In our complex and rapidly changing world, the ability to effectively analyze problems is crucial for professionals across nearly every domain. Problem analysis forms the foundation for identifying, dissecting, and understanding complex challenges and is essential for developing effective solutions. It is therefore of great importance to map problems at the highest level of complexity before research or policy is formulated. Such higher-level complexity analysis indeed helps to address the underlying causes of the problem, rather than just treating its superficial symptoms. Too often in practice, we focus on the immediately visible causes instead of addressing the underlying causes of the problem. That is why it is essential to develop an approach that effectively addresses the core of the problem and not just its consequences.

But how can you map problems at the highest level of complexity, and why is this actually necessary? How do you proceed after the problems have been mapped? And suppose it is not possible to identify these complex problems; what are the consequences? What are the points of attention and tips for mapping and solving such complex issues? These questions will be answered in this blog and the blogs that will follow.

Chapter 1.

Part 1

Problem analysis at the highest level of complexity: tips, tools, and considerations

What exactly is problem analysis?

Problem analysis is a systematic approach to identifying, understanding, and solving complex problems. It entails a thorough examination of the nature, causes, consequences, and potential solutions of a problem. At the highest level of complexity in problem analysis, multiple perspectives, variables, and interrelations are considered to penetrate the core of the problem (Heerkens & van Winden, 2020).

Two examples: poverty & customer dissatisfaction

Let us briefly explore two examples to elucidate why problem analysis at the highest level of complexity is necessary.

The first example involves poverty. Poverty can result from various factors, such as unstable government or corruption, outdated structures and techniques that no longer fit market developments, or a country’s economic inability to repay debts, thus experiencing economic instability. In other words, if you want to combat poverty, you must not only focus on assisting poor people, although that naturally helps, but you must also address the core problem to have a long-term effect. And, it is precisely these core problems that can best be mapped out with thorough problem analysis, to then address and solve them effectively, one by one.

The second example involves customer dissatisfaction. Often, when dealing with customer dissatisfaction, a company’s sales department is addressed, upon which various solutions are devised to improve the contact between sales and customers. However, the cause of customer dissatisfaction can also lie in mismanagement, employee dissatisfaction, or insufficient training of sales staff, aspects that are often overlooked. Insufficient training and employee dissatisfaction can lead to problems, such as inadequate product knowledge, incorrect information to customers, and inconsistent service. This results in frustration and decreased satisfaction among customers but also among employees. By recognizing this, organizations can implement targeted solutions, such as better training and support for employees, to improve overall customer satisfaction.

Naturally, one can think of numerous other examples where it becomes evident that it is crucial to address the core of the problem rather than only its consequences.

In this blog series, we will discuss several methods and techniques that can help you map out the problem at the highest level of complexity. Remember, this is an essential first step for researchers and policymakers to, for example, effectively address and solve very complex (social) problems.

Benefits of problem analysis at the highest level of complexity

Before exploring deeper into the methods that can assist you in mapping out the problem at the highest level of complexity, it is important to understand why you should do this.

Firstly, it is logical that problem analysis at the highest level of complexity enables researchers and policymakers to address the core of the problem rather than its consequences. This can lead to more effective solutions that also produce visible effects in the long term. Thus, hopefully, the problem will be addressed and solved in a long-lasting and sustainable manner, hopefully for good.

A good problem analysis will also help to sharpen the rationale and context of your research, for example, and engage the reader in understanding why research is initially necessary. Furthermore, many costs are saved because the core problems are addressed. This enhances the efficiency of a solution. Additionally, it assists a researcher or policymaker in gaining a better grasp of relevant theories and insights because then you know exactly what the core of the problem is and can search for solutions in a targeted manner.

Moreover, a good problem analysis will aid you in conducting more targeted, improved interviews and research. Remember, in any research, it is always essential to ensure validity, reliability, and reproducibility. Validity means that you are measuring what you intend to measure, and by bringing the core of the problem at the highest level of complexity into view, you can thus improve the validity of your research and your research questions and thereby also assure a reliable result. For more information on creating higher validity, reliability, and reproducibility, and other important criteria that are essential in research, read this blog.

When we explore the literature, it becomes evident that there are additional benefits to conducting a problem analysis at the highest level of complexity. These advantages are listed below.

Strategic Benefits:

• Enhancing Strategic Insight: A thorough problem analysis enables organizations to gain deeper insights into their strategic positioning, objectives, and market environment. This allows them to make more informed decisions and adapt to changing circumstances (Van der Pligt, 2019).
• Improved Risk Management: A systematic problem analysis assists organizations in identifying and understanding potential risks and threats, enabling them to take proactive measures to mitigate or manage these risks (Katsov, 2020).
• Proactive Planning and Foresight: Problem analysis equips organizations to anticipate future challenges and opportunities and prepare for them, resulting in proactive planning and strategic decision-making (Hofmann et al., 2017).
• Competitive Advantage Through Deep Understanding: A thorough analysis of problems allows organizations to develop a deep understanding of their market, competitors, and customers, thereby achieving strategic advantages over their competitors (Porter, 1985).
• Identification of New Opportunities: Analyzing problems enables organizations to discover potential new market opportunities and innovative solutions that can lead to growth and a competitive advantage (Christensen, 2003).

