope: Where are you seeing the problem? Does the metric describe what is happening at one plant or all plants? Is it one product, a product family, or all products? By making the problem statement factual and specific about what observable phenomenon we saw when and where, we create for the team a clear and effective baseline against which to measure improvements.
  4. Omit Judgments and Opinions about Underlying Causes. Maslow observes that “If the only tool you have is a hammer, you tend to see every problem as a nail.” We all have biases, and when we make assumptions about the underlying cause, we bias the process to overlook other possible causes.

    In theory, this could be a time-saver — if you hit upon the correct root cause. However, in our experience this rarely happens. Making assumptions about the causes almost always makes a problem more difficult to solve instead of easier to solve. This is because if one or more important underlying causes are overlooked by the bias introduced in the problem-statement, the problem will not be solved before the project goes through quite a lot of rework.

    Most people have some sort of bias or hunch, slight or strong, about possible underlying causes of most problems and they will consider these first.

    For example, some people easily incline toward thinking that the technology is not what it could or should be and theorize that this is the cause of most of the problems they encounter. Others are quick to suspect that the incentives are misaligned. And still others may speculate first that processes are not sufficiently defined and adhered to. These hunches are developed based on experience and people with diverse experience and biases tend to serve a project well.

    However, no matter how confident in the theory about the root cause, inclusion of an assumption about the cause or the solution in the problem statement is more likely to impede results than accelerate them. A hunch makes an excellent servant (in the problem analysis phase of the project) but a poor master. Leave any comment about possible underlying causes out of the problem statement.

    If you follow these four guidelines, your project will have a much better chance of arriving at, implementing, and validating an effective solution that produces lasting results.
confirmation bias, Continuous Improvement

Look for the “No!”

look for the no

As the saying goes, “With experience comes wisdom… and confirmation bias!”

As you may know, confirmation bias is the tendency to pursue and embrace information that matches our existing beliefs. Human nature encourages us to seek out and enjoy people who write or say exactly what we think, and we often gravitate toward these sources not for information but for confirmation.

Naturally, this can be dangerous when engaged in CI or other problem solving efforts!

When we find ourselves feeling overly-good about an opinion or conclusion, a better course of action, and one that aligns with ‘critical thinking’ best practices, is to make every effort to “prove ourselves wrong!”

In other words, consider alternatives. Or, as philosopher and journalist Emile Chartier Alain put it, “Nothing is more dangerous than an idea when it’s the only one you have.”

Here are five suggestions for avoiding the “confirmation bias” pitfall:

  1. Don’t Believe Everything You’re Told; the 1st step is to consider more than one point of view – “prove yourself wrong!”
  2. Don’t Believe Everything You Think
  3. Ask Questions
  4. Research Deeper
  5. Evaluate Your Work

Innovation

Faster innovation!

close the barn door
SLOW INNOVATION = NO INNOVATION!

Recent posts have focused on innovation and problem solving, which requires knowledge, critical thinking, and, in many cases, creative thinking.

One interesting example of how we might apply creativity when solving problem is called the Theory of Inventive Problem-Solving.

The concept dates back to the 1950’s and Russian innovator G.S. Altshuller’s belief that innovation processes could be improved and accelerated by studying patterns in problems and solutions. Altlshuller and his team analyzed millions of patents to identify patterns, and they deduced from this data a small number of principles that can be applied to make the creative process more predictably effective. The result, TRIZ, is an acronym for Russian words that translate as “the theory of inventive problem solving.”

The fundamental premise is that there is nothing new so, whatever your challenge, if you understand it both in its specific and general form and you do the research, you will find that someone somewhere has already solved it. Then if you focus your creativity on adapting the general solution to your particular challenge, you will achieve your breakthrough faster and more predictably.

It’s About Time!
TRIZ accelerates breakthroughs by guiding the human intellect along paths most likely to be fruitful. And speed of innovation is essential because most people and groups abandon a “stretch” goal fairly quickly and settle for a compromise; and “slow innovation = no innovation.”

The developers and practitioners of TRIZ observe that problems often emerge from contradictions, and that most solutions aim at compromising with the contradictions instead of overcoming them. Here are some of the contradictions that may appear in the workplace:

  • It takes time to do something the right way, but the thing must be done quickly
  • A task requires precision, but it must be done without precise tools
  • A product must have dozens of features, but it must be simple to use.

Each problem is a specific example of a general contradiction. TRIZ research has paired every general contradiction with a small number of general solutions. So a practitioner of TRIZ can focus their effort and intellect on translating the specific problem into one of several dozen general problems. The next step is to look up in the TRIZ resources the general solutions that have been applied to that general problem in the past. Then one focuses one’s creativity on identifying and testing specific solutions that could apply the general solution to the problem at hand.

imagineering, Leadership

Are Questions the Answer to Making Breakthrough Solutions?

questions

An article published in 2020 as part of the Drucker Forum’s “shape the debate” series raised some interesting perspectives about leadership and making breakthrough improvements.

