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Problems, Questions, and Solutions

September 12, 2024

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An oft-quoted marketing truism is: “People don’t want quarter-inch drill bits. They want quarter-inch holes.” The source of this quote is unclear. The late Harvard Business School professor Clayton M. Christensen credited another HBS Professor, Theodore Levitt, as the originator. The staff at Quote Investigator (QI) reports the earliest strong match for the adage occurred in an advertisement in a Somerset, Pennsylvania newspaper in 1942. The advertisement read: “Hardware stores report that over one million men bought one-quarter inch drills in one year. Not one of those million men wanted the drills. They wanted quarter inch holes in metal or wood.” As the QI staff notes, “The message is cautionary. If a company obsessively focuses on selling drill bits and their customers start to cut holes with waterjets or lasers, then the company is in deep trouble.”

 

There is another adage that is equally true: “If you don’t know the cause, you can’t solve the problem.” The Mind Tools content team observes, “In medicine, it’s easy to understand the difference between treating the symptoms and curing the condition. A broken wrist, for example, really hurts! But painkillers will only take away the symptoms; you’ll need a different treatment to help your bones heal properly. But what do you do when you have a problem at work? Do you jump straight in and treat the symptoms, or do you stop to consider whether there’s actually a deeper problem that needs your attention? If you only fix the symptoms — what you see on the surface — the problem will almost certainly return, and need fixing over and over again.”[1]

 

Successful businesses dig deep into the questions raised by those two adages: What problems do clients need to solve? What is causing those problems? What is the solution? The Mind Tool content team notes, root cause analysis has five steps: 1) Define the problem; 2) Collect data; 3) Identify causal factors; 4) Identify root cause(s); and, 5) Implement solutions. Since answering those questions is important for company success, there has been a lot of attention given to causal artificial intelligence (AI) — a technique in artificial intelligence that builds a causal model and can thereby make inferences using causality rather than just correlation.

 

Identifying Problems

 

One would think that identifying a problem would be easy. Aren’t problems obvious? Not according to Dwayne Spradlin, Executive Director of HPS Strategy and Business Building at the Vanderbilt University Medical Center. He writes, “Most companies aren’t sufficiently rigorous in defining the problems they’re attempting to solve and articulating why those issues are important. Without that rigor, organizations miss opportunities, waste resources, and end up pursuing innovation initiatives that aren’t aligned with their strategies.”[2] Every company experiences pain points and executives try their best to address them — sometimes too quickly. Spradlin explains, “The situation is exacerbated by what Stefan Thomke and Donald Reinertsen have identified as the fallacy of ‘The sooner the project is started, the sooner it will be finished.’ … Ironically, that approach is more likely to waste time and money and reduce the odds of success than one that strives at the outset to achieve an in-depth understanding of the problem and its importance to the firm.”

 

It’s important to ask people experiencing problems to help explain them. After all, they are also going to be the people who help implement any solutions that are found. However, as the Mind Tools staff notes, once a problem is defined data collection is important. In today’s business world, you can’t talk about data without talking about how artificial intelligence can help analyze that data. AI may identify other challenges that are contributing to corporate pain points. Spradlin suggests taking a four-step approach to identifying problems. Those steps are:

 

Step 1: Establish the Need for a Solution. Spradlin writes, “The purpose of this step is to articulate the problem in the simplest terms possible: ‘We are looking for X in order to achieve Z as measured by W.’ Such a statement, akin to an elevator pitch, is a call to arms that clarifies the importance of the issue and helps secure resources to address it.”

 

Step 2: Justify the Need. Spradlin explains, “The purpose of answering the questions in this step is to explain why your organization should attempt to solve the problem.”

 

Step 3: Contextualize the Problem. According to Spradlin, “Examining past efforts to find a solution can save time and resources and generate highly innovative thinking. If the problem is industrywide, it’s crucial to understand why the market has failed to address it.”

 

Step 4: Write the Problem Statement. Spradlin writes, “Now it’s time to write a full description of the problem you’re seeking to solve and the requirements the solution must meet. The problem statement, which captures all that the organization has learned through answering the questions in the previous steps, helps establish a consensus on what a viable solution would be and what resources would be required to achieve it.”

 

Asking Questions

 

Once a problem is identified, finding the root cause(s) of the problem is crucial. Asking questions is essential to finding root causes. One well-known technique is called the “5 Whys.” Jonathan Hancock, an editor at Mind Tools, explains, “Sakichi Toyoda, the Japanese industrialist, inventor, and founder of Toyota Industries, developed the 5 Whys technique in the 1930s. It became popular in the 1970s, and Toyota still uses it to solve problems today. … You can use 5 Whys for troubleshooting, quality improvement, and problem solving, but it is most effective when used to resolve simple or moderately difficult problems.”[3] The first why question is: “Why is the problem occurring?” Hancock notes, “Search for answers that are grounded in fact: they must be accounts of things that have actually happened, not guesses at what might have happened.” Hancock continues, “For each of the answers that you generated [from the first question], ask four further ‘whys’ in succession. Each time, frame the question in response to the answer you’ve just recorded.” During this type of exercise, your team should consider questions like: What sequence of events leads to the problem? What conditions allow the problem to occur? What other problems surround the occurrence of the central problem?

