Before Your Organization Invests in a Solution, How Well Does It Understand the Problem It’s Supposed to Solve?

Imagine it’s Monday morning at a mid-sized company. Customer complaints have been climbing for months and senior leaders are concerned about inconsistent service. During an afternoon leadership meeting, after someone points out that employees aren’t following customer service processes consistently, another one chimes in with: “We need training.”

By Wednesday, the Learning & Development team is tasked with creating a refresher customer service training course. All department Managers—who must ensure everyone completes it—prepare and send out the necessary announcements. Someone suggests adding completion rates to a project management dashboard—because you know, someone needs to track all of this. Within a few weeks of its launch, hundreds of people complete the training, but three months later customer complaints are about the same.

What if employees already knew what to do? What if the process itself was cumbersome? What if technology made things unnecessarily difficult? What if staffing levels made following the prescribed process nearly impossible during peak periods? What if managers are rewarding speed while the organization insists on telling a story about prioritizing quality? What if you dared to start asking different questions? Suddenly, the problem looks very different.

Organizations spend enormous amounts of money on solutions before doing enough work to understand what problems actually needs solving, what conditions are causing them, what people need in order to be able to do things differently, and what must change in the overarching system for the solution to work.

Ignore this scenario at your own risk. This isn’t just about an inefficient use of resources. This is precisely the type of scenario that can weaken organizational capability. By the way, the story at the top of this article isn’t fiction. It’s based on true events. I’m not saying this incident alone was the downfall of a major enterprise, but it indeed was demonstrative of all the sorts of problems, combined—and the flawed thinking—that were the many straws that well, you know how that saying goes.

When a Solution Becomes the Starting Point

Performance problems rarely arrive neatly labeled with their causes. Leaders see declining sales, customer complaints, poor quality, missed deadlines, low adoption, disengagement, turnover, or inconsistent performance. Those are observable outcomes. They tell us something is happening. They do not necessarily tell us why. Yet the leap from observation to solution can happen remarkably quickly.

It’s all too common that, when employees aren’t performing consistently, someone assumes that provide training is going to fix that. Or, if communication is poor, then another communication platform must be the answer. Productivity is low, so of course they should be automated. And when people aren’t using the new technology that just cost a million dollars, pile on more training and communication. Please make this stop! Each of these solutions may eventually prove appropriate, however, the real problem lies in making decisions based on assumptions before sufficient analysis has occurred.

Experts in Human Performance Technology make this distinction explicitly clear regrading needs analysis. Organizations should first define the gap, collect evidence about its source, examine both people and systemic causes, consider the environment in which performance occurs, and only then should you attempt to identify possible solutions.

Training becomes appropriate when the analysis identifies knowledge, skill, or behavior gaps that training can reasonably address. Other causes may require changes to policy, technology, work environments, organizational structures, standard operating procedures, or even leadership. In other words, a request for a solution is not evidence that the organization has correctly diagnosed the problem.

The System May Be Part of the Problem

This distinction becomes especially important when technology is involved. While it’s seemingly straightforward for organizations to invest in technology based on what a tool is capable of doing, the harder question is whether that capability can be realized within the work people actually perform.

A recent study by Mertens and colleagues (2026) examined a technology implementation in an Australian hospital that initially appeared useful and easy to use. Adoption nevertheless declined over time. Interviews revealed problems involving existing workload, workflow disruption, cognitive demands, and complex interdependencies among tasks, technologies, and coworkers.

The researchers concluded that understanding technology adoption requires looking beyond the technology itself to the organizational context in which people must integrate it into their work. That finding matters far beyond hospitals. A technically sound solution can fail when it enters a poorly understood system. This is why due diligence needs to ask more than, “Will this solution work?” Leaders also need to ask, “Will it work here, for this problem, within this system, under these conditions?”

Implementation Cannot Repair a Bad Diagnosis

Unfortunately, Change Management too often enters the picture after a major decision is already made and technology has been purchased. This is backward. Restructuring needs approval after proper diagnosis, not beforehand. When a major change or new processes are designed haphazardly as an afterthought, it’s absurd to expect that people would adopt it with ease or that the adoption will be sustained.

Organizational readiness research suggests that implementation occurs within a much larger set of conditions. A systematic review of readiness assessments found that successful change adoption depends on the degree to which adequate attention is given to the implementation climate, communication networks, organizational structures, culture, leadership engagement, available resources, access to information, and compatibility between the intervention and the environment (Miake-Lye et al., 2020). These aren’t merely factors to manage after selecting a solution. Some of them should influence whether the proposed solution makes sense in the first place.

The same principle applies to learning. Training cannot compensate for conflicting incentives, poorly designed work, inadequate resources, confusing processes, ineffective tools, or managers who reinforce behaviors that contradict what people were taught. Your organization can create an excellent learning experience and still produce little meaningful performance improvement if the environment sends people back to the same conditions that created the problem.

This is one of the persistent threats to organizational capability identified in White Wolf Consulting’s research: organizations can repeatedly discuss, patch, escalate, revisit, and rename problems without examining them deeply enough to remove their causes. The result is an accumulation of workarounds rather than stronger capability.

Becoming Better at Solving the Right Problems

Perhaps the more interesting question is: “What happens when an organization becomes highly competent at implementing solutions but remains weak at diagnosing problems?” It can purchase sophisticated technology, develop excellent training, mobilize project teams, communicate extensively, track adoption, engage consultants, and build beautiful dashboards. This often results in every function involved being successful at executing its assigned purpose while the organization fails to solve the original problem.

Rigorous analysis can feel slower at the beginning because it requires leaders to tolerate questions before receiving answers. And it takes time to get to the right answers. It may challenge assumptions, reveal uncomfortable conditions, or show that the solution someone championed isn’t the one the evidence supports. That’s precisely why the work matters.

Strong organizational capability includes the ability to distinguish symptoms from causes, understand the system surrounding performance, identify what people genuinely need, and design solutions around evidence rather than assumptions.

Before committing money, people, time, and organizational energy to the next solution, give qualified experts permission to investigate the problem first. Let them talk to the people doing the work. Let them examine the processes, technology, incentives, expectations, environment, skills, resources, and competing priorities. And perhaps most importantly, let the evidence change the answer. The difficult work that happens before solution design may turn out to be one of the most valuable parts of the investment.

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References

Centers for Disease Control and Prevention. (2025, February 5). Assess training needs: Conducting needs analysis. https://www.cdc.gov/training-development/php/about/assess-training-needs-conducting-needs-analysis.html

Christensen, B. D. (2018). From needs assessment to needs analysis. Performance Improvement, 57(5), 36–44. https://doi.org/10.1002/pfi.21785

Mertens, A., Khoa, M., De Toni, F., & Parker, S. K. (2026). Why technology implementation fails: From adoption to dynamic technology integration. European Journal of Work and Organizational Psychology. https://doi.org/10.1080/1359432X.2026.2684522

Miake-Lye, I. M., Delevan, D. M., Ganz, D. A., Mittman, B. S., & Finley, E. P. (2020). Unpacking organizational readiness for change: An updated systematic review and content analysis of assessments. BMC Health Services Research, 20, 106. https://doi.org/10.1186/s12913-020-4926-z