Despite modern improvements, many businesses that rely on data entry systems are still held back by inaccurate data. Bad data can come from many possible sources, but you might want to start your search at the very beginning, with your data entry operators.
If you’re lucky, the problem is simply inconsistently entered data. But don’t blame your data entry personnel. The real culprit is inadequate training and lax business rules—and that’s your responsibility.
Regardless of how many data entry operators you manage, and the environment in which they work, data entry errors can be a serious problem. A seemingly simple data entry error can wreak total havoc in your system. Whether you’re a consultant hired to oversee a data entry project or a manager, this article can help you explain to data entry operators the value of the data they’re handling.
First of two parts
This is the first installment in a two-part series highlighting six factors you can use to illustrate the value of accuracy to data entry operators.
The perils of errors
Let’s suppose your purchase order software automatically fills in customer information such as shipping and billing addresses when the operator enters a customer number. If the operator enters the wrong number and subsequently fails to verify that the address information is correct, the order—and the bill—goes to the wrong customer. Not only do you have to resend the order to the angry customer, you must also arrange to pick up or receive the incorrectly sent items. Next, accounting must credit the incorrectly invoiced customer and invoice the right customer. All in all, it’s a costly and labor-intensive solution to a mistake that could have easily been avoided at the data entry level.
A competent data entry clerk knows:
- · The company’s business and purposes.
- · The type of data that’s processed.
- · When unprocessed data items don’t fit the mold.
- · Where data entry fits into the bigger picture. In other words, the data entry operator knows how mistakes affect the workflow—both incoming and outgoing.
- · Accuracy takes precedence over speed.
- · When to ask for help.
How do you hire this level of competence? You don’t. But you can create it through training and ongoing support.
Knowing the business
Your data entry personnel don’t need to view the quarterly reports, hear stockholder demands, or share the confidence of the CEO. What they do need to know is your product and your customers. In fact, they should be as familiar with your products and customers as you are. This is not to say that they have to know the ins and outs of every product. Knowing how to fill a customer’s order properly will do.
Sharing the business is the easiest way to impart this level of knowledge. Let’s suppose your personnel fill orders for steel products fabricated and stored in an attached warehouse. A tour of the warehouse is in order. Identify the different products by sight so operators have a visual image of what the company sells. Let them watch deliveries and observe the warehouse employees filling orders.
Data entry operators will never need the expertise that an account manager possesses—but they need to be familiar enough to point out potential errors before those errors are acted on. Knowing the product can go a long way toward spotting potential errors.
Letting the operator follow the data from beginning to end is a great idea if geography allows it. It won’t take long for the operator to know how misspelled entries and inaccurate product codes affect the next person (and so on) down the line. Use that to your benefit by allowing the operators to see just how badly a simple data entry error can muck up the entire works.
You can also appeal to their pride. A few hours spent following the data trail can open an operator’s eyes to just how many people see their work—the good and the bad. They can quickly learn how mistakes affect people they may not even know. And, it certainly can’t hurt if they also learn how much other employees appreciate them because their work is consistently devoid of errors. (Of course, this operator probably doesn’t need your training!)
If possible, let your employees get to know the customers. While this isn’t possible in all shops, be prepared to take advantage of opportunities as they arise. For example, when customers visit the facility, introduce them to your department; let them actually chat if there’s time and the customer’s willing.
Putting a face with a name can spark an invaluable connection between your operators and the customer. That connection can lead to a genuine sense of concern on the part of your operators to see that the customer’s needs are fulfilled in a timely manner—it’s worth the effort when it works.
Knowing the data
Knowing the difference between sheet and roll metal is one thing—understanding that the product code on an order form is wrong is better. We routinely put data entry operators to work when they don’t have a clue what they’re inputting.
For example, let’s suppose an account manager uses the wrong product code on an order form. If the software isn’t sophisticated enough to reject the entry, the incorrect order goes through—unless the data entry operator is familiar enough with the data to know it isn’t right.
It isn’t critical that the operator have the product codes memorized; in fact, doing so might be impossible depending on the size of your product list. What is critical is that the operator be familiar enough with the data to know when it doesn’t look right. In addition, the operator needs to know how to respond to the problem, whether that means turning the problem over to a supervisor or phoning the account manager for clarification.
New operators need time to learn the data before actually entering it. That may require a few days of training and time spent reviewing product codes and learning the logic behind those codes. Most of the time, these codes aren’t just random values.
Suppose the data string fs-1118.5 represents a stock piece of flat sheet metal that’s 11 x 18 feet and a half-inch thick. Once the data entry clerks know what the code means, they are more apt to identify and correct mistakes instead of introducing those mistakes into the system. The path to resolving possible errors is unique to your system, but it really depends on you. The path should be clear. Create a checklist if necessary, but don’t leave it up to employees to take the initiative.
Shops with high volume need to make priorities clear, and for most of you that priority should be accuracy, not speed. Both are important, but don’t put your operators at odds with your center’s purpose by offering bonuses for volume without also demanding accuracy.
For example, let’s suppose your data entry operators input data sets and your minimum standard is 250 per day. To boost production, you offer a bonus to clerks inputting 300 per day. What you’ll probably experience is a huge boost in production with a decrease in accuracy—not your intention. Instead, keep the minimum standard, or even lower it if necessary to ensure accuracy. Determine the maximum errors allowed, and then give recognition for accuracy and volume.