 

When problems are more complex and data is available, AI can help find needed answers. But AI needs to be helped by having people ask the right questions. Kevin Kelly, founding Executive Editor of Wired magazine, insists there has never been a more important time in history to ask good questions because artificial intelligence has made getting answers cheap.[1] He explains, “Pablo Picasso brilliantly anticipated this inversion in 1964 when he told the writer William Fifield, ‘Computers are useless. They only give you answers.’ There is great opportunity and a lot of money to be made in developing new technologies to provide instant, cheap, correct answers to the world’s billions of questions every minute. … Answers are on their way to becoming a commodity. It will not be an exaggeration to say that if you want an answer in the future you will ask a machine. It will deliver a great one for free. The role of humans, at least for a while, will be to ask questions. To ask a great question will be seen as the mark of an educated person. A great question, ironically, produces not only a good answer, but also more good follow-up questions. Great question creators will be seen, properly, as the engines that generate the new industries, new brands and new possibilities that our restless species can explore. A good question is worth a million good answers. Questioning is simply more powerful than answering.”

 

The point is, before you spend a lot of money looking for a solution to a problem, try asking the best questions you can. It’s reported that Albert Einstein once said, “If I had an hour to solve a problem and my life depended on the solution, I would spend the first 55 minutes determining the proper question to ask, for once I knew the proper question, I could solve the problem in less than five minutes.”

 

Finding Solutions

 

Leadership guru Denis McLaughlin writes, “[Once you’ve asked all the right questions, it’s time to explore] as many possible solutions you can until you find the one that is the most promising and practical.”[5] One way to do that is with scenario planning, To help companies find promising solutions, Enterra Solutions® created Enterra Business WarGaming™. Business WarGaming enables organizations to leverage their data to make strategic decisions by anticipating the moves of their competitors and taking direct action to beat the competition, mitigate risk, navigate uncertainty, and maximize market opportunity. Part of Enterra Business WarGaming is the Enterra Global Insights and Decision Superiority System™ (EGIDS™) — powered by the Enterra Autonomous Decision Science™ platform — which can help business leaders rapidly explore a multitude of options and scenarios. Even after selecting a good solution, McLaughlin suggests keeping an open mind. He quotes Dr. Robert Anthony, who asserts, “If you find a good solution and become attached to it, the solution may become your next problem.” Remember that as conditions change new scenarios can always be explored for promising course corrections.

 

The ultimate goal, McLaughlin asserts, is to “make sure the solution really sticks.” He concludes, “Even though you are solving problems, this is still change and it takes more work to stick with change than it does to implement change. You will have to gain alignment for the solution by selling the benefits, handing off leadership to the team that will be using the solution every day, allowing issues to be raised and ensuring they are quickly addressed.”

 

Concluding Thoughts

 

Problem-solving may lead to more than improved business processes. It could lead to new opportunities. For example, one of the benefits of artificial intelligence is that good models can let you rapidly explore different outcomes by changing variables. This can be very useful when thinking about the future. Alan Gershenhorn, former Executive Vice President and Chief Commercial Officer for UPS, believes some of the most important questions organizations should ask begin with “what if.”[6] He notes that the rise of the internet initiated “a massive exercise in ‘What if?’ that has disrupted whole industries.” Gershenhorn insists, “If an organization asks ‘What if?’ enough — and empowers its people to act on the ‘What ifs?’ — it will discover new opportunities and new possibilities.” One of the most important things any business can do is help teach its employees how to ask good questions when confronting a problem. Amazing things could result.

 

Footnotes
[1] Mind Tools Content Team, “Root Cause Analysis,” Mind Tools,
[2] Dwayne Spradlin, “Are You Solving the Right Problem?” Harvard Business Review, September 2012.
[3] Jonathan Hancock, “5 Whys,” Mind Tools.
[4] Kevin Kelly, “With AI, Answers Are Cheap, But Questions Are The Future,” KK.org, 6 March 2017.
[5] Denis McLaughlin, “You can’t solve a problem you don’t understand.” denisgmclaughlin.com, 6 January 2015.
[6] Alan Gershenhorn, “How Asking ‘What If?’ Will Lead Us to Tomorrow’s Innovations,” Yahoo News, 2 September 2016.

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