Data Entry Speed and Accuracy Measures

They go hand in hand, but not in the way most people think. As counter intuitive as it Production Based Data Entry Environment may seem, data entry keyers that type at a much higher than average rate, also tend to have the lowest error rate. This goes against the conventional wisdom that more speed leads to more errors. Unlike speeding while driving a car – which anyone can do, higher speeds with keyers are a sign of proficiency of the skill, and that proficiency extends to accuracy also.

Another confusing aspect in judging the skill of an operator is that many typing tests assess accuracy in a way that doesn’t make sense. The usual way has been to take the typing speed and subtract each error (as if it magically disappears) to get at a net speed. For example, a gross typing speed of 40 wpm minus 5 errors equals a net typing speed of 35 wpm, with a 100% accuracy rate implied. The reason this doesn’t make sense is to consider the real world implications of data entered in this manner in a company. The 5 errors do not magically disappear. They happen, only being corrected when caught – which may or may not take place until damage is done. A better way to assess accuracy is to keep the speed and error data separate and therefore known. This keeps the accuracy data visible to ensure an organization making a hiring decision has the full picture.

There is still a problem in comparing a fast data entry employee to an average one as far as accuracy goes, even with both figures known. This is because the surface measures can make it appear that the faster one has less accuracy. An example of this would look something like the following scenario.

  • Average speed : 40 wpm with 3 errors
  • Above average speed: 60 wpm with 4 errors

This shows that the above average keyer had more errors (less accuracy). A more accurate way to figure it would be to figure the accuracy as a percentage. The ‘winner’ results would be flipped then as shown below.

  • Average speed: 3/40 wpm = 8% errors (92% accuracy rate)
  • Average speed: 4/60 wpm = 7% errors (93% accuracy rate)

So the 60 wpm keyer has not only a better accuracy rate, but completes 50% more work than the average keyer while doing so. Now let us look at these numbers in the usual way:

  • Average speed: 40 wpm – 3 errors = net 37wpm
  • Average speed: 60 wpm – 4 errors = net 56 wpm

This clearly shows the proficiency (both speed and inferred accuracy) is much higher for the 60 wpm typist.  The danger though is that, although  a fast keyer tends to have lower error rates due solely to their skill overall, the exceptions to this can fall through the cracks. For example, a keyer that types at 75 wpm with 7 errors will look like they have good accuracy and great speed at 68 wpm after the errors are removed. It will not reflect the 9% errors (91% accuracy rate).

What is the Best Way to Judge Data Entry Speed and Accuracy?

Ideally, the best way to judge results with data entry skill that most reflects true speed and accuracy rates is to records these two measures. If a ‘net speed’ must be arrived at, do not use the subtraction method. Use instead the error percentage: errors/wpm. This is the way to get to a true accuracy rate (100-error percentage).

It may seem like too much detail but when you consider the damage that inaccurate data can do to workflows, customer satisfaction, and so on, it pays greatly to flesh out a true accuracy rate on the people who will be entering it.

A good way to go about ensuring proficient data entry skill (speed & accuracy), is to look for above average speed first – then from that pool of candidates looks for the best accuracy rates. Average, or below average keying speed is a sign of lower overall proficiency with this skill. Like any other skill, those who have spent the most time practicing, will be more proficient at it. This means you can rule out the hunt and peck types and others who only learned how to type on Twitter, by texting on their cell phones, or chatting.

Instead, you will want touch typists. These are the individuals that took an actual typing class or two at some point early in their lives and/or have a work history where the bulk of their duties involved performing data entry.

The Ten Thousand Hour Rule as it Relates to Data Entry Proficiency

Proficient data entry specialists will have relevant experience that is measured in years. Have you ever heard of the 10,000 rule? This rule states that if you spend 10,000 hours repeating the same thing (practicing), you will become very good to great at it. You can look at any skill and see how this plays out for the most part. Think of any other skill, say athletes or musicians, and you will see the most proficient are those that have this type of repetition in their histories. Professional baseball players, for example; many have been playing since they were in little league as children.

The same holds true for a data entry specialist that is truly proficient at their skill – measured on both accuracy and speed. So, if using this line of thinking, they will have five years of full time data entry experience on average (FTE = 2,080 hours * 5 years = 10,400 hours). Note: an administrative employee that types as part of a myriad of other duties assigned to them, will not approach this level in the same time frame as a small portion of their time is actually devoted to typing.

This may explain why the average typing speed seems low – in the 38-40wpm range (research). Furthermore, accuracy parallels speed results in that higher speeds correlate with higher accuracy. In other words, data entry operators are either proficient or not. Speed and accuracy are very much intertwined. The most proficient at one measure correlates strongly with similar proficiency of the other.