Manual data entry is one of the biggest headaches in companies from different sectors. Manually processed tasks are more susceptible to human errors, which interfere directly with the performance of results. That is because inaccurate information hinders leaders in decision-making and can lead to catastrophic actions.
In addition to these first points mentioned above, other numerous problems arise when manufacturing companies still use the manual method to collect, input, or store data. That’s why our team of experts has created this guide with five reasons why you should not have manual data entry in your plant.
1. Manual data entry can drive to human errors
As you might imagine, problem number one is related to human error. A natural feature of human beings is that we are never fully focused. For many reasons, we can be distracted when performing a task, commiting errors that can only be identified later when they have already hindered the progress of activities.
And there are several factors that interfere with the probability of “human error” occurring. Either due to the complexity of a job, extensive working hours, excessive pressure from managers, among other reasons that lead the employee to be tired and exhausted when executing the activities.
Thus, it becomes very difficult to perform a task with primacy and quality. With a drop in performance, the employee is susceptible to make mistakes, damaging the progress of processes.
Since manual data is entered incorrectly, it can lead to all sorts of problems. You may have incorrect account numbers, prices, or information. And if you rely on this type of information to make big decisions, you may be making the wrong decisions.
If you think this is not a big issue, I guess you might end up changing your opinion with this video from ATSB (Australian Transport Safety Bureau). They show how a “simple” manual data input error lead to a huge accident.
2. Data availability and decision making
How do you query the manually entered data in your plant? And when do you consult them?
This is a huge challenge. Manually entered data has to be stored somewhere. And here you have two possibilities: either you take this data to a system or you view it on paper.
Both can lead to a lack of availability. In the midst of a large volume of data, the manual process makes it difficult to read information for decision making, especially when the information is registered on paper. Thus, a lot of data can be forgotten or left aside in analyses.
Moreover, the way you display this information can be a real nightmare. Without a dashboard that makes it easy to simply and easily look at the numbers, your decision making will be impaired. Or, even worse, you will have no motivation to keep tracking those figures and forget about the spreadsheet or paper that took hours to make.
3. Your analysis is always late
Yes. Your analysis has a natural delay in the collection, insertion, or visualization of manual data. It can be hours, days, weeks, or months, but there is a certainty of this lag.
Collecting the data from the factory and inserting them into sheets of paper or spreadsheets of excellence takes time. And it can be expensive for your company, because you never really know what’s happening now, in real-time.
Let’s think of a real situation, which occurs in many factories: a certain machine was stopped for a long time and caused production to drop a lot that day. Without having the data in real-time or with low latency, you don’t know the reason for that machine shut down and you don’t realize how long it actually happened. By the time you get that information in hand, it’s probably already too late. The same reasoning applies to production differences between shifts and OEE, for example.
(The best way to solve this is with digital production analysis systems that ensure real-time visibility for both operators and plant managers.)
You might also like: The biggest problems in running your factory with Excel
4. Manual data input is slow and ineffective
No matter how fast humans can type, write, process data, and think quickly, speed will always be a problem in data entry. Employees do not work at the exact speed during an entire workday.
Manual data entry obviously needs people. As you know, professionals get sick, need to take vacations, and can be expensive when your business grows, since it needs more and more people simply to run around the factory collecting data.
This means you have to go through the hiring process again and again, which can be stressful because the cost of a bad hire can be more than a slight inconvenience.
Also, if you want to take this data to an excel spreadsheet, you always need that person known in every factory as the “macro guy”. It happens, as we mentioned above, that the macro guy also gets sick, takes a vacation or leaves the company. And when he’s not there, who will take care of the giant excel spreadsheet?
5- Money wasting and hidden costs
Many managers believe they are saving by not hiring a digital system for data collection, insertion, and analysis. Unfortunately, this is just a false assumption.
Although manual data entry may seem a relatively low-cost operation, this is not always true. The many hidden costs of internal entry often outweigh the benefits of this type of initiative. Data entry can be a time-consuming task, as you allocate a staff resource to be practically on account of this activity.
Also, if a serious error has been occurring, you may not be able to correct it instantly (remember that it’s impossible to have data on paper, running around the production line, and accessing it in real-time. This does not actually exist). Of course, this will cost the company a lot of money to fix later, or it will already have meant a lot of wasted cash without the previous rectification of this error.
How to solve manual data inputs challenges?
The most solid and consistent option is to actually adopt internal systems that can help your company eliminate manual data input. This applies to finance, HR, production, supply chain. All areas can benefit from digital solutions.
The most important thing is to start with simple steps, choosing an area to serve as a pilot project. The digital transformation process has to start somewhere. To create new results, a transformation of mind, business, and value models is necessary for a real revolution to occur. Digital transformation is actually about people and how to solve problems and generate value.
According to PWC, cost reductions of digital initiatives in the industry sector has been achieving 3.6% p.a. on average. “Digital technologies enable shorter operational lead times, higher asset utilization and maximum product quality; all told, our survey respondents expect to save US$421 bn in costs each year for the next five years. ” (Full results here)
