India vs. China: The other side of the story

I was asked by a reader, “so why do you think you will win your bet with Benny?” Most of India’s strengths are self-evident and have been widely written up. Here are a couple of thoughts on why I still believe I will win the bet:

• Be careful what you wish for, or in other words, how China may fall victim to its own success: The Chinese government tends to think big and right now it is trying to start 1000 BPOs by 2010. 1000 is a large enough number that it attracts attention (which by the way is what I think the government was trying to do) but it is too large a number of companies in too short a time for them to learn how to compete smart. If they can’t compete smart, they will compete hard which means they will undercut each other on price and overbid each other on paying workers. Pretty soon they will face the exact same problems India is facing: high employee churn rates, wage inflation and lower margins. The Chinese government has to help Chinese BPOs grow smart rather than just grow fast and that can’t be done by spending money alone.
  
• When it comes to quality, perception is as important as reality: While the Chinese BPO industry has existed for years, they have very little experience serving US and European customers and dealing with their quality expectations. The newer Chinese BPOs also tend to have less extensive quality management experience and technologies. [There are exceptions to every rule: I have met some Chinese BPOs who are investing quite heavily on their quality, while others seem to have very few if any quality experts on staff.] Furthermore, often the definition of quality in BPO engagements is quite subjective. If US customers believe that China has a quality problem, they will perceive lower quality in the processes run by Chinese vendors. Indian vendors addressed this quality perception problem by aggressively adopting CMM and reaching CMMI certification levels that were often higher than their customers’. [Look out for an upcoming post on why CMMI is not sufficient for BPO as opposed to IT outsourcing. But the reality is that the market broadly perceives it as a quality certification.] Chinese BPO vendors can’t follow that exact same strategy. The leading Indian BPO vendors have already invested years in reaching the highest levels of CMM. Even after spending years, the Chinese BPOs can at best match the Indian vendors in CMMI certification, not beat them at it.

Time for some BPO magic: 99.9% accuracy = 1.8% accuracy!

Fifteen Stanford students are working with me this quarter as part of a Stanford Marketing class. One of them recently asked me: “How can you say there is a quality problem with Business Process Outsourcing (BPO) if most vendors advertise 99.9% accuracy?” Before I could answer him, I had to explain what 99.9% accuracy really meant:

• Is it document-level, field-level or even character-level accuracy? Or how 99.9% accuracy can equal 2% accuracy! If 99.9% of documents have no errors, that is indeed an impressive level of quality. Let’s assume that the 99.9% accuracy is actually a field level number. Now, an insurance claim may easily have 200 fields. In that case, the document-level accuracy would just be 82% (if you like math, this is 0.999 multiplied by itself 200 times). However, usually once you ask the vendor, you will find that such a high accuracy level is actually a character-level accuracy. If 99.9% of characters have no errors, and most fields have 20 characters, then an average document field would only have 98% accuracy. Assuming 200 fields on average per document, if 98% of fields have no errors, then on average the document-level accuracy would be just 1.8%. In other words, if the character-level accuracy is 99.9%, only about 2% of documents would be error free. Make absolutely sure what is the context for the reported 99.9% accuracy, because it may translate to only 82% or even just 2% document level accuracy.
  
• Was the base of the field-level accuracy the hypothetical number of fields that might be filled out or the actual number of fields that were filled out? Or how 99% accuracy can equal 90% accuracy! I recently analyzed an insurance claim that had almost a thousand fields. For example, it had space to specify about 30 separate diagnoses along with associated details. However, most of the time the claims contained just one to three diagnoses and an average claim had only about 100 fields out of 1000 filled out. If there was an error in ten fields in such a document, is that 90% accuracy or 99% accuracy? Remember that in most cases, only a small subset of fields are filled out for each document. Thus, whether we divide the errors by the total number of fields that could have been filled our or the number of fields that were actually filled out can significantly affect the reported error rate.
  
• How was the accuracy evaluated? Or how 99.9% accuracy can equal 89.9% accuracy! Several vendors use double-entry for quality control and assume that any field that was consistently typed by both operators was not an error. Sounds reasonable, doesn’t it? After all, there is only one way in which a field can be processed correctly and multiple ways in which it can be processed incorrectly. Thus, if two operators typed the field consistently, they must have gotten it right! I recently evaluated a BPO vendor who leverages double-entry and discovered an interesting fact that completely blew this assumption out of the water. Over 50% of the errors in the insurance claims processed by the vendor came from fields being left blank. I was really intrigued by this pattern and researched it further. It turns out, in double-entry if the operator has any difficulty reading a field, they may leave the field blank assuming the 2nd operator will get it right. Leaving a field blank also reduces the probability that a discrepancy will be reported [a field may be entered incorrectly several different ways, but left blank only one way]. Even without collusion this can lead to systematic under-reporting of operator errors in a double-entry system. Essentially, the operators quickly figure out that if they try to interpret bad handwriting and put in their best guess, then the supervisor usually reports an error. However, if they are ‘lazy’ and simply leave the field blank, the supervisor rarely complains. Humans are really smart and quickly learn from such feedback, even when the lesson they learn is exactly contrary to what the BPO vendor would want them to do. In this specific case, if 50% of the errors come from fields left blank, 25% on average and up to 50% of the errors would not have been caught by the double-entry. Let us assume that the average first-time quality of the operators as reported by the double-entry system is 10%. The real first-time quality of the operators would thus be 13% to 20%. Now, almost all of the errors caught by the double entry system would have been corrected, and thus, the vendor might reasonably report a 99.9% accuracy. In reality, the 3% to 10% of the cases where both operators incorrectly left the field blank would never be caught, and the actual accuracy rate would be between 89.9% and 96.9%.