Operational Efficiency:

• Streamlining Processes: A thorough problem analysis can help identify inefficiencies and bottlenecks in operational processes. This enables organizations to streamline and optimize these processes for smoother operations (Liker, 2004).
• Cost Savings Through Optimization: By analyzing problems and improving processes, organizations can achieve cost savings through more efficient resource use, waste reduction, and optimization of operational expenses (Goldratt & Cox, 2004).
• Increased Productivity: An effective problem analysis can lead to improved operational processes and workflows, resulting in increased employee productivity and more efficient use of time and resources (Syverson, 2011).
• More Efficient Resource Allocation: Gaining insight into operational challenges and bottlenecks allows organizations to allocate their resources more effectively to the most critical areas, thereby improving overall efficiency and performance (Coelli et al., 2005).
• Reduced Waste and Simplification: Problem analysis enables organizations to identify and reduce waste by simplifying processes, thus enhancing operational efficiency and lowering costs (Ohno, 1988).

Innovation and Growth

• Better Problem Solving: A thorough problem analysis lays the foundation for effective problem-solving by enabling organizations to understand the underlying causes of problems and to develop targeted solutions (Kahneman, 2011).
• Stimulating Creative Thinking: Problem analysis can stimulate creative thinking by identifying challenges and generating innovative solutions that go beyond conventional approaches (Amabile, 1996).
• Development of New Products/Services: By analyzing problems, organizations can discover new needs and opportunities, which can lead to the development of innovative products and services that stimulate growth (Schilling, 2017).
• Process Improvements: A thorough analysis of problems can assist organizations in identifying inefficiencies and improving processes, thus increasing their operational efficiency and creating room for growth (Imai, 1986).
• Access to New Markets: Problem analysis can help organizations identify new market opportunities and develop strategies to enter new markets, thereby expanding their customer base and seizing growth opportunities (Kim & Mauborgne, 2005).
• Improving Customer Satisfaction: By addressing problems that affect customer satisfaction, organizations can improve their products and services, resulting in higher customer satisfaction and loyalty (Heskett et al., 1994).
• Increased Employee Engagement: Involving employees in problem analysis can increase their engagement by giving them the opportunity to contribute to identifying and solving challenges, leading to improved performance and innovation (Harter et al., 2002).
• Building a Learning Organization: Problem analysis encourages a culture of continuous learning and improvement, where organizations gather valuable insights from problems and use them to constantly enhance their processes and performance (Senge, 1990).
• Sustainable Growth and Competitiveness: By effectively addressing problems and developing innovative solutions, organizations can achieve sustainable growth and strengthen their competitiveness by adapting to changing market conditions (Porter, 1985).
• Future-Proofing: A thorough problem analysis enables organizations to prepare for future challenges and opportunities, making them more resilient and better equipped to adapt to changing circumstances (Hamel & Prahalad, 1994).

Sustainable Development Goals:

The global community has established Sustainable Development Goals, abbreviated as SDGs, as an ambitious and comprehensive agenda to eradicate poverty, tackle inequality, and protect the planet by 2030. Although these goals are commendable, they remain an immense challenge due to their complexity and interconnectedness. A thorough problem analysis at the highest level of complexity is therefore crucial to realize the SDGs. Below are the key benefits of such an in-depth analysis:

• Holistic approach to challenges: The SDGs are closely intertwined and cannot be addressed in isolation (Griggs et al., 2017). A problem analysis at the highest complexity level enables policymakers to understand the interconnections between the various goals and develop a holistic approach (Nilsson et al., 2016). This prevents partial solutions that may have unintended negative effects on other goals.
• Identifying leverage effects: By embracing the complexity of the SDGs, leverage effects can be identified wherein efforts in one area have positive consequences for multiple goals (Weitz et al., 2018). A thorough analysis can expose such catalysts, leading to a more efficient allocation of resources and a greater impact (Obersteiner et al., 2016).
• Anticipating challenges and conflicts: The SDGs may conflict with each other or with other policy goals in certain contexts (Pradhan et al., 2017). A deep problem analysis can identify potential tensions and bottlenecks early on, allowing policymakers to anticipate and take mitigating measures (Bennich et al., 2020).
• Inclusion of diverse perspectives: Complex problems require input from different disciplines and stakeholders (Messerli et al., 2019). A comprehensive problem analysis offers the opportunity to integrate diverse perspectives and local knowledge, leading to a richer understanding of the challenges and more widely supported solutions (Hajer et al., 2015).
• Adapting to changing circumstances: The implementation of the SDGs is not a static process but will be influenced by changing socio-economic, political, and environmental conditions (Biermann et al., 2017). An ongoing, in-depth problem analysis enables policymakers to adjust in a timely manner and adapt their approach to new developments (Boas et al., 2016).
• Building capacity and knowledge: Analyzing problems at the highest level of complexity will result in the development of specific skills and expertise (Caiado et al., 2018). Ultimately, this process contributes to the development of analytical capabilities and the accumulation of knowledge, which benefits the effectiveness of policy interventions in the long term  (Bennich et al., 2020).

Conclusion

To summarize, problem analysis at the highest level of complexity is a potent tool that empowers organizations to tackle deep-seated challenges and achieve sustainable success. By embracing complexity and conducting thorough analyses, companies can gain strategic insights, enhance operational efficiency, and foster innovation. This approach enables continuous improvement, the development of competitive advantages, and readiness for future challenges in an ever-evolving world.

For the Sustainable Development Goals (SDGs), problem analysis serves as a complex yet indispensable tool. By examining interconnections, identifying leverage points, and anticipating potential conflicts, policymakers can formulate more effective strategies. A comprehensive analysis at the highest complexity level is vital for achieving the SDGs by 2030.

Mapping Complexity: a step-by-step guide and key considerations

Now, the crucial question arises: How do you map problems at the highest complexity level? What is the best step-by-step approach? Which key considerations should you keep in mind, and what actions should you avoid? These questions will be addressed in this blog post (click here), along with subsequent entries.

For any inquiries or further information, please do not hesitate to reach out to me.

Read part 2…

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