By Paul Gamble, Managing Director, Seneca Resources
For years, when an important project stalled, many companies responded the same way: hire another person or supplement the team.
If reporting was taking too long, they hired an analyst. If a system migration fell behind, they looked for a project manager or a developer. If the business needed better visibility into operations, they added another person to the IT team.
Today, that approach is becoming harder to sustain.
Teams are smaller and budgets are tighter, but, at the same time, companies are under pressure to modernize systems, improve reporting, prepare for AI, and make better use of the data they already have.
As a result, more organizations are discovering that they do not necessarily have a hiring problem; they have a data problem and in most cases, adding another person will not solve it.
The Real Issue Often Starts with Disconnected Data
Most companies already have more information than they know what to do with. The challenge is that the data often lives in too many places.
Some of it is in spreadsheets. Some is in a CRM. Some lives inside reports, PDFs, emails, or legacy applications. Different departments may maintain their own systems and processes. Important information may be manually updated or recreated over and over again.
Over time, the result is a patchwork environment where data is scattered, inconsistent, and difficult to use.
That creates a ripple effect across the business:
- Reporting becomes manual and time consuming
- Teams spend more time gathering information than acting on it
- Leaders struggle to get a clear picture of what is happening
- Projects take longer because no one has confidence in the data
- Internal teams become overwhelmed trying to hold everything together
When those problems begin to surface, many organizations assume they need to hire more people. That may be part of the answer. But in order to solve the issue permanently, companies first need to understand what is actually causing the problem.
Why Hiring Alone Does Not Solve the Problem
When a company adds another person without addressing the underlying issue, it often creates more complexity.
The new employee still has to work inside the same environment. They inherit the same disconnected systems, the same spreadsheets, the same manual reporting processes, and the same lack of visibility.
That may help in the short term, but it rarely changes the root cause.
A construction company I worked with recently faced exactly this challenge.
The company, which had a relatively small IT team of fewer than 20 people, was receiving project information from more than a dozen different systems and sources. Drawings, updates, schedules, and operational data were flowing in from all directions. None of it was centralized. None of it was structured in a way that allowed the company to report against it efficiently.
The company could have tried to hire another analyst or another IT resource, but that would not have solved the problem.
Another person would still have spent much of their time chasing information across twelve different systems, reconciling conflicting data, and manually assembling reports. The underlying issue was not a lack of effort or capacity. It was that the company had no single source of truth.
What the organization needed was a way to bring all of that information together into a single place where it could be organized, structured, and reported against. In this case, that meant creating a data warehouse and a plan for how information should flow across the business.
Once that became clear, the conversation changed. Instead of asking, “Who should we hire?” the better question became, “How should we design a solution?”
A Better Approach Starts with the Bottleneck
The companies making the most progress today are approaching these situations differently.
Rather than starting with a job title, they begin by mapping the problem.
They look at where information originates, how it moves through the organization, where it gets stuck, and which activities consume the most time. They bring together the people closest to the issue, often across operations, finance, IT, and the business itself, and use those conversations to identify the real bottleneck.
Only after they understand the problem do they decide whether they need technology, automation, outside expertise, or additional people.
That is very different from the traditional approach of immediately opening a requisition and hoping the right hire will somehow fix the issue.
Instead, they are stepping back and asking a different set of questions:
- Where is the work slowing down?
- How does data move through the organization today?
- Which processes are still manual?
- Where are people spending time that could be automated?
- If we could solve one or two things, what would have the biggest impact?
Those questions often uncover a much larger issue beneath the surface.
For one medical device manufacturer, the problem appeared to be a reporting issue. The company relied heavily on Microsoft Power BI, a business intelligence platform used to create dashboards and visualize performance data, but the dashboards had to be built and updated manually. Reports were created on an ad hoc basis, which consumed time and made it difficult for the business to get consistent information.
At first glance, it might have seemed like the company needed another person to help build reports.
But the real opportunity was to automate the process itself, standardize how information was collected, and create dashboards that updated automatically.
By focusing on the underlying bottleneck rather than immediately adding headcount, the company was able to explore a more effective long-term solution.
Why This Matters Even More as Companies Prepare for AI
The pressure to use AI is making these challenges more urgent. According to a 2025 McKinsey survey, 78 percent of organizations now use AI in at least one business function, up from 55 percent just two years earlier.
Across industries, leadership teams are asking what role AI can play in improving efficiency, reducing costs, and creating better insight. But many companies are discovering that they cannot take advantage of AI until they first solve the problems surrounding their data.
An insurance company we recently worked with faced this challenge.
The organization had decades of policy information stored inside written documents. Valuable information existed inside those files, but because the data was unstructured, the company had no practical way to analyze it or use it.
Historically, the only option would have been to assign people to manually review and extract the information.
Instead, the company used natural language processing and machine learning to pull the data from those documents and move it into a structured format.
That did more than improve reporting. It created the foundation the company needed to eventually use AI more effectively.
The lesson is an important one: companies do not become “AI ready” by hiring another developer or buying another tool.
They become ready by understanding their data, organizing it, and creating a strategy for how it should flow through the business.
Before You Hire, Step Back and Ask a Different Question
There are certainly situations where companies need more people. But before creating another requisition, it is worth asking whether the challenge is really a staffing problem at all.
In many organizations, the bigger issue is that no one has stepped back and fully defined the problem.
The company knows reporting takes too long. It knows projects are falling behind. It knows employees are spending too much time in spreadsheets, reworking information, or manually pulling data from one system to another. But it may not yet understand why those things are happening or what would actually solve them.
That is why the most effective organizations begin with diagnosis rather than hiring.
- What is really slowing us down?
- Where is information breaking down?
- What would happen if we solved the underlying issue instead of simply adding another person?
Sometimes the answer is another hire, but increasingly, the answer is a better process, a clearer data strategy, a new technology approach, or a solution that allows the team to work differently.
Because the real challenge is often not that companies are hiring too quickly. It is that many companies do not yet realize the real problem they are trying to solve.