So what was my answer to the Stanford student? Be very careful what 99.9% accuracy really means. If a vendor has a real document-level error rate of 99.9%, they would really have exceptionally high quality. By the way, this vendor may still have a quality problem: they may simply be spending too much to achieve that level of quality!

Interesting push for considering the Total Cost while outsourcing

I am about to quote widely from two anti-outsourcing tirades. While I usually prefer not to link to extreme views, these two posts between them make a very important point: labor cost is only a small component of the total cost of ownership and if you make outsourcing decisions based on labor costs, you are setting yourself up for failure. If we are truly going to be rational about outsourcing, we need to acknowledge and learn from the truth embedded in the most extreme views. [Not that these posts are even close to being the most extreme views on this topic.]

The first post by Bill Waddell at www.evolvingexcellence.com/blog/2006/08/get_real_folks.html makes the point that companies do not have a clear sense of what their true cost is because they do not sufficiently account for factors such as the cost of lead time, quality, inventory carrying costs, supply chain risk, etc. I would tend to agree. In fact, in the Business Process Outsourcing space, I have often met customers whose cost of correcting errors is three times their outsourcing cost, yet they focus more on the labor cost differential than the error rate differential between their in-house operations and outsourcing vendors.

I have a better idea: How about if manufacturers figure out what their cost really is first. Forget about the cost of lead time and quality. Most companies have no idea what it costs to take widget materials A,B,C and D; put them together into sub-widgets E and F; slap those together into a final widget G; then put that into a cardboard box. Never mind the higher level questions of how long it takes or how many they get right.

When companies cannot figure out the cost of running and taking care of the widget making machines, or the cost of moving widget parts around their factories, the esoteric costs of such matters as lead time are the least of their worries. In most cases, 'cost' means the number they get when they add up the 2/3 or so of the direct labor time they can track plus the invoice price of the materials, then multiply the labor number by about six or seven and call that the cost of a widget. That number is about as accurate as calculating the temperature by looking at a lake and deciding that, since the lake isn't frozen it must be greater than 32 degrees, and it's not boiling so it has to be less than 212, so the temperature must be exactly in the middle - 122 degrees. Precisely 122 point 0, in fact.

For a company to take a manufactured cost that includes a 40-50% wildassguess factor and compare that to an fob Guangdong price, then decide to close a factory and throw people out of work based on the comparison is somewhere between insane and criminal. Deciding to outsource because the cost just couldn't be reduced any more, when the company never had a clue what the cost was to begin with is equally absurd.

The second post, by Kevin Meyer at www.evolvingexcellence.com/blog/2006/11/local_outsourci.html makes the point that companies can save much more money by eliminating waste than by reducing labor costs via outsourcing. Once again, I tend to agree that this lesson applies to Business Process Outsourcing as well. For example, at the Total cost of errors site we highlighted one company where a 0.1 percentage point change in error rates had the same bottom line impact as a 30% reduction in labor costs due to outsourcing. [The full case study is available at http://www.totalcostoferrors.com/atcecasestudy.]

But the bottom line is that there are really only two justifiable reasons to outsource, especially globally: to access unique capabilities and to be closer to the customer. Labor cost is not one of them. In the traditional financial world, labor cost happens to be one of the most controllable, therefore it's easy to go a few thousand miles away to save a few bucks an hour. But what about the total supply chain cost? How much cash is being chewed up in inventory on the high seas? What happens if a quality problem is found after a boatload of parts has already set sail? What is your new customer lead time? Not to mention intellectual property issues and the rapidly-rising labor costs in some outsourcing havens like China that is already forcing some companies to globetrot to another low labor cost location.

A 20% "labor penalty" is nothing compared to the internal process and methods waste at most manufacturing companies. Take the time to really use lean methods to streamline how the operation runs. Focus on one piece flow, respect your employees, and develop a high performance workforce... you usually get what you pay for. The savings from even a first-pass lean waste reduction kaizen or value stream mapping exercise will often be twice the cost of the labor of the process.

It works. That's why truly lean companies, such as Danaher, Parker-Hannifin, American Apparel, and others are building more plants in the U.S., to compete globally.

While I agree with several points raised by these authors, I do believe at least in the case of Business Process Outsourcing, the better outsourcing vendors are adopting lean practices and six sigma far more aggressively than their customers. Eventually, if the outsourcing vendors deliver truly lean processes that US companies still struggle to match, then the outsourcing vendors’ labor cost advantages will only be further enhanced by the additional financial benefits of the lean processes adopted by them. That day is not here today, but if American companies do not aggressively start improving the overall cost of their processes, soon the Indian firms will be by far the world experts in business process quality and innovation.

New Rational Outsourcing article published by the Outsourcing Journal

An article I co-authored just got published by the Outsourcing Journal (monthly newsletter and website sponsored by the Everest Group and part of www.outsourcing-center.com—the largest online educational resource on outsourcing) . The article is directly related to the topic of this blog. You can read it at http://www.outsourcing-journal.com/sep2006-barnard.html. For your convenience, here is the abstract:

FOCUS ON: Back-Office Errors
Beyond merely asserting 'Quality is Key': If you can't quantify the benefits of quality, you are only paying lip service to it:
As companies rush abroad to cut back-office costs, they forget one thing: the cost of small increases in error rates can wipe out the cost reductions from cheaper labor. Based on interviews with more than 50 financial services firms, BeyondCore determined that if the data-entry associated with one document costs $1, the downstream costs incurred for one document with a data-entry error can easily add up to $300. The solution: place far greater emphasis on quality than on processing cost.