The simple premise shared by consultant and author John Hagel is that “questions” are the answer.

“The most effective leaders of the future will be those who have the most powerful and inspiring questions,” Hagel said. “…and who are willing to acknowledge they don’t have the answers, and that they need and want help in finding the answers. It’s in sharp contrast to the conventional view of leaders as the ones who have the answers to all the questions.”

This view aligns nicely with ours, as we’ve found that posing questions of and involving the people closest to the work is the shortest path to the largest gains.

After all, where do new ideas that lead to lasting solutions come from?

They come from people… that is, if those people are asked.

Here are three different approaches to identifying new ideas and solutions along with some of the questions we might ask the right people while studying the related work:

  1. Classic brainstorming. When studying the current situation and causes does not lead directly to identifying lasting solutions, you need to elicit a number of different ideas from your team by asking questions that stimulate creativity. How can we increase our productivity by 10 percent? What are the most common obstacles causing the process to stall? What is the most difficult aspect…”

    Before you launch into your brainstorming, make sure you have convened a diverse group of people with some knowledge or interest in the problem at hand. Keep in mind that it is always easier for people to “think outside the box” when they come from outside the box.

    The classic rules for brainstorming are:
    • No criticism of ideas—no idea is too crazy
    • Go for quantity of ideas and worry about quality later
    • Brainstorm individually first and then read the ideas out round robin style it is okay to pass
    • Build on positive aspects of other ideas to create new ideas
    • Capture the ideas on flip charts or on large Post-Its that everyone can see and read
  2. Tools such as the Six Thinking Hats and Heuristic Discovery, which systematically change one’s perspective to open-up new possibilities for solving problems.
    • First, state the problem in terms of an opportunity or goal. For example, a keyboard refurbishing operation needed to increase throughput, so they would ask: “How to we double our daily throughput of refurbished keyboards?”
    • Second, create a picture or map of the problem as part of the system, labeling each of the significant components.
    • Third, describe the impact of each component as it impacts the goal. Use a question format. For example:
      • What tools might we use to increase throughput?
      • How can we make sure that people’s skills are sufficient to double the throughput?
      • How can we make sure that people’s speed is sufficient to double the throughput?
      • How can we ensure the workspace layout enhances throughput?
    • Fourth, Prioritize these and generate ideas for solutions to the component problems that are most likely to impact
  3. Imagineering perfection, which helps you surface possibilities to leap past incremental improvements…
    • “What would this process look like if everything were right?”
    • What would it mean if the input we need always arrives on time and exactly the way we need and want it—no delays, no expediting, no rework?
    • What if every step of the work process were to go exactly as it should with no waste, no rework?
    • What if our work produced exactly what the customer needs, on time, exactly as they require it all the time? What would this look like?
    • What exactly does the customer need for perfection?
Continuous Improvement, Conventional Wisdom

Another Pitfall Akin to Confirmation Bias

Thinking outside-of-the box?

Our previous post shared some thoughts on the pitfall of “confirmation bias,” which is the tendency to pursue and embrace information that matches our existing beliefs.

A somewhat related concept that can, surprisingly, be equally as dangerous is “conventional wisdom,” which has been defined as “the body of ideas or explanations generally accepted as true by the public or by experts in a field.” It is frequently referenced as “inside-the-box” thinking, as opposed to taking an approach that challenges convention (i.e., “outside-the-box” thinking).

But contrary to popular belief (or, to ‘conventional wisdom’ – ha ha!), this seemingly safe practice can be both an asset and a liability!

On the plus-side, conventional wisdom speeds up consensus and increases our confidence in our decision making, leaving us to focus our attention on challenges for which there is no conventional wisdom to guide us. And conventional wisdom has much truth within it — having been developed over decades of observations.

For example, conventional wisdom holds that specialization is good. A person can get very fast and reliable doing the same thing the same way again and again, a-la Henry Ford’s production line.

However, while specialization can increase both efficiency and quality when demand is consistent at optimum levels, it can quickly become counterproductive, costly, and even wasteful if the demand for work is uncertain.

For example, a commercial bakery could purchase one large capacity mixer that could produce 100,000 loaves for far less cost per loaf than two smaller mixers. The large mixer produces large batch sizes; that’s how it gets its great efficiencies. But if the market is looking for variety, none of which is ordered in bulk, the large mixer results in the worst of both worlds: you either produce large batch sizes and have a lot of scrap if the demand does not materialize in time, or you waste the purchased capacity by preparing batch sizes more closely tied to current demand for the product variety. Either way, you can never really produce enough variety for the market, because the equipment produces only one variety at a time.

So like many things in life, when we find ourselves needing to research the marketplace, assess root causes, or study work processes, we must beware of both confirmation bias and its kin conventional wisdom, lest we make sub-optimum (or worse!) choices that feel good at the start but come back to bite us in the end.