When we talk about preparing for 2027, it’s easy to think of budgets, business goals, new investments, or projects that will begin after the Christmas holidays. Something similar happens in quality: ideas emerge, such as digitizing processes, improving traceability, reducing manual tasks, or having more information available for decision-making.
The problem is that January comes around quickly. And when it does, many of those ideas are still just that: ideas. We know there are processes that could work better; we know that certain tasks take too much time; and we probably have some Excel spreadsheet that no one wants to mess with too much because only one person really understands how it works. But between production, audits, issues, and day-to-day work, major improvements can spend months waiting for the right moment.
That’s why perhaps the question for these last few months of the year shouldn’t be “What are we going to implement in 2027?”, but rather an earlier one:
What do we want to be doing better by 2027?
Waiting until January is also a decision
There’s no need to turn September into January or start all the projects planned for next year right now. In fact, that would probably be a mistake. What we can do, however, is take advantage of these months to take a step back and assess how we’re working.
Because quality issues don’t always appear to be major problems. They often come disguised as small tasks that we’ve come to accept as normal: downloading information to prepare a report, searching for the latest version of a document, copying data from one record to another, following up via email on the status of an issue, or asking someone where certain information can be found.
None of this seems particularly serious on its own. Production continues, audits are prepared, and the work gets done. That is precisely why it is so easy to put up with these inefficiencies for years. The problem arises when we add them all up.
How many hours does the team spend gathering information that already exists? How long does it take for a deviation to be identified—from the moment it occurs until it reaches the person who needs to take action? How many processes still depend on someone remembering to send an email, update a spreadsheet, or notify the next person in charge? If we want to improve something by 2027, now is a good time to start there—not by looking for a solution just yet, but by better understanding the problem.
What quality processes are holding your team back today?
There is an important difference between a process that works and a process that works well. A control process can be carried out on paper for years and still fulfill its purpose perfectly. An Excel spreadsheet can contain all the information needed to manage certain metrics. Even an email chain can be used to report an issue and ensure it is ultimately resolved. The question is, how much effort does it take to make all of that work?
Let’s consider, for example, an inspection carried out on the production floor. The operator fills out the log, someone later compiles that information, and when it comes time to analyze it, another person enters or consolidates it into a separate document. The data exists from the very beginning, but it takes the organization hours, days, or even weeks to turn it into truly usable information.
Something similar happens with documentation. The problem isn’t always a lack of procedures, instructions, or records. Sometimes the opposite is true: there are so many files, versions, and locations that figuring out which document is the right one becomes part of the job.
And then there’s traceability. As long as everything is working properly, reconstructing the history of a process may seem unimportant. The difficulty arises when a deviation occurs and we need to answer specific questions: what happened, when, in which batch, under what conditions, who performed the inspection, and what actions were taken afterward. That’s when we discover whether we actually have information or simply have data scattered across many locations.
Situations like these are interesting because they help us identify where there is a real opportunity for improvement. Not because using Excel, paper, or email is necessarily wrong, but because there comes a point where maintaining certain processes that way costs more than it seems.
Not everything needs to be digitized at the same time
When a company begins to identify these situations, the opposite impulse may arise. The urge to fix everything. Document management, audits, controls, nonconformities, corrective actions, indicators, measurement tools, traceability… The list can grow very quickly. But digitizing ten poorly defined processes doesn’t necessarily bring us any closer to a digital operation.
In many cases, a good place to start is to identify a specific process where the effort involved is clearly disproportionate to the result. This is something that happens frequently, takes up time, leads to errors, or makes it difficult to obtain information when it is needed.
It could be a checklist that’s still being circulated on paper. It could be a set of documents that’s hard to keep track of. It could be the process of handling a nonconformity that requires sending several emails before it can be closed. Or it could be a metric that requires several hours of Excel work at the end of each month to analyze.
Then the conversation shifts. We’re no longer talking about “digitizing quality”—a term broad enough to mean almost anything. We’re talking about solving a specific problem. And that allows us to start small without thinking small.
If we manage to improve a process, we can measure what has changed, see how the team responds, and figure out what we need to do differently before tackling the next one. A well-executed initial improvement can yield far more insights than trying to transform the entire management system all at once.
From “We want to digitize” to a project that can actually be implemented
There are goals that sound good in a meeting but are difficult to implement on the factory floor. “We want to improve traceability,” “We need to cut down on paper,” “We need to digitize quality.”
We probably all agree on that. The problem arises when someone asks , “What are we doing on Monday?”
That’s where an idea needs to become a project. If the problem lies in nonconformities, perhaps the goal isn’t simply to “digitize” them, but to ensure that a deviation is automatically routed to the appropriate person, its status can be tracked, and evidence of the actions taken is recorded.
If the problem lies with plant-level controls, the goal could be to have results recorded directly where they are generated so they can be accessed without having to wait for someone to consolidate the data later.
And if the problem is related to documentation, perhaps the important thing isn’t “uploading the documents to the cloud,” but rather ensuring that people know which version is current and that changes are properly tracked. The difference may seem small, but it completely changes the project.
Once we know what we want to improve, we can then decide whether we need to change a procedure, reorganize responsibilities, train the team, or implement technology. If we start with the tool, we run the risk of tailoring the problem to the solution we’ve just purchased. Technology should come after the question, not before.
What should we keep in mind before 2027 begins?
Perhaps the goal for these last few months of the year doesn’t have to be to complete a transformation. It may simply be to reach January with a much clearer picture of our situation.
Which processes are causing us to waste the most time? Where are we still relying too much on manual tasks? What information is difficult to retrieve? What problems keep cropping up? And which of these would make the most sense to tackle first? Answering these questions is already a step forward.
It also allows you to talk to the people who are closest to the process. From an office, it may seem obvious what should be digitized first; on the factory floor, the answer may be completely different. Someone who performs daily checks is likely aware of friction points that never show up in a procedure.
And there’s another important point: knowing where we’re starting from.
If we want to reduce the time it takes to resolve an incident, we need to know how long it currently takes. If we want to reduce administrative tasks, we need to know what tasks we’re performing. If we’re looking for greater traceability, we must first identify what information we’re currently able to reconstruct and what gets lost along the way. Otherwise, we may end up in 2027 with more technology and still not know if we’re actually working more efficiently.
2027 doesn’t start in January
We don’t know what issues a plant will face next year, what a new customer will require, or which project will end up becoming a priority. Planning doesn’t mean trying to guess. It means being better prepared.
We still have several months to observe how we’re working, identify where the biggest friction points are, and decide what deserves our attention. Not so we can rush out and buy a tool or digitize just for the sake of digitizing, but so we can distinguish the important problems from those minor inconveniences we can continue to live with.
Perhaps later we’ll discover that we need quality management software. Perhaps an improvement can be achieved simply by changing the way we work. And perhaps we’ll find a small process whose digitization could become the first step in a much larger project. That will come later.
For now, the question might be quite a bit simpler:
If, in December 2027, we look back and say that our quality management really improved this year, what would have had to change? The answer is probably a good place to start.
Content written by:
Jordi Blanco Corrales, Co-founder and Product Manager at Kapture.io QMS
With more than 20 years of experience in the field of industrial quality, Jordi Blanco has witnessed the evolution of an industry characterized by continuous improvement, digitalization, and ever-increasing demands. His vision combines operational expertise, market insight, and technology to help organizations make better decisions and strengthen their competitiveness